Introducing litter quality to the ecosystem model LPJ-GUESS: Effects on short- and long-term soil carbon dynamics

Science.gov (United States)

Portner, Hanspeter; Wolf, Annett; Rühr, Nadine; Bugmann, Harald

2010-05-01

Many biogeochemical models have been applied to study the response of the carbon cycle to changes in climate, whereby the process of carbon uptake (photosynthesis) has usually gained more attention than the equally important process of carbon release by respiration. The decomposition of soil organic matter is driven by a combination of factors like soil temperature, soil moisture and litter quality. We have introduced dependence on litter substrate quality to heterotrophic soil respiration in the ecosystem model LPJ-GUESS [Smith et al.(2001)]. We were interested in differences in model projections before and after the inclusion of the dependency both in respect to short- and long-term soil carbon dynamics. The standard implementation of heterotrophic soil respiration in LPJ-GUESS is a simple carbon three-pool model whose decay rates are dependent on soil temperature and soil moisture. We have added dependence on litter quality by coupling LPJ-GUESS to the soil carbon model Yasso07 [Tuomi et al.(2008)]. The Yasso07 model is based on an extensive number of measurements of litter decomposition of forest soils. Apart from the dependence on soil temperature and soil moisture, the Yasso07 model uses carbon soil pools representing different substrate qualities: acid hydrolyzable, water soluble, ethanol soluble, lignin compounds and humus. Additionally Yasso07 differentiates between woody and non-woody litter. In contrary to the reference implementation of LPJ-GUESS, in the new model implementation, the litter now is divided according to its specific quality and added to the corresponding soil carbon pool. The litter quality thereby differs between litter source (leaves, roots, stems) and plant functional type (broadleaved, needleleaved, grass). The two contrasting model implementations were compared and validated at one specific CarboEuropeIP site (Lägern, Switzerland) and on a broader scale all over Switzerland. Our focus lay on the soil respiration for the years 2006

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.

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.

Synaptic scaling enables dynamically distinct short- and long-term memory formation.

Directory of Open Access Journals (Sweden)

Christian Tetzlaff

2013-10-01

Full Text Available Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling - a slow process usually associated with the maintenance of activity homeostasis - combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes.

Synaptic scaling enables dynamically distinct short- and long-term memory formation.

Science.gov (United States)

Tetzlaff, Christian; Kolodziejski, Christoph; Timme, Marc; Tsodyks, Misha; Wörgötter, Florentin

2013-10-01

Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling - a slow process usually associated with the maintenance of activity homeostasis - combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes.

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.

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

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.

An Overview of Short-term Statistical Forecasting Methods

DEFF Research Database (Denmark)

Elias, Russell J.; Montgomery, Douglas C.; Kulahci, Murat

2006-01-01

An overview of statistical forecasting methodology is given, focusing on techniques appropriate to short- and medium-term forecasts. Topics include basic definitions and terminology, smoothing methods, ARIMA models, regression methods, dynamic regression models, and transfer functions. Techniques...... for evaluating and monitoring forecast performance are also summarized....

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

NARCIS (Netherlands)

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

1998-01-01

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

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.

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

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)

Rich spectrum of neural field dynamics in the presence of short-term synaptic depression

Science.gov (United States)

Wang, He; Lam, Kin; Fung, C. C. Alan; Wong, K. Y. Michael; Wu, Si

2015-09-01

In continuous attractor neural networks (CANNs), spatially continuous information such as orientation, head direction, and spatial location is represented by Gaussian-like tuning curves that can be displaced continuously in the space of the preferred stimuli of the neurons. We investigate how short-term synaptic depression (STD) can reshape the intrinsic dynamics of the CANN model and its responses to a single static input. In particular, CANNs with STD can support various complex firing patterns and chaotic behaviors. These chaotic behaviors have the potential to encode various stimuli in the neuronal system.

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

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.

Exploiting short-term memory in soft body dynamics as a computational resource.

Science.gov (United States)

Nakajima, K; Li, T; Hauser, H; Pfeifer, R

2014-11-06

Soft materials are not only highly deformable, but they also possess rich and diverse body dynamics. Soft body dynamics exhibit a variety of properties, including nonlinearity, elasticity and potentially infinitely many degrees of freedom. Here, we demonstrate that such soft body dynamics can be employed to conduct certain types of computation. Using body dynamics generated from a soft silicone arm, we show that they can be exploited to emulate functions that require memory and to embed robust closed-loop control into the arm. Our results suggest that soft body dynamics have a short-term memory and can serve as a computational resource. This finding paves the way towards exploiting passive body dynamics for control of a large class of underactuated systems. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

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...

Limitless capacity: a dynamic object-oriented approach to short-term memory.

Science.gov (United States)

Macken, Bill; Taylor, John; Jones, Dylan

2015-01-01

The notion of capacity-limited processing systems is a core element of cognitive accounts of limited and variable performance, enshrined within the short-term memory construct. We begin with a detailed critical analysis of the conceptual bases of this view and argue that there are fundamental problems - ones that go to the heart of cognitivism more generally - that render it untenable. In place of limited capacity systems, we propose a framework for explaining performance that focuses on the dynamic interplay of three aspects of any given setting: the particular task that must be accomplished, the nature and form of the material upon which the task must be performed, and the repertoire of skills and perceptual-motor functions possessed by the participant. We provide empirical examples of the applications of this framework in areas of performance typically accounted for by reference to capacity-limited short-term memory processes.

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

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.

Limitless capacity: A dynamic object-oriented approach to short-term memory

Directory of Open Access Journals (Sweden)

Bill eMacken

2015-03-01

Full Text Available The notion of capacity-limited processing systems is a core element of cognitive accounts of limited and variable performance, enshrined within the short-term memory construct. We begin with a detailed critical analysis of the conceptual bases of this view and argue that there are fundamental problems – ones that go to the heart of cognitivism more generally – that render it untenable. In place of limited capacity systems, we propose a framework for explaining performance that focuses on the dynamic interplay of three aspects of any given setting: the particular task that must be accomplished, the nature and form of the material upon which the task must be performed, and the repertoire of skills and perceptual-motor functions possessed by the participant. We provide empirical examples of the applications of this framework in areas of performance typically accounted for by reference to capacity-limited short-term memory processes.

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.

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

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.

Reconciling long-term cultural diversity and short-term collective social behavior.

Science.gov (United States)

Valori, Luca; Picciolo, Francesco; Allansdottir, Agnes; Garlaschelli, Diego

2012-01-24

An outstanding open problem is whether collective social phenomena occurring over short timescales can systematically reduce cultural heterogeneity in the long run, and whether offline and online human interactions contribute differently to the process. Theoretical models suggest that short-term collective behavior and long-term cultural diversity are mutually excluding, since they require very different levels of social influence. The latter jointly depends on two factors: the topology of the underlying social network and the overlap between individuals in multidimensional cultural space. However, while the empirical properties of social networks are intensively studied, little is known about the large-scale organization of real societies in cultural space, so that random input specifications are necessarily used in models. Here we use a large dataset to perform a high-dimensional analysis of the scientific beliefs of thousands of Europeans. We find that interopinion correlations determine a nontrivial ultrametric hierarchy of individuals in cultural space. When empirical data are used as inputs in models, ultrametricity has strong and counterintuitive effects. On short timescales, it facilitates a symmetry-breaking phase transition triggering coordinated social behavior. On long timescales, it suppresses cultural convergence by restricting it within disjoint groups. Moreover, ultrametricity implies that these results are surprisingly robust to modifications of the dynamical rules considered. Thus the empirical distribution of individuals in cultural space appears to systematically optimize the coexistence of short-term collective behavior and long-term cultural diversity, which can be realized simultaneously for the same moderate level of mutual influence in a diverse range of online and offline settings.

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

Science.gov (United States)

Kemps, Eva; Andrade, Jackie

2012-05-01

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

Short-term mechanisms influencing volumetric brain dynamics

NARCIS (Netherlands)

Dieleman, Nikki; Koek, Huiberdina L.; Hendrikse, Jeroen

2017-01-01

With the use of magnetic resonance imaging (MRI) and brain analysis tools, it has become possible to measure brain volume changes up to around 0.5%. Besides long-term brain changes caused by atrophy in aging or neurodegenerative disease, short-term mechanisms that influence brain volume may exist.

Short-term wavelike dynamics of bacterial populations in response to nutrient input from fresh plant residues

NARCIS (Netherlands)

Zelenev, V.V.; Bruggen, van A.H.C.; Semenov, A.M.

2005-01-01

The objectives of the research were to investigate short-term dynamics of bacterial populations in soil after a disturbance in the form of fresh organic matter incorporation and to investigate how these dynamics are linked to those of some environmental parameters. To reach these objectives, soil

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.

Short-term dynamics of second-growth mixed mesophytic forest strata in West Virginia

Science.gov (United States)

Cynthia C. Huebner; Steven L. Stephenson; Harold S. Adams; Gary W. Miller

2007-01-01

The short-term dynamics of mixed mesophytic forest strata in West Virginia were examined using similarity analysis and linear correlation of shared ordination space. The overstory tree, understory tree, shrub/vine, and herb strata were stable over a six year interval, whereas the tree seedling and sapling strata were unstable. All strata but the shrub/vine and tree...

Short- and long-term variations in non-linear dynamics of heart rate variability

DEFF Research Database (Denmark)

Kanters, J K; Højgaard, M V; Agner, E

1996-01-01

OBJECTIVES: The purpose of the study was to investigate the short- and long-term variations in the non-linear dynamics of heart rate variability, and to determine the relationships between conventional time and frequency domain methods and the newer non-linear methods of characterizing heart rate...... rate and describes mainly linear correlations. Non-linear predictability is correlated with heart rate variability measured as the standard deviation of the R-R intervals and the respiratory activity expressed as power of the high-frequency band. The dynamics of heart rate variability changes suddenly...

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....

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...

Short-term Mobility and Increased Partnership Concurrency among Men in Zimbabwe.

Directory of Open Access Journals (Sweden)

Susan Cassels

Full Text Available Migration has long been understood as an underlying factor for HIV transmission, and sexual partner concurrency has been increasingly studied as an important component of HIV transmission dynamics. However, less work has examined the role of short-term mobility in sexual partner concurrency using a network approach. Short-term mobility may be a risk for HIV for the migrant's partner as well either through the partner's risk behaviors while the migrant is away, such as the partner having additional partners, or via exposure to the return migrant.Using data from the 2010-11 Zimbabwe Demographic and Health Survey, weighted generalized linear regression models were used to investigate the associations between short-term mobility and partnership concurrency at the individual and partnership levels.At the individual level, we find strong evidence of an association between short-term mobility and concurrency. Men who traveled were more likely to have concurrent partnerships compared to men who did not travel and the relationship was non-linear: each trip was associated with a 2% higher probability of concurrency, with a diminishing risk at 60 trips (p<0.001. At the partnership level, short-term mobility by the male only or both partners was associated with male concurrency. Couples in which the female only traveled exhibited less male concurrency.Short-term mobility has the ability to impact population-level transmission dynamics by facilitating partnership concurrency and thus onward HIV transmission. Short-term migrants may be an important population to target for HIV testing, treatment, or social and behavioral interventions to prevent the spread of HIV.

Constraints on Dynamic Triggering from very Short term Microearthquake Aftershocks at Parkfield

Science.gov (United States)

Ampuero, J.; Rubin, A.

2004-12-01

The study of microearthquakes helps bridge the gap between laboratory experiments and data from large earthquakes, the two disparate scales that have contributed so far to our understanding of earthquake physics. Although they are frequent, microearthquakes are difficult to analyse. Applying high precision relocation techniques, Rubin and Gillard (2000) observed a pronounced asymmetry in the spatial distribution of the earliest and nearest aftershocks of microearthquakes along the San Andreas fault (they occur more often to the NW of the mainshock). It was suggested that this could be related to the velocity contrast across the fault. Preferred directivity of dynamic rupture pulses running along a bimaterial interface (to the SE in the case of the SAF) is expected on theoretical grounds. Our numerical simulations of crack-like rupture on such interfaces show a pronounced asymmetry of the stress histories beyond the rupture ends, and suggest two possible mechanisms for the observed asymmetry: First, that it results from an asymmmetry in the static stress field following arrest of the mainshock (closer to failure to the NW), or second, that it is due to a short-duration tensile pulse that propagates to the SE, which could reduce the number of aftershocks to the SE by dynamic triggering of any nucleation site close enough to failure to have otherwise produced an aftershock. To distinguish betwen these mechanisms we need observations of dynamic triggering in microseismicity. For small events triggered at a distance of some mainshock radii, triggering time scales are so short that seismograms of both events overlap. To detect the occurrence of compound events and very short term aftershocks in the HRSN Parkfield archived waveforms we have developed an automated search algorithm based on empirical Green's function (EGF) deconvolution. Optimal EGFs are first selected by the coherency of the cross-component convolution with respect to the target event. Then Landweber

Task set induces dynamic reallocation of resources in visual short-term memory.

Science.gov (United States)

Sheremata, Summer L; Shomstein, Sarah

2017-08-01

Successful interaction with the environment requires the ability to flexibly allocate resources to different locations in the visual field. Recent evidence suggests that visual short-term memory (VSTM) resources are distributed asymmetrically across the visual field based upon task demands. Here, we propose that context, rather than the stimulus itself, determines asymmetrical distribution of VSTM resources. To test whether context modulates the reallocation of resources to the right visual field, task set, defined by memory-load, was manipulated to influence visual short-term memory performance. Performance was measured for single-feature objects embedded within predominantly single- or two-feature memory blocks. Therefore, context was varied to determine whether task set directly predicts changes in visual field biases. In accord with the dynamic reallocation of resources hypothesis, task set, rather than aspects of the physical stimulus, drove improvements in performance in the right- visual field. Our results show, for the first time, that preparation for upcoming memory demands directly determines how resources are allocated across the visual field.

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.

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.

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.

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...

Factors in Outcomes of Short-Term Dynamic Psychotherapy for Chronic vs. Nonchronic Major Depression

Science.gov (United States)

LUBORSKY, LESTER; DIGUER, LOUIS; CACCIOLA, JOHN; BARBER, JACQUES P.; MORAS, KARLA; SCHMIDT, KELLY; DERUBEIS, ROBERT J.

1996-01-01

The benefits, and variables influencing the benefits, of short-term dynamic psychotherapy for chronic major depression versus nonchronic major depression were examined for 49 patients. The two diagnostic groups started at the same level on the Beck Depression Inventory (BDI) and Global Assessment of Functioning Scale (GAF) and benefited similarly. The bases for the benefits were examined by linear models explaining 35% of termination BDI variance and 47% of termination GAF scores. By far the largest contributor to outcome was initial GAF, followed by presence of more than one comorbid Axis I diagnosis. Initial level of depression on the BDI was not a significant predictor of termination BDI. The chronic/ nonchronic distinction accounted for less than 1% of explained variance, and little was added by personality disorder, age, or gender. PMID:22700274

Simulating the Effects of Short-Term Synaptic Plasticity on Postsynaptic Dynamics in the Globus Pallidus

Directory of Open Access Journals (Sweden)

Moran eBrody

2013-08-01

Full Text Available The rat globus pallidus (GP is one of the nuclei of the basal ganglia and plays an important role in a variety of motor and cognitive processes. In vivo studies have shown that repetitive stimulation evokes complex modulations of GP activity. In vitro and computational studies have suggested that short-term synaptic plasticity (STP could be one of the underlying mechanisms. The current study used simplified single compartment modeling to explore the possible effect of STP on the activity of GP neurons during low and high frequency stimulation. To do this we constructed a model of a GP neuron connected to a small network of neurons from the three major input sources to GP neurons: striatum (Str, subthalamic nucleus (STN and GP collaterals. All synapses were implemented with a kinetic model of STP. The in vitro recordings of responses to low frequency repetitive stimulation were highly reconstructed, including rate changes and locking to the stimulus. Mainly involved were fast forms of plasticity which have been found at these synapses. . The simulations were qualitatively compared to a data set previously recorded in vitro in our lab. Reconstructions of experimental responses to high frequency stimulation required adding slower forms of plasticity to the STN and GP collateral synapses, as well as adding metabotropic receptors to the STN-GP synapses. These finding suggest the existence of as yet unreported slower short-term dynamics in the GP. The computational model made additional predictions about GP activity during low and high frequency stimulation that may further our understanding of the mechanisms underlying repetative stimulation of the GP.

Critical neural networks with short- and long-term plasticity

Science.gov (United States)

Michiels van Kessenich, L.; Luković, M.; de Arcangelis, L.; Herrmann, H. J.

2018-03-01

In recent years self organized critical neuronal models have provided insights regarding the origin of the experimentally observed avalanching behavior of neuronal systems. It has been shown that dynamical synapses, as a form of short-term plasticity, can cause critical neuronal dynamics. Whereas long-term plasticity, such as Hebbian or activity dependent plasticity, have a crucial role in shaping the network structure and endowing neural systems with learning abilities. In this work we provide a model which combines both plasticity mechanisms, acting on two different time scales. The measured avalanche statistics are compatible with experimental results for both the avalanche size and duration distribution with biologically observed percentages of inhibitory neurons. The time series of neuronal activity exhibits temporal bursts leading to 1 /f decay in the power spectrum. The presence of long-term plasticity gives the system the ability to learn binary rules such as xor, providing the foundation of future research on more complicated tasks such as pattern recognition.

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.

Short-horizon regulation for long-term investors

NARCIS (Netherlands)

Shi, Z.; Werker, B.J.M.

2012-01-01

We study the effects of imposing repeated short-horizon regulatory constraints on long-term investors. We show that Value-at-Risk and Expected Shortfall constraints, when imposed dynamically, lead to similar optimal portfolios and wealth distributions. We also show that, in utility terms, the costs

The relation between short-term emotion dynamics and psychological well-being: A meta-analysis.

Science.gov (United States)

Houben, Marlies; Van Den Noortgate, Wim; Kuppens, Peter

2015-07-01

Not only how good or bad people feel on average, but also how their feelings fluctuate across time is crucial for psychological health. The last 2 decades have witnessed a surge in research linking various patterns of short-term emotional change to adaptive or maladaptive psychological functioning, often with conflicting results. A meta-analysis was performed to identify consistent relationships between patterns of short-term emotion dynamics-including patterns reflecting emotional variability (measured in terms of within-person standard deviation of emotions across time), emotional instability (measured in terms of the magnitude of consecutive emotional changes), and emotional inertia of emotions over time (measured in terms of autocorrelation)-and relatively stable indicators of psychological well-being or psychopathology. We determined how such relationships are moderated by the type of emotional change, type of psychological well-being or psychopathology involved, valence of the emotion, and methodological factors. A total of 793 effect sizes were identified from 79 articles (N = 11,381) and were subjected to a 3-level meta-analysis. The results confirmed that overall, low psychological well-being co-occurs with more variable (overall ρ̂ = -.178), unstable (overall ρ̂ = -.205), but also more inert (overall ρ̂ = -.151) emotions. These effect sizes were stronger when involving negative compared with positive emotions. Moreover, the results provided evidence for consistency across different types of psychological well-being and psychopathology in their relation with these dynamical patterns, although specificity was also observed. The findings demonstrate that psychological flourishing is characterized by specific patterns of emotional fluctuations across time, and provide insight into what constitutes optimal and suboptimal emotional functioning. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

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

The (lack of) effect of dynamic visual noise on the concreteness effect in short-term memory.

Science.gov (United States)

Castellà, Judit; Campoy, Guillermo

2018-05-17

It has been suggested that the concreteness effect in short-term memory (STM) is a consequence of concrete words having more distinctive and richer semantic representations. The generation and storage of visual codes in STM could also play a crucial role on the effect because concrete words are more imaginable than abstract words. If this were the case, the introduction of a visual interference task would be expected to disrupt recall of concrete words. A Dynamic Visual Noise (DVN) display, which has been proven to eliminate the concreteness effect on long-term memory (LTM), was presented along encoding of concrete and abstract words in a STM serial recall task. Results showed a main effect of word type, with more item errors in abstract words, a main effect of DVN, which impaired global performance due to more order errors, but no interaction, suggesting that DVN did not have any impact on the concreteness effect. These findings are discussed in terms of LTM participation through redintegration processes and in terms of the language-based models of verbal STM.

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.

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.

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

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.

Behavior control in the sensorimotor loop with short-term synaptic dynamics induced by self-regulating neurons

Directory of Open Access Journals (Sweden)

Hazem eToutounji

2014-05-01

Full Text Available The behavior and skills of living systems depend on the distributed control provided by specialized and highly recurrent neural networks. Learning and memory in these systems is mediated by a set of adaptation mechanisms, known collectively as neuronal plasticity. Translating principles of recurrent neural control and plasticity to artificial agents has seen major strides, but is usually hampered by the complex interactions between the agent's body and its environment. One of the important standing issues is for the agent to support multiple stable states of behavior, so that its behavioral repertoire matches the requirements imposed by these interactions. The agent also must have the capacity to switch between these states in time scales that are comparable to those by which sensory stimulation varies. Achieving this requires a mechanism of short-term memory that allows the neurocontroller to keep track of the recent history of its input, which finds its biological counterpart in short-term synaptic plasticity. This issue is approached here by deriving synaptic dynamics in recurrent neural networks. Neurons are introduced as self-regulating units with a rich repertoire of dynamics. They exhibit homeostatic properties for certain parameter domains, which result in a set of stable states and the required short-term memory. They can also operate as oscillators, which allow them to surpass the level of activity imposed by their homeostatic operation conditions. Neural systems endowed with the derived synaptic dynamics can be utilized for the neural behavior control of autonomous mobile agents. The resulting behavior depends also on the underlying network structure, which is either engineered, or developed by evolutionary techniques. The effectiveness of these self-regulating units is demonstrated by controlling locomotion of a hexapod with eighteen degrees of freedom, and obstacle-avoidance of a wheel-driven robot.

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…

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

Conversion of short-term to long-term memory in the novel object recognition paradigm.

Science.gov (United States)

Moore, Shannon J; Deshpande, Kaivalya; Stinnett, Gwen S; Seasholtz, Audrey F; Murphy, Geoffrey G

2013-10-01

It is well-known that stress can significantly impact learning; however, whether this effect facilitates or impairs the resultant memory depends on the characteristics of the stressor. Investigation of these dynamics can be confounded by the role of the stressor in motivating performance in a task. Positing a cohesive model of the effect of stress on learning and memory necessitates elucidating the consequences of stressful stimuli independently from task-specific functions. Therefore, the goal of this study was to examine the effect of manipulating a task-independent stressor (elevated light level) on short-term and long-term memory in the novel object recognition paradigm. Short-term memory was elicited in both low light and high light conditions, but long-term memory specifically required high light conditions during the acquisition phase (familiarization trial) and was independent of the light level during retrieval (test trial). Additionally, long-term memory appeared to be independent of stress-mediated glucocorticoid release, as both low and high light produced similar levels of plasma corticosterone, which further did not correlate with subsequent memory performance. Finally, both short-term and long-term memory showed no savings between repeated experiments suggesting that this novel object recognition paradigm may be useful for longitudinal studies, particularly when investigating treatments to stabilize or enhance weak memories in neurodegenerative diseases or during age-related cognitive decline. Copyright © 2013 Elsevier Inc. All rights reserved.

Continuous Timescale Long-Short Term Memory Neural Network for Human Intent Understanding

Directory of Open Access Journals (Sweden)

Zhibin Yu

2017-08-01

Full Text Available Understanding of human intention by observing a series of human actions has been a challenging task. In order to do so, we need to analyze longer sequences of human actions related with intentions and extract the context from the dynamic features. The multiple timescales recurrent neural network (MTRNN model, which is believed to be a kind of solution, is a useful tool for recording and regenerating a continuous signal for dynamic tasks. However, the conventional MTRNN suffers from the vanishing gradient problem which renders it impossible to be used for longer sequence understanding. To address this problem, we propose a new model named Continuous Timescale Long-Short Term Memory (CTLSTM in which we inherit the multiple timescales concept into the Long-Short Term Memory (LSTM recurrent neural network (RNN that addresses the vanishing gradient problem. We design an additional recurrent connection in the LSTM cell outputs to produce a time-delay in order to capture the slow context. Our experiments show that the proposed model exhibits better context modeling ability and captures the dynamic features on multiple large dataset classification tasks. The results illustrate that the multiple timescales concept enhances the ability of our model to handle longer sequences related with human intentions and hence proving to be more suitable for complex tasks, such as intention recognition.

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

Parent-Offspring Conflict over Short-Term Mating Strategies

Directory of Open Access Journals (Sweden)

Spyroulla Georgiou

2011-12-01

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

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…

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 ...

Computer simulation of yielding supports under static and short-term dynamic load

Directory of Open Access Journals (Sweden)

Kumpyak Oleg

2018-01-01

Full Text Available Dynamic impacts that became frequent lately cause large human and economic losses, and their prevention methods are not always effective and reasonable. The given research aims at studying the way of enhancing explosion safety of building structures by means of yielding supports. The paper presents results of numerical studies of strength and deformation property of yielding supports in the shape of annular tubes under static and short-term dynamic loading. The degree of influence of yielding supports was assessed taking into account three peculiar stages of deformation: elastic; elasto-plastic; and elasto-plastic with hardening. The methodology for numerical studies performance was described using finite element analysis with program software Ansys Mechanical v17.2. It was established that rigidity of yielding supports influences significantly their stress-strain state. The research determined that with the increase in deformable elements rigidity dependence between load and deformation of the support in elastic and plastic stages have linear character. Significant reduction of the dynamic response and increase in deformation time of yielding supports were observed due to increasing the plastic component. Therefore, it allows assuming on possibility of their application as supporting units in RC beams.

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.

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

International Nuclear Information System (INIS)

Chen, Kuilin; Yu, Jie

2014-01-01

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

Calibration of short rate term structure models from bid-ask coupon bond prices

Science.gov (United States)

Gomes-Gonçalves, Erika; Gzyl, Henryk; Mayoral, Silvia

2018-02-01

In this work we use the method of maximum entropy in the mean to provide a model free, non-parametric methodology that uses only market data to provide the prices of the zero coupon bonds, and then, a term structure of the short rates. The data used consists of the prices of the bid-ask ranges of a few coupon bonds quoted in the market. The prices of the zero coupon bonds obtained in the first stage, are then used as input to solve a recursive set of equations to determine a binomial recombinant model of the short term structure of the interest rates.

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.

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.

Development of Dynamic Spent Nuclear Fuel Environmental Effect Analysis Model

International Nuclear Information System (INIS)

Jeong, Chang Joon; Ko, Won Il; Lee, Ho Hee; Cho, Dong Keun; Park, Chang Je

2010-07-01

The dynamic environmental effect evaluation model for spent nuclear fuel has been developed and incorporated into the system dynamic DANESS code. First, the spent nuclear fuel isotope decay model was modeled. Then, the environmental effects were modeled through short-term decay heat model, short-term radioactivity model, and long-term heat load model. By using the developed model, the Korean once-through nuclear fuel cycles was analyzed. The once-through fuel cycle analysis was modeled based on the Korean 'National Energy Basic Plan' up to 2030 and a postulated nuclear demand growth rate until 2150. From the once-through results, it is shown that the nuclear power demand would be ∼70 GWe and the total amount of the spent fuel accumulated by 2150 would be ∼168000 t. If the disposal starts from 2060, the short-term decay heat of Cs-137 and Sr-90 isotopes are W and 1.8x10 6 W in 2100. Also, the total long-term heat load in 2100 will be 4415 MW-y. From the calculation results, it was found that the developed model is very convenient and simple for evaluation of the environmental effect of the spent nuclear fuel

Patient affect experiencing following therapist interventions in short-term dynamic psychotherapy.

Science.gov (United States)

Town, Joel M; Hardy, Gillian E; McCullough, Leigh; Stride, Chris

2012-01-01

The aim of this research was to examine the relationship between therapist interventions and patient affect responses in Short-Term Dynamic Psychotherapy (STDP). The Affect Experiencing subscale from the Achievement of Therapeutic Objectives Scale (ATOS) was adapted to measure individual immediate affect experiencing (I-AES) responses in relation to therapist interventions coded within the preceding speaking turn, using the Psychotherapy Interaction Coding (PIC) system. A hierarchical linear modelling procedure was used to assess the change in affect experiencing and the relationship between affect experiencing and therapist interventions within and across segments of therapy. Process data was taken from six STDP cases; in total 24 hours of video-taped sessions were examined. Therapist interventions were found to account for a statistically significant amount of variance in immediate affect experiencing. Higher levels of immediate affect experiencing followed the therapist's use of Confrontation, Clarification and Support compared to Questions, Self-disclosure and Information interventions. Therapist Confrontation interventions that attempted to direct pressure towards either the visceral experience of affect or a patient's defences against feelings led to the highest levels of immediate affect experiencing. The type of therapist intervention accounts for a small but significant amount of the variation observed in a patient's immediate emotional arousal. Empirical findings support clinical theory in STDP that suggests strategic verbal responses promote the achievement of this specific therapeutic objective.

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.

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.

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

Revisiting short-term price and volatility dynamics in day-ahead electricity markets with rising wind power

International Nuclear Information System (INIS)

Li, Yuanjing

2015-01-01

This paper revisits the short-term price and volatility dynamics in day-ahead electricity markets in consideration of an increasing share of wind power, using an example of the Nord Pool day-ahead market and the Danish wind generation. To do so, a GARCH process is applied, and market coupling and the counterbalance effect of hydropower in the Scandinavian countries are additionally accounted for. As results, we found that wind generation weakly dampens spot prices with an elasticity of 0.008 and also reduces price volatility with an elasticity of 0.02 in the Nordic day-ahead market. The results shed lights on the importance of market coupling and interactions between wind power and hydropower in the Nordic system through cross-border exchanges, which play an essential role in price stabilization. Additionally, an EGARCH specification confirms an asymmetric influence of the price innovations, whereby negative shocks produce larger volatility in the Nordic spot market. While considering heavy tails in error distributions can improve model fits significantly, the EGARCH model outperforms the GARCH model on forecast evaluations. (author)

Smart Demand for Improving Short-term Voltage Control on Distribution Networks

DEFF Research Database (Denmark)

Garcia-Valle, Rodrigo; P. Da Silva, Luiz C.; Xu, Zhao

2009-01-01

customer integration to aid power system performance is almost inevitable. This study introduces a new type of smart demand side technology, denoted demand as voltage controlled reserve (DVR), to improve short-term voltage control, where customers are expected to play a more dynamic role to improve voltage...... control. The technology can be provided by thermostatically controlled loads as well as other types of load. This technology is proven to be effective in case of distribution systems with a large composition of induction motors, where the voltage presents a slow recovery characteristic due to deceleration...... of the motors during faults. This study presents detailed models, discussion and simulation tests to demonstrate the technical viability and effectiveness of the DVR technology for short-term voltage control....

Role of short-term dispersal on the dynamics of Zika virus in an extreme idealized environment

Directory of Open Access Journals (Sweden)

Victor M. Moreno

2017-02-01

Full Text Available In November 2015, El Salvador reported their first case of Zika virus (ZIKV infection, an event followed by an explosive outbreak that generated over 6000 suspected cases in a period of two months. National agencies began implementing control measures that included vector control and recommending an increased use of repellents. Further, in response to the alarming and growing number of microcephaly cases in Brazil, the importance of avoiding pregnancies for two years was stressed. In this paper, we explore the role of mobility within communities characterized by extreme poverty, crime and violence. Specifically, the role of short term mobility between two idealized interconnected highly distinct communities is explored in the context of ZIKV outbreaks. We make use of a Lagrangian modeling approach within a two-patch setting in order to highlight the possible effects that short-term mobility, within highly distinct environments, may have on the dynamics of ZIKV outbreak when the overall goal is to reduce the number of cases not just in the most affluent areas but everywhere. Outcomes depend on existing mobility patterns, levels of disease risk, and the ability of federal or state public health services to invest in resource limited areas, particularly in those where violence is systemic. The results of simulations in highly polarized and simplified scenarios are used to assess the role of mobility. It quickly became evident that matching observed patterns of ZIKV outbreaks could not be captured without incorporating increasing levels of heterogeneity. The number of distinct patches and variations on patch connectivity structure required to match ZIKV patterns could not be met within the highly aggregated model that is used in the simulations. Keywords: Vector-borne diseases, Zika virus, Residence times, Multi-patch model

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.

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)

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.

Short-term exposure to a synthetic estrogen disrupts mating dynamics in a pipefish.

Science.gov (United States)

Partridge, Charlyn; Boettcher, Anne; Jones, Adam G

2010-11-01

Sexual selection is responsible for the evolution of some of the most elaborate traits occurring in nature, many of which play a vital role in competition over access to mates and individual reproductive fitness. Because expression of these traits is typically regulated by sex-steroids there is a significant potential for their expression to be affected by the presence of certain pollutants, such as endocrine disrupting compounds. Endocrine disruptors have been shown to alter primary sexual traits and impact reproduction, but few studies have investigated how these compounds affect secondary sexual trait expression and how that may, in turn, impact mating dynamics. In this study we examine how short-term exposure to a synthetic estrogen impacts secondary sexual trait expression and mating dynamics in the Gulf pipefish, a species displaying sex-role reversal. Our results show that only 10days of exposure to 17α-ethinylestradiol results in adult male pipefish developing female-like secondary sexual traits. While these males are capable of reproduction, females discriminate against exposed males in mate choice trials. In natural populations, this type of discrimination would reduce male mating opportunities, thus potentially reducing their long-term reproductive success. Importantly, the effects of these compounds on mating dynamics and mating opportunity would not be observed using the current standard methods of assessing environmental contamination. However, disrupting these processes could have profound effects on the viability of exposed populations. Copyright © 2010 Elsevier Inc. All rights reserved.

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.

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.

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)

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

International Nuclear Information System (INIS)

Wolter, H.

1990-01-01

For the first time, the modeling of long-term quantitative conditions within the short-term planning of the application of power stations is made via their shadow prices. It corresponds to a decomposition of the quantitative conditions by means of the method of the Langrange relaxation. The shadow prices determined by the planning for energy application regarding long- term quantitative conditions pass into the short-term planning for power station application and subsidize or rather punish the application of limited amounts as for as they are not claimed for sufficiently or excessively. The clear advantage of this modeling is that the short-term planning of power station application can deviate from the envisioned energy application regarding the total optimum, because the shadow prices contain all information about the cost effect of the energy shifts in the residual total period, which become necessary due to the deviations in the short-term period to be planned in the current short-term period. (orig./DG) [de

Social evolution and genetic interactions in the short and long term.

Science.gov (United States)

Van Cleve, Jeremy

2015-08-01

The evolution of social traits remains one of the most fascinating and feisty topics in evolutionary biology even after half a century of theoretical research. W.D. Hamilton shaped much of the field initially with his 1964 papers that laid out the foundation for understanding the effect of genetic relatedness on the evolution of social behavior. Early theoretical investigations revealed two critical assumptions required for Hamilton's rule to hold in dynamical models: weak selection and additive genetic interactions. However, only recently have analytical approaches from population genetics and evolutionary game theory developed sufficiently so that social evolution can be studied under the joint action of selection, mutation, and genetic drift. We review how these approaches suggest two timescales for evolution under weak mutation: (i) a short-term timescale where evolution occurs between a finite set of alleles, and (ii) a long-term timescale where a continuum of alleles are possible and populations evolve continuously from one monomorphic trait to another. We show how Hamilton's rule emerges from the short-term analysis under additivity and how non-additive genetic interactions can be accounted for more generally. This short-term approach reproduces, synthesizes, and generalizes many previous results including the one-third law from evolutionary game theory and risk dominance from economic game theory. Using the long-term approach, we illustrate how trait evolution can be described with a diffusion equation that is a stochastic analogue of the canonical equation of adaptive dynamics. Peaks in the stationary distribution of the diffusion capture classic notions of convergence stability from evolutionary game theory and generally depend on the additive genetic interactions inherent in Hamilton's rule. Surprisingly, the peaks of the long-term stationary distribution can predict the effects of simple kinds of non-additive interactions. Additionally, the peaks

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-05-17

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

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...

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…

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.

The role of model dynamics in ensemble Kalman filter performance for chaotic systems

Science.gov (United States)

Ng, G.-H.C.; McLaughlin, D.; Entekhabi, D.; Ahanin, A.

2011-01-01

The ensemble Kalman filter (EnKF) is susceptible to losing track of observations, or 'diverging', when applied to large chaotic systems such as atmospheric and ocean models. Past studies have demonstrated the adverse impact of sampling error during the filter's update step. We examine how system dynamics affect EnKF performance, and whether the absence of certain dynamic features in the ensemble may lead to divergence. The EnKF is applied to a simple chaotic model, and ensembles are checked against singular vectors of the tangent linear model, corresponding to short-term growth and Lyapunov vectors, corresponding to long-term growth. Results show that the ensemble strongly aligns itself with the subspace spanned by unstable Lyapunov vectors. Furthermore, the filter avoids divergence only if the full linearized long-term unstable subspace is spanned. However, short-term dynamics also become important as non-linearity in the system increases. Non-linear movement prevents errors in the long-term stable subspace from decaying indefinitely. If these errors then undergo linear intermittent growth, a small ensemble may fail to properly represent all important modes, causing filter divergence. A combination of long and short-term growth dynamics are thus critical to EnKF performance. These findings can help in developing practical robust filters based on model dynamics. ?? 2011 The Authors Tellus A ?? 2011 John Wiley & Sons A/S.

Insensitivity of visual short-term memory to irrelevant visual information

OpenAIRE

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

2002-01-01

Several authors have hypothesised 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, 1996a). Experiment 1 replicated the effect of DVN on pegword imagery. Experiments 2 and 3 showed no effect of ...

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.

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

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...

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

Development of Dynamic Environmental Effect Calculation Model

International Nuclear Information System (INIS)

Jeong, Chang Joon; Ko, Won Il

2010-01-01

The short-term, long-term decay heat, and radioactivity are considered as main environmental parameters of SF and HLA. In this study, the dynamic calculation models for radioactivity, short-term decay heat, and long-term heat load of the SF are developed and incorporated into the Doneness code. The spent fuel accumulation has become a major issue for sustainable operation of nuclear power plants. If a once-through fuel cycle is selected, the SF will be disposed into the repository. Otherwise, in case of fast reactor or reuse cycle, the SF will be reprocessed and the high level waste will be disposed

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.

Short term and medium term power distribution load forecasting by neural networks

International Nuclear Information System (INIS)

Yalcinoz, T.; Eminoglu, U.

2005-01-01

Load forecasting is an important subject for power distribution systems and has been studied from different points of view. In general, load forecasts should be performed over a broad spectrum of time intervals, which could be classified into short term, medium term and long term forecasts. Several research groups have proposed various techniques for either short term load forecasting or medium term load forecasting or long term load forecasting. This paper presents a neural network (NN) model for short term peak load forecasting, short term total load forecasting and medium term monthly load forecasting in power distribution systems. The NN is used to learn the relationships among past, current and future temperatures and loads. The neural network was trained to recognize the peak load of the day, total load of the day and monthly electricity consumption. The suitability of the proposed approach is illustrated through an application to real load shapes from the Turkish Electricity Distribution Corporation (TEDAS) in Nigde. The data represents the daily and monthly electricity consumption in Nigde, Turkey

Turkey's short-term gross annual electricity demand forecast by fuzzy logic approach

International Nuclear Information System (INIS)

Kucukali, Serhat; Baris, Kemal

2010-01-01

This paper aims to forecast Turkey's short-term gross annual electricity demand by applying fuzzy logic methodology while general information on economical, political and electricity market conditions of the country is also given. Unlike most of the other forecast models about Turkey's electricity demand, which usually uses more than one parameter, gross domestic product (GDP) based on purchasing power parity was the only parameter used in the model. Proposed model made good predictions and captured the system dynamic behavior covering the years of 1970-2014. The model yielded average absolute relative errors of 3.9%. Furthermore, the model estimates a 4.5% decrease in electricity demand of Turkey in 2009 and the electricity demand growth rates are projected to be about 4% between 2010 and 2014. It is concluded that forecasting the Turkey's short-term gross electricity demand with the country's economic performance will provide more reliable projections. Forecasting the annual electricity consumption of a country could be made by any designer with the help of the fuzzy logic procedure described in this paper. The advantage of this model lies on the ability to mimic the human thinking and reasoning.

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.

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

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.

The Achievement of Therapeutic Objectives Scale: Interrater Reliability and Sensitivity to Change in Short-Term Dynamic Psychotherapy and Cognitive Therapy

Science.gov (United States)

Valen, Jakob; Ryum, Truls; Svartberg, Martin; Stiles, Tore C.; McCullough, Leigh

2011-01-01

This study examined interrater reliability and sensitivity to change of the Achievement of Therapeutic Objectives Scale (ATOS; McCullough, Larsen, et al., 2003) in short-term dynamic psychotherapy (STDP) and cognitive therapy (CT). The ATOS is a process scale originally developed to assess patients' achievements of treatment objectives in STDP,…

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.

Panorama 2012 - Short-term trends in the gas industry

International Nuclear Information System (INIS)

Lecarpentier, Armelle

2011-12-01

Against the background of an energy market beset by the Fukushima crisis, the Arab spring and economic uncertainty, 2011 saw dynamic growth in demand for natural gas, although developments varied widely from region to region. New trends are emerging in the gas market, and these will have both short-term and longer-term impacts on how the industry develops. (author)

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.

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.

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

A Spatiotemporal Multi-View-Based Learning Method for Short-Term Traffic Forecasting

Directory of Open Access Journals (Sweden)

Shifen Cheng

2018-06-01

Full Text Available Short-term traffic forecasting plays an important part in intelligent transportation systems. Spatiotemporal k-nearest neighbor models (ST-KNNs have been widely adopted for short-term traffic forecasting in which spatiotemporal matrices are constructed to describe traffic conditions. The performance of the models is closely related to the spatial dependencies, the temporal dependencies, and the interaction of spatiotemporal dependencies. However, these models use distance functions and correlation coefficients to identify spatial neighbors and measure the temporal interaction by only considering the temporal closeness of traffic, which result in existing ST-KNNs that cannot fully reflect the essential features of road traffic. This study proposes an improved spatiotemporal k-nearest neighbor model for short-term traffic forecasting by utilizing a multi-view learning algorithm named MVL-STKNN that fully considers the spatiotemporal dependencies of traffic data. First, the spatial neighbors for each road segment are automatically determined using cross-correlation under different temporal dependencies. Three spatiotemporal views are built on the constructed spatiotemporal closeness, periodic, and trend matrices to represent spatially heterogeneous traffic states. Second, a spatiotemporal weighting matrix is introduced into the ST-KNN model to recognize similar traffic patterns in the three spatiotemporal views. Finally, the results of traffic pattern recognition under these three spatiotemporal views are aggregated by using a neural network algorithm to describe the interaction of spatiotemporal dependencies. Extensive experiments were conducted using real vehicular-speed datasets collected on city roads and expressways. In comparison with baseline methods, the results show that the MVL-STKNN model greatly improves short-term traffic forecasting by lowering the mean absolute percentage error between 28.24% and 46.86% for the city road dataset and

Critical dynamics of the Potts model: short-time Monte Carlo simulations

International Nuclear Information System (INIS)

Silva, Roberto da; Drugowich de Felicio, J.R.

2004-01-01

We calculate the new dynamic exponent θ of the 4-state Potts model, using short-time simulations. Our estimates θ1=-0.0471(33) and θ2=-0.0429(11) obtained by following the behavior of the magnetization or measuring the evolution of the time correlation function of the magnetization corroborate the conjecture by Okano et al. [Nucl. Phys. B 485 (1997) 727]. In addition, these values agree with previous estimate of the same dynamic exponent for the two-dimensional Ising model with three-spin interactions in one direction, that is known to belong to the same universality class as the 4-state Potts model. The anomalous dimension of initial magnetization x0=zθ+β/ν is calculated by an alternative way that mixes two different initial conditions. We have also estimated the values of the static exponents β and ν. They are in complete agreement with the pertinent results of the literature

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.

Compromise between Short- and Long-Term Financial Sustainability: A Hybrid Model for Supporting R&D Decisions

Directory of Open Access Journals (Sweden)

Kao-Yi Shen

2017-03-01

Full Text Available The debate of “short-termism” has gained increasing interests from various fields, ranging from management to economics; it mainly concerns the decisions or actions taken by businesses that might yield short-term returns at the cost of long-term value or sustainability. Previous studies have highlighted this dilemma faced by managers, mainly from the pressure of capital markets or short-sighted shareholders who crave for immediate financial outcomes; intelligent decision aids that can compromise between the short- and long-term financial sustainability, based on a company’s policy, are highly needed. Therefore, the aim of this study is to develop a multiple-rule-based hybrid decision model to support management teams on prioritizing new R&D projects, considering the financial prospects in dual timeframes (i.e., short- and long-term for sustainability. Furthermore, in the presence of business uncertainty and the limited knowledge of managers on new projects, the intuitionistic fuzzy technique is incorporated. A case of selecting new R&D projects for an IC design company is illustrated using the proposed approach, and the financial data from a group of public-listed IC stocks from Taiwan are inducted to form the decision model. The findings not only support the IC design company to select new projects but also provide business insights to facilitate the understandings of this controversial issue in managerial practice.

Identifying attachment ruptures underlying severe music performance anxiety in a professional musician undertaking an assessment and trial therapy of Intensive Short-Term Dynamic Psychotherapy (ISTDP).

Science.gov (United States)

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

2016-01-01

Kenny has proposed that severe music performance anxiety that is unresponsive to usual treatments such as cognitive-behaviour therapy may be one manifestation of unresolved attachment ruptures in early life. Intensive Short-Term Dynamic Psychotherapy specifically targets early relationship trauma. Accordingly, a trial of Intensive Short-Term Dynamic Psychotherapy with severely anxious musicians was implemented to assess whether resolution of attachment ruptures resulted in clinically significant relief from music performance anxiety. Volunteer musicians participating in a nationally funded study were screened for MPA severity. Those meeting the critical cut-off score on the Kenny Music Performance Anxiety Inventory were offered a trial of Intensive Short-Term Dynamic Psychotherapy. In this paper, we present the theoretical foundations and rationale for the treatment approach, followed by sections of a verbatim transcript and process analysis of the assessment phase of treatment that comprised a 3-h trial therapy session. The 'case' was a professional orchestral musician (male, aged 55) who had suffered severe music performance anxiety over the course of his entire career, which spanned more than 30 years at the time he presented for treatment following his failure to secure a position at audition. The participant was able to access the pain, rage and grief associated with unresolved attachment ruptures with both parents that demonstrated the likely nexus between early attachment trauma and severe music performance anxiety. Intensive Short-Term Dynamic Psychotherapy is a potentially cost-effective treatment for severe music performance anxiety. Further research using designs with higher levels of evidence are required before clinical recommendations can be made for the use of this therapy with this population.

Short-term and long-term Interconnectedness of stock returns in Western Europe and the global market

OpenAIRE

Panda, Ajaya Kumar; Nanda, Swagatika

2017-01-01

Background: The present study examines the short term dynamics and long term equilibrium relationship among the stock markets of 17 countries in Western Europe as well as the world market, using time series techniques. Methods: Weekly returns of market benchmark indices of the respective countries are used from the second week of 1995 to the fourth week of December 2013. Results: The study finds that the market returns of Austria, Belgium, the Netherlands, and France are relatively less dynam...

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.

Effective description of the short-time dynamics in open quantum systems

Science.gov (United States)

Rossi, Matteo A. C.; Foti, Caterina; Cuccoli, Alessandro; Trapani, Jacopo; Verrucchi, Paola; Paris, Matteo G. A.

2017-09-01

We address the dynamics of a bosonic system coupled to either a bosonic or a magnetic environment and derive a set of sufficient conditions that allow one to describe the dynamics in terms of the effective interaction with a classical fluctuating field. We find that for short interaction times the dynamics of the open system is described by a Gaussian noise map for several different interaction models and independently on the temperature of the environment. In order to go beyond a qualitative understanding of the origin and physical meaning of the above short-time constraint, we take a general viewpoint and, based on an algebraic approach, suggest that any quantum environment can be described by classical fields whenever global symmetries lead to the definition of environmental operators that remain well defined when increasing the size, i.e., the number of dynamical variables, of the environment. In the case of the bosonic environment this statement is exactly demonstrated via a constructive procedure that explicitly shows why a large number of environmental dynamical variables and, necessarily, global symmetries, entail the set of conditions derived in the first part of the work.

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.

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.

Modelling short and long-term risks in power markets: Empirical evidence from Nord Pool

International Nuclear Information System (INIS)

Nomikos, Nikos K.; Soldatos, Orestes A.

2010-01-01

In this paper we propose a three-factor spike model that accounts for different speeds of mean reversion between normal and spiky shocks in the Scandinavian power market. In this model both short and long-run factors are unobservable and are hence estimated as latent variables using the Kalman filter. The proposed model has several advantages. First, it seems to capture in a parsimonious way the most important risks that practitioners face in the market, such as spike risk, short-term risk and long-term risk. Second, it explains the seasonal risk premium observed in the market and improves the fit between theoretical and observed forward prices, particularly for long-dated forward contracts. Finally, closed-form solutions for forward contracts, derived from the model, are consistent with the fact that the correlation between contracts of different maturities is imperfect. The resulting model is very promising, providing a very useful policy analysis and financial engineering tool to market participants for risk management and derivative pricing particularly for long-dated contracts.

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.

Modeling the Interest Rate Term Structure: Derivatives Contracts Dynamics and Evaluation

Directory of Open Access Journals (Sweden)

Pedro L. Valls Pereira

2005-06-01

Full Text Available This article deals with a model for the term structure of interest rates and the valuation of derivative contracts directly dependent on it. The work is of a theoretical nature and deals, exclusively, with continuous time models, making ample use of stochastic calculus results and presents original contributions that we consider relevant to the development of the fixed income market modeling. We develop a new multifactorial model of the term structure of interest rates. The model is based on the decomposition of the yield curve into the factors level, slope, curvature, and the treatment of their collective dynamics. We show that this model may be applied to serve various objectives: analysis of bond price dynamics, valuation of derivative contracts and also market risk management and formulation of operational strategies which is presented in another article.

Short- and long-term evolutionary dynamics of bacterial insertion sequences: insights from Wolbachia endosymbionts.

Science.gov (United States)

Cerveau, Nicolas; Leclercq, Sébastien; Leroy, Elodie; Bouchon, Didier; Cordaux, Richard

2011-01-01

Transposable elements (TE) are one of the major driving forces of genome evolution, raising the question of the long-term dynamics underlying their evolutionary success. Long-term TE evolution can readily be reconstructed in eukaryotes, thanks to many degraded copies constituting genomic fossil records of past TE proliferations. By contrast, bacterial genomes usually experience high sequence turnover and short TE retention times, thereby obscuring ancient TE evolutionary patterns. We found that Wolbachia bacterial genomes contain 52-171 insertion sequence (IS) TEs. IS account for 11% of Wolbachia wRi, which is one of the highest IS genomic coverage reported in prokaryotes to date. We show that many IS groups are currently expanding in various Wolbachia genomes and that IS horizontal transfers are frequent among strains, which can explain the apparent synchronicity of these IS proliferations. Remarkably, >70% of Wolbachia IS are nonfunctional. They constitute an unusual bacterial IS genomic fossil record providing direct empirical evidence for a long-term IS evolutionary dynamics following successive periods of intense transpositional activity. Our results show that comprehensive IS annotations have the potential to provide new insights into prokaryote TE evolution and, more generally, prokaryote genome evolution. Indeed, the identification of an important IS genomic fossil record in Wolbachia demonstrates that IS elements are not always of recent origin, contrary to the conventional view of TE evolution in prokaryote genomes. Our results also raise the question whether the abundance of IS fossils is specific to Wolbachia or it may be a general, albeit overlooked, feature of prokaryote genomes.

A rotated Dynamic Nelson-Siegel model with macro-financial applications

OpenAIRE

Nyholm, Ken

2015-01-01

A factor rotation scheme is applied to the well-known Dynamic Nelson-Siegel model facilitating direct parametrization of the short rate process. The model-implied term structure of term premia is derived in closed-form, and macroeconomic variables are included in a Taylor-rule- type fashion. Four empirical experiments are performed on US data covering the period from 1990 to 2014. It is found that macroeconomic variables impact the evolution of the short rate until 2002, after which their eff...

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.

Intrinsic dynamics of heart regulatory systems on short timescales: from experiment to modelling

International Nuclear Information System (INIS)

Khovanov, I A; Khovanova, N A; McClintock, P V E; Stefanovska, A

2009-01-01

We discuss open problems related to the stochastic modelling of cardiac function. The work is based on an experimental investigation of the dynamics of heart rate variability (HRV) in the absence of respiratory perturbations. We consider first the cardiac control system on short timescales via an analysis of HRV within the framework of a random walk approach. Our experiments show that HRV on timescales of less than a minute takes the form of free diffusion, close to Brownian motion, which can be described as a non-stationary process with stationary increments. Secondly, we consider the inverse problem of modelling the state of the control system so as to reproduce the experimentally observed HRV statistics of. We discuss some simple toy models and identify open problems for the modelling of heart dynamics

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.

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

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.

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.

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)

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.…

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…

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).

Dynamic behavior of HTSC opening switch models controlled by short over-critical current pulses

International Nuclear Information System (INIS)

Agafonov, A.V.; Krastelev, E.G.; Voronin, V.S.

1999-01-01

We present results of experimental research of dynamical properties of thin films of YBa 2 Cu 3 O 7 HTSC-switch models under action of short overcritical current pulses to test this method of control of fast high-power opening switches for accelerator applications

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).

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.

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...

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.

[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

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

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.

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.

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

Neural dynamics underlying attentional orienting to auditory representations in short-term memory.

Science.gov (United States)

Backer, Kristina C; Binns, Malcolm A; Alain, Claude

2015-01-21

Sounds are ephemeral. Thus, coherent auditory perception depends on "hearing" back in time: retrospectively attending that which was lost externally but preserved in short-term memory (STM). Current theories of auditory attention assume that sound features are integrated into a perceptual object, that multiple objects can coexist in STM, and that attention can be deployed to an object in STM. Recording electroencephalography from humans, we tested these assumptions, elucidating feature-general and feature-specific neural correlates of auditory attention to STM. Alpha/beta oscillations and frontal and posterior event-related potentials indexed feature-general top-down attentional control to one of several coexisting auditory representations in STM. Particularly, task performance during attentional orienting was correlated with alpha/low-beta desynchronization (i.e., power suppression). However, attention to one feature could occur without simultaneous processing of the second feature of the representation. Therefore, auditory attention to memory relies on both feature-specific and feature-general neural dynamics. Copyright © 2015 the authors 0270-6474/15/351307-12$15.00/0.

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.

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.

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

International Nuclear Information System (INIS)

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

2008-01-01

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

Turkey's short-term gross annual electricity demand forecast by fuzzy logic approach

Energy Technology Data Exchange (ETDEWEB)

Kucukali, Serhat [Civil Engineering Department, Zonguldak Karaelmas University, Incivez 67100, Zonguldak (Turkey); Baris, Kemal [Mining Engineering Department, Zonguldak Karaelmas University, Incivez 67100, Zonguldak (Turkey)

2010-05-15

This paper aims to forecast Turkey's short-term gross annual electricity demand by applying fuzzy logic methodology while general information on economical, political and electricity market conditions of the country is also given. Unlike most of the other forecast models about Turkey's electricity demand, which usually uses more than one parameter, gross domestic product (GDP) based on purchasing power parity was the only parameter used in the model. Proposed model made good predictions and captured the system dynamic behavior covering the years of 1970-2014. The model yielded average absolute relative errors of 3.9%. Furthermore, the model estimates a 4.5% decrease in electricity demand of Turkey in 2009 and the electricity demand growth rates are projected to be about 4% between 2010 and 2014. It is concluded that forecasting the Turkey's short-term gross electricity demand with the country's economic performance will provide more reliable projections. Forecasting the annual electricity consumption of a country could be made by any designer with the help of the fuzzy logic procedure described in this paper. The advantage of this model lies on the ability to mimic the human thinking and reasoning. (author)

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

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.

Short-term variability of CYG X-1

International Nuclear Information System (INIS)

Oda, M.; Doi, K.; Ogawara, Y.; Takagishi, K.; Wada, M.

1975-01-01

The short-term X-ray variability distinguishes Cyg X-1, which is the most likely candidate of the black hole, from other X-ray sources. Present status of our knowledge on this short-term variation mainly from the Uhuru, the MIT and the GSFC observations is reviewed. The nature of impulsive variations which compose the time variation exceeding the statistical fluctuation is discussed. There are indications that the energy spectrum of large pulses is harder than the average spectrum or the large pulses are the characteristics of the hard component of the spectrum if it is composed of two, soft and hard, components. Features of the variations may be partly simulated by the superposition of random short-noise pulses with a fraction of a second duration. However, the autocorrelation analysis and the dynamic spectrum analysis indicate that the correlation lasts for several seconds and in the variation buried are some regularities which exhibit power concentrations in several frequency bands; 0.2 -- 0.3, 0.4 -- 0.5, 0.8, 1.2 -- 1.5 Hz. There are several possible interpretation of these results in terms of: e.g. a) a mixture of short-noise pulses with two or more constant durations, b) the shape of the basic shot-noise pulse, c) bunching of the pulses, d) superposition of wave-packets or temporal oscillations. But we have not yet reached any definite understandings in the nature of the variabilities. The sub-structure of the fluctuations on a time scale of milli-second suggested by two investigations is also discussed. (auth.)

A generalized one-factor term structure model and pricing of interest rate derivative securities

NARCIS (Netherlands)

Jiang, George J.

1997-01-01

The purpose of this paper is to propose a nonparametric interest rate term structure model and investigate its implications on term structure dynamics and prices of interest rate derivative securities. The nonparametric spot interest rate process is estimated from the observed short-term interest

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.

Short-Term and Long-Term Educational Mobility of Families: A Two-Sex Approach.

Science.gov (United States)

Song, Xi; Mare, Robert D

2017-02-01

We use a multigenerational perspective to investigate how families reproduce and pass their educational advantages to succeeding generations. Unlike traditional mobility studies that have typically focused on one-sex influences from fathers to sons, we rely on a two-sex approach that accounts for interactions between males and females-the process in which males and females mate and have children with those of similar educational statuses and jointly determine the educational status attainment of their offspring. Using data from the Panel Study of Income Dynamics, we approach this issue from both a short-term and a long-term perspective. For the short term, grandparents' educational attainments have a direct association with grandchildren's education as well as an indirect association that is mediated by parents' education and demographic behaviors. For the long term, initial educational advantages of families may benefit as many as three subsequent generations, but such advantages are later offset by the lower fertility of highly educated persons. Yet, all families eventually achieve the same educational distribution of descendants because of intermarriages between families of high- and low-education origin.

Short-term wind power combined forecasting based on error forecast correction

International Nuclear Information System (INIS)

Liang, Zhengtang; Liang, Jun; Wang, Chengfu; Dong, Xiaoming; Miao, Xiaofeng

2016-01-01

Highlights: • The correlation relationships of short-term wind power forecast errors are studied. • The correlation analysis method of the multi-step forecast errors is proposed. • A strategy selecting the input variables for the error forecast models is proposed. • Several novel combined models based on error forecast correction are proposed. • The combined models have improved the short-term wind power forecasting accuracy. - Abstract: With the increasing contribution of wind power to electric power grids, accurate forecasting of short-term wind power has become particularly valuable for wind farm operators, utility operators and customers. The aim of this study is to investigate the interdependence structure of errors in short-term wind power forecasting that is crucial for building error forecast models with regression learning algorithms to correct predictions and improve final forecasting accuracy. In this paper, several novel short-term wind power combined forecasting models based on error forecast correction are proposed in the one-step ahead, continuous and discontinuous multi-step ahead forecasting modes. First, the correlation relationships of forecast errors of the autoregressive model, the persistence method and the support vector machine model in various forecasting modes have been investigated to determine whether the error forecast models can be established by regression learning algorithms. Second, according to the results of the correlation analysis, the range of input variables is defined and an efficient strategy for selecting the input variables for the error forecast models is proposed. Finally, several combined forecasting models are proposed, in which the error forecast models are based on support vector machine/extreme learning machine, and correct the short-term wind power forecast values. The data collected from a wind farm in Hebei Province, China, are selected as a case study to demonstrate the effectiveness of the proposed

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.

Short-term adaptations as a response to travel time: results of a stated adaptation experimentincreases

NARCIS (Netherlands)

Psarra, I.; Arentze, T.A.; Timmermans, H.J.P.

2016-01-01

This study focused on short-term dynamics of activity-travel behavior as a response to travel time increases. It is assumed that short-term changes are triggered by stress, which is defined as the deviation between an individual’s aspirations and his or her daily experiences. When stress exceeds a

The interaction of short-term and long-term memory in phonetic category formation

Science.gov (United States)

Harnsberger, James D.

2002-05-01

This study examined the role that short-term memory capacity plays in the relationship between novel stimuli (e.g., non-native speech sounds, native nonsense words) and phonetic categories in long-term memory. Thirty native speakers of American English were administered five tests: categorial AXB discrimination using nasal consonants from Malayalam; categorial identification, also using Malayalam nasals, which measured the influence of phonetic categories in long-term memory; digit span; nonword span, a short-term memory measure mediated by phonetic categories in long-term memory; and paired-associate word learning (word-word and word-nonword pairs). The results showed that almost all measures were significantly correlated with one another. The strongest predictor for the discrimination and word-nonword learning results was nonword (r=+0.62) and digit span (r=+0.51), respectively. When the identification test results were partialed out, only nonword span significantly correlated with discrimination. The results show a strong influence of short-term memory capacity on the encoding of phonetic detail within phonetic categories and suggest that long-term memory representations regulate the capacity of short-term memory to preserve information for subsequent encoding. The results of this study will also be discussed with regards to resolving the tension between episodic and abstract models of phonetic category structure.

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.

Spatiotemporal discrimination in neural networks with short-term synaptic plasticity

Science.gov (United States)

Shlaer, Benjamin; Miller, Paul

2015-03-01

Cells in recurrently connected neural networks exhibit bistability, which allows for stimulus information to persist in a circuit even after stimulus offset, i.e. short-term memory. However, such a system does not have enough hysteresis to encode temporal information about the stimuli. The biophysically described phenomenon of synaptic depression decreases synaptic transmission strengths due to increased presynaptic activity. This short-term reduction in synaptic strengths can destabilize attractor states in excitatory recurrent neural networks, causing the network to move along stimulus dependent dynamical trajectories. Such a network can successfully separate amplitudes and durations of stimuli from the number of successive stimuli. Stimulus number, duration and intensity encoding in randomly connected attractor networks with synaptic depression. Front. Comput. Neurosci. 7:59., and so provides a strong candidate network for the encoding of spatiotemporal information. Here we explicitly demonstrate the capability of a recurrent neural network with short-term synaptic depression to discriminate between the temporal sequences in which spatial stimuli are presented.

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

Short-term memory in the service of executive control functions

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Farshad Alizadeh Mansouri

2015-12-01

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

Short-term wind power forecasting: probabilistic and space-time aspects

DEFF Research Database (Denmark)

Tastu, Julija

work deals with the proposal and evaluation of new mathematical models and forecasting methods for short-term wind power forecasting, accounting for space-time dynamics based on geographically distributed information. Different forms of power predictions are considered, starting from traditional point...... into the corresponding models are analysed. As a final step, emphasis is placed on generating space-time trajectories: this calls for the prediction of joint multivariate predictive densities describing wind power generation at a number of distributed locations and for a number of successive lead times. In addition......Optimal integration of wind energy into power systems calls for high quality wind power predictions. State-of-the-art forecasting systems typically provide forecasts for every location individually, without taking into account information coming from the neighbouring territories. It is however...

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

Mind the gap: modelling event-based and millennial-scale landscape dynamics

NARCIS (Netherlands)

Baartman, J.E.M.

2012-01-01

This research looks at landscape dynamics – erosion and deposition – from two different perspectives: long-term landscape evolution over millennial timescales on the one hand and short-term event-based erosion and deposition at the other hand. For the first, landscape evolution models (LEMs) are

Short- and long-term antidepressant effects of ketamine in a rat chronic unpredictable stress model.

Science.gov (United States)

Jiang, Yinghong; Wang, Yiqiang; Sun, Xiaoran; Lian, Bo; Sun, Hongwei; Wang, Gang; Du, Zhongde; Li, Qi; Sun, Lin

2017-08-01

This research was aimed to evaluate the behaviors of short- or long-term antidepressant effects of ketamine in rats exposed to chronic unpredictable stress (CUS). Ketamine, a glutamate noncompetitive NMDA receptor antagonist, regulates excitatory amino acid functions, such as anxiety disorders and major depression, and plays an important role in synaptic plasticity and learning and memory. After 42 days of CUS model, male rats received either a single injection of ketamine (10 mg/kg; day 43) or 15 daily injections (days 43-75). The influence of ketamine on behavioral reactivity was assessed 24 hr (short-term) or 7 weeks after ketamine treatment (long-term). Behavioral tests used to assess the effects of these treatments included the sucrose preference (SP), open field (OF), elevated plus maze (EPM), forced swimming (FS), and water maze (WM) to detect anxiety-like behavior (OF and EPM), forced swimming (FS), and water maze (WM). Results: Short-term ketamine administration resulted in increases of body weight gain, higher sensitivity to sucrose, augmented locomotor activity in the OF, more entries into the open arms of the EPM, along increased activity in the FS test; all responses indicative of reductions in depression/despair in anxiety-eliciting situations. No significant differences in these behaviors were obtained under conditions of long-term ketamine administration ( p  > .05). The CUS + Ketamine group showed significantly increased activity as compared with the CUS + Vehicle group for analysis of the long-term effects of ketamine (* p   .05). Taken together these findings demonstrate that a short-term administration of ketamine induced rapid antidepressant-like effects in adult male rats exposed to CUS conditions, effects that were not observed in response to the long-term treatment regime.

Clustering of short and long-term co-movements in international financial and commodity markets in wavelet domain

Science.gov (United States)

Lahmiri, Salim; Uddin, Gazi Salah; Bekiros, Stelios

2017-11-01

We propose a general framework for measuring short and long term dynamics in asset classes based on the wavelet presentation of clustering analysis. The empirical results show strong evidence of instability of the financial system aftermath of the global financial crisis. Indeed, both short and long-term dynamics have significantly changed after the global financial crisis. This study provides an interesting insights complex structure of global financial and economic system.

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.

Forecasting stock return volatility: A comparison between the roles of short-term and long-term leverage effects

Science.gov (United States)

Pan, Zhiyuan; Liu, Li

2018-02-01

In this paper, we extend the GARCH-MIDAS model proposed by Engle et al. (2013) to account for the leverage effect in short-term and long-term volatility components. Our in-sample evidence suggests that both short-term and long-term negative returns can cause higher future volatility than positive returns. Out-of-sample results show that the predictive ability of GARCH-MIDAS is significantly improved after taking the leverage effect into account. The leverage effect for short-term volatility component plays more important role than the leverage effect for long-term volatility component in affecting out-of-sample forecasting performance.

Integration and segregation of large-scale brain networks during short-term task automatization.

Science.gov (United States)

Mohr, Holger; Wolfensteller, Uta; Betzel, Richard F; Mišić, Bratislav; Sporns, Olaf; Richiardi, Jonas; Ruge, Hannes

2016-11-03

The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes.

Tc1 mouse model of trisomy-21 dissociates properties of short- and long-term recognition memory.

Science.gov (United States)

Hall, Jessica H; Wiseman, Frances K; Fisher, Elizabeth M C; Tybulewicz, Victor L J; Harwood, John L; Good, Mark A

2016-04-01

The present study examined memory function in Tc1 mice, a transchromosomic model of Down syndrome (DS). Tc1 mice demonstrated an unusual delay-dependent deficit in recognition memory. More specifically, Tc1 mice showed intact immediate (30sec), impaired short-term (10-min) and intact long-term (24-h) memory for objects. A similar pattern was observed for olfactory stimuli, confirming the generality of the pattern across sensory modalities. The specificity of the behavioural deficits in Tc1 mice was confirmed using APP overexpressing mice that showed the opposite pattern of object memory deficits. In contrast to object memory, Tc1 mice showed no deficit in either immediate or long-term memory for object-in-place information. Similarly, Tc1 mice showed no deficit in short-term memory for object-location information. The latter result indicates that Tc1 mice were able to detect and react to spatial novelty at the same delay interval that was sensitive to an object novelty recognition impairment. These results demonstrate (1) that novelty detection per se and (2) the encoding of visuo-spatial information was not disrupted in adult Tc1 mice. The authors conclude that the task specific nature of the short-term recognition memory deficit suggests that the trisomy of genes on human chromosome 21 in Tc1 mice impacts on (perirhinal) cortical systems supporting short-term object and olfactory recognition memory. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Short-time quantum dynamics of sharp boundaries potentials

Energy Technology Data Exchange (ETDEWEB)

Granot, Er' el, E-mail: erel@ariel.ac.il; Marchewka, Avi

2015-02-15

Despite the high prevalence of singular potential in general, and rectangular potentials in particular, in applied scattering models, to date little is known about their short time effects. The reason is that singular potentials cause a mixture of complicated local as well as non-local effects. The object of this work is to derive a generic method to calculate analytically the short-time impact of any singular potential. In this paper it is shown that the scattering of a smooth wavefunction on a singular potential is totally equivalent, in the short-time regime, to the free propagation of a singular wavefunction. However, the latter problem was totally addressed analytically in Ref. [7]. Therefore, this equivalency can be utilized in solving analytically the short time dynamics of any smooth wavefunction at the presence of a singular potentials. In particular, with this method the short-time dynamics of any problem where a sharp boundaries potential (e.g., a rectangular barrier) is turned on instantaneously can easily be solved analytically.

Short-time quantum dynamics of sharp boundaries potentials

Science.gov (United States)

Granot, Er'el; Marchewka, Avi

2015-02-01

Despite the high prevalence of singular potential in general, and rectangular potentials in particular, in applied scattering models, to date little is known about their short time effects. The reason is that singular potentials cause a mixture of complicated local as well as non-local effects. The object of this work is to derive a generic method to calculate analytically the short-time impact of any singular potential. In this paper it is shown that the scattering of a smooth wavefunction on a singular potential is totally equivalent, in the short-time regime, to the free propagation of a singular wavefunction. However, the latter problem was totally addressed analytically in Ref. [7]. Therefore, this equivalency can be utilized in solving analytically the short time dynamics of any smooth wavefunction at the presence of a singular potentials. In particular, with this method the short-time dynamics of any problem where a sharp boundaries potential (e.g., a rectangular barrier) is turned on instantaneously can easily be solved analytically.

Short-time quantum dynamics of sharp boundaries potentials

International Nuclear Information System (INIS)

Granot, Er'el; Marchewka, Avi

2015-01-01

Despite the high prevalence of singular potential in general, and rectangular potentials in particular, in applied scattering models, to date little is known about their short time effects. The reason is that singular potentials cause a mixture of complicated local as well as non-local effects. The object of this work is to derive a generic method to calculate analytically the short-time impact of any singular potential. In this paper it is shown that the scattering of a smooth wavefunction on a singular potential is totally equivalent, in the short-time regime, to the free propagation of a singular wavefunction. However, the latter problem was totally addressed analytically in Ref. [7]. Therefore, this equivalency can be utilized in solving analytically the short time dynamics of any smooth wavefunction at the presence of a singular potentials. In particular, with this method the short-time dynamics of any problem where a sharp boundaries potential (e.g., a rectangular barrier) is turned on instantaneously can easily be solved analytically

Short-Term Gains, Long-Term Pains: How Cues about State Aid Learning in Dynamic Environments

Science.gov (United States)

Gureckis, Todd M.; Love, Bradley C.

2009-01-01

Successful investors seeking returns, animals foraging for food, and pilots controlling aircraft all must take into account how their current decisions will impact their future standing. One challenge facing decision makers is that options that appear attractive in the short-term may not turn out best in the long run. In this paper, we explore…

Explaining Macroeconomic and Term Structure Dynamics Jointly in a Non-linear DSGE Model

DEFF Research Database (Denmark)

Andreasen, Martin Møller

This paper shows how a standard DSGE model can be extended to reproduce the dynamics in the 10 year yield curve for the post-war US economy with a similar degree of precision as in reduced form term structure models. At the same time, we are able to reproduce the dynamics of four key macro...... variables almost perfectly. Our extension of a standard DSGE model is to introduce three non-stationary shocks which allow us to explain interest rates with medium and long maturities without distorting the dynamics of the macroeconomy....

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.

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.

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.

Short-term recurrent chaos and role of Toxin Producing Phytoplankton (TPP) on chaotic dynamics in aquatic systems

International Nuclear Information System (INIS)

Upadhyay, Ranjit Kumar; Rao, V. Sree Hari

2009-01-01

We propose a new mathematical model for aquatic populations. This model incorporates mutual interference in all the three populations and an extra mortality term in zooplankton population and also taking into account the toxin liberation process of TPP population. The proposed model generalizes several other known models in the literature. The principal interest in this paper is in a numerical study of the model's behaviour. It is observed that both types of food chains display same type of chaotic behaviour, short-term recurrent chaos, with different generating mechanisms. Toxin producing phytoplankton (TPP) reduces the grazing pressure of zooplankton. To observe the role of TPP, we consider Holling types I, II and III functional forms for this process. Our study suggests that toxic substances released by TPP population may act as bio-control by changing the state of chaos to order and extinction.

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.

Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-23

In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operator can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.

Short-term plasticity and long-term potentiation mimicked in single inorganic synapses

Science.gov (United States)

Ohno, Takeo; Hasegawa, Tsuyoshi; Tsuruoka, Tohru; Terabe, Kazuya; Gimzewski, James K.; Aono, Masakazu

2011-08-01

Memory is believed to occur in the human brain as a result of two types of synaptic plasticity: short-term plasticity (STP) and long-term potentiation (LTP; refs , , , ). In neuromorphic engineering, emulation of known neural behaviour has proven to be difficult to implement in software because of the highly complex interconnected nature of thought processes. Here we report the discovery of a Ag2S inorganic synapse, which emulates the synaptic functions of both STP and LTP characteristics through the use of input pulse repetition time. The structure known as an atomic switch, operating at critical voltages, stores information as STP with a spontaneous decay of conductance level in response to intermittent input stimuli, whereas frequent stimulation results in a transition to LTP. The Ag2S inorganic synapse has interesting characteristics with analogies to an individual biological synapse, and achieves dynamic memorization in a single device without the need of external preprogramming. A psychological model related to the process of memorizing and forgetting is also demonstrated using the inorganic synapses. Our Ag2S element indicates a breakthrough in mimicking synaptic behaviour essential for the further creation of artificial neural systems that emulate characteristics of human memory.

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.

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.

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)

What are the differences between long-term, short-term, and working memory?

Science.gov (United States)

Cowan, Nelson

2008-01-01

In the recent literature there has been considerable confusion about the three types of memory: long-term, short-term, and working memory. This chapter strives to reduce that confusion and makes up-to-date assessments of these types of memory. Long- and short-term memory could differ in two fundamental ways, with only short-term memory demonstrating (1) temporal decay and (2) chunk capacity limits. Both properties of short-term memory are still controversial but the current literature is rather encouraging regarding the existence of both decay and capacity limits. Working memory has been conceived and defined in three different, slightly discrepant ways: as short-term memory applied to cognitive tasks, as a multi-component system that holds and manipulates information in short-term memory, and as the use of attention to manage short-term memory. Regardless of the definition, there are some measures of memory in the short term that seem routine and do not correlate well with cognitive aptitudes and other measures (those usually identified with the term "working memory") that seem more attention demanding and do correlate well with these aptitudes. The evidence is evaluated and placed within a theoretical framework depicted in Fig. 1.

Long-term plasticity determines the postsynaptic response to correlated afferents with multivesicular short-term synaptic depression

Directory of Open Access Journals (Sweden)

Alexander David Bird

2014-01-01

Full Text Available Synchrony in a presynaptic population leads to correlations in vesicle occupancy at the active sites for neurotransmitter release. The number of independent release sites per presynaptic neuron, a synaptic parameter recently shown to be modifed during long-term plasticity, will modulate these correlations and therefore have a significant effect on the firing rate of the postsynaptic neuron. To understand how correlations from synaptic dynamics and from presynaptic synchrony shape the postsynaptic response, we study a model of multiple release site short-term plasticity and derive exact results for the crosscorrelation function of vesicle occupancy and neurotransmitter release, as well as the postsynaptic voltage variance. Using approximate forms for the postsynaptic firing rate in the limits of low and high correlations, we demonstrate that short-term depression leads to a maximum response for an intermediate number of presynaptic release sites, and that this leads to a tuning-curve response peaked at an optimal presynaptic synchrony setby the number of neurotransmitter release sites per presynaptic neuron. These effects arise because, above a certain level of correlation, activity in the presynaptic population is overly strong resulting in wastage of the pool of releasable neurotransmitter. As the nervous system operates under constraints of efficient metabolism it is likely that this phenomenon provides an activity-dependent constraint on network architecture.

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...

Borehole modelling: a comparison between a steady-state model and a novel dynamic model in a real ON/OFF GSHP operation

International Nuclear Information System (INIS)

De Rosa, M; Tagliafico, L A; Ruiz-Calvo, F; Corberán, J M; Montagud, C

2014-01-01

The correct design and optimization of complex energy systems requires the ability to reproduce the dynamic thermal behavior of each system component. In ground source heat pump (GSHP) systems, modelling the borehole heat exchangers (BHE) dynamic response is especially relevant in the development of control strategies for energy optimization purposes. Over the last years, several models have been developed but most of them are based on steady- state approaches, which makes them unsuitable for short-term simulation purposes. In fact, in order to accurately predict the evolution of the fluid temperatures due to the ON/OFF cycles of the heat pump, it is essential to correctly characterize the dynamic response of BHE for very short time periods. The aim of the present paper is to compare the performance of an analytical steady-state model, available in TRNSYS environment (Type 557), with a novel short-term dynamic model. The new dynamic model is based on the thermal-network approach coupled with a vertical discretization of the borehole which takes into account both the advection due to the fluid circulating along the U-tube, and the heat transfer in the borehole and in the ground. These two approaches were compared against experimental data collected from a real GSHP system installed at the Universitat Politecnica de Valencia. The analysis was performed comparing the outlet temperature profiles predicted by both models during daily standard ON/OFF operating conditions, both in heating and cooling mode, and the between both approaches were highlighted. Finally, the obtained results have been discussed focusing on the potential impact that the differences found in the prediction of the temperature evolution could have in design and optimization of GSHP systems

Sleep Quality, Short-Term and Long-Term CPAP Adherence

Science.gov (United States)

Somiah, Manya; Taxin, Zachary; Keating, Joseph; Mooney, Anne M.; Norman, Robert G.; Rapoport, David M.; Ayappa, Indu

2012-01-01

Study Objectives: Adherence to CPAP therapy is low in patients with obstructive sleep apnea/hypopnea syndrome (OSAHS). The purpose of the present study was to evaluate the utility of measures of sleep architecture and sleep continuity on the CPAP titration study as predictors of both short- and long-term CPAP adherence. Methods: 93 patients with OSAHS (RDI 42.8 ± 34.3/h) underwent in-laboratory diagnostic polysomnography, CPAP titration, and follow-up polysomnography (NPSG) on CPAP. Adherence to CPAP was objectively monitored. Short-term (ST) CPAP adherence was averaged over 14 days immediately following the titration study. Long-term (LT) CPAP adherence was obtained in 56/93 patients after approximately 2 months of CPAP use. Patients were grouped into CPAP adherence groups for ST ( 4 h) and LT adherence ( 4 h). Sleep architecture, sleep disordered breathing (SDB) indices, and daytime outcome variables from the diagnostic and titration NPSGs were compared between CPAP adherence groups. Results: There was a significant relationship between ST and LT CPAP adherence (r = 0.81, p CPAP adherence groups had significantly lower %N2 and greater %REM on the titration NPSG. A model combining change in sleep efficiency and change in sleep continuity between the diagnostic and titration NPSGs predicted 17% of the variance in LT adherence (p = 0.006). Conclusions: These findings demonstrate that characteristics of sleep architecture, even on the titration NPSG, may predict some of the variance in CPAP adherence. Better sleep quality on the titration night was related to better CPAP adherence, suggesting that interventions to improve sleep on/prior to the CPAP titration study might be used as a therapeutic intervention to improve CPAP adherence. Citation: Somiah M; Taxin Z; Keating J; Mooney AM; Norman RG; Rapoport DM; Ayappa I. Sleep quality, short-term and long-term CPAP adherence. J Clin Sleep Med 2012;8(5):489-500. PMID:23066359

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.

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

Genetic deletion of melanin-concentrating hormone neurons impairs hippocampal short-term synaptic plasticity and hippocampal-dependent forms of short-term memory.

Science.gov (United States)

Le Barillier, Léa; Léger, Lucienne; Luppi, Pierre-Hervé; Fort, Patrice; Malleret, Gaël; Salin, Paul-Antoine

2015-11-01

The cognitive role of melanin-concentrating hormone (MCH) neurons, a neuronal population located in the mammalian postero-lateral hypothalamus sending projections to all cortical areas, remains poorly understood. Mainly activated during paradoxical sleep (PS), MCH neurons have been implicated in sleep regulation. The genetic deletion of the only known MCH receptor in rodent leads to an impairment of hippocampal dependent forms of memory and to an alteration of hippocampal long-term synaptic plasticity. By using MCH/ataxin3 mice, a genetic model characterized by a selective deletion of MCH neurons in the adult, we investigated the role of MCH neurons in hippocampal synaptic plasticity and hippocampal-dependent forms of memory. MCH/ataxin3 mice exhibited a deficit in the early part of both long-term potentiation and depression in the CA1 area of the hippocampus. Post-tetanic potentiation (PTP) was diminished while synaptic depression induced by repetitive stimulation was enhanced suggesting an alteration of pre-synaptic forms of short-term plasticity in these mice. Behaviorally, MCH/ataxin3 mice spent more time and showed a higher level of hesitation as compared to their controls in performing a short-term memory T-maze task, displayed retardation in acquiring a reference memory task in a Morris water maze, and showed a habituation deficit in an open field task. Deletion of MCH neurons could thus alter spatial short-term memory by impairing short-term plasticity in the hippocampus. Altogether, these findings could provide a cellular mechanism by which PS may facilitate memory encoding. Via MCH neuron activation, PS could prepare the day's learning by increasing and modulating short-term synaptic plasticity in the hippocampus. © 2015 Wiley Periodicals, Inc.

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

Neuroticism and conscientiousness respectively constrain and facilitate short-term plasticity within the working memory neural network.

Science.gov (United States)

Dima, Danai; Friston, Karl J; Stephan, Klaas E; Frangou, Sophia

2015-10-01

Individual differences in cognitive efficiency, particularly in relation to working memory (WM), have been associated both with personality dimensions that reflect enduring regularities in brain configuration, and with short-term neural plasticity, that reflects task-related changes in brain connectivity. To elucidate the relationship of these two divergent mechanisms, we tested the hypothesis that personality dimensions, which reflect enduring aspects of brain configuration, inform about the neurobiological framework within which short-term, task-related plasticity, as measured by effective connectivity, can be facilitated or constrained. As WM consistently engages the dorsolateral prefrontal (DLPFC), parietal (PAR), and anterior cingulate cortex (ACC), we specified a WM network model with bidirectional, ipsilateral, and contralateral connections between these regions from a functional magnetic resonance imaging dataset obtained from 40 healthy adults while performing the 3-back WM task. Task-related effective connectivity changes within this network were estimated using Dynamic Causal Modelling. Personality was evaluated along the major dimensions of Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness. Only two dimensions were relevant to task-dependent effective connectivity. Neuroticism and Conscientiousness respectively constrained and facilitated neuroplastic responses within the WM network. These results suggest individual differences in cognitive efficiency arise from the interplay between enduring and short-term plasticity in brain configuration. © 2015 Wiley Periodicals, Inc.

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.

A methodology based on dynamic artificial neural network for short-term forecasting of the power output of a PV generator

International Nuclear Information System (INIS)

Almonacid, F.; Pérez-Higueras, P.J.; Fernández, Eduardo F.; Hontoria, L.

2014-01-01

Highlights: • The output of the majority of renewables energies depends on the variability of the weather conditions. • The short-term forecast is going to be essential for effectively integrating solar energy sources. • A new method based on artificial neural network to predict the power output of a PV generator one hour ahead is proposed. • This new method is based on dynamic artificial neural network to predict global solar irradiance and the air temperature. • The methodology developed can be used to estimate the power output of a PV generator with a satisfactory margin of error. - Abstract: One of the problems of some renewables energies is that the output of these kinds of systems is non-dispatchable depending on variability of weather conditions that cannot be predicted and controlled. From this point of view, the short-term forecast is going to be essential for effectively integrating solar energy sources, being a very useful tool for the reliability and stability of the grid ensuring that an adequate supply is present. In this paper a new methodology for forecasting the output of a PV generator one hour ahead based on dynamic artificial neural network is presented. The results of this study show that the proposed methodology could be used to forecast the power output of PV systems one hour ahead with an acceptable degree of accuracy

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

Short-term dissolved organic carbon dynamics reflect water management and precipitation patterns in a subtropical estuary

Directory of Open Access Journals (Sweden)

Peter Regier

2016-12-01

a better understanding of short-term DOC dynamics and associated hydrological drivers and indicates the importance of high-frequency measurements to accurately constraining coastal carbon processes and budgets, particularly in coastal systems increasingly altered by hydrologic restoration and climate change.

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)

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.

Short-term and long-term effects of GDP on traffic deaths in 18 OECD countries, 1960-2011.

Science.gov (United States)

Dadgar, Iman; Norström, Thor

2017-02-01

Research suggests that increases in gross domestic product (GDP) lead to increases in traffic deaths plausibly due to the increased road traffic induced by an expanding economy. However, there also seems to exist a long-term effect of economic growth that is manifested in improved traffic safety and reduced rates of traffic deaths. Previous studies focus on either the short-term, procyclical effect, or the long-term, protective effect. The aim of the present study is to estimate the short-term and long-term effects jointly in order to assess the net impact of GDP on traffic mortality. We extracted traffic death rates for the period 1960-2011 from the WHO Mortality Database for 18 OECD countries. Data on GDP/capita were obtained from the Maddison Project. We performed error correction modelling to estimate the short-term and long-term effects of GDP on the traffic death rates. The estimates from the error correction modelling for the entire study period suggested that a one-unit increase (US$1000) in GDP/capita yields an instantaneous short-term increase in the traffic death rate by 0.58 (pGDP leads to an immediate increase in traffic deaths. However, after the mid-1970s this short-term effect is more than outweighed by a markedly stronger protective long-term effect, whereas the reverse is true for the period before the mid-1970s. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Short-Term Wind Power Forecasting Based on Clustering Pre-Calculated CFD Method

Directory of Open Access Journals (Sweden)

Yimei Wang

2018-04-01

Full Text Available To meet the increasing wind power forecasting (WPF demands of newly built wind farms without historical data, physical WPF methods are widely used. The computational fluid dynamics (CFD pre-calculated flow fields (CPFF-based WPF is a promising physical approach, which can balance well the competing demands of computational efficiency and accuracy. To enhance its adaptability for wind farms in complex terrain, a WPF method combining wind turbine clustering with CPFF is first proposed where the wind turbines in the wind farm are clustered and a forecasting is undertaken for each cluster. K-means, hierarchical agglomerative and spectral analysis methods are used to establish the wind turbine clustering models. The Silhouette Coefficient, Calinski-Harabaz index and within-between index are proposed as criteria to evaluate the effectiveness of the established clustering models. Based on different clustering methods and schemes, various clustering databases are built for clustering pre-calculated CFD (CPCC-based short-term WPF. For the wind farm case studied, clustering evaluation criteria show that hierarchical agglomerative clustering has reasonable results, spectral clustering is better and K-means gives the best performance. The WPF results produced by different clustering databases also prove the effectiveness of the three evaluation criteria in turn. The newly developed CPCC model has a much higher WPF accuracy than the CPFF model without using clustering techniques, both on temporal and spatial scales. The research provides supports for both the development and improvement of short-term physical WPF systems.

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.

What are the differences between long-term, short-term, and working memory?

OpenAIRE

Cowan, Nelson

2008-01-01

In the recent literature there has been considerable confusion about the three types of memory: long-term, short-term, and working memory. This chapter strives to reduce that confusion and makes up-to-date assessments of these types of memory. Long- and short-term memory could differ in two fundamental ways, with only short-term memory demonstrating (1) temporal decay and (2) chunk capacity limits. Both properties of short-term memory are still controversial but the current literature is rath...

Short-term action potential memory and electrical restitution: A cellular computational study on the stability of cardiac repolarization under dynamic pacing.

Directory of Open Access Journals (Sweden)

Massimiliano Zaniboni

Full Text Available Electrical restitution (ER is a major determinant of repolarization stability and, under fast pacing rate, it reveals memory properties of the cardiac action potential (AP, whose dynamics have never been fully elucidated, nor their ionic mechanisms. Previous studies have looked at ER mainly in terms of changes in AP duration (APD when the preceding diastolic interval (DI changes and described dynamic conditions where this relationship shows hysteresis which, in turn, has been proposed as a marker of short-term AP memory and repolarization stability. By means of numerical simulations of a non-propagated human ventricular AP, we show here that measuring ER as APD versus the preceding cycle length (CL provides additional information on repolarization dynamics which is not contained in the companion formulation. We focus particularly on fast pacing rate conditions with a beat-to-beat variable CL, where memory properties emerge from APD vs CL and not from APD vs DI and should thus be stored in APD and not in DI. We provide an ion-currents characterization of such conditions under periodic and random CL variability, and show that the memory stored in APD plays a stabilizing role on AP repolarization under pacing rate perturbations. The gating kinetics of L-type calcium current seems to be the main determinant of this safety mechanism. We also show that, at fast pacing rate and under otherwise identical pacing conditions, a periodically beat-to-beat changing CL is more effective than a random one in stabilizing repolarization. In summary, we propose a novel view of short-term AP memory, differentially stored between systole and diastole, which opens a number of methodological and theoretical implications for the understanding of arrhythmia development.

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.

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.

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.

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.

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.

Time Perspective and Identity Formation: Short-Term Longitudinal Dynamics in College Students

Science.gov (United States)

Luyckx, Koen; Lens, Willy; Smits, Ilse; Goossens, Luc

2010-01-01

Planning for the future and developing a personalized identity are conceived of as important developmental tasks that adolescents and emerging adults are confronted with on the pathway to adulthood. The present study set out to examine whether both tasks develop in tandem by using a short-term longitudinal dataset consisting of 371 college…

Modeling context-sensitive, dynamic activity travel behavior by linking short-and long-term responses to accumulated stress

NARCIS (Netherlands)

Psarra, I.; Liao, F.; Arentze, T.A.; Timmermans, H.J.P.

2014-01-01

As existing activity-based models of travel demand simulate activity travel patterns for a typical day, dynamic models simulate behavioral response to endogenous or exogenous change along various time horizons. Prior research predominantly addressed a specific kind of change, which usually affected

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

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

Science.gov (United States)

Limongi, Roberto; Silva, Angélica M

2016-11-01

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

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)

Short-Term Load Forecasting Based Automatic Distribution Network Reconfiguration: Preprint

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-07-26

In the traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of load forecasting technique can provide accurate prediction of load power that will happen in future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during the longer time period instead of using the snapshot of load at the time when the reconfiguration happens, and thus it can provide information to the distribution system operator (DSO) to better operate the system reconfiguration to achieve optimal solutions. Thus, this paper proposes a short-term load forecasting based approach for automatically reconfiguring distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with support vector regression (SVR) based forecaster and parallel parameters optimization. And the network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum loss at the future time. The simulation results validate and evaluate the proposed approach.

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

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.

Short-term incentive schemes for hospital managers

Directory of Open Access Journals (Sweden)

Lucas Malambe

2013-10-01

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

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…

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.

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...

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...

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.

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.

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

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...

Dynamical arrest in dense short-ranged attractive colloids

International Nuclear Information System (INIS)

Foffi, G; Sciortino, F; Zaccarelli, E; Tartaglia, P

2004-01-01

We study thermodynamic and dynamic properties of model colloidal systems interacting with a hard core repulsion and a short-range attraction, and provide an overall picture of their phase diagrams which shows a very rich phenomenology. We focus on the slow dynamic properties of this model, investigating in detail the glass transition lines (both repulsive and attractive), the glass-glass transitions and the location of the higher order singularities. We discuss the relative location of the glass lines and of the metastable liquid-gas binodal, an issue relevant for the understanding of low density arrested states of matter

Carbon-14 dynamics in rice: an extension of the ORYZA2000 model

Energy Technology Data Exchange (ETDEWEB)

Galeriu, D.; Melintescu, A. [' ' Horia Hulubei' ' National Institute for Physics and Nuclear Engineering, Life and Environmental Physics Department, 30 Reactorului St., POB MG-6, Bucharest-Magurele (Romania)

2014-03-15

Carbon-14 ({sup 14}C) is a radionuclide of major interest in nuclear power production. The Fukushima accident changed the public attitude on the use of nuclear energy all over the world. In terms of nuclear safety, the need of quality-assured radiological models was emphasized by many international organizations, and for models used by decision-makers (i.e. regulatory environmental models and radiological models), a moderate conservatism, transparency, relative simplicity and user friendliness are required. Because the interaction between crops and the environment is complex and regulated by many feedback mechanisms, however, these requirements are difficult to accomplish. The present study makes a step forward regarding the development of a robust model dealing with food contamination after a short-term accidental emission and considers a single crop species, rice (Oryza sativa), one of the most widely used rice species. Old and more recent experimental data regarding the carbon dynamics in rice plants are reviewed, and a well-established crop growth model, ORYZA2000, is used and adapted in order to assess the dynamics of {sup 14}C in rice after a short-term exposure to {sup 14}CO{sub 2}. Here, the model is used to investigate the role of the genotype, management and weather on the concentration of radiocarbon at harvest. (orig.)

Modelling the heat dynamics of buildings using stochastic

DEFF Research Database (Denmark)

Andersen, Klaus Kaae; Madsen, Henrik

2000-01-01

This paper describes the continuous time modelling of the heat dynamics of a building. The considered building is a residential like test house divided into two test rooms with a water based central heating. Each test room is divided into thermal zones in order to describe both short and long term...... variations. Besides modelling the heat transfer between thermal zones, attention is put on modelling the heat input from radiators and solar radiation. The applied modelling procedure is based on collected building performance data and statistical methods. The statistical methods are used in parameter...

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)

Long-term and short-term action-effect links and their impact on effect monitoring.

Science.gov (United States)

Wirth, Robert; Steinhauser, Robert; Janczyk, Markus; Steinhauser, Marco; Kunde, Wilfried

2018-04-23

People aim to produce effects in the environment, and according to ideomotor theory, actions are selected and executed via anticipations of their effects. Further, to ensure that an action has been successful and an effect has been realized, we must be able to monitor the consequences of our actions. However, action-effect links might vary between situations, some might apply for a majority of situations, while others might only apply to special occasions. With a combination of behavioral and electrophysiological markers, we show that monitoring of self-produced action effects interferes with other tasks, and that the length of effect monitoring is determined by both, long-term action-effect links that hold for most situations, and short-term action-effect links that emerge from a current setting. Effect monitoring is fast and frugal when these action-effect links allow for valid anticipation of action effects, but otherwise effect monitoring takes longer and delays a subsequent task. Specific influences of long-term and short-term links on the P1/N1 and P3a further allow to dissect the temporal dynamics of when these links interact for the purpose of effect monitoring. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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.)

Bayesian dynamic modeling of time series of dengue disease case counts.

Science.gov (United States)

Martínez-Bello, Daniel Adyro; López-Quílez, Antonio; Torres-Prieto, Alexander

2017-07-01

The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model's short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful

Short- and long-term forecast for chaotic and random systems (50 years after Lorenz's paper)

International Nuclear Information System (INIS)

Bunimovich, Leonid A

2014-01-01

We briefly review a history of the impact of the famous 1963 paper by E Lorenz on hydrodynamics, physics and mathematics communities on both sides of the iron curtain. This paper was an attempt to apply the ideas and methods of dynamical systems theory to the problem of weather forecast. Its major discovery was the phenomenon of chaos in dissipative dynamical systems which makes such forecasts rather problematic, if at all possible. In this connection we present some recent results which demonstrate that both a short-term and a long-term forecast are actually possible for the most chaotic dynamical (as well as for the most random, like IID and Markov chain) systems. Moreover, there is a sharp transition between the time interval where one may use a short-term forecast and the times where a long-term forecast is applicable. Finally we discuss how these findings could be incorporated into the forecast strategy outlined in the Lorenz's paper. (invited article)

Short-term versus long-term heart rate variability in ischemic cardiomyopathy risk stratification

Directory of Open Access Journals (Sweden)

Andreas eVoss

2013-12-01

Full Text Available In industrialized countries with aging populations, heart failure affects 0.3%-2% of the general population. The investigation of 24h-ECG recordings revealed the potential of nonlinear indices of heart rate variability (HRV for enhanced risk stratification in patients with ischemic heart failure (IHF. However, long-term analyses are time-consuming, expensive and delay the initial diagnosis. The objective of this study was to investigate whether 30min short-term HRV analysis is sufficient for comparable risk stratification in IHF in comparison to 24h-HRV analysis. From 256 IHF patients (221 at low risk (IHFLR and 35 at high risk (IHFHR a 24h beat-to-beat time series b the first 30min segment c the 30min most stationary day segment and d the 30min most stationary night segment were investigated. We calculated linear (time and frequency domain and nonlinear HRV analysis indices. Optimal parameter sets for risk stratification in IHF were determined for 24 hours and for each 30min segment by applying discriminant analysis on significant clinical and non-clinical indices. Long- and short-term HRV indices from frequency domain and particularly from nonlinear dynamics revealed high univariate significances (p

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...

Very-long-term and short-term chromatic adaptation: are their influences cumulative?

Science.gov (United States)

Belmore, Suzanne C; Shevell, Steven K

2011-02-09

Very-long-term (VLT) chromatic adaptation results from exposure to an altered chromatic environment for days or weeks. Color shifts from VLT adaptation are observed hours or days after leaving the altered environment. Short-term chromatic adaptation, on the other hand, results from exposure for a few minutes or less, with color shifts measured within seconds or a few minutes after the adapting light is extinguished; recovery to the pre-adapted state is complete in less than an hour. Here, both types of adaptation were combined. All adaptation was to reddish-appearing long-wavelength light. Shifts in unique yellow were measured following adaptation. Previous studies demonstrate shifts in unique yellow due to VLT chromatic adaptation, but shifts from short-term chromatic adaptation to comparable adapting light can be far greater than from VLT adaptation. The question considered here is whether the color shifts from VLT adaptation are cumulative with large shifts from short-term adaptation or, alternatively, does simultaneous short-term adaptation eliminate color shifts caused by VLT adaptation. The results show the color shifts from VLT and short-term adaptation together are cumulative, which indicates that both short-term and very-long-term chromatic adaptation affect color perception during natural viewing. Copyright © 2010 Elsevier Ltd. All rights reserved.

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.

Short-Term Expectation Formation Versus Long-Term Equilibrium Conditions: The Danish Housing Market

Directory of Open Access Journals (Sweden)

Andreas Hetland

2017-09-01

Full Text Available The primary contribution of this paper is to establish that the long-swings behavior observed in the market price of Danish housing since the 1970s can be understood by studying the interplay between short-term expectation formation and long-run equilibrium conditions. We introduce an asset market model for housing based on uncertainty rather than risk, which under mild assumptions allows for other forms of forecasting behavior than rational expectations. We test the theory via an I(2 cointegrated VAR model and find that the long-run equilibrium for the housing price corresponds closely to the predictions from the theoretical framework. Additionally, we corroborate previous findings that housing markets are well characterized by short-term momentum forecasting behavior. Our conclusions have wider relevance, since housing prices play a role in the wider Danish economy, and other developed economies, through wealth effects.

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

Tc1 mouse model of trisomy-21 dissociates properties of short- and long-term recognition memory

OpenAIRE

Hall, Jessica H.; Wiseman, Frances K.; Fisher, Elizabeth M.C.; Tybulewicz, Victor L.J.; Harwood, John L.; Good, Mark A.

2016-01-01

The present study examined memory function in Tc1 mice, a transchromosomic model of Down syndrome (DS). Tc1 mice demonstrated an unusual delay-dependent deficit in recognition memory. More specifically, Tc1 mice showed intact immediate (30sec), impaired short-term (10-min) and intact long-term (24-h) memory for objects. A similar pattern was observed for olfactory stimuli, confirming the generality of the pattern across sensory modalities. The specificity of the behavioural deficits in Tc1 mi...

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...

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.

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...

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.

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.

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...

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...

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)

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

Directory of Open Access Journals (Sweden)

MI Chang-hong

2016-02-01

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

Factors Influencing Short-term Synaptic Plasticity in the Avian Cochlear Nucleus Magnocellularis

Directory of Open Access Journals (Sweden)

Jason Tait Sanchez Quinones

2015-01-01

Full Text Available Defined as reduced neural responses during high rates of activity, synaptic depression is a form of short-term plasticity important for the temporal filtering of sound. In the avian cochlear nucleus magnocellularis (NM, an auditory brainstem structure, mechanisms regulating short-term synaptic depression include pre-, post-, and extrasynaptic factors. Using varied paired-pulse stimulus intervals, we found that the time course of synaptic depression lasts up to four seconds at late-developing NM synapses. Synaptic depression was largely reliant on exogenous Ca 2+ -dependent probability of presynaptic neurotransmitter release, and to a lesser extent, on the desensitization of postsynaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid-type glutamate receptor (AMPA-R. Interestingly, although extrasynaptic glutamate clearance did not play a significant role in regulating synaptic depression, blocking glutamate clearance at early-developing synapses altered synaptic dynamics, changing responses from depression to facilitation. These results suggest a developmental shift in the relative reliance on pre-, post-, and extrasynaptic factors in regulating short-term synaptic plasticity in NM.

A Neural Network Model to Learn Multiple Tasks under Dynamic Environments

Science.gov (United States)

Tsumori, Kenji; Ozawa, Seiichi

When environments are dynamically changed for agents, the knowledge acquired in an environment might be useless in future. In such dynamic environments, agents should be able to not only acquire new knowledge but also modify old knowledge in learning. However, modifying all knowledge acquired before is not efficient because the knowledge once acquired may be useful again when similar environment reappears and some knowledge can be shared among different environments. To learn efficiently in such environments, we propose a neural network model that consists of the following modules: resource allocating network, long-term & short-term memory, and environment change detector. We evaluate the model under a class of dynamic environments where multiple function approximation tasks are sequentially given. The experimental results demonstrate that the proposed model possesses stable incremental learning, accurate environmental change detection, proper association and recall of old knowledge, and efficient knowledge transfer.

Handling geological and economic uncertainties in balancing short-term and long-term objectives in waterflooding optimization

NARCIS (Netherlands)

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

2017-01-01

Model-based economic optimization of oil production has a significant scope to increase financial life-cycle performance. The net-present-value (NPV) objective in this optimization, because of its nature, focuses on long-term gains, whereas short-term production is not explicitly addressed. At the

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

Fractional-order leaky integrate-and-fire model with long-term memory and power law dynamics.

Science.gov (United States)

Teka, Wondimu W; Upadhyay, Ranjit Kumar; Mondal, Argha

2017-09-01

Pyramidal neurons produce different spiking patterns to process information, communicate with each other and transform information. These spiking patterns have complex and multiple time scale dynamics that have been described with the fractional-order leaky integrate-and-Fire (FLIF) model. Models with fractional (non-integer) order differentiation that generalize power law dynamics can be used to describe complex temporal voltage dynamics. The main characteristic of FLIF model is that it depends on all past values of the voltage that causes long-term memory. The model produces spikes with high interspike interval variability and displays several spiking properties such as upward spike-frequency adaptation and long spike latency in response to a constant stimulus. We show that the subthreshold voltage and the firing rate of the fractional-order model make transitions from exponential to power law dynamics when the fractional order α decreases from 1 to smaller values. The firing rate displays different types of spike timing adaptation caused by changes on initial values. We also show that the voltage-memory trace and fractional coefficient are the causes of these different types of spiking properties. The voltage-memory trace that represents the long-term memory has a feedback regulatory mechanism and affects spiking activity. The results suggest that fractional-order models might be appropriate for understanding multiple time scale neuronal dynamics. Overall, a neuron with fractional dynamics displays history dependent activities that might be very useful and powerful for effective information processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Extrapolation of dynamic load behaviour on hydroelectric turbine blades with cyclostationary modelling

Science.gov (United States)

Poirier, Marc; Gagnon, Martin; Tahan, Antoine; Coutu, André; Chamberland-lauzon, Joël

2017-01-01

In this paper, we present the application of cyclostationary modelling for the extrapolation of short stationary load strain samples measured in situ on hydraulic turbine blades. Long periods of measurements allow for a wide range of fluctuations representative of long-term reality to be considered. However, sampling over short periods limits the dynamic strain fluctuations available for analysis. The purpose of the technique presented here is therefore to generate a representative signal containing proper long term characteristics and expected spectrum starting with a much shorter signal period. The final objective is to obtain a strain history that can be used to estimate long-term fatigue behaviour of hydroelectric turbine runners.

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.

Short-term variability of Cyg X-1

International Nuclear Information System (INIS)

Oda, M.; Doi, K.; Ogawara, Y.

1976-01-01

The short-term X-ray variability distinguishes Cyg X-1, which is the most likely candidate for a black hole, from other X-ray sources. The present status of our knowledge on this short-term variation, mainly from the UHURU, the MIT and the GSFC observations, is reviewed. The nature of impulsive variations which compose the time variation exceeding the statistical fluctuation is discussed. There are indications that the energy spectrum of large pulses is harder than the average spectrum, or that the large pulses are the characteristics of the hard component of the spectrum if it is composed of two, soft and hard, components. Features of the variations may be partly simulated by the superposition of random shot-noise pulses with a fraction of a second duration. However, the autocorrelation analysis and the dynamic spectrum analysis indicate that the correlation lasts for several seconds and in the variation are buried some regularities which exhibit power concentrations in several frequency bands; 0.2-0.3, 0.4-0.5, 0.8, 1.2-1.5 Hz. There are several possible interpretations of these results in terms of; e.g. (a) a mixture of shot-noise pulses with two or more constant durations, (b) the shape of the basic shot-noise pulse, (c) bunching of the pulses, (d) superposition of wave-packets or temporal oscillations. But we have not yet reached any definite understandings in the nature of the variabilities. The substructure of the fluctuations on a time scale of milliseconds suggested by two investigations is also discussed. (Auth.)

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.

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.

Predicting long-term and short-term tidal flat morphodynamics using a dynamic equilibrium theory

NARCIS (Netherlands)

Hu, Z.; Wang, Z.B.; Zitman, T.J.; Stive, M.J.F.; Bouma, T.J.

2015-01-01

Dynamic equilibrium theory is a fruitful concept, which we use to systematically explain the tidal flat morphodynamic response to tidal currents, wind waves, sediment supply, and other sedimentological drivers. This theory stems from a simple analytical model that derives the tide- or wave-dominated

Short-term energy outlook. Quarterly projections, 2nd quarter 1994

Energy Technology Data Exchange (ETDEWEB)

1994-05-01

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. The forecast period for this issue of the Outlook extends from the second quarter of 1994 through the fourth quarter of 1995. Values for the first quarter of 1994, 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. The historical energy data, compiled into the second quarter 1994 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 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.

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

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.

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.

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

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.

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...

Human-Structure Dynamic Interaction during Short-Distance Free Falls

Directory of Open Access Journals (Sweden)

E. Shahabpoor

2016-01-01

Full Text Available The dynamic interactions of falling human bodies with civil structures, regardless of their potentially critical effects, have sparsely been researched in contact biomechanics. The physical contact models suggested in the existing literature, particularly for short-distant falls in home settings, assume the human body falls on a “rigid” (not vibrating ground. A similar assumption is usually made during laboratory-based fall tests, including force platforms. Based on observations from a set of pediatric head-first free fall tests, the present paper shows that the dynamics of the grounded force plate are not always negligible when doing fall test in a laboratory setting. By using a similar analogy for lightweight floor structures, it is shown that ignoring the dynamics of floors in the contact model can result in an up to 35% overestimation of the peak force experienced by a falling human. A nonlinear contact model is suggested, featuring an agent-based modelling approach, where the dynamics of the falling human and the impact object (force plate or a floor structure here are each modelled using a single-degree-of-freedom model to simulate their dynamic interactions. The findings of this research can have wide applications in areas such as impact biomechanics and sports science.

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 ...

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 ...

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.

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.

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).

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.

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

Directory of Open Access Journals (Sweden)

Barata José T

2007-04-01

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

On the relationship between short- and long-term memory

DEFF Research Database (Denmark)

Sørensen, Thomas Alrik

James (1890) divided memory into separate stores; primary and secondary – or short-term and long-term memory. The interaction between the two stores often assumes that information initially is represented in volatile short-term store before entering and consolidating in the more durable long-term......, accepted). Counter to popular beliefs this suggest that long-term memory precedes short-term memory and not vice versa....... memory system (e.g. Atkinson & Shiffrin, 1968). Short-term memory seems to provide a surprising processing bottleneck where only a very limited amount of information can be represented at any given moment (Miller, 1956; Cowan, 2001). A number of studies have investigated the nature of this processing...

Patterns of Change in Interpersonal Problems During and After Short-term and Long-term Psychodynamic Group Therapy: A Randomized Clinical Trial.

Science.gov (United States)

Fjeldstad, Anette; Høglend, Per; Lorentzen, Steinar

2017-05-01

In this study, we compared the patterns of change in interpersonal problems between short-term and long-term psychodynamic group therapy. A total of 167 outpatients with mixed diagnoses were randomized to 20 or 80 weekly sessions of group therapy. Interpersonal problems were assessed with the Inventory of Interpersonal Problems at six time points during the 3-year study period. Using linear mixed models, change was linearly modelled in two steps. Earlier (within the first 6 months) and later (during the last 2.5 years) changes in five subscales were estimated. Contrary to what we expected, short-term therapy induced a significantly larger early change than long-term therapy on the cold subscale and there was a trend on the socially avoidant subscale, using a Bonferroni-adjusted alpha. There was no significant difference between short-term and long-term group therapy for improving problems in the areas cold, socially avoidant, nonassertive, exploitable, and overly nurturant over the 3 years.

Decoupling the short- and long-term behavior of stochastic volatility

DEFF Research Database (Denmark)

Bennedsen, Mikkel; Lunde, Asger; Pakkanen, Mikko

behavior) from long memory and persistence (long-term behavior) in a simple and parsimonious way, which allows us to successfully model volatility at all intraday time scales. Our prime model is based on the so-called Brownian semistationary process and we derive a number of theoretical properties...... measures of close to two thousand individual US equities, we find that both roughness and persistence appear to be universal properties of volatility. Inspired by the empirical findings, we introduce a new class of continuous-time stochastic volatility models, capable of decoupling roughness (short-term...

Short-term memory and long-term memory are still different.

Science.gov (United States)

Norris, Dennis

2017-09-01

A commonly expressed view is that short-term memory (STM) is nothing more than activated long-term memory. If true, this would overturn a central tenet of cognitive psychology-the idea that there are functionally and neurobiologically distinct short- and long-term stores. Here I present an updated case for a separation between short- and long-term stores, focusing on the computational demands placed on any STM system. STM must support memory for previously unencountered information, the storage of multiple tokens of the same type, and variable binding. None of these can be achieved simply by activating long-term memory. For example, even a simple sequence of digits such as "1, 3, 1" where there are 2 tokens of the digit "1" cannot be stored in the correct order simply by activating the representations of the digits "1" and "3" in LTM. I also review recent neuroimaging data that has been presented as evidence that STM is activated LTM and show that these data are exactly what one would expect to see based on a conventional 2-store view. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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...

Follicular dynamics, interval to ovulation and fertility after AI in short-term progesterone and PGF2α oestrous synchronization protocol in sheep.

Science.gov (United States)

Cox, J F; Allende, R; Lara, E; Leiva, A; Díaz, T; Dorado, J; Saravia, F

2012-12-01

The study was aimed to assess the influence that short-term progesterone treatments have on follicular dynamics, oestrus and ovulation in sheep. The treatment was tested thereafter in a field trial to assess its fertility after AI with fresh semen. In a first experiment, 12 ewes without CL were grouped to receive a new (n = 6) or used CIDR (n = 6) for 7 days and blood samples were obtained to follow plasma progesterone profiles. In a second experiment, 39 cycling ewes were synchronized by a 7-day P4+PGF2α protocol using a new (n = 20) or a 7-day used CIDR (n = 19). Half of both groups received 400 IU eCG and half remained untreated as controls. Ultrasound ovarian examination and oestrous detection were used to compare follicular dynamics, oestrus and ovulation in both groups. In a third experiment, 288 ewes in 3 farms were synchronized by the short-term P4+PGF2α+eCG protocol and ewes were AI with fresh semen 24 h after oestrous detection. Lambing performance was used to test the fertility of the treatment. In Experiment 1, ewes with new inserts presented higher P4 concentration than ewes with used inserts throughout the sampling period (p 0.10). However, ewes treated with eCG show shorter interval to oestrus (p = 0.004) and tend to have larger mature CL (p = 0.06). In Experiment 3, oestrous presentation and lambing performance after AI with fresh semen was considered normal compared to published results. Results suggest that the oestrous synchronization protocol based on P4+PGF2α allows little control of follicular dynamics without compromising fertility after AI with fresh semen provided that eCG is added at the end of the treatment. © 2012 Blackwell Verlag GmbH.

Improving short-term forecasting during ramp events by means of Regime-Switching Artificial Neural Networks

Science.gov (United States)

Gallego, C.; Costa, A.; Cuerva, A.

2010-09-01

Since nowadays wind energy can't be neither scheduled nor large-scale storaged, wind power forecasting has been useful to minimize the impact of wind fluctuations. In particular, short-term forecasting (characterised by prediction horizons from minutes to a few days) is currently required by energy producers (in a daily electricity market context) and the TSO's (in order to keep the stability/balance of an electrical system). Within the short-term background, time-series based models (i.e., statistical models) have shown a better performance than NWP models for horizons up to few hours. These models try to learn and replicate the dynamic shown by the time series of a certain variable. When considering the power output of wind farms, ramp events are usually observed, being characterized by a large positive gradient in the time series (ramp-up) or negative (ramp-down) during relatively short time periods (few hours). Ramp events may be motivated by many different causes, involving generally several spatial scales, since the large scale (fronts, low pressure systems) up to the local scale (wind turbine shut-down due to high wind speed, yaw misalignment due to fast changes of wind direction). Hence, the output power may show unexpected dynamics during ramp events depending on the underlying processes; consequently, traditional statistical models considering only one dynamic for the hole power time series may be inappropriate. This work proposes a Regime Switching (RS) model based on Artificial Neural Nets (ANN). The RS-ANN model gathers as many ANN's as different dynamics considered (called regimes); a certain ANN is selected so as to predict the output power, depending on the current regime. The current regime is on-line updated based on a gradient criteria, regarding the past two values of the output power. 3 Regimes are established, concerning ramp events: ramp-up, ramp-down and no-ramp regime. In order to assess the skillness of the proposed RS-ANN model, a single

Improving creativity performance by short-term meditation

Science.gov (United States)

2014-01-01

Background One form of meditation intervention, the integrative body-mind training (IBMT) has been shown to improve attention, reduce stress and change self-reports of mood. In this paper we examine whether short-term IBMT can improve performance related to creativity and determine the role that mood may play in such improvement. Methods Forty Chinese undergraduates were randomly assigned to short-term IBMT group or a relaxation training (RT) control group. Mood and creativity performance were assessed by the Positive and Negative Affect Schedule (PANAS) and Torrance Tests of Creative Thinking (TTCT) questionnaire respectively. Results As predicted, the results indicated that short-term (30 min per day for 7 days) IBMT improved creativity performance on the divergent thinking task, and yielded better emotional regulation than RT. In addition, cross-lagged analysis indicated that both positive and negative affect may influence creativity in IBMT group (not RT group). Conclusions Our results suggested that emotion-related creativity-promoting mechanism may be attributed to short-term meditation. PMID:24645871

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.

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.

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.

The Structure and Content of Long-Term and Short-Term Mate Preferences

Directory of Open Access Journals (Sweden)

Peter K. Jonason

2013-12-01

Full Text Available This study addresses two limitations in the mate preferences literature. First, research all-too-often relies on single-item assessments of mate preferences precluding more advanced statistical techniques like factor analysis. Second, when factor analysis could be done, it exclusively has done for long-term mate preferences, at the exclusion of short-term mate preferences. In this study (N = 401, we subjected 20 items designed to measure short- and long-term mate preferences to both principle components (n = 200 and confirmatory factor analysis (n = 201. In the long-term context, we replicated previous findings that there are three different categories of preferences: physical attractiveness, interpersonal warmth, and social status. In the short-term context, physical attractiveness occupied two parts of the structure, social status dropped out, and interpersonal warmth remained. Across short- and long-term contexts, there were slight changes in what defined the shared dimensions (i.e., physical attractiveness and interpersonal warmth, suggesting prior work that applies the same inventory to each context might be flawed. We also replicated sex differences and similarities in mate preferences and correlates with sociosexuality and mate value. We adopt an evolutionary paradigm to understand our results.

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

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.

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.

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.

New insights into the short pitch corrugation development enigma based on 3D-FE dynamic vehicle-track coupled modelling in frictional rolling contact

NARCIS (Netherlands)

Li, S.; Li, Z.; Nunez Vicencio, Alfredo; Dollevoet, R.P.B.J.

2017-01-01

A three-dimensional (3D) finite element (FE) dynamic frictional rolling contact model is presented for the study of short pitch corrugation that considers direct and instantaneous coupling between the contact mechanics and the structural dynamics in a vehicle-track system. In this study, we examine

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

OpenAIRE

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

2017-01-01

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

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.

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…

Distinct cerebellar engrams in short-term and long-term motor learning.

Science.gov (United States)

Wang, Wen; Nakadate, Kazuhiko; Masugi-Tokita, Miwako; Shutoh, Fumihiro; Aziz, Wajeeha; Tarusawa, Etsuko; Lorincz, Andrea; Molnár, Elek; Kesaf, Sebnem; Li, Yun-Qing; Fukazawa, Yugo; Nagao, Soichi; Shigemoto, Ryuichi

2014-01-07

Cerebellar motor learning is suggested to be caused by long-term plasticity of excitatory parallel fiber-Purkinje cell (PF-PC) synapses associated with changes in the number of synaptic AMPA-type glutamate receptors (AMPARs). However, whether the AMPARs decrease or increase in individual PF-PC synapses occurs in physiological motor learning and accounts for memory that lasts over days remains elusive. We combined quantitative SDS-digested freeze-fracture replica labeling for AMPAR and physical dissector electron microscopy with a simple model of cerebellar motor learning, adaptation of horizontal optokinetic response (HOKR) in mouse. After 1-h training of HOKR, short-term adaptation (STA) was accompanied with transient decrease in AMPARs by 28% in target PF-PC synapses. STA was well correlated with AMPAR decrease in individual animals and both STA and AMPAR decrease recovered to basal levels within 24 h. Surprisingly, long-term adaptation (LTA) after five consecutive daily trainings of 1-h HOKR did not alter the number of AMPARs in PF-PC synapses but caused gradual and persistent synapse elimination by 45%, with corresponding PC spine loss by the fifth training day. Furthermore, recovery of LTA after 2 wk was well correlated with increase of PF-PC synapses to the control level. Our findings indicate that the AMPARs decrease in PF-PC synapses and the elimination of these synapses are in vivo engrams in short- and long-term motor learning, respectively, showing a unique type of synaptic plasticity that may contribute to memory consolidation.

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...

Modelling the long-term vertical dynamics of salt marshes

Science.gov (United States)

Zoccarato, Claudia; Teatini, Pietro

2017-04-01

Salt marshes are vulnerable environments hosting complex interactions between physical and biological processes with a strong influence on the dynamics of the marsh evolution. The estimation and prediction of the elevation of a salt-marsh platform is crucial to forecast the marsh growth or regression under different scenarios considering, for example, the potential climate changes. The long-term vertical dynamics of a salt marsh is predicted with the aid of an original finite-element (FE) numerical model accounting for the marsh accretion and compaction and for the variation rates of the relative sea level rise, i.e., land subsidence of the marsh basement and eustatic rise of the sea level. The accretion term considers the vertical sedimentation of organic and inorganic material over the marsh surface, whereas the compaction reflects the progressive consolidation of the porous medium under the increasing load of the overlying younger deposits. The modelling approach is based on a 2D groundwater flow simulator, which provides the pressure evolution within a compacting/accreting vertical cross-section of the marsh assuming that the groundwater flow obeys the relative Darcy's law, coupled to a 1D vertical geomechanical module following Terzaghi's principle of effective intergranular stress. Soil porosity, permeability, and compressibility may vary with the effective intergranular stress according to empirically based relationships. The model also takes into account the geometric non-linearity arising from the consideration of large solid grain movements by using a Lagrangian approach with an adaptive FE mesh. The element geometry changes in time to follow the deposit consolidation and the element number increases in time to follow the sedimentation of new material. The numerical model is tested on different realistic configurations considering the influence of (i) the spatial distribution of the sedimentation rate in relation to the distance from the marsh margin, (ii

Short-Term Effects of Drying-Rewetting and Long-Term Effects of Nutrient Loading on Periphyton N:P Stoichiometry

Directory of Open Access Journals (Sweden)

Andres D. Sola

2018-01-01

Full Text Available Nitrogen (N and phosphorus (P concentrations and N:P ratios critically influence periphyton productivity and nutrient cycling in aquatic ecosystems. In coastal wetlands, variations in hydrology and water source (fresh or marine influence nutrient availability, but short-term effects of drying and rewetting and long-term effects of nutrient exposure on periphyton nutrient retention are uncertain. An outdoor microcosm experiment simulated short-term exposure to variation in drying-rewetting frequency on periphyton mat nutrient retention. A 13-year dataset from freshwater marshes of the Florida Everglades was examined for the effect of long-term proximity to different N and P sources on mat-forming periphyton nutrient standing stocks and stoichiometry. Field sites were selected from one drainage with shorter hydroperiod and higher connectivity to freshwater anthropogenic nutrient supplies (Taylor Slough/Panhandle, TS/Ph and another drainage with longer hydroperiod and higher connectivity to marine nutrient supplies (Shark River Slough, SRS. Total P, but not total N, increased in periphyton mats exposed to both low and high drying-rewetting frequency with respect to the control mats in our experimental microcosm. In SRS, N:P ratios slightly decreased downstream due to marine nutrient supplies, while TS/Ph increased. Mats exposed to short-term drying-rewetting had higher nutrient retention, similar to nutrient standing stocks from long-term field data. Periphyton mat microbial communities may undergo community shifts upon drying-rewetting and chronic exposure to nutrient loads. Additional work on microbial species composition may further explain how periphyton communities interact with drying-rewetting dynamics to influence nutrient cycling and retention in wetlands.

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....

Perturbation analysis of transient population dynamics using matrix projection models

DEFF Research Database (Denmark)

Stott, Iain

2016-01-01

Non-stable populations exhibit short-term transient dynamics: size, growth and structure that are unlike predicted long-term asymptotic stable, stationary or equilibrium dynamics. Understanding transient dynamics of non-stable populations is important for designing effective population management...... these methods to know exactly what is being measured. Despite a wealth of existing methods, I identify some areas that would benefit from further development....

Defect production in simulated cascades: Cascade quenching and short-term annealing

International Nuclear Information System (INIS)

Heinisch, H.L.

1983-01-01

Defect production in displacement cascades in copper has been modeled using the MARLOWE code to generate cascades and the stochastic annealing code ALSOME to simulate cascade quenching and short-term annealing of isolated cascades. Quenching is accomplished by using exaggerated values for defect mobilities and for critical reaction distances in ALSOME for a very short time. The quenched cascades are then short-term annealed with normal parameter values. The quenching parameter values were empirically determined by comparison with results of resistivity measurements. Throughout the collisional, quenching and short-term annealing phases of cascade development, the high energy cascades continue to behave as a collection of independent lower energy lobes. For recoils above about 30 keV the total number of defects and the numbers of free defects scale with the damage energy. As the energy decreases from 30 keV, defect production varies with the changing nature of the cascade configuration, resulting in more defects per unit damage energy. The simulated annealing of a low fluence of interacting cascades revealed an interstitial shielding effect on depleted zones during Stage I recovery. (orig.)

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.

Development and application of a short- /long-term composited drought index in the upper Huaihe River basin, China

Directory of Open Access Journals (Sweden)

M. Yu

2015-06-01

Full Text Available Accurate and reliable drought monitoring is of primary importance for drought mitigation and reduction of social-ecological vulnerability. The aim of the paper was to propose a short-term/long-term composited drought index (CDI which could be widely used for drought monitoring and early warning in China. In the study, the upper Huaihe River basin above the Xixian gauge station, which has been hit by severe droughts frequently in recent decades, was selected as the case study site. The short-term CDI was developed by the Principle Component Analysis of the self-calibrating Palmer Drought Severity Index (sc-PDSI, the 1- and 3-month Standardized Precipitation Evapotranspiration Index (SPEI, Z Index (ZIND, the Soil Moisture Index (SMI with the long-term CDI being formulated by use of the self-calibrating Palmer Hydrology Drought Index (sc-PHDI, the 6-, 12-, 18- and 24-month SPEI, the Standardized Streamflow Index (SSI, the SMI. The sc-PDSI, the PHDI, the ZIND, the SPEI on a monthly time scale were calculated based on the monthly air temperature and precipitation, and the monthly SMI and SSI were computed based on the simulated soil moisture and runoff by the distributed Xinanjiang model. The thresholds of the short-term/long-term CDI were determined according to frequency statistics of different drought indices. Finally, the feasibility of the two CDIs was investigated against the scPDSI, the SPEI and the historical drought records. The results revealed that the short-term/long-term CDI could capture the onset, severity, persistence of drought events very well with the former being better at identifying the dynamic evolution of drought condition while the latter better at judging the changing trend of drought over a long time period.

Short-range dynamics and prediction of mesoscale flow patterns in the MISTRAL field experiment

Energy Technology Data Exchange (ETDEWEB)

Weber, R.O.; Kaufmann, P.; Talkner, P. [Paul Scherrer Inst. (PSI), Villigen (Switzerland)

1997-06-01

In a limited area of about 50 km by 50 km with complex topography, wind measurements on a dense network were performed during the MISTRAL field experiment in 1991-1992. From these data the characteristic wind fields were identified by an automated classification method. The dynamics of the resulting twelve typical regional flow patterns is studied. It is discussed how transitions between the flow patterns take place and how well the transition probabilities can be described in the framework of a Markov model. Guided by this discussion, a variety of prediction models were tested which allow a short-term forecast of the flow pattern type. It is found that a prediction model which uses forecast information from the synoptic scale has the best forecast skill. (author) 2 figs., 7 refs.

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…

Implementing a short-term loyalty program : case: Bosch Lawn & Garden and the Ventum short-term loyalty program

OpenAIRE

Logvinova, Veronika

2015-01-01

In 2015, one of the Bosch Home and Garden divisions, Bosch Lawn and Garden, has made a strategic decision to adopt a points-based short-term loyalty program called Ventum LG in the German supermarkets and petrol stations. It was decided that the base of this program will be completed Ventum PT short-term loyalty program which was managed by another division, Bosch Power Tools, and proved to be successful. This thesis aims to evaluate the worthiness of the Ventum LG loyalty program for Bosch L...

Dynamic panel data models

NARCIS (Netherlands)

Bun, M.J.G.; Sarafidis, V.

2013-01-01

This Chapter reviews the recent literature on dynamic panel data models with a short time span and a large cross-section. Throughout the discussion we considerlinear models with additional endogenous covariates. First we give a broad overview of available inference methods placing emphasis on GMM.

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

Short-term memory in olfactory network dynamics

Science.gov (United States)

Stopfer, Mark; Laurent, Gilles

1999-12-01

Neural assemblies in a number of animal species display self-organized, synchronized oscillations in response to sensory stimuli in a variety of brain areas.. In the olfactory system of insects, odour-evoked oscillatory synchronization of antennal lobe projection neurons (PNs) is superimposed on slower and stimulus-specific temporal activity patterns. Hence, each odour activates a specific and dynamic projection neuron assembly whose evolution during a stimulus is locked to the oscillation clock. Here we examine, using locusts, the changes in population dynamics of projection-neuron assemblies over repeated odour stimulations, as would occur when an animal first encounters and then repeatedly samples an odour for identification or localization. We find that the responses of these assemblies rapidly decrease in intensity, while they show a marked increase in spike time precision and inter-neuronal oscillatory coherence. Once established, this enhanced precision in the representation endures for several minutes. This change is stimulus-specific, and depends on events within the antennal lobe circuits, independent of olfactory receptor adaptation: it may thus constitute a form of sensory memory. Our results suggest that this progressive change in olfactory network dynamics serves to converge, over repeated odour samplings, on a more precise and readily classifiable odour representation, using relational information contained across neural assemblies.

Mathematical analysis and algorithms for efficiently and accurately implementing stochastic simulations of short-term synaptic depression and facilitation

Directory of Open Access Journals (Sweden)

Mark D McDonnell

2013-05-01

Full Text Available The release of neurotransmitter vesicles after arrival of a pre-synaptic action potential at cortical synapses is known to be a stochastic process, as is the availability of vesicles for release. These processes are known to also depend on the recent history of action-potential arrivals, and this can be described in terms of time-varying probabilities of vesicle release. Mathematical models of such synaptic dynamics frequently are based only on the mean number of vesicles released by each pre-synaptic action potential, since if it is assumed there are sufficiently many vesicle sites, then variance is small. However, it has been shown recently that variance across sites can be significant for neuron and network dynamics, and this suggests the potential importance of studying short-term plasticity using simulations that do generate trial-to-trial variability. Therefore, in this paper we study several well-known conceptual models for stochastic availability and release. We state explicitly the random variables that these models describe and propose efficient algorithms for accurately implementing stochastic simulations of these random variables in software or hardware. Our results are complemented by mathematical analysis and statement of pseudo-code algorithms.

Short- and long-term behavioural, physiological and stoichiometric responses to predation risk indicate chronic stress and compensatory mechanisms.

Science.gov (United States)

Van Dievel, Marie; Janssens, Lizanne; Stoks, Robby

2016-06-01

Prey organisms are expected to use different short- and long-term responses to predation risk to avoid excessive costs. Contrasting both types of responses is important to identify chronic stress responses and possible compensatory mechanisms in order to better understand the full impact of predators on prey life history and population dynamics. Using larvae of the damselfly Enallagma cyathigerum, we contrasted the effects of short- and long-term predation risk, with special focus on consequences for body stoichiometry. Under short-term predation risk, larvae reduced growth rate, which was associated with a reduced food intake, increased metabolic rate and reduced glucose content. Under long-term predation risk, larvae showed chronic predator stress as indicated by persistent increases in metabolic rate and reduced food intake. Despite this, larvae were able to compensate for the short-term growth reduction under long-term predation risk by relying on physiological compensatory mechanisms, including reduced energy storage. Only under long-term predation risk did we observe an increase in body C:N ratio, as predicted under the general stress paradigm (GSP). Although this was caused by a predator-induced decrease in N content, there was no associated increase in C content. These stoichiometric changes could not be explained by GSP responses because, under chronic predation risk, there was no decrease in N-rich proteins or increase in C-rich fat and sugars; instead glycogen decreased. Our results highlight the importance of compensatory mechanisms and the value of explicitly integrating physiological mechanisms to obtain insights into the temporal dynamics of non-consumptive effects, including effects on body stoichiometry.

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.

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-07-17

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

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...

Short-term memory and electrical restitution in the canine transmural ventricle

International Nuclear Information System (INIS)

Zhang, Hong; Ueyama, Takeshi; Lin, Shien-Fong; Wang, Juan; Wu, Rui-Juan

2011-01-01

Cardiac short-term memory is an intrinsic property of paced myocardium that reflects the influence of pacing history. Using an optical mapping method to record membrane voltage and intracellular calcium (Ca 2+ i ), this study investigated the properties and mechanisms of short-term memory in isolated and perfused canine wedge preparations. In addition to the dynamic and S1S2 pacing protocols, a perturbed downsweep pacing protocol was used to get a complete overview of the restitution portrait. Abrupt changes in basic cycle length (BCL) were applied to investigate the accommodation process of action potential duration (APD). The results showed unobvious differences of memory among the epi-, mid- and endo-myocytes, implying an insignificant memory-induced transient heterogeneity in APD across the transmural canine hearts. With the decrease of pacing rate S1, memory gradually elevated and achieved a maximum around 400 ms, and then reduced as S1 decreased further, indicating a non-monotonic relationship between memory and the pacing rate. After suppressing the Ca 2+ i transient with ryanodine (3 µmol l −1 ), the accommodation process of APD to a new BCL significantly abbreviated (τ = 37.41 ± 4.42 stimuli before ryanodine, τ = 15.84 ± 4.74 stimuli after ryanodine, p < 0.01). Therefore, Ca 2+ i cycling was suggested to play an important role in memory during dynamic pacing

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...

Effect of BRCA1/2 mutation on short-term and long-term breast cancer survival: a systematic review and meta-analysis.

Science.gov (United States)

Lee, Eun-Ha; Park, Sue K; Park, Boyoung; Kim, Sung-Won; Lee, Min Hyuk; Ahn, Sei Hyun; Son, Byung Ho; Yoo, Keun-Young; Kang, Daehee

2010-07-01

Reports of BRCA genetic mutations and risk of death or recurrence are inconsistent. This study aimed to compare overall and disease-free breast cancer survival rates between BRCA1/2 mutation carriers and non-carriers for short-term and long-term outcomes separately. We searched the PUBMED and EMBASE databases and retrieved 452 articles using keywords that included breast cancer, BRCA mutation, and survival. Seventeen articles were selected for systematic review and among them 11 were included in our meta-analysis. We used the random-effects model to calculate the summary hazard ratio and corresponding 95% confidence interval. BRCA1 mutation carriers had significantly lower short-term and long-term overall survival rates (OSR) relative to non-carriers (HR = 1.92 [95% CI = 1.45-2.53]; 1.33 [1.12-1.58], respectively), while both short-term and long-term OSR of BRCA2 carriers did not differ from non-carriers (HR = 1.30 [95% CI = 0.95-1.76]; 1.12 [95% CI = 0.86-1.45], respectively). For short-term progression-free survival rate (PFSR), BRCA1 mutation carriers had a significantly lower rate than non-carriers (HR = 1.54 [95% CI = 1.12-2.12]), while BRCA2 mutation carriers had a similar PFSR (HR = 1.23 [95% CI = 0.96-1.58]). For long-term PFSRs, we found no significant results. Our results suggest that BRCA1 mutation decreases short-term and long-term OSRs and short-term PFSR, however, BRCA2 mutation does not affect either short-term or long-term survival rate, which is attributed to the different carcinogenic pathways for BRCA1 and BRCA2.

Functional hoarseness in children: short-term play therapy with family dynamic counseling as therapy of choice.

Science.gov (United States)

Kollbrunner, Jürg; Seifert, Eberhard

2013-09-01

Children with nonorganic voice disorders (NVDs) are treated mainly using direct voice therapy techniques such as the accent method or glottal attack changes and indirect methods such as vocal hygiene and voice education. However, both approaches tackle only the symptoms and not etiological factors in the family dynamics and therefore often enjoy little success. The aim of the "Bernese Brief Dynamic Intervention" (BBDI) for children with NVD was to extend the effectiveness of pediatric voice therapies with a psychosomatic concept combining short-term play therapy with the child and family dynamic counseling of the parents. This study compares the therapeutic changes in three groups where different procedures were used, before intervention and 1 year afterward: counseling of parents (one to two consultations; n = 24), Brief Dynamic Intervention on the lines of the BBDI (three to five play therapy sessions with the child plus two to four sessions with the parents; n = 20), and traditional voice therapy (n = 22). A Voice Questionnaire for Parents developed by us with 59 questions to be answered on a four-point Likert scale was used to measure the change. According to the parents' assessment, a significant improvement in voice quality was achieved in all three methods. Counseling of parents (A) appears to have led parents to give their child more latitude, for example, they stopped nagging the child or demanding that he/she should behave strictly by the rules. After BBDI (B), the mothers were more responsive to their children's wishes and the children were more relaxed and their speech became livelier. At home, they called out to them less often at a distance, which probably improved parent-child dialog. Traditional voice therapy (C) seems to have had a positive effect on the children's social competence. BBDI seems to have the deepest, widest, and therefore probably the most enduring therapeutic effect on children with NVD. Copyright © 2013 The Voice Foundation

Short-Term Memory for Order but Not for Item Information Is Impaired in Developmental Dyslexia

Science.gov (United States)

Hachmann, Wibke M.; Bogaerts, Louisa; Szmalec, Arnaud; Woumans, Evy; Duyck, Wouter; Job, Remo

2014-01-01

Recent findings suggest that people with dyslexia experience difficulties with the learning of serial order information during the transition from short-to long-term memory (Szmalec et al. "Journal of Experimental Psychology: Learning, Memory, & Cognition" 37(5): 1270-1279, 2011). At the same time, models of short-term memory…

Non-linear dynamical classification of short time series of the rössler system in high noise regimes.

Science.gov (United States)

Lainscsek, Claudia; Weyhenmeyer, Jonathan; Hernandez, Manuel E; Poizner, Howard; Sejnowski, Terrence J

2013-01-01

Time series analysis with delay differential equations (DDEs) reveals non-linear properties of the underlying dynamical system and can serve as a non-linear time-domain classification tool. Here global DDE models were used to analyze short segments of simulated time series from a known dynamical system, the Rössler system, in high noise regimes. In a companion paper, we apply the DDE model developed here to classify short segments of encephalographic (EEG) data recorded from patients with Parkinson's disease and healthy subjects. Nine simulated subjects in each of two distinct classes were generated by varying the bifurcation parameter b and keeping the other two parameters (a and c) of the Rössler system fixed. All choices of b were in the chaotic parameter range. We diluted the simulated data using white noise ranging from 10 to -30 dB signal-to-noise ratios (SNR). Structure selection was supervised by selecting the number of terms, delays, and order of non-linearity of the model DDE model that best linearly separated the two classes of data. The distances d from the linear dividing hyperplane was then used to assess the classification performance by computing the area A' under the ROC curve. The selected model was tested on untrained data using repeated random sub-sampling validation. DDEs were able to accurately distinguish the two dynamical conditions, and moreover, to quantify the changes in the dynamics. There was a significant correlation between the dynamical bifurcation parameter b of the simulated data and the classification parameter d from our analysis. This correlation still held for new simulated subjects with new dynamical parameters selected from each of the two dynamical regimes. Furthermore, the correlation was robust to added noise, being significant even when the noise was greater than the signal. We conclude that DDE models may be used as a generalizable and reliable classification tool for even small segments of noisy data.

Inverse stochastic–dynamic models for high-resolution Greenland ice core records

Directory of Open Access Journals (Sweden)

N. Boers

2017-12-01

Full Text Available Proxy records from Greenland ice cores have been studied for several decades, yet many open questions remain regarding the climate variability encoded therein. Here, we use a Bayesian framework for inferring inverse, stochastic–dynamic models from δ18O and dust records of unprecedented, subdecadal temporal resolution. The records stem from the North Greenland Ice Core Project (NGRIP, and we focus on the time interval 59–22 ka b2k. Our model reproduces the dynamical characteristics of both the δ18O and dust proxy records, including the millennial-scale Dansgaard–Oeschger variability, as well as statistical properties such as probability density functions, waiting times and power spectra, with no need for any external forcing. The crucial ingredients for capturing these properties are (i high-resolution training data, (ii cubic drift terms, (iii nonlinear coupling terms between the δ18O and dust time series, and (iv non-Markovian contributions that represent short-term memory effects.

Inverse stochastic-dynamic models for high-resolution Greenland ice core records

Science.gov (United States)

Boers, Niklas; Chekroun, Mickael D.; Liu, Honghu; Kondrashov, Dmitri; Rousseau, Denis-Didier; Svensson, Anders; Bigler, Matthias; Ghil, Michael

2017-12-01

Proxy records from Greenland ice cores have been studied for several decades, yet many open questions remain regarding the climate variability encoded therein. Here, we use a Bayesian framework for inferring inverse, stochastic-dynamic models from δ18O and dust records of unprecedented, subdecadal temporal resolution. The records stem from the North Greenland Ice Core Project (NGRIP), and we focus on the time interval 59-22 ka b2k. Our model reproduces the dynamical characteristics of both the δ18O and dust proxy records, including the millennial-scale Dansgaard-Oeschger variability, as well as statistical properties such as probability density functions, waiting times and power spectra, with no need for any external forcing. The crucial ingredients for capturing these properties are (i) high-resolution training data, (ii) cubic drift terms, (iii) nonlinear coupling terms between the δ18O and dust time series, and (iv) non-Markovian contributions that represent short-term memory effects.

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.

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

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

DEFF Research Database (Denmark)

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

2008-01-01

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

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...

DOES SHORT TERM DEBT AFFECT PROFITABILITY? EVIDENCE FROM THE ROMANIAN LISTED COMPANIES

Directory of Open Access Journals (Sweden)

MILOŞ LAURA RAISA

2015-12-01

Full Text Available This study aims at providing new empirical evidence on the influence of debt (both on short and long term on corporate profitability, with application to the Romanian companies listed on the Bucharest Stock Exchange. Panel data are analyzed for 50 companies belonging to different fields of activity during 2003-2014 using a fixed effect regression model. After we control for size, growth, liquidity, and tangibility of assets, the results reveal that short-term debt has a negative influence on corporate profitability.

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.

Semantic and phonological contributions to short-term repetition and long-term cued sentence recall.

Science.gov (United States)

Meltzer, Jed A; Rose, Nathan S; Deschamps, Tiffany; Leigh, Rosie C; Panamsky, Lilia; Silberberg, Alexandra; Madani, Noushin; Links, Kira A

2016-02-01

The function of verbal short-term memory is supported not only by the phonological loop, but also by semantic resources that may operate on both short and long time scales. Elucidation of the neural underpinnings of these mechanisms requires effective behavioral manipulations that can selectively engage them. We developed a novel cued sentence recall paradigm to assess the effects of two factors on sentence recall accuracy at short-term and long-term stages. Participants initially repeated auditory sentences immediately following a 14-s retention period. After this task was complete, long-term memory for each sentence was probed by a two-word recall cue. The sentences were either concrete (high imageability) or abstract (low imageability), and the initial 14-s retention period was filled with either an undemanding finger-tapping task or a more engaging articulatory suppression task (Exp. 1, counting backward by threes; Exp. 2, repeating a four-syllable nonword). Recall was always better for the concrete sentences. Articulatory suppression reduced accuracy in short-term recall, especially for abstract sentences, but the sentences initially recalled following articulatory suppression were retained better at the subsequent cued-recall test, suggesting that the engagement of semantic mechanisms for short-term retention promoted encoding of the sentence meaning into long-term memory. These results provide a basis for using sentence imageability and subsequent memory performance as probes of semantic engagement in short-term memory for sentences.

Short-term and long-term sick-leave in Sweden

DEFF Research Database (Denmark)

Blank, N; Diderichsen, Finn

1995-01-01

The primary aim of the study was to analyse similarities and differences between repeated spells of short-term sick-leave (more than 3 spells of less than 7 days' duration in a 12-month period) and long-term absence through sickness (at least 1 spell of more than 59 days' duration in a 12-month p...

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…

In-medium short-range dynamics of nucleons: Recent theoretical and experimental advances

Energy Technology Data Exchange (ETDEWEB)

Atti, Claudio Ciofi degli, E-mail: ciofi@pg.infn.it

2015-08-14

The investigation of in-medium short-range dynamics of nucleons, usually referred to as the study of short-range correlations (SRCs), is a key issue in nuclear and hadronic physics. As a matter of fact, even in the simplified assumption that the nucleus could be described as a system of protons and neutrons interacting via effective nucleon–nucleon (NN) interactions, several non trivial problems arise concerning the description of in-medium (NN short-range dynamics, namely: (i) the behavior of the NN interaction at short inter-nucleon distances in medium cannot be uniquely constrained by the experimental NN scattering phase shifts due to off-shell effects; (ii) by rigorous renormalization group (RG) techniques entire families of phase equivalent interactions differing in the short-range part can be derived; (iii) the in-medium NN interaction may be, in principle, different from the free one; (iv) when the short inter-nucleon separation is of the order of the nucleon size, the question arises of possible effects from quark and gluon degrees of freedom. For more than fifty years, experimental evidence of SRCs has been searched by means of various kinds of nuclear reactions, without however convincing results, mainly because the effects of SRCs arise from non observable quantities, like, e.g., the momentum distributions, and have been extracted from observable cross sections where short- and long-range effects, effects from nucleonic and non nucleonic degrees of freedom, and effects from final state interaction, could not be unambiguously separated out. Recent years, however, were witness of new progress in the field: from one side, theoretical and computational progress has allowed one to solve ab initio the many-nucleon non relativistic Schrödinger equation in terms of realistic NN interactions, obtaining realistic microscopic wave functions, unless the case of parametrized wave functions used frequently in the past, moreover the development of advanced

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.

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.

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.

NUMERICAL SIMULATION OF YIELDING SUPPORTS IN THE SHAPE OF ANNULAR TUBES UNDER STATIC AND SHORT-TERM DYNAMIC LOADING

Directory of Open Access Journals (Sweden)

Oleg G. Kumpyak

2017-12-01

Full Text Available Occurrence of extreme man-made impacts on buildings and structures has become frequent lately as a consequence of condensed explosives or explosive combustion of gas- vapor or air-fuel mixtures. Such accidents involve large human and economic losses, and their prevention methods are not always effective and reasonable. The given research aims at studying the way of enhancing explosion safety of building structures by means of yielding supports. The paper presents results of numerical studies (finite element, 3D nonlinear of strength and deformability of yielding supports in the shape of annular tubes under static and short-term dynamic loading. The degree of influence of yielding supports was assessed taking into account three peculiar stages of deformation: elastic; elasto-plastic; elasto-plastic with hardening. The methodology for numerical studies performance was described. It was established that rigidity of yielding supports influences significantly their stress-strain state. The research determined that with increase of deformable elements rigidity dependency between load and deformation of yielding supports in elastic and plastic stages have linear character. Significant reduction of dynamic response and increase of deformation time of yielding supports was observed by increasing the plastic component. Therefore it allows assuming on possibility of their application as supporting units in reinforced concrete constructions

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.

Long-Term Bacterial Dynamics in a Full-Scale Drinking Water Distribution System

NARCIS (Netherlands)

Prest, E.I.E.D.; Weissbrodt, D.G.; Hammes, F; van Loosdrecht, Mark C.M.; Vrouwenvelder, J.S.

2016-01-01

Large seasonal variations in microbial drinking water quality can occur in distribution networks, but are often not taken into account when evaluating results from short-term water sampling campaigns. Temporal dynamics in bacterial community characteristics were investigated during a two-year

Long-term evaluation of orbital dynamics in the Sun-planet system considering axial-tilt

Science.gov (United States)

Bakhtiari, Majid; Daneshjou, Kamran

2018-05-01

In this paper, the axial-tilt (obliquity) effect of planets on the motion of planets’ orbiter in prolonged space missions has been investigated in the presence of the Sun gravity. The proposed model is based on non-simplified perturbed dynamic equations of planetary orbiter motion. From a new point of view, in this work, the dynamic equations regarding a disturbing body in elliptic inclined three-dimensional orbit are derived. The accuracy of this non-simplified method is validated with dual-averaged method employed on a generalized Earth-Moon system. It is shown that the neglected short-time oscillations in dual-averaged technique can accumulate and propel to remarkable errors in the prolonged evolution. After validation, the effects of the planet’s axial-tilt on eccentricity, inclination and right ascension of the ascending node of the orbiter are investigated. Moreover, a generalized model is provided to study the effects of third-body inclination and eccentricity on orbit characteristics. It is shown that the planet’s axial-tilt is the key to facilitating some significant changes in orbital elements in long-term mission and short-time oscillations must be considered in accurate prolonged evaluation.

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.

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.

Musical and Verbal Memory in Alzheimer's Disease: A Study of Long-Term and Short-Term Memory

Science.gov (United States)

Menard, Marie-Claude; Belleville, Sylvie

2009-01-01

Musical memory was tested in Alzheimer patients and in healthy older adults using long-term and short-term memory tasks. Long-term memory (LTM) was tested with a recognition procedure using unfamiliar melodies. Short-term memory (STM) was evaluated with same/different judgment tasks on short series of notes. Musical memory was compared to verbal…

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

A least squares approach for efficient and reliable short-term versus long-term optimization

DEFF Research Database (Denmark)

Christiansen, Lasse Hjuler; Capolei, Andrea; Jørgensen, John Bagterp

2017-01-01

The uncertainties related to long-term forecasts of oil prices impose significant financial risk on ventures of oil production. To minimize risk, oil companies are inclined to maximize profit over short-term horizons ranging from months to a few years. In contrast, conventional production...... optimization maximizes long-term profits over horizons that span more than a decade. To address this challenge, the oil literature has introduced short-term versus long-term optimization. Ideally, this problem is solved by a posteriori multi-objective optimization methods that generate an approximation...... the balance between the objectives, leaving an unfulfilled potential to increase profits. To promote efficient and reliable short-term versus long-term optimization, this paper introduces a natural way to characterize desirable Pareto points and proposes a novel least squares (LS) method. Unlike hierarchical...

Facilitative Effects of Forgetting from Short-Term Memory on Growth of Long-Term Memory in Retardates

Science.gov (United States)

Sperber, Richard D.

1976-01-01

Competing explanations of the beneficial effect of spacing in retardate discrimination learning were tested. Results are inconsistent with consolidation and rehearsal theories but support the prediction of the Geber, Greenfield, and House spacing model that forgetting from short-term memory facilities retardate learning. (Author/SB)

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…

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

Science.gov (United States)

Zhang, J; Nawata, K

2018-05-01

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

Do Short-Term Managerial Objectives Lead to Under- or Over-Investment in Long-Term Projects

OpenAIRE

Lucian Arye Bebchuk; Lars A. Stole

1994-01-01

This paper studies managerial decisions about investment in long-run projects in the presence of imperfect information (the market knows less about such investments than the firm's managers) and short-term managerial objectives (the managers are concerned about the short-term stock price as well as the long-term stock price). Prior work has suggested that imperfect information and short-term managerial objectives induce managers to underinvest in long-run projects. We show that either underin...

The Short-Term Dynamics of Peers and Delinquent Behavior: An Analysis of Bi-weekly Changes Within a High School Student Network

NARCIS (Netherlands)

F.M. Weerman (Frank); P. Wilcox (Pamela); C.J. Sullivan (Christopher J.)

2017-01-01

markdownabstract_Objectives:_ To analyze short-term changes in peer affiliations, offending behavior and routine activities in order to evaluate three different processes: peer selection, peer socialization and situational peer influences. _Methods:_ The short-term longitudinal TEENS study was

Assessing the associative deficit of older adults in long-term and short-term/working memory.

Science.gov (United States)

Chen, Tina; Naveh-Benjamin, Moshe

2012-09-01

Older adults exhibit a deficit in associative long-term memory relative to younger adults. However, the literature is inconclusive regarding whether this deficit is attenuated in short-term/working memory. To elucidate the issue, three experiments assessed younger and older adults' item and interitem associative memory and the effects of several variables that might potentially contribute to the inconsistent pattern of results in previous studies. In Experiment 1, participants were tested on item and associative recognition memory with both long-term and short-term retention intervals in a single, continuous recognition paradigm. There was an associative deficit for older adults in the short-term and long-term intervals. Using only short-term intervals, Experiment 2 utilized mixed and blocked test designs to examine the effect of test event salience. Blocking the test did not attenuate the age-related associative deficit seen in the mixed test blocks. Finally, an age-related associative deficit was found in Experiment 3, under both sequential and simultaneous presentation conditions. Even while accounting for some methodological issues, the associative deficit of older adults is evident in short-term/working memory.

Short- and long-term tannin induced carbon, nitrogen and phosphorus dynamics in Corsican pine litter

NARCIS (Netherlands)

Nierop, K.G.J.; Verstraten, J.M.; Tietema, A.; Westerveld, J.W.; Wartenbergh, P.E.

2006-01-01

Pine litter amended with either tannic acid (TA) or condensed tannins (CTs) was studied to assess the effects on C, N and P mineralization in relation to the fate of tannins by incubation experiments during various time intervals. TA induced a rapid short-term effect resulting in high C respiration

The pedagogy of Short-Term Study-Abroad Programs

Directory of Open Access Journals (Sweden)

Jude Gonsalvez

2013-10-01

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

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)

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

Science.gov (United States)

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

2014-07-01

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

Relationship between short and long term radon measurements

International Nuclear Information System (INIS)

Martinez, T.; Ramirez, D.; Navarrete, M.; Cabrera, L.; Ramirez, A.; Gonzalez, P.

2000-01-01

In this work the radon group of the Faculty of Chemistry at the National University of Mexico presents the results obtained in the establishment of a relation between the short and long term radon measures made with passive electret detectors E-PERM type LLT and HST. The measures were carried out inside single family dwellings (open house condition) located in the southeast of Mexico City (in Xochimilco) during the four seasons of the year 1997. A correlation was established between the short term measures (five days) and those of a long term for every season as well as an annual average, with an equation that relates them. The objective and advantage of this correlation are that with a short term measure it is possible to predict the annual mean radon concentration, that represents a saving of human and economic resources. (author)

Impact of short-term severe accident management actions in a long-term perspective. Final Report

International Nuclear Information System (INIS)

2000-03-01

The present systems for severe accident management are focused on mitigating the consequences of special severe accident phenomena and to reach a safe plant state. However, in the development of strategies and procedures for severe accident management, it is also important to consider the long-term perspective of accident management and especially to secure the safe state of the plant. The main reason for this is that certain short-term actions have an impact on the long-term scenario. Both positive and negative effects from short-term actions on the accident management in the long-term perspective have been included in this paper. Short-term actions are accident management measures taken within about 24 hours after the initiating event. The purpose of short-term actions is to reach a stable status of the plant. The main goal in the long-term perspective is to maintain the reactor in a stable state and prevent uncontrolled releases of activity. The purpose of this short Technical Note, deliberately limited in scope, is to draw attention to potential long-term problems, important to utilities and regulatory authorities, arising from the way a severe accident would be managed during the first hours. Its objective is to encourage discussions on the safest - and maybe also most economical - way to manage a severe accident in the long term by not making the situation worse through inappropriate short-term actions, and on the identification of short-term actions likely to make long-term management easier and safer. The Note is intended as a contribution to the knowledge base put at the disposal of Member countries through international collaboration. The scope of the work has been limited to a literature search. Useful further activities have been identified. However, there is no proposal, at this stage, for more detailed work to be undertaken under the auspices of the CSNI. Plant-specific applications would need to be developed by utilities

A systems biology analysis of long and short-term memories of osmotic stress adaptation in fungi

Directory of Open Access Journals (Sweden)

You Tao

2012-05-01

Full Text Available Abstract Background Saccharomyces cerevisiae senses hyperosmotic conditions via the HOG signaling network that activates the stress-activated protein kinase, Hog1, and modulates metabolic fluxes and gene expression to generate appropriate adaptive responses. The integral control mechanism by which Hog1 modulates glycerol production remains uncharacterized. An additional Hog1-independent mechanism retains intracellular glycerol for adaptation. Candida albicans also adapts to hyperosmolarity via a HOG signaling network. However, it remains unknown whether Hog1 exerts integral or proportional control over glycerol production in C. albicans. Results We combined modeling and experimental approaches to study osmotic stress responses in S. cerevisiae and C. albicans. We propose a simple ordinary differential equation (ODE model that highlights the integral control that Hog1 exerts over glycerol biosynthesis in these species. If integral control arises from a separation of time scales (i.e. rapid HOG activation of glycerol production capacity which decays slowly under hyperosmotic conditions, then the model predicts that glycerol production rates elevate upon adaptation to a first stress and this makes the cell adapts faster to a second hyperosmotic stress. It appears as if the cell is able to remember the stress history that is longer than the timescale of signal transduction. This is termed the long-term stress memory. Our experimental data verify this. Like S. cerevisiae, C. albicans mimimizes glycerol efflux during adaptation to hyperosmolarity. Also, transient activation of intermediate kinases in the HOG pathway results in a short-term memory in the signaling pathway. This determines the amplitude of Hog1 phosphorylation under a periodic sequence of stress and non-stressed intervals. Our model suggests that the long-term memory also affects the way a cell responds to periodic stress conditions. Hence, during osmohomeostasis, short-term memory is

Fine tuning support vector machines for short-term wind speed forecasting

International Nuclear Information System (INIS)

Zhou Junyi; Shi Jing; Li Gong

2011-01-01

Research highlights: → A systematic approach to tuning SVM models for wind speed prediction is proposed. → Multiple kernel functions and a wide range of tuning parameters are evaluated, and optimal parameters for each kernel function are obtained. → It is found that the forecasting performance of SVM is closely related to the dynamic characteristics of wind speed. → Under the optimal combination of parameters, different kernels give comparable forecasting accuracy. -- Abstract: Accurate forecasting of wind speed is critical to the effective harvesting of wind energy and the integration of wind power into the existing electric power grid. Least-squares support vector machines (LS-SVM), a powerful technique that is widely applied in a variety of classification and function estimation problems, carries great potential for the application of short-term wind speed forecasting. In this case, tuning the model parameters for optimal forecasting accuracy is a fundamental issue. This paper, for the first time, presents a systematic study on fine tuning of LS-SVM model parameters for one-step ahead wind speed forecasting. Three SVM kernels, namely linear, Gaussian, and polynomial kernels, are implemented. The SVM parameters considered include the training sample size, SVM order, regularization parameter, and kernel parameters. The results show that (1) the performance of LS-SVM is closely related to the dynamic characteristics of wind speed; (2) all parameters investigated greatly affect the performance of LS-SVM models; (3) under the optimal combination of parameters after fine tuning, the three kernels give comparable forecasting accuracy; (4) the performance of linear kernel is worse than the other two kernels when the training sample size or SVM order is small. In addition, LS-SVMs are compared against the persistence approach, and it is found that they can outperform the persistence model in the majority of cases.

Short-term memory of motor network performance via activity-dependent potentiation of Na+/K+ pump function.

Science.gov (United States)

Zhang, Hong-Yan; Sillar, Keith T

2012-03-20

Brain networks memorize previous performance to adjust their output in light of past experience. These activity-dependent modifications generally result from changes in synaptic strengths or ionic conductances, and ion pumps have only rarely been demonstrated to play a dynamic role. Locomotor behavior is produced by central pattern generator (CPG) networks and modified by sensory and descending signals to allow for changes in movement frequency, intensity, and duration, but whether or how the CPG networks recall recent activity is largely unknown. In Xenopus frog tadpoles, swim bout duration correlates linearly with interswim interval, suggesting that the locomotor network retains a short-term memory of previous output. We discovered an ultraslow, minute-long afterhyperpolarization (usAHP) in network neurons following locomotor episodes. The usAHP is mediated by an activity- and sodium spike-dependent enhancement of electrogenic Na(+)/K(+) pump function. By integrating spike frequency over time and linking the membrane potential of spinal neurons to network performance, the usAHP plays a dynamic role in short-term motor memory. Because Na(+)/K(+) pumps are ubiquitously expressed in neurons of all animals and because sodium spikes inevitably accompany network activity, the usAHP may represent a phylogenetically conserved but largely overlooked mechanism for short-term memory of neural network function. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

African Journals Online (AJOL)

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

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.

Short-term economics of virtual power plants

International Nuclear Information System (INIS)

Kok, J.K.

2009-08-01

The Virtual Power Plant (VPP) has gained an increasing interest over the last few years. A VPP is a flexible representation of a portfolio of Distributed Energy Resources (DER: distributed generation, demand response and electricity storage). One of the key activities of a VPP is the delivery of (near-)real-time balancing services. In order to operate such a (near-)real-time coordination activity optimally, the VPP needs to maintain a dynamic merit-order list of all DER participating in the VPP. In order to make optimal decisions based on this list, the merit order needs to be based on the true marginal cost (or marginal benefit in case of demand response) of the individual DER units. The marginal electricity costs of most types of DER are highly dependent on local context and, hence, change over time. From analysis of the short-term bid strategies of various DER units, the existence of a bid strategy spectrum becomes clear. On one end of the spectrum, bidding strategies are based straightforwardly on true marginal cost or benefit. Further along the spectrum, optimal bidding strategies become less dependent on marginal cost levels and more on the price dynamics in the (VPP) market context. These results are relevant for VPP operations both from business and technical perspectives.

Errors in nonword repetition: bridging short- and long-term memory.

Science.gov (United States)

Santos, F H; Bueno, O F A; Gathercole, S E

2006-03-01

According to the working memory model, the phonological loop is the component of working memory specialized in processing and manipulating limited amounts of speech-based information. The Children's Test of Nonword Repetition (CNRep) is a suitable measure of phonological short-term memory for English-speaking children, which was validated by the Brazilian Children's Test of Pseudoword Repetition (BCPR) as a Portuguese-language version. The objectives of the present study were: i) to investigate developmental aspects of the phonological memory processing by error analysis in the nonword repetition task, and ii) to examine phoneme (substitution, omission and addition) and order (migration) errors made in the BCPR by 180 normal Brazilian children of both sexes aged 4-10, from preschool to 4th grade. The dominant error was substitution [F(3,525) = 180.47; P long than in short items, was observed [F(3,519) = 108.36; P long-term memory contributes to holding memory trace. The findings were discussed in terms of distinctiveness, clustering and redintegration hypotheses.

Analytical Modeling of Transient Process In Terms of One-Dimensional Problem of Dynamics With Kinematic Action

Directory of Open Access Journals (Sweden)

Kravets Victor V.

2016-05-01

Full Text Available One-dimensional dynamic design of a component characterized by inertia coefficient, elastic coefficient, and coefficient of energy dispersion. The component is affected by external action in the form of time-independent initial kinematic disturbances and varying ones. Mathematical model of component dynamics as well as a new form of analytical representation of transient in terms of one-dimensional problem of kinematic effect is provided. Dynamic design of a component is being carried out according to a theory of modal control.

RADFOOD--a dynamic model for radioactivity transfer through the human food chain

International Nuclear Information System (INIS)

Koch, J.; Tadmor, J.

1986-01-01

Radioactive fallout presents a short-term risk due to its direct deposition on agricultural crops, as well as a long-term risk resulting from its deposition on soil and subsequent uptake by crops. A dynamic model, RADFOOD, was developed, based on different existing models. It simulates transport of fallout radionuclides through agricultural food chains to man and evaluates the radiation doses resulting from consumption of contaminated food. Transport was modeled through compartments representing various environmental elements of food products. Internal radiation doses (whole-body weighted doses) following ingestion of contaminated foodstuffs were then estimated. Specific types of crops, soils and diet of man and livestock were considered. A sample calculation was performed in which individual and collective radiation doses, as well as associated health effects, resulting from fallout contamination were evaluated. They were estimated for food consumption beginning at various times after the fallout deposition and for different consumption durations. A sensitivity analysis, performed for the main model parameters, showed that the radiation dose is sensitive, for the short-term period, to changes in initial deposition levels and in the parameters characterizing initial fallout interception and resuspension

The effect of permafrost thaw on short- and long-term carbon accumulation in permafrost mires

Science.gov (United States)

Olid, Carolina; Klaminder, Jonatan; Monteux, Sylvain; Johansson, Margareta; Dorrepaal, Ellen

2017-04-01

validate these hypotheses, an empirically based peat development model was applied to peat cores collected from manipulated thaw (n=6) and control (n=6) plots. Short- (decades) and long-(centuries) term C accumulation rates were estimated using a combined 210Pb and 14C chronology. In contrast to previous studies, our approach is long term and allows applying an empirical mass balance to evaluate depth-explicit changes in C inputs, C losses, and net C accumulation rates in response to permafrost thaw. Comparing shallow versus deep soil C does not only reflect short versus long-term C dynamics but also shows how the responses vary depending on different soil conditions. Our goal is to provide insights to better understand permafrost C dynamics to improve theoretical and predictive climate impact models.

Short-term memory binding deficits in Alzheimer's disease

OpenAIRE

Parra, Mario; Abrahams, S.; Fabi, K.; Logie, R.; Luzzi, S.; Della Sala, Sergio

2009-01-01

Alzheimer's disease impairs long term memories for related events (e.g. faces with names) more than for single events (e.g. list of faces or names). Whether or not this associative or ‘binding’ deficit is also found in short-term memory has not yet been explored. In two experiments we investigated binding deficits in verbal short-term memory in Alzheimer's disease. Experiment 1 : 23 patients with Alzheimer's disease and 23 age and education matched healthy elderly were recruited. Participants...

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.

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

Relationship between short-term sexual strategies and sexual jealousy.

Science.gov (United States)

Mathes, Eugene W

2005-02-01

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

Analysis of recurrent neural networks for short-term energy load forecasting

Science.gov (United States)

Di Persio, Luca; Honchar, Oleksandr

2017-11-01

Short-term forecasts have recently gained an increasing attention because of the rise of competitive electricity markets. In fact, short-terms forecast of possible future loads turn out to be fundamental to build efficient energy management strategies as well as to avoid energy wastage. Such type of challenges are difficult to tackle both from a theoretical and applied point of view. Latter tasks require sophisticated methods to manage multidimensional time series related to stochastic phenomena which are often highly interconnected. In the present work we first review novel approaches to energy load forecasting based on recurrent neural network, focusing our attention on long/short term memory architectures (LSTMs). Such type of artificial neural networks have been widely applied to problems dealing with sequential data such it happens, e.g., in socio-economics settings, for text recognition purposes, concerning video signals, etc., always showing their effectiveness to model complex temporal data. Moreover, we consider different novel variations of basic LSTMs, such as sequence-to-sequence approach and bidirectional LSTMs, aiming at providing effective models for energy load data. Last but not least, we test all the described algorithms on real energy load data showing not only that deep recurrent networks can be successfully applied to energy load forecasting, but also that this approach can be extended to other problems based on time series prediction.

Impact of long-term and short-term therapies on seminal parameters

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Jlenia Elia

2013-04-01

Full Text Available Aim: The aim of this work was: i to evaluate the prevalence of male partners of subfertile couples being treated with long/short term therapies for non andrological diseases; ii to study their seminal profile for the possible effects of their treatments on spermatogenesis and/or epididymal maturation. Methods: The study group was made up of 723 subjects, aged between 25 and 47 years. Semen analysis was performed according to World Health Organization (WHO guidelines (1999. The Superimposed Image Analysis System (SIAS, which is based on the computerized superimposition of spermatozoa images, was used to assess sperm motility parameters. Results: The prevalence of subjects taking pharmacological treatments was 22.7% (164/723. The prevalence was 3.7% (27/723 for the Short-Term Group and 18.9% (137/723 for the Long-Term Group. The subjects of each group were also subdivided into subgroups according to the treatments being received. Regarding the seminal profile, we did not observe a significant difference between the Long-Term, Short-Term or the Control Group. However, regarding the subgroups, we found a significant decrease in sperm number and progressive motility percentage in the subjects receiving treatment with antihypertensive drugs compared with the other subgroups and the Control Group. Conclusions: In the management of infertile couples, the potential negative impact on seminal parameters of any drugs being taken as Long-Term Therapy should be considered. The pathogenic mechanism needs to be clarified.

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)

Short term wind speed forecasting in La Venta, Oaxaca, Mexico, using artificial neural networks

Energy Technology Data Exchange (ETDEWEB)

Cadenas, Erasmo [Facultad de Ingenieria Mecanica, Universidad Michoacana de San Nicolas de Hidalgo, Santiago Tapia No. 403, Centro, 5000, Mor., Mich. (Mexico); Rivera, Wilfrido [Centro de Ivestigacion en Energia, Universidad Nacional Autonoma de Mexico, Apartado Postal 34, Temixco 62580, Morelos (Mexico)

2009-01-15

In this paper the short term wind speed forecasting in the region of La Venta, Oaxaca, Mexico, applying the technique of artificial neural network (ANN) to the hourly time series representative of the site is presented. The data were collected by the Comision Federal de Electricidad (CFE) during 7 years through a network of measurement stations located in the place of interest. Diverse configurations of ANN were generated and compared through error measures, guaranteeing the performance and accuracy of the chosen models. First a model with three layers and seven neurons was chosen, according to the recommendations of diverse authors, nevertheless, the results were not sufficiently satisfactory so other three models were developed, consisting of three layers and six neurons, two layers and four neurons and two layers and three neurons. The simplest model of two layers, with two input neurons and one output neuron, was the best for the short term wind speed forecasting, with mean squared error and mean absolute error values of 0.0016 and 0.0399, respectively. The developed model for short term wind speed forecasting showed a very good accuracy to be used by the Electric Utility Control Centre in Oaxaca for the energy supply. (author)

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

Science.gov (United States)

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

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.

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.

Correlation structures in short-term variabilities of stock indices and exchange rates

Science.gov (United States)

Nakamura, Tomomichi; Small, Michael

2007-09-01

Financial data usually show irregular fluctuations and some trends. We investigate whether there are correlation structures in short-term variabilities (irregular fluctuations) among financial data from the viewpoint of deterministic dynamical systems. Our method is based on the small-shuffle surrogate method. The data we use are daily closing price of Standard & Poor's 500 and the volume, and daily foreign exchange rates, Euro/US Dollar (USD), British Pound/USD and Japanese Yen/USD. We found that these data are not independent.

Short-term flow induced crystallization in isotactic polypropylene : how short is short?

NARCIS (Netherlands)

Ma, Z.; Balzano, L.; Portale, G.; Peters, G.W.M.

2013-01-01

The so-called "short-term flow" protocol is widely applied in experimental flow-induced crystallization studies on polymers in order to separate the nucleation and subsequent growth processes [Liedauer et al. Int. Polym. Proc. 1993, 8, 236–244]. The basis of this protocol is the assumption that

Saving and Re-building Lives: Determinants of Short-term and Long-term Disaster Relief

Directory of Open Access Journals (Sweden)

Geethanjali SELVARETNAM

2014-11-01

Full Text Available We analyse both theoretically and empirically, the factors that influence the amount of humanitarian aid received by countries which are struck by natural disasters, particularly distinguishing between immediate disaster relief and long term humanitarian aid. The theoretical model is able to make predictions as well as explain some of the peculiarities in the empirical results. We show that both short and long term humanitarian aid increases with number of people killed, financial loss and level of corruption, while GDP per capita had no effect. More populated countries receive more humanitarian aid. Earthquake, tsunami and drought attract more aid.

Comparison of Short Term with Long Term Catheterization after Anterior Colporrhaphy Surgery

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F. Movahed

2010-07-01

Full Text Available Introduction & Objective: This belief that overfilling the bladder after anterior colporrhaphy might have a negative influence on surgical outcome, causes routine catheterization after operation. This study was done to compare short term (24h with long term (72h catheterization after anterior colporrhaphy.Materials & Methods: This randomized clinical trial was carried out at Kosar Hospital , Qazvin (Iran in 2005-2006. One hundred cases candidating for anterior colporrhaphy , were divided in two equal groups . In the first group foley catheter was removed 24 hours and in the second group 72 hours after the operation. Before removing catheter, urine sample was obtained for culture . After removal and urination, residual volume was determinded. If the volume exceeded 200 ml or retention occured, the catheter would be fixed for more 72 hours. Need for recatheterization, urinary retention, positive urine culture,and hospital stay were surveyed. The data was analyzed using T and Fisher tests.Results: Residual volume exceeding 200 ml and the need for recatheterization occurred in one case (2% in the short term group but in the long term group none of the subjects needed recatheterization (P=1. Retention was not seen. In the both groups, one case (2% had positive urine culture with no statistically significant difference (P=1. Mean hospital stay was short in the first group (P=0.00.Conclusion: Short term catheterization after anterior colporrhaphy does not cause urinary retention and decreases hospital stay.

Clinical trials with rasagiline: evidence for short-term and long-term effects.

Science.gov (United States)

Siderowf, Andrew; Stern, Matthew

2006-05-23

Rasagiline (N-propargyl-1 (R)-aminoindan) is a selective, potent irreversible inhibitor of MAO-B that possesses neuroprotective and anti-apoptotic properties in a variety of in vitro and in vivo animal models relevant to Parkinson's disease (PD). Several randomized controlled clinical trials have demonstrated the safety and efficacy of rasagiline as monotherapy in PD and as adjunctive therapy for patients receiving levodopa. In addition, the 1-year randomized, delayed-start analysis of the TEMPO study suggests that rasagiline may slow the rate of progression of PD. The randomized delayed-start paradigm has potential to differentiate short-term symptomatic effects from long-term effects of anti-parkinsonian agents. In the future, long-term trials to examine the potential disease-modifying effects of rasagiline, which incorporate biological markers as well as clinical endpoints, may further elucidate the role of rasagiline in the treatment of both early and advanced PD.

Short-term versus long-term market opportunities and financial constraints

International Nuclear Information System (INIS)

Ferrari, Angelo

1999-01-01

This presentation discusses gas developments in Europe, the European Gas Directive, short term vs. long term, and Snam's new challenges. The European gas market is characterized by (1) The role of gas in meeting the demand for energy, which varies greatly from one country to another, (2) A growing market, (3) Decreasing role of domestic production, and (4) Increasing imports. Within the European Union, the Gas Directive aims to transform single national markets into one integrated European market by introducing third party access to the network for eligible clients as a means of increasing the competition between operators. The Gas Directive would appear to modify the form of the market rather than its size, and in particular the sharing of responsibility and risk among operators. The market in the future will offer operators the possibility to exploit opportunities deriving mainly from demands for increased flexibility. Opportunities linked to entrepreneurial initiatives require long-term investments characteristic of the gas business. Risks and opportunities must be balanced evenly between different operators. If everyone takes on their own risks and responsibilities, this means a wider distribution of the risks of long-term vs. short-term, currently borne by the gas companies that are integrated, into a market that tends to favour the short-term. A gradual liberalization process should allow incumbent operators to gradually diversify their activities in new gas market areas or enter new business activities. They could move beyond their local and European boundaries in pursuit of an international dimension. The market will have to make the transition from the national to the European dimension: as an example, Snam covers 90% of the Italian market, but its share of an integrated European market will be about 15%

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.

Dynamic energy-demand models. A comparison

International Nuclear Information System (INIS)

Yi, Feng

2000-01-01

This paper compares two second-generation dynamic energy demand models, a translog (TL) and a general Leontief (GL), in the study of price elasticities and factor substitutions of nine Swedish manufacturing industries: food, textiles, wood, paper, printing, chemicals, non-metallic minerals, base metals and machinery. Several model specifications are tested with likelihood ratio test. There is a disagreement on short-run adjustments; the TL model accepts putty-putty production technology of immediate adjustments, implying equal short- and long-run price elasticities of factors, while the GL model rejects immediate adjustments, giving out short-run elasticities quite different from the long-run. The two models also disagree in substitutability in many cases. 21 refs

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)

Short-Term Load Forecasting Based on Wavelet Transform and Least Squares Support Vector Machine Optimized by Fruit Fly Optimization Algorithm

Directory of Open Access Journals (Sweden)

Wei Sun

2015-01-01

Full Text Available Electric power is a kind of unstorable energy concerning the national welfare and the people’s livelihood, the stability of which is attracting more and more attention. Because the short-term power load is always interfered by various external factors with the characteristics like high volatility and instability, a single model is not suitable for short-term load forecasting due to low accuracy. In order to solve this problem, this paper proposes a new model based on wavelet transform and the least squares support vector machine (LSSVM which is optimized by fruit fly algorithm (FOA for short-term load forecasting. Wavelet transform is used to remove error points and enhance the stability of the data. Fruit fly algorithm is applied to optimize the parameters of LSSVM, avoiding the randomness and inaccuracy to parameters setting. The result of implementation of short-term load forecasting demonstrates that the hybrid model can be used in the short-term forecasting of the power system.

Prediction Models for Dynamic Demand Response

Energy Technology Data Exchange (ETDEWEB)

Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

2015-11-02

As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D²R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D²R, which we address in this paper. Our first contribution is the formal definition of D²R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D²R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D²R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D²R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D²R. Also, prediction models require just few days’ worth of data indicating that small amounts of

Stochastic health effects assessment due to short-term external exposure

International Nuclear Information System (INIS)

Raicevic, J.J.; Raskob, W.; Merkle, M.; Ninkovic, M.M.

2001-01-01

The new model for calculation of stochastic health effects is presented in this paper. The exposure pathways which are briefly considered are the short-term external exposure due to passage of the radioactive cloud (cloudshine) and the short-term external exposure due to radioactive material deposited on skin and clothes (skin contamination). The quantitative assessment of stochastic effects is expressed in numbers of deaths, which are given as a functions of the time at the accident, and age at death, what on the other side enables estimation of the number of deaths within the specified range of the time/age parameters. That means the model calculates the number of deaths within one particular year, summed up over all ages at deaths, or vice versa, it finds the number of deaths within the specified range of ages at death, summed up over all observation times. Results presented in this paper are implemented in the module LATEHEAL, which is incorporated in RODOS, a new European system for decision support for nuclear emergencies. (author)