A Field Experimental Design of a Strengths-Based Training to Overcome Academic Procrastination: Short- and Long-Term Effect

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Lennart Visser

2017-11-01

Full Text Available This study reports on the effect of a newly developed 4-week strengths-based training approach to overcome academic procrastination, given to first-year elementary teacher education students (N = 54. The training was based on a strengths-based approach, in which elements of the cognitive behavioral approach were also used. The purpose of the training was to promote awareness of the personal strengths of students who experience academic procrastination regularly and to teach them how to use their personal strengths in situations in which they usually tend to procrastinate. With a pretest-posttest control group design (two experimental groups: n = 31, control group: n = 23, the effect of the training on academic procrastination was studied after 1, 11, and 24 weeks. Results of a one-way analysis of covariance revealed a significant short-term effect of the training. In the long term (after 11 and 24 weeks, the scores for academic procrastination for the intervention groups remained stable, whereas the scores for academic procrastination for the control group decreased to the same level as those of the intervention groups. The findings of this study suggest that a strengths-based approach can be helpful to students at an early stage of their academic studies to initiate their individual process of dealing with academic procrastination. The findings for the long term show the importance of measuring the outcomes of an intervention not only shortly after the intervention but also in the long term. Further research is needed to find out how the short-term effect can be maintained in the long-term.

A Field Experimental Design of a Strengths-Based Training to Overcome Academic Procrastination: Short- and Long-Term Effect.

Science.gov (United States)

Visser, Lennart; Schoonenboom, Judith; Korthagen, Fred A J

2017-01-01

This study reports on the effect of a newly developed 4-week strengths-based training approach to overcome academic procrastination, given to first-year elementary teacher education students ( N = 54). The training was based on a strengths-based approach, in which elements of the cognitive behavioral approach were also used. The purpose of the training was to promote awareness of the personal strengths of students who experience academic procrastination regularly and to teach them how to use their personal strengths in situations in which they usually tend to procrastinate. With a pretest-posttest control group design (two experimental groups: n = 31, control group: n = 23), the effect of the training on academic procrastination was studied after 1, 11, and 24 weeks. Results of a one-way analysis of covariance revealed a significant short-term effect of the training. In the long term (after 11 and 24 weeks), the scores for academic procrastination for the intervention groups remained stable, whereas the scores for academic procrastination for the control group decreased to the same level as those of the intervention groups. The findings of this study suggest that a strengths-based approach can be helpful to students at an early stage of their academic studies to initiate their individual process of dealing with academic procrastination. The findings for the long term show the importance of measuring the outcomes of an intervention not only shortly after the intervention but also in the long term. Further research is needed to find out how the short-term effect can be maintained in the long-term.

A strategic approach to short- and long-term irradiated WWER fuel management

International Nuclear Information System (INIS)

Wilcox, P.; Conboy, T.M.

1994-01-01

A methodology is presented for comparison of alternative options for short-term and long-term irradiated fuel management. The value of this methodology is that all interested parties can take part in the analysis and derive the basis for decision-making. The methodology can answer questions as: When can uranium and plutonium recovered by reprocessing be recycled cost effectively in WWER? If reprocessing is not the short-term option chosen, is storage of irradiated fuel at the original licensed nuclear reactor site preferable to a separate storage-only-site? Are modular vault dry stores and cooling ponds which necessitate significant capital investment prior to deployment, more costly overall than their options? Should the most suitable form of irradiated fuel management be determined only by cost constraints? The key stages of the methodology are: 1) Assessing the current situation; 2) Assessing priorities; 3) Option/possible solutions; 4) Generic storage systems; 5) Cost/funding analysis; 6) Selection criteria; 7) Optioneering/evaluation. The conclusions that can be reached from this methodological approach lead to firm recommendations based on objective assessments. The methodology builds on existing expertise. It is not an imposed solution allowing an excellent exchange of knowledge and skills between the people involved

A strategic approach to short- and long-term irradiated WWER fuel management

Energy Technology Data Exchange (ETDEWEB)

Wilcox, P [BNFL International Ltd., Warrington (United Kingdom); Conboy, T M [BNFL Engineering Ltd., Manchester (United Kingdom)

1994-12-31

A methodology is presented for comparison of alternative options for short-term and long-term irradiated fuel management. The value of this methodology is that all interested parties can take part in the analysis and derive the basis for decision-making. The methodology can answer questions as: When can uranium and plutonium recovered by reprocessing be recycled cost effectively in WWER? If reprocessing is not the short-term option chosen, is storage of irradiated fuel at the original licensed nuclear reactor site preferable to a separate storage-only-site? Are modular vault dry stores and cooling ponds which necessitate significant capital investment prior to deployment, more costly overall than their options? Should the most suitable form of irradiated fuel management be determined only by cost constraints? The key stages of the methodology are: (1) Assessing the current situation; (2) Assessing priorities; (3) Option/possible solutions; (4) Generic storage systems; (5) Cost/funding analysis; (6) Selection criteria; (7) Optioneering/evaluation. The conclusions that can be reached from this methodological approach lead to firm recommendations based on objective assessments. The methodology builds on existing expertise. It is not an imposed solution allowing an excellent exchange of knowledge and skills between the people involved.

Short-Term State Forecasting-Based Optimal Voltage Regulation in Distribution Systems: Preprint

Energy Technology Data Exchange (ETDEWEB)

Yang, Rui; Jiang, Huaiguang; Zhang, Yingchen

2017-05-17

A novel short-term state forecasting-based optimal power flow (OPF) approach for distribution system voltage regulation is proposed in this paper. An extreme learning machine (ELM) based state forecaster is developed to accurately predict system states (voltage magnitudes and angles) in the near future. Based on the forecast system states, a dynamically weighted three-phase AC OPF problem is formulated to minimize the voltage violations with higher penalization on buses which are forecast to have higher voltage violations in the near future. By solving the proposed OPF problem, the controllable resources in the system are optimally coordinated to alleviate the potential severe voltage violations and improve the overall voltage profile. The proposed approach has been tested in a 12-bus distribution system and simulation results are presented to demonstrate the performance of the proposed approach.

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

The Demonstration of Short-Term Consolidation.

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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)

A New Two-Stage Approach to Short Term Electrical Load Forecasting

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Dragan Tasić

2013-04-01

Full Text Available In the deregulated energy market, the accuracy of load forecasting has a significant effect on the planning and operational decision making of utility companies. Electric load is a random non-stationary process influenced by a number of factors which make it difficult to model. To achieve better forecasting accuracy, a wide variety of models have been proposed. These models are based on different mathematical methods and offer different features. This paper presents a new two-stage approach for short-term electrical load forecasting based on least-squares support vector machines. With the aim of improving forecasting accuracy, one more feature was added to the model feature set, the next day average load demand. As this feature is unknown for one day ahead, in the first stage, forecasting of the next day average load demand is done and then used in the model in the second stage for next day hourly load forecasting. The effectiveness of the presented model is shown on the real data of the ISO New England electricity market. The obtained results confirm the validity advantage of the proposed approach.

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...

Short-term solar irradiation forecasting based on Dynamic Harmonic Regression

International Nuclear Information System (INIS)

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

2015-01-01

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

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

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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.

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

Evaluating the quality of scenarios of short-term wind power generation

DEFF Research Database (Denmark)

Pinson, Pierre; Girard, R.

2012-01-01

Scenarios of short-term wind power generation are becoming increasingly popular as input to multi-stage decision-making problems e.g. multivariate stochastic optimization and stochastic programming. The quality of these scenarios is intuitively expected to substantially impact the benets from...... their use in decision-making. So far however, their verication is almost always focused on their marginal distributions for each individual lead time only, thus overlooking their temporal interdependence structure. The shortcomings of such an approach are discussed. Multivariate verication tools, as well...... as diagnostic approaches based on event-based verication are then presented. Their application to the evaluation of various sets of scenarios of short-term wind power generation demonstrates them as valuable discrimination tools....

The effects of long- and short-term interdisciplinary treatment approaches in women with fibromyalgia: a randomized controlled trial.

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Saral, Ilknur; Sindel, Dilsad; Esmaeilzadeh, Sina; Sertel-Berk, Hanife Ozlem; Oral, Aydan

2016-10-01

We investigated the effects of long- and short-term interdisciplinary treatment approaches for reducing symptoms and improving health-related quality of life (HRQoL) and physical functions of patients with fibromyalgia and compared the effects of two different interdisciplinary treatment approaches. We conducted a prospective, randomized, controlled trial involving 66 women with fibromyalgia eligible for the study at a university hospital setting. The patients were randomized into three groups (allocation ratio 1:1:1) using a computer-generated random numbers: a long-term interdisciplinary treatment group (LG, n = 22) that participated in 10 sessions (3-h once-weekly session for 10 weeks) of cognitive behavioral therapy (CBT) together with exercise training and other fibromyalgia related educational programs (two full days); a short-term interdisciplinary treatment group (SG, n = 22) that received two full days of educational, exercise, and CBT programs; and a control group (CG, n = 22). The patients were evaluated at baseline and 6 months after treatment using the visual analog scale (pain, fatigue, and sleep), Fibromyalgia Impact Questionnaire, Beck Depression Inventory, Short Form-36, tender point numbers, and pressure algometry as primary outcomes. The statistical analysis was confined to the 'per-protocol' set. No blinding was performed. The number of patients analyzed was 21 in the LG, 19 in the SG, and 19 in the CG. The intensity of pain (p treatment approaches when compared with controls; the long-term treatment was found more effective in reducing pain than the short-term. Both, long- and short-term interdisciplinary treatments were effective in reducing the severity of some symptoms and disease activity in patients with fibromyalgia. The short-term program well meets the needs of women with fibromyalgia particularly in relation to pain and health status as measured using FIQ; however, a long-term program may be beneficial in reducing fatigue and

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

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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.

Feature-Based Visual Short-Term Memory Is Widely Distributed and Hierarchically Organized.

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Dotson, Nicholas M; Hoffman, Steven J; Goodell, Baldwin; Gray, Charles M

2018-06-15

Feature-based visual short-term memory is known to engage both sensory and association cortices. However, the extent of the participating circuit and the neural mechanisms underlying memory maintenance is still a matter of vigorous debate. To address these questions, we recorded neuronal activity from 42 cortical areas in monkeys performing a feature-based visual short-term memory task and an interleaved fixation task. We find that task-dependent differences in firing rates are widely distributed throughout the cortex, while stimulus-specific changes in firing rates are more restricted and hierarchically organized. We also show that microsaccades during the memory delay encode the stimuli held in memory and that units modulated by microsaccades are more likely to exhibit stimulus specificity, suggesting that eye movements contribute to visual short-term memory processes. These results support a framework in which most cortical areas, within a modality, contribute to mnemonic representations at timescales that increase along the cortical hierarchy. Copyright © 2018 Elsevier Inc. All rights reserved.

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)

A New Neural Network Approach to Short Term Load Forecasting of Electrical Power Systems

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Farshid Keynia

2011-03-01

Full Text Available Short-term load forecast (STLF is an important operational function in both regulated power systems and deregulated open electricity markets. However, STLF is not easy to handle due to the nonlinear and random-like behaviors of system loads, weather conditions, and social and economic environment variations. Despite the research work performed in the area, more accurate and robust STLF methods are still needed due to the importance and complexity of STLF. In this paper, a new neural network approach for STLF is proposed. The proposed neural network has a novel learning algorithm based on a new modified harmony search technique. This learning algorithm can widely search the solution space in various directions, and it can also avoid the overfitting problem, trapping in local minima and dead bands. Based on this learning algorithm, the suggested neural network can efficiently extract the input/output mapping function of the forecast process leading to high STLF accuracy. The proposed approach is tested on two practical power systems and the results obtained are compared with the results of several other recently published STLF methods. These comparisons confirm the validity of the developed approach.

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.

Subthreshold pharmacological and genetic approaches to analyzing CaV2.1-mediated NMDA receptor signaling in short-term memory.

Science.gov (United States)

Takahashi, Eiki; Niimi, Kimie; Itakura, Chitoshi

2010-10-25

Ca(V)2.1 is highly expressed in the nervous system and plays an essential role in the presynaptic modulation of neurotransmitter release machinery. Recently, the antiepileptic drug levetiracetam was reported to inhibit presynaptic Ca(V)2.1 functions, reducing glutamate release in the hippocampus, although the precise physiological role of Ca(V)2.1-regulated synaptic functions in cognitive performance at the system level remains unknown. This study examined whether Ca(V)2.1 mediates hippocampus-dependent spatial short-term memory using the object location and Y-maze tests, and perirhinal cortex-dependent nonspatial short-term memory using the object recognition test, via a combined pharmacological and genetic approach. Heterozygous rolling Nagoya (rol/+) mice carrying the Ca(V)2.1alpha(1) mutation had normal spatial and nonspatial short-term memory. A 100mg/kg dose of levetiracetam, which is ineffective in wild-type controls, blocked spatial short-term memory in rol/+ mice. At 5mg/kg, the N-methyl-D-aspartate (NMDA) receptor blocker (+/-)-3-(2-carboxypiperazin-4-yl)-propyl-1-phosphonic acid (CPP), which is ineffective in wild-type controls, also blocked the spatial short-term memory in rol/+ mice. Furthermore, a combination of subthreshold doses of levetiracetam (25 mg/kg) and CPP (2.5mg/kg) triggered a spatial short-term memory deficit in rol/+ mice, but not in wild-type controls. Similar patterns of nonspatial short-term memory were observed in wild-type and rol/+ mice when injected with levetiracetam (0-300 mg/kg). These results indicate that Ca(V)2.1-mediated NMDA receptor signaling is critical in hippocampus-dependent spatial short-term memory and differs in various regions. The combination subthreshold pharmacological and genetic approach presented here is easily performed and can be used to study functional signaling pathways in neuronal circuits. Copyright © 2010 Elsevier B.V. All rights reserved.

An Ensemble Approach for Improved Short-to-Intermediate-Term Seismic Potential Evaluation

Science.gov (United States)

Yu, Huaizhong; Zhu, Qingyong; Zhou, Faren; Tian, Lei; Zhang, Yongxian

2017-06-01

Pattern informatics (PI), load/unload response ratio (LURR), state vector (SV), and accelerating moment release (AMR) are four previously unrelated subjects, which are sensitive, in varying ways, to the earthquake's source. Previous studies have indicated that the spatial extent of the stress perturbation caused by an earthquake scales with the moment of the event, allowing us to combine these methods for seismic hazard evaluation. The long-range earthquake forecasting method PI is applied to search for the seismic hotspots and identify the areas where large earthquake could be expected. And the LURR and SV methods are adopted to assess short-to-intermediate-term seismic potential in each of the critical regions derived from the PI hotspots, while the AMR method is used to provide us with asymptotic estimates of time and magnitude of the potential earthquakes. This new approach, by combining the LURR, SV and AMR methods with the choice of identified area of PI hotspots, is devised to augment current techniques for seismic hazard estimation. Using the approach, we tested the strong earthquakes occurred in Yunnan-Sichuan region, China between January 1, 2013 and December 31, 2014. We found that most of the large earthquakes, especially the earthquakes with magnitude greater than 6.0 occurred in the seismic hazard regions predicted. Similar results have been obtained in the prediction of annual earthquake tendency in Chinese mainland in 2014 and 2015. The studies evidenced that the ensemble approach could be a useful tool to detect short-to-intermediate-term precursory information of future large earthquakes.

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.

Short-Term Wind Speed Forecasting Using Decomposition-Based Neural Networks Combining Abnormal Detection Method

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Xuejun Chen

2014-01-01

Full Text Available As one of the most promising renewable resources in electricity generation, wind energy is acknowledged for its significant environmental contributions and economic competitiveness. Because wind fluctuates with strong variation, it is quite difficult to describe the characteristics of wind or to estimate the power output that will be injected into the grid. In particular, short-term wind speed forecasting, an essential support for the regulatory actions and short-term load dispatching planning during the operation of wind farms, is currently regarded as one of the most difficult problems to be solved. This paper contributes to short-term wind speed forecasting by developing two three-stage hybrid approaches; both are combinations of the five-three-Hanning (53H weighted average smoothing method, ensemble empirical mode decomposition (EEMD algorithm, and nonlinear autoregressive (NAR neural networks. The chosen datasets are ten-minute wind speed observations, including twelve samples, and our simulation indicates that the proposed methods perform much better than the traditional ones when addressing short-term wind speed forecasting problems.

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.

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)

A New Approach to Detection of Systematic Errors in Secondary Substation Monitoring Equipment Based on Short Term Load Forecasting

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Javier Moriano

2016-01-01

Full Text Available In recent years, Secondary Substations (SSs are being provided with equipment that allows their full management. This is particularly useful not only for monitoring and planning purposes but also for detecting erroneous measurements, which could negatively affect the performance of the SS. On the other hand, load forecasting is extremely important since they help electricity companies to make crucial decisions regarding purchasing and generating electric power, load switching, and infrastructure development. In this regard, Short Term Load Forecasting (STLF allows the electric power load to be predicted over an interval ranging from one hour to one week. However, important issues concerning error detection by employing STLF has not been specifically addressed until now. This paper proposes a novel STLF-based approach to the detection of gain and offset errors introduced by the measurement equipment. The implemented system has been tested against real power load data provided by electricity suppliers. Different gain and offset error levels are successfully detected.

Assessing the short term impact of air pollution on mortality: a matching approach.

Science.gov (United States)

Baccini, Michela; Mattei, Alessandra; Mealli, Fabrizia; Bertazzi, Pier Alberto; Carugno, Michele

2017-02-10

The opportunity to assess short term impact of air pollution relies on the causal interpretation of the exposure-response association. However, up to now few studies explicitly faced this issue within a causal inference framework. In this paper, we reformulated the problem of assessing the short term impact of air pollution on health using the potential outcome approach to causal inference. We considered the impact of high daily levels of particulate matter ≤10 μm in diameter (PM 10 ) on mortality within two days from the exposure in the metropolitan area of Milan (Italy), during the period 2003-2006. Our research focus was the causal impact of a hypothetical intervention setting daily air pollution levels under a pre-fixed threshold. We applied a matching procedure based on propensity score to estimate the total number of attributable deaths (AD) during the study period. After defining the number of attributable deaths in terms of difference between potential outcomes, we used the estimated propensity score to match each high exposure day, namely each day with a level of exposure higher than 40 μg/m 3 , with a day with similar background characteristics but a level of exposure lower than 40 μg/m 3 . Then, we estimated the impact by comparing mortality between matched days. During the study period daily exposures larger than 40 μg/m 3 were responsible for 1079 deaths (90% CI: 116; 2042). The impact was more evident among the elderly than in the younger age classes. Exposures ≥ 40 μg/m 3 were responsible, among the elderly, for 1102 deaths (90% CI: 388, 1816), of which 797 from cardiovascular causes and 243 from respiratory causes. Clear evidence of an impact on respiratory mortality was found also in the age class 65-74, with 87 AD (90% CI: 11, 163). The propensity score matching turned out to be an appealing method to assess historical impacts in this field, which guarantees that the estimated total number of AD can be derived directly as sum

The neural bases of the short-term storage of verbal information are anatomically variable across individuals.

Science.gov (United States)

Feredoes, Eva; Tononi, Giulio; Postle, Bradley R

2007-10-10

What are the precise brain regions supporting the short-term retention of verbal information? A previous functional magnetic resonance imaging (fMRI) study suggested that they may be topographically variable across individuals, occurring, in most, in regions posterior to prefrontal cortex (PFC), and that detection of these regions may be best suited to a single-subject (SS) approach to fMRI analysis (Feredoes and Postle, 2007). In contrast, other studies using spatially normalized group-averaged (SNGA) analyses have localized storage-related activity to PFC. To evaluate the necessity of the regions identified by these two methods, we applied repetitive transcranial magnetic stimulation (rTMS) to SS- and SNGA-identified regions throughout the retention period of a delayed letter-recognition task. Results indicated that rTMS targeting SS analysis-identified regions of left perisylvian and sensorimotor cortex impaired performance, whereas rTMS targeting the SNGA-identified region of left caudal PFC had no effect on performance. Our results support the view that the short-term retention of verbal information can be supported by regions associated with acoustic, lexical, phonological, and speech-based representation of information. They also suggest that the brain bases of some cognitive functions may be better detected by SS than by SNGA approaches to fMRI data analysis.

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

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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.

Evaluating the quality of scenarios of short-term wind power generation

International Nuclear Information System (INIS)

Pinson, P.; Girard, R.

2012-01-01

Highlights: ► Presentation of the desirable properties of wind power generation scenarios. ► Description of various evaluation frameworks (univariate, multivariate, diagnostic). ► Highlighting of the properties of current approaches to scenario generation. ► Guidelines for future evaluation/benchmark exercises. -- Abstract: Scenarios of short-term wind power generation are becoming increasingly popular as input to multistage decision-making problems e.g. multivariate stochastic optimization and stochastic programming. The quality of these scenarios is intuitively expected to substantially impact the benefits from their use in decision-making. So far however, their verification is almost always focused on their marginal distributions for each individual lead time only, thus overlooking their temporal interdependence structure. The shortcomings of such an approach are discussed. Multivariate verification tools, as well as diagnostic approaches based on event-based verification are then presented. Their application to the evaluation of various sets of scenarios of short-term wind power generation demonstrates them as valuable discrimination tools.

A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-25

This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.

Response of stream invertebrates to short-term salinization: A mesocosm approach

International Nuclear Information System (INIS)

Cañedo-Argüelles, Miguel; Grantham, Theodore E.; Perrée, Isabelle; Rieradevall, Maria; Céspedes-Sánchez, Raquel; Prat, Narcís

2012-01-01

Salinization is a major and growing threat to freshwater ecosystems, yet its effects on aquatic invertebrates have been poorly described at a community-level. Here we use a controlled experimental setting to evaluate short-term stream community responses to salinization, under conditions designed to replicate the duration (72 h) and intensity (up to 5 mS cm −1 ) of salinity pulses common to Mediterranean rivers subjected to mining pollution during runoff events. There was a significant overall effect, but differences between individual treatments and the control were only significant for the highest salinity treatment. The community response to salinization was characterized by a decline in total invertebrate density, taxon richness and diversity, an increase in invertebrate drift and loss of the most sensitive taxa. The findings indicate that short-term salinity increases have a significant impact on the stream invertebrate community, but concentrations of 5 mS cm −1 are needed to produce a significant ecological response. - Highlights: ► Short-term salinization has a significant impact on the aquatic invertebrates. ► A significant short-term ecological response is registered at 5 mS cm −1 . ► Salinization causes a decline in invertebrate density, richness and diversity. ► Biotic quality indices decline with increasing salinity and exposure time. - Short-term salinization in a stream mesocosm caused a significant response in the aquatic invertebrate community and led to declines in biological quality indices.

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.

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

Prepectoral Implant-Based Breast Reconstruction and Postmastectomy Radiotherapy: Short-Term Outcomes

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Steven Sigalove, MD

2017-12-01

Conclusions:. Immediate implant-based prepectoral breast reconstruction followed by PMRT appears to be well tolerated, with no excess risk of adverse outcomes, at least in the short term. Longer follow-up is needed to better understand the risk of PMRT in prepectorally reconstructed breasts.

Short-term incentive schemes for hospital managers

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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.

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.)

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

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Rudolf Scitovski

2012-12-01

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

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...

Audit of long-term and short-term liabilities

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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.

An adaptive network-based fuzzy inference system for short-term natural gas demand estimation: Uncertain and complex environments

International Nuclear Information System (INIS)

Azadeh, A.; Asadzadeh, S.M.; Ghanbari, A.

2010-01-01

Accurate short-term natural gas (NG) demand estimation and forecasting is vital for policy and decision-making process in energy sector. Moreover, conventional methods may not provide accurate results. This paper presents an adaptive network-based fuzzy inference system (ANFIS) for estimation of NG demand. Standard input variables are used which are day of the week, demand of the same day in previous year, demand of a day before and demand of 2 days before. The proposed ANFIS approach is equipped with pre-processing and post-processing concepts. Moreover, input data are pre-processed (scaled) and finally output data are post-processed (returned to its original scale). The superiority and applicability of the ANFIS approach is shown for Iranian NG consumption from 22/12/2007 to 30/6/2008. Results show that ANFIS provides more accurate results than artificial neural network (ANN) and conventional time series approach. The results of this study provide policy makers with an appropriate tool to make more accurate predictions on future short-term NG demand. This is because the proposed approach is capable of handling non-linearity, complexity as well as uncertainty that may exist in actual data sets due to erratic responses and measurement errors.

Feature-based and object-based attention orientation during short-term memory maintenance.

Science.gov (United States)

Ku, Yixuan

2015-12-01

Top-down attention biases the short-term memory (STM) processing at multiple stages. Orienting attention during the maintenance period of STM by a retrospective cue (retro-cue) strengthens the representation of the cued item and improves the subsequent STM performance. In a recent article, Backer et al. (Backer KC, Binns MA, Alain C. J Neurosci 35: 1307-1318, 2015) extended these findings from the visual to the auditory domain and combined electroencephalography to dissociate neural mechanisms underlying feature-based and object-based attention orientation. Both event-related potentials and neural oscillations explained the behavioral benefits of retro-cues and favored the theory that feature-based and object-based attention orientation were independent. Copyright © 2015 the American Physiological Society.

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.

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

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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.

Questioning short-term memory and its measurement: Why digit span measures long-term associative learning.

Science.gov (United States)

Jones, Gary; Macken, Bill

2015-11-01

Traditional accounts of verbal short-term memory explain differences in performance for different types of verbal material by reference to inherent characteristics of the verbal items making up memory sequences. The role of previous experience with sequences of different types is ostensibly controlled for either by deliberate exclusion or by presenting multiple trials constructed from different random permutations. We cast doubt on this general approach in a detailed analysis of the basis for the robust finding that short-term memory for digit sequences is superior to that for other sequences of verbal material. Specifically, we show across four experiments that this advantage is not due to inherent characteristics of digits as verbal items, nor are individual digits within sequences better remembered than other types of individual verbal items. Rather, the advantage for digit sequences stems from the increased frequency, compared to other verbal material, with which digits appear in random sequences in natural language, and furthermore, relatively frequent digit sequences support better short-term serial recall than less frequent ones. We also provide corpus-based computational support for the argument that performance in a short-term memory setting is a function of basic associative learning processes operating on the linguistic experience of the rememberer. The experimental and computational results raise questions not only about the role played by measurement of digit span in cognition generally, but also about the way in which long-term memory processes impact on short-term memory functioning. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

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)

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

International Nuclear Information System (INIS)

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

2010-01-01

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

Model documentation report: Short-Term Hydroelectric Generation Model

International Nuclear Information System (INIS)

1993-08-01

The purpose of this report is to define the objectives of the Short- Term Hydroelectric Generation Model (STHGM), describe its basic approach, and to provide details on the model structure. This report is intended as a reference document for model analysts, users, and the general public. Documentation of the model is in accordance with the Energy Information Administration's (AYE) legal obligation to provide adequate documentation in support of its models (Public Law 94-385, Section 57.b.2). The STHGM performs a short-term (18 to 27- month) forecast of hydroelectric generation in the United States using an autoregressive integrated moving average (UREMIA) time series model with precipitation as an explanatory variable. The model results are used as input for the short-term Energy Outlook

Aging of Dissolved Copper and Copper-based Nanoparticles in Five Different Soils: Short-term Kinetics vs. Long-term Fate

Science.gov (United States)

With the growing availability and use of copper-based nanomaterials (Cu-NMs), there is increasing concern regarding their release and potential impact on the environment. In this study, the short term (≤5 d) aging profile and the long-term (135 d) speciation of dissolved Cu, cop...

GSM base stations: short-term effects on well-being.

Science.gov (United States)

Augner, Christoph; Florian, Matthias; Pauser, Gernot; Oberfeld, Gerd; Hacker, Gerhard W

2009-01-01

The purpose of this study was to examine the effects of short-term GSM (Global System for Mobile Communications) cellular phone base station RF-EMF (radiofrequency electromagnetic fields) exposure on psychological symptoms (good mood, alertness, calmness) as measured by a standardized well-being questionnaire. Fifty-seven participants were selected and randomly assigned to one of three different exposure scenarios. Each of those scenarios subjected participants to five 50-min exposure sessions, with only the first four relevant for the study of psychological symptoms. Three exposure levels were created by shielding devices in a field laboratory, which could be installed or removed during the breaks between sessions such that double-blinded conditions prevailed. The overall median power flux densities were 5.2 microW/m(2) during "low," 153.6 microW/m(2) during "medium," and 2126.8 microW/m(2) during "high" exposure sessions. For scenario HM and MH, the first and third sessions were "low" exposure. The second session was "high" and the fourth was "medium" in scenario HM; and vice versa for scenario MH. Scenario LL had four successive "low" exposure sessions constituting the reference condition. Participants in scenarios HM and MH (high and medium exposure) were significantly calmer during those sessions than participants in scenario LL (low exposure throughout) (P = 0.042). However, no significant differences between exposure scenarios in the "good mood" or "alertness" factors were obtained. We conclude that short-term exposure to GSM base station signals may have an impact on well-being by reducing psychological arousal. (c) 2008 Wiley-Liss, Inc.

A neutral network based technique for short-term forecasting of anomalous load periods

Energy Technology Data Exchange (ETDEWEB)

Sforna, M [ENEL, s.p.a, Italian Power Company (Italy); Lamedica, R; Prudenzi, A [Rome Univ. ` La Sapienza` , Rome (Italy); Caciotta, M; Orsolini Cencelli, V [Rome Univ. III, Rome (Italy)

1995-01-01

The paper illustrates a part of the research activity conducted by authors in the field of electric Short Term Load Forecasting (STLF) based on Artificial Neural Network (ANN) architectures. Previous experiences with basic ANN architectures have shown that, even though these architecture provide results comparable with those obtained by human operators for most normal days, they evidence some accuracy deficiencies when applied to `anomalous` load conditions occurring during holidays and long weekends. For these periods a specific procedure based upon a combined (unsupervised/supervised) approach has been proposed. The unsupervised stage provides a preventive classification of the historical load data by means of a Kohonen`s Self Organizing Map (SOM). The supervised stage, performing the proper forecasting activity, is obtained by using a multi-layer percept ron with a back propagation learning algorithm similar to the ones above mentioned. The unconventional use of information deriving from the classification stage permits the proposed procedure to obtain a relevant enhancement of the forecast accuracy for anomalous load situations.

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

An Untargeted Metabolomics Approach to Characterize Short-Term and Long-Term Metabolic Changes after Bariatric Surgery.

Directory of Open Access Journals (Sweden)

Sophie H Narath

Full Text Available Bariatric surgery is currently one of the most effective treatments for obesity and leads to significant weight reduction, improved cardiovascular risk factors and overall survival in treated patients. To date, most studies focused on short-term effects of bariatric surgery on the metabolic profile and found high variation in the individual responses to surgery. The aim of this study was to identify relevant metabolic changes not only shortly after bariatric surgery (Roux-en-Y gastric bypass but also up to one year after the intervention by using untargeted metabolomics. 132 serum samples taken from 44 patients before surgery, after hospital discharge (1-3 weeks after surgery and at a 1-year follow-up during a prospective study (NCT01271062 performed at two study centers (Austria and Switzerland. The samples included 24 patients with type 2 diabetes at baseline, thereof 9 with diabetes remission after one year. The samples were analyzed by using liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS, HILIC-QExactive. Raw data was processed with XCMS and drift-corrected through quantile regression based on quality controls. 177 relevant metabolic features were selected through Random Forests and univariate testing and 36 metabolites were identified. Identified metabolites included trimethylamine-N-oxide, alanine, phenylalanine and indoxyl-sulfate which are known markers for cardiovascular risk. In addition we found a significant decrease in alanine after one year in the group of patients with diabetes remission relative to non-remission. Our analysis highlights the importance of assessing multiple points in time in subjects undergoing bariatric surgery to enable the identification of biomarkers for treatment response, cardiovascular benefit and diabetes remission. Key-findings include different trend pattern over time for various metabolites and demonstrated that short term changes should not necessarily be used to identify

Effects of short term and long term soil warming on ecosystem phenology of a sub-arctic grassland: an NDVI-based approach

Science.gov (United States)

Leblans, Niki; Sigurdsson, Bjarni D.; Janssens, Ivan A.

2014-05-01

Phenology has been defined as the study of the timing of recurring biological events and the causes of their timing with regard to abiotic and biotic factors. Ecosystem phenology, including the onset of the growing season and its senescence in autumn, plays an important role in the carbon, water and energy exchange between biosphere and atmosphere at higher latitudes. Factors that influence ecosystem phenology can therefore induce important climate-controlling feedback mechanisms. Global surface temperatures have been predicted to increase in the coming decades. Hence, a better understanding of the effect of temperature on ecosystem phenology is essential. Natural geothermal soil temperature gradients in Iceland offer a unique opportunity to study the soil temperature (Ts) dependence of ecosystem phenology and distinguish short-term (transient) warming effects (in recently established Ts gradients) from long-term (permanent) effects (in centuries-old Ts gradients). This research was performed in the framework of an international research project (ForHot; www.forhot.is). ForHot includes two natural grassland areas with gradients in Ts, dominated by Festuca sp., Agrostis sp.. The first warmed area was created in 2008, when an earthquake in S-Iceland caused geothermal systems to be shifted to previously cold soils. The second area is located about 3 km away from this newly warmed grassland. For this area, there are proofs that the natural soil warming has been continuous for at least 300 year. In the present study we focus on Ts elevation gradients of +0 to +10°C. The experiment consists of five transects with five temperature levels (+0,+1,+3,+5 and +10°C) in the two aforementioned grassland ecosystems (n=25 in each grassland). From April until November 2013, weekly measurements of the normalized difference vegetation index (NDVI) were taken. In the short-term warmed grassland, the greening of the vegetation was 36 days advanced at +10°C Ts and the date of 50

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.

Chances of short-term cooling trends over Canada for the next decades

Science.gov (United States)

Grenier, Patrick; de Elia, Ramon; Chaumont, Diane

2014-05-01

As climate services continue to develop in Quebec, Canada, an increasing number of requests are made for providing information relevant for the near term. As a response, one approach has been to consider short-term cooling trends as a basis for climate products. This project comprises different aspects: technical steps, knowledge transfer, and societal use. Each step does represent a different challenge. The technical part, i.e. producing probabilistic distributions of short-term temperature trends, involves relatively complex scenario construction methods including bias-related post-processing, and access to wide simulation and observation databases. Calculations are performed on 60 CMIP5-based scenarios on a grid covering Canada during the period 2006-2035, and for 5, 10, 15, 20 and 25-year trend durations. Knowledge transfer implies overcoming misinterpretation, given that probabilistic projections based on simulation ensembles are not perfectly related to real-Earth possible outcomes. Finally, societal use of this information remains the biggest challenge. On the one hand, users clearly state their interest in near-term relevant information, and intuitively it seems clear that short-term cooling trends embedded within the long-term warming path should be considered in adaptation plans, for avoiding over-adaptation. On the other hand, the exact way of incorporating such information within a decision-making process has proven not to be obvious. Irrespective of that, the study and communication of short-term cooling chances is necessary for preventing decision-makers to infer from the eventual occurrence of such a trend that global warming isn't happening. The presentation will discuss the three aspects aforementioned.

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

Short-term hydro-thermal scheduling using particle swarm optimization method

International Nuclear Information System (INIS)

Yu, Binghui; Yuan, Xiaohui; Wang, Jinwen

2007-01-01

The approaches based on different particle swarm optimization (PSO) techniques are applied to solve the short-term hydro-thermal scheduling problem. In the proposed methods, many constraints of the hydro-thermal system, such as power balance, water balance, reservoir volume limits and the operation limits of hydro and thermal plants, are considered. The feasibility of the proposed algorithm is demonstrated through an example system, and the results are compared with the results of a genetic algorithm and evolutionary programming approaches. The experimental results show that all the PSO algorithms have the ability to achieve nearly global solutions, but a local version of PSO with inertia weight appears to be the best amongst all the PSOs in terms of high quality solution

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

International Nuclear Information System (INIS)

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

2017-01-01

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

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

Science.gov (United States)

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

2018-02-01

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

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.

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.

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).

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

Science.gov (United States)

Ak, Ronay; Fink, Olga; Zio, Enrico

2016-08-01

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

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

Science.gov (United States)

Anderson, K. R.

2016-12-01

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

Performance of fuzzy approach in Malaysia short-term electricity load forecasting

Science.gov (United States)

Mansor, Rosnalini; Zulkifli, Malina; Yusof, Muhammad Mat; Ismail, Mohd Isfahani; Ismail, Suzilah; Yin, Yip Chee

2014-12-01

Many activities such as economic, education and manafucturing would paralyse with limited supply of electricity but surplus contribute to high operating cost. Therefore electricity load forecasting is important in order to avoid shortage or excess. Previous finding showed festive celebration has effect on short-term electricity load forecasting. Being a multi culture country Malaysia has many major festive celebrations such as Eidul Fitri, Chinese New Year and Deepavali but they are moving holidays due to non-fixed dates on the Gregorian calendar. This study emphasis on the performance of fuzzy approach in forecasting electricity load when considering the presence of moving holidays. Autoregressive Distributed Lag model was estimated using simulated data by including model simplification concept (manual or automatic), day types (weekdays or weekend), public holidays and lags of electricity load. The result indicated that day types, public holidays and several lags of electricity load were significant in the model. Overall, model simplification improves fuzzy performance due to less variables and rules.

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.

A Short Term Analogue Memory

DEFF Research Database (Denmark)

Shah, Peter Jivan

1992-01-01

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

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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.

Brain oscillatory substrates of visual short-term memory capacity.

Science.gov (United States)

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

2009-11-17

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

Pro short-term procurement - Broker/trader

International Nuclear Information System (INIS)

Hoellen, E.E.

1990-01-01

The author presents his opinion on the issue of short-term versus long-term procurement of uranium and enrichment and the impact on reliability of supply. The progression of the market has been one of increasing commoditization. Utility buyers have moved towards purchasing uranium on the spot market and linking long-term contracts to spot-market pricing. There is some logic to the argument that utilities and the industry in general would be best served by this approach. Inventories would be worked off much more quickly, and unnecessary supply would be shut off until prices recovered to profitable levels. The result would be a healthier market with no detriment to the reliability of supply

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.

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

Czech Academy of Sciences Publication Activity Database

Reissigová, Jindra; Zvolský, M.

2018-01-01

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

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.

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

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

Room Volume Estimation Based on Ambiguity of Short-Term Interaural Phase Differences Using Humanoid Robot Head

Directory of Open Access Journals (Sweden)

Ryuichi Shimoyama

2016-07-01

Full Text Available Humans can recognize approximate room size using only binaural audition. However, sound reverberation is not negligible in most environments. The reverberation causes temporal fluctuations in the short-term interaural phase differences (IPDs of sound pressure. This study proposes a novel method for a binaural humanoid robot head to estimate room volume. The method is based on the statistical properties of the short-term IPDs of sound pressure. The humanoid robot turns its head toward a sound source, recognizes the sound source, and then estimates the ego-centric distance by its stereovision. By interpolating the relations between room volume, average standard deviation, and ego-centric distance experimentally obtained for various rooms in a prepared database, the room volume was estimated by the binaural audition of the robot from the average standard deviation of the short-term IPDs at the estimated distance.

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 data forecasting based on wavelet transformation and chaos theory

Science.gov (United States)

Wang, Yi; Li, Cunbin; Zhang, Liang

2017-09-01

A sketch of wavelet transformation and its application was given. Concerning the characteristics of time sequence, Haar wavelet was used to do data reduction. After processing, the effect of “data nail” on forecasting was reduced. Chaos theory was also introduced, a new chaos time series forecasting flow based on wavelet transformation was proposed. The largest Lyapunov exponent was larger than zero from small data sets, it verified the data change behavior still met chaotic behavior. Based on this, chaos time series to forecast short-term change behavior could be used. At last, the example analysis of the price from a real electricity market showed that the forecasting method increased the precision of the forecasting more effectively and steadily.

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

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

A self-adaptive chaotic particle swarm algorithm for short term hydroelectric system scheduling in deregulated environment

International Nuclear Information System (INIS)

Jiang Chuanwen; Bompard, Etorre

2005-01-01

This paper proposes a short term hydroelectric plant dispatch model based on the rule of maximizing the benefit. For the optimal dispatch model, which is a large scale nonlinear planning problem with multi-constraints and multi-variables, this paper proposes a novel self-adaptive chaotic particle swarm optimization algorithm to solve the short term generation scheduling of a hydro-system better in a deregulated environment. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed approach introduces chaos mapping and an adaptive scaling term into the particle swarm optimization algorithm, which increases its convergence rate and resulting precision. The new method has been examined and tested on a practical hydro-system. The results are promising and show the effectiveness and robustness of the proposed approach in comparison with the traditional particle swarm optimization algorithm

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

Directory of Open Access Journals (Sweden)

Dongxiao Niu

2015-01-01

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

Fragile visual short-term memory is an object-based and location-specific store

NARCIS (Netherlands)

Pinto, Y.; Sligte, I.G.; Shapiro, K.L.; Lamme, V.A.F.

2013-01-01

Fragile visual short-term memory (FM) is a recently discovered form of visual short-term memory. Evidence suggests that it provides rich and high-capacity storage, like iconic memory, yet it exists, without interference, almost as long as visual working memory. In the present study, we sought to

Security threats to automotive CAN networks-Practical examples and selected short-term countermeasures

International Nuclear Information System (INIS)

Hoppe, Tobias; Kiltz, Stefan; Dittmann, Jana

2011-01-01

The IT security of automotive systems is an evolving area of research. To analyse the current situation and the potentially growing tendency of arising threats we performed several practical tests on recent automotive technology. With a focus on automotive systems based on CAN bus technology, this article summarises the results of four selected tests performed on the control systems for the window lift, warning light and airbag control system as well as the central gateway. These results are supplemented in this article by a classification of these four attack scenarios using the established CERT taxonomy and an analysis of underlying security vulnerabilities, and especially, potential safety implications. With respect to the results of these tests, in this article we further discuss two selected countermeasures to address basic weaknesses exploited in our tests. These are adaptations of intrusion detection (discussing three exemplary detection patterns) and IT-forensic measures (proposing proactive measures based on a forensic model). This article discusses both looking at the four attack scenarios introduced before, covering their capabilities and restrictions. While these reactive approaches are short-term measures, which could already be added to today's automotive IT architecture, long-term concepts also are shortly introduced, which are mainly preventive but will require a major redesign. Beneath a short overview on respective research approaches, we discuss their individual requirements, potential and restrictions.

Persistent spatial information in the frontal eye field during object-based short-term memory.

Science.gov (United States)

Clark, Kelsey L; Noudoost, Behrad; Moore, Tirin

2012-08-08

Spatial attention is known to gate entry into visual short-term memory, and some evidence suggests that spatial signals may also play a role in binding features or protecting object representations during memory maintenance. To examine the persistence of spatial signals during object short-term memory, the activity of neurons in the frontal eye field (FEF) of macaque monkeys was recorded during an object-based delayed match-to-sample task. In this task, monkeys were trained to remember an object image over a brief delay, regardless of the locations of the sample or target presentation. FEF neurons exhibited visual, delay, and target period activity, including selectivity for sample location and target location. Delay period activity represented the sample location throughout the delay, despite the irrelevance of spatial information for successful task completion. Furthermore, neurons continued to encode sample position in a variant of the task in which the matching stimulus never appeared in their response field, confirming that FEF maintains sample location independent of subsequent behavioral relevance. FEF neurons also exhibited target-position-dependent anticipatory activity immediately before target onset, suggesting that monkeys predicted target position within blocks. These results show that FEF neurons maintain spatial information during short-term memory, even when that information is irrelevant for task performance.

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)

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

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

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.

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.

Influence of halogen irradiance on short- and long-term wear resistance of resin-based composite materials.

LENUS (Irish Health Repository)

Bhamra, Gurcharn S

2009-02-01

The Oregon Health Science University (OHSU) four-chamber oral wear simulator was used to examine the impact of halogen irradiance on the short- and long-term wear behavior of four-methacrylate resin-based composites (RBCs). The hypothesis proposed was that exacerbated wear would occur following the long-term wear of RBCs irradiated under non-optimized irradiance conditions.

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

Short-Term fo F2 Forecast: Present Day State of Art

Science.gov (United States)

Mikhailov, A. V.; Depuev, V. H.; Depueva, A. H.

An analysis of the F2-layer short-term forecast problem has been done. Both objective and methodological problems prevent us from a deliberate F2-layer forecast issuing at present. An empirical approach based on statistical methods may be recommended for practical use. A forecast method based on a new aeronomic index (a proxy) AI has been proposed and tested over selected 64 severe storm events. The method provides an acceptable prediction accuracy both for strongly disturbed and quiet conditions. The problems with the prediction of the F2-layer quiet-time disturbances as well as some other unsolved problems are discussed

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

Science.gov (United States)

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

2012-01-01

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

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.

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.

Short-term Power Load Forecasting Based on Balanced KNN

Science.gov (United States)

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

2018-03-01

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

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.

A PSO based Artificial Neural Network approach for short term unit commitment problem

Directory of Open Access Journals (Sweden)

AFTAB AHMAD

2010-10-01

Full Text Available Unit commitment (UC is a non-linear, large scale, complex, mixed-integer combinatorial constrained optimization problem. This paper proposes, a new hybrid approach for generating unit commitment schedules using swarm intelligence learning rule based neural network. The training data has been generated using dynamic programming for machines without valve point effects and using genetic algorithm for machines with valve point effects. A set of load patterns as inputs and the corresponding unit generation schedules as outputs are used to train the network. The neural network fine tunes the best results to the desired targets. The proposed approach has been validated for three thermal machines with valve point effects and without valve point effects. The results are compared with the approaches available in the literature. The PSO-ANN trained model gives better results which show the promise of the proposed methodology.

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

Science.gov (United States)

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

2014-12-25

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

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.

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

KAUST Repository

Sanawar, Huma

2018-02-02

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

Short-Term Electricity-Load Forecasting Using a TSK-Based Extreme Learning Machine with Knowledge Representation

Directory of Open Access Journals (Sweden)

Chan-Uk Yeom

2017-10-01

Full Text Available This paper discusses short-term electricity-load forecasting using an extreme learning machine (ELM with automatic knowledge representation from a given input-output data set. For this purpose, we use a Takagi-Sugeno-Kang (TSK-based ELM to develop a systematic approach to generating if-then rules, while the conventional ELM operates without knowledge information. The TSK-ELM design includes a two-phase development. First, we generate an initial random-partition matrix and estimate cluster centers for random clustering. The obtained cluster centers are used to determine the premise parameters of fuzzy if-then rules. Next, the linear weights of the TSK fuzzy type are estimated using the least squares estimate (LSE method. These linear weights are used as the consequent parameters in the TSK-ELM design. The experiments were performed on short-term electricity-load data for forecasting. The electricity-load data were used to forecast hourly day-ahead loads given temperature forecasts; holiday information; and historical loads from the New England ISO. In order to quantify the performance of the forecaster, we use metrics and statistical characteristics such as root mean squared error (RMSE as well as mean absolute error (MAE, mean absolute percent error (MAPE, and R-squared, respectively. The experimental results revealed that the proposed method showed good performance when compared with a conventional ELM with four activation functions such sigmoid, sine, radial basis function, and rectified linear unit (ReLU. It possessed superior prediction performance and knowledge information and a small number of rules.

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

Directory of Open Access Journals (Sweden)

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.

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...

A neuromorphic circuit mimicking biological short-term memory.

Science.gov (United States)

Barzegarjalali, Saeid; Parker, Alice C

2016-08-01

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

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.

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

Retention interval affects visual short-term memory encoding.

Science.gov (United States)

Bankó, Eva M; Vidnyánszky, Zoltán

2010-03-01

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

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 and working memory impairments in aphasia.

Science.gov (United States)

Potagas, Constantin; Kasselimis, Dimitrios; Evdokimidis, Ioannis

2011-08-01

The aim of the present study is to investigate short-term memory and working memory deficits in aphasics in relation to the severity of their language impairment. Fifty-eight aphasic patients participated in this study. Based on language assessment, an aphasia score was calculated for each patient. Memory was assessed in two modalities, verbal and spatial. Mean scores for all memory tasks were lower than normal. Aphasia score was significantly correlated with performance on all memory tasks. Correlation coefficients for short-term memory and working memory were approximately of the same magnitude. According to our findings, severity of aphasia is related with both verbal and spatial memory deficits. Moreover, while aphasia score correlated with lower scores in both short-term memory and working memory tasks, the lack of substantial difference between corresponding correlation coefficients suggests a possible primary deficit in information retention rather than impairment in working memory. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Novel Short-Term Maintenance Strategy for Power Transmission and Transformation Equipment Based on Risk-Cost-Analysis

Directory of Open Access Journals (Sweden)

Hang Yang

2017-11-01

Full Text Available Current studies on preventive condition-based maintenance of power transmission and transformation equipment mainly focus on mid-term or long-term maintenance, and cannot meet the requirements of short-term especially temporary maintenance. In order to solve the defects of the present preventive maintenance strategies, according to the engineering application and based on risk-cost analysis, a short-term maintenance strategy is proposed in this manuscript. For the equipment working in bad health condition, its active maintenance costs and operation risk costs are evaluated, respectively. Then the latest maintenance time is calculated in accordance with the principle that its operation risk costs are no higher than active maintenance costs. Utilizing the latest maintenance time, the best maintenance time is calculated by setting the maximum relative earnings of postponing maintenance as the target, which provides the operation staffs with comprehensive maintenance-decision support. In the end, different cases on the IEEE 24-bus system are simulated. The effectiveness and advantages of the proposed strategy are demonstrated by the simulation results.

Fuzzy approach for short term load forecasting

Energy Technology Data Exchange (ETDEWEB)

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

2006-04-15

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

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

The stability of the international oil trade network from short-term and long-term perspectives

Science.gov (United States)

Sun, Qingru; Gao, Xiangyun; Zhong, Weiqiong; Liu, Nairong

2017-09-01

To examine the stability of the international oil trade network and explore the influence of countries and trade relationships on the trade stability, we construct weighted and unweighted international oil trade networks based on complex network theory using oil trading data between countries from 1996 to 2014. We analyze the stability of international oil trade network (IOTN) from short-term and long-term aspects. From the short-term perspective, we find that the trade volumes play an important role on the stability. Moreover, the weighted IOTN is stable; however, the unweighted networks can better reflect the actual evolution of IOTN. From the long-term perspective, we identify trade relationships that are maintained during the whole sample period to reveal the situation of the whole international oil trade. We provide a way to quantitatively measure the stability of complex network from short-term and long-term perspectives, which can be applied to measure and analyze trade stability of other goods or services.

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)

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...

Short-term change detection for UAV video

Science.gov (United States)

Saur, Günter; Krüger, Wolfgang

2012-11-01

In the last years, there has been an increased use of unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. An important application in this context is change detection in UAV video data. Here we address short-term change detection, in which the time between observations ranges from several minutes to a few hours. We distinguish this task from video motion detection (shorter time scale) and from long-term change detection, based on time series of still images taken between several days, weeks, or even years. Examples for relevant changes we are looking for are recently parked or moved vehicles. As a pre-requisite, a precise image-to-image registration is needed. Images are selected on the basis of the geo-coordinates of the sensor's footprint and with respect to a certain minimal overlap. The automatic imagebased fine-registration adjusts the image pair to a common geometry by using a robust matching approach to handle outliers. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed length of shadows, and compression or transmission artifacts. To detect changes in image pairs we analyzed image differencing, local image correlation, and a transformation-based approach (multivariate alteration detection). As input we used color and gradient magnitude images. To cope with local misalignment of image structures we extended the approaches by a local neighborhood search. The algorithms are applied to several examples covering both urban and rural scenes. The local neighborhood search in combination with intensity and gradient magnitude differencing clearly improved the results. Extended image differencing performed better than both the correlation based approach and the multivariate alternation detection. The algorithms are adapted to be used in semi-automatic workflows for the ABUL video exploitation system of Fraunhofer

Music in the mountains: creating sustainable therapy programs from short-term missions

Directory of Open Access Journals (Sweden)

Rachel Foxell

2015-01-01

Full Text Available This field report describes the experiences of a Registered Music Therapist (RMT living, working, and musicking1 during a short-term health mission to Northern India. Using a sustainability approach, collaboration with several local and global health organisations resulted in the development of a therapeutic music program for children with disabilities. Disability is a complex phenomenon, and in rural areas of India, disability is viewed as a foundation for shame and exclusion. The Community-based project, Samvedna, oversees the therapy, healthcare, and education of over 100 children with a disability in remote villages and is heavily involved in disability advocacy in the area. Sustainable programs are more effective for individuals and communities in both the short and long term. RMTs and other health professionals can be instrumental in setting up sustainable programs, such as teaching specific skills and knowledge to local teams, provided there is thorough preparation and ongoing collaboration to determine the priorities and expectations of the program.

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....

Short-term mechanisms influencing volumetric brain dynamics

Directory of Open Access Journals (Sweden)

Nikki Dieleman

2017-01-01

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

Time-Based Loss in Visual Short-Term Memory Is from Trace Decay, Not Temporal Distinctiveness

Science.gov (United States)

Ricker, Timothy J.; Spiegel, Lauren R.; Cowan, Nelson

2014-01-01

There is no consensus as to why forgetting occurs in short-term memory tasks. In past work, we have shown that forgetting occurs with the passage of time, but there are 2 classes of theories that can explain this effect. In the present work, we investigate the reason for time-based forgetting by contrasting the predictions of temporal…

Modified Pfannenstiel Open Approach as an Alternative to Laparoscopic Total Proctocolectomy and IPAA: Comparison of Short- and Long-term Outcomes and Quality of Life.

Science.gov (United States)

Duraes, Leonardo C; Schroeder, Destiny A; Dietz, David W

2018-05-01

A laparoscopic approach to total proctocolectomy with IPAA has been suggested to have better short-term outcomes and cosmesis, whereas open surgery by midline incision may result in shorter operative times. We hypothesized that a modified Pfannenstiel open approach would combine the advantages of both techniques. The purpose of this study was to compare outcomes of open total proctocolectomy with IPAA using a modified Pfannenstiel incision versus those following the laparoscopic approach. This was a retrospective study comparing patients submitted to open IPAA using modified Pfannenstiel incision versus laparoscopy from 1998 to 2014. The study was conducted at a high-volume tertiary referral center. Among 1275 patients, 119 patients underwent the laparoscopic approach and 33 underwent the modified Pfannenstiel approach. Short- and long-term outcomes were evaluated, and quality-of-life questionnaires were assessed. Patients who underwent the modified Pfannenstiel approach were younger, more often women, and had lower BMI and ASA classification compared with those who underwent laparoscopy. Surgical time was lower in Pfannenstiel, and no difference was observed in length of hospital stay. No difference was observed in postoperative complications, pouch failure rate, or quality of life. Patients were then matched 1:1 by diagnosis, sex, age (±5 y) and BMI (±5 kg/m). The Pfannenstiel approach still had a shorter surgical time. No difference was observed in the length of hospital stay, complications, pouch failure, or quality of life. In long-term follow-up, pouchitis symptoms occurred more frequently in Pfannenstiel (mean follow-up = 7.3 y), and seepage was more frequently observed in the laparoscopy group (mean follow-up = 4.2 y). These differences were not observed in matched patients. The study was limited by its retrospective design and inherent selection bias. The modified Pfannenstiel approach provides equivalent short- and long-term outcomes and similar

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)

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.

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.

Pro short-term procurement - U.S. utility

International Nuclear Information System (INIS)

Thompson, R.D.

1990-01-01

The author expresses the opinion that rather than focusing market discussions around short-term versus long-term procurement strategies, the parties need to be focusing on how long it is going to take to get to a predominantly market-based price both in uranium and enrichment. Long-term contracts are going to be around and will always be an important part of buyers' and sellers' strategies. It is evident that the annual term contract price renegotiations around the world are resulting in continually lower prices. When these price negotiations finally arrive in the range of the market price, a commodity market that resembles other energy commodity markets can be obtained

International Short-Term Countermeasures Survey - 2012 Update

International Nuclear Information System (INIS)

Ingham, Grant

2013-01-01

Nuclear emergency planning, preparedness, response, and management, in general, are essential elements of any country's nuclear power programme. Part of nuclear emergency planning and preparedness is the implementation of national emergency plans, including detailed procedures for the implementation of short-term countermeasures, before during, and after the release of radioactive substances. The timely and appropriate implementation of short-term countermeasures, such as sheltering, evacuation, and iodine prophylaxis, can, in case of a nuclear emergency with a release of radioactive material, considerably reduce the doses to the public in the vicinity of the nuclear installation. Although international guidelines exist, national procedures and practices may differ due to different national habits, cultural specificity, and societal needs. Different national procedures and practices may, however, in the case of a radioactive release affecting two neighbouring countries, lead to different decisions in the implementation of countermeasures. In order to better understand existing approaches and to facilitate the comparison of national practices, the NEA decided to launch a questionnaire on current practices regarding short-term countermeasures, updating a similar survey performed in 1994 and 2003, as countries' practices have since evolved and been modified. In 2012, it was decided to reevaluate the country approaches in light of the early lessons learnt from the Fukushima Daiichi NPP accident. The information collected may be used to understand the basis for decisions in various countries, and, if deemed appropriate, as a basis for international harmonisation. This may also assist member countries to explain to the public affected by an emergency why the decisions in neighbouring countries may vary. This report summarises the information given by member countries and includes nine sections to explore the different aspects, covering the following topics: member

Peptide-based anti-PCSK9 vaccines - an approach for long-term LDLc management.

Directory of Open Access Journals (Sweden)

Gergana Galabova

Full Text Available Low Density Lipoprotein (LDL hypercholesterolemia, and its associated cardiovascular diseases, are some of the leading causes of death worldwide. The ability of proprotein convertase subtilisin/kexin 9 (PCSK9 to modulate circulating LDL cholesterol (LDLc concentrations made it a very attractive target for LDLc management. To date, the most advanced approaches for PCSK9 inhibition are monoclonal antibody (mAb therapies. Although shown to lower LDLc significantly, mAbs face functional limitations because of their relatively short in vivo half-lives necessitating frequent administration. Here, we evaluated the long-term efficacy and safety of PCSK9-specific active vaccines in different preclinical models.PCSK9 peptide-based vaccines were successfully selected by our proprietary technology. To test their efficacy, wild-type (wt mice, Ldlr+/- mice, and rats were immunized with highly immunogenic vaccine candidates. Vaccines induced generation of high-affine PCSK9-specific antibodies in all species. Group mean total cholesterol (TC concentration was reduced by up to 30%, and LDLc up to 50% in treated animals. Moreover, the PCSK9 vaccine-induced humoral immune response persisted for up to one year in mice, and reduced cholesterol levels significantly throughout the study. Finally, the vaccines were well tolerated in all species tested.Peptide-based anti-PCSK9 vaccines induce the generation of antibodies that are persistent, high-affine, and functional for up to one year. They are powerful and safe tools for long-term LDLc management, and thus may represent a novel therapeutic approach for the prevention and/or treatment of LDL hypercholesterolemia-related cardiovascular diseases in humans.

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.

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.

Short-Term Wind Power Forecasting Using the Enhanced Particle Swarm Optimization Based Hybrid Method

OpenAIRE

Wen-Yeau Chang

2013-01-01

High penetration of wind power in the electricity system provides many challenges to power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecasting method of wind speed and power generation can help power system operators reduce the risk of an unreliable electricity supply. This paper proposes an enhanced particle swarm optimization (EPSO) based hybrid forecasting method for short-term wi...

Role of serial order in the impact of talker variability on short-term memory: testing a perceptual organization-based account.

Science.gov (United States)

Hughes, Robert W; Marsh, John E; Jones, Dylan M

2011-11-01

In two experiments, we examined the impact of the degree of match between sequential auditory perceptual organization processes and the demands of a short-term memory task (memory for order vs. item information). When a spoken sequence of digits was presented so as to promote its perceptual partitioning into two distinct streams by conveying it in alternating female (F) and male (M) voices (FMFMFMFM)--thereby disturbing the perception of true temporal order--recall of item order was greatly impaired (as compared to recall of item identity). Moreover, an order error type consistent with the formation of voice-based streams was committed more quickly in the alternating-voice condition (Exp. 1). In contrast, when the perceptual organization of the sequence mapped well onto an optimal two-group serial rehearsal strategy--by presenting the two voices in discrete clusters (FFFFMMMM)--order, but not item, recall was enhanced (Exp. 2). The results are consistent with the view that the degree of compatibility between perceptual and deliberate sequencing processes is a key determinant of serial short-term memory performance. Alternative accounts of talker variability effects in short-term memory, based on the concept of a dedicated phonological short-term store and a capacity-limited focus of attention, are also reviewed.

Independence of long-term contextual memory and short-term perceptual hypotheses: Evidence from contextual cueing of interrupted search.

Science.gov (United States)

Schlagbauer, Bernhard; Mink, Maurice; Müller, Hermann J; Geyer, Thomas

2017-02-01

Observers are able to resume an interrupted search trial faster relative to responding to a new, unseen display. This finding of rapid resumption is attributed to short-term perceptual hypotheses generated on the current look and confirmed upon subsequent looks at the same display. It has been suggested that the contents of perceptual hypotheses are similar to those of other forms of memory acquired long-term through repeated exposure to the same search displays over the course of several trials, that is, the memory supporting "contextual cueing." In three experiments, we investigated the relationship between short-term perceptual hypotheses and long-term contextual memory. The results indicated that long-term, contextual memory of repeated displays neither affected the generation nor the confirmation of short-term perceptual hypotheses for these displays. Furthermore, the analysis of eye movements suggests that long-term memory provides an initial benefit in guiding attention to the target, whereas in subsequent looks guidance is entirely based on short-term perceptual hypotheses. Overall, the results reveal a picture of both long- and short-term memory contributing to reliable performance gains in interrupted search, while exerting their effects in an independent manner.

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...

Laparoscopic and open subtotal colectomies have similar short-term results.

Science.gov (United States)

Hoogenboom, Froukje J; Bosker, Robbert J I; Groen, Henk; Meijerink, Wilhelmus J H J; Lamme, Bas; Pierie, Jean Pierre E N

2013-01-01

Laparoscopic subtotal colectomy (STC) is a complex procedure. It is possible that short-term benefits for segmental resections cannot be attributed to this complex procedure. This study aims to assess differences in short-term results for laparoscopic versus open STC during a 15-year single-institute experience. We reviewed consecutive patients undergoing laparoscopic or open elective or subacute STC from January 1997 to December 2012. Fifty-six laparoscopic and 50 open STCs were performed. The operation time was significantly longer in the laparoscopic group, median 266 min (range 121-420 min), compared to 153 min (range 90-408 min) in the open group (p < 0.001). Median hospital stay showed no statistical difference, 14 days (range 1-129 days) in the laparoscopic and 13 days (range 1-85 days) in the open group. Between-group postoperative complications were not statistically different. Laparoscopic STC has short-term results similar to the open procedure, except for a longer operation time. The laparoscopic approach for STC is therefore only advisable in selected patients combined with extensive preoperative counseling. Copyright © 2013 S. Karger AG, Basel.

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 ...

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...

Understanding Short-Term Nonmigrating Tidal Variability in the Ionospheric Dynamo Region from SABER Using Information Theory and Bayesian Statistics

Science.gov (United States)

Kumari, K.; Oberheide, J.

2017-12-01

Nonmigrating tidal diagnostics of SABER temperature observations in the ionospheric dynamo region reveal a large amount of variability on time-scales of a few days to weeks. In this paper, we discuss the physical reasons for the observed short-term tidal variability using a novel approach based on Information theory and Bayesian statistics. We diagnose short-term tidal variability as a function of season, QBO, ENSO, and solar cycle and other drivers using time dependent probability density functions, Shannon entropy and Kullback-Leibler divergence. The statistical significance of the approach and its predictive capability is exemplified using SABER tidal diagnostics with emphasis on the responses to the QBO and solar cycle. Implications for F-region plasma density will be discussed.

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

International Nuclear Information System (INIS)

Ahmed El Hachemi Mazighi

2004-01-01

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

Pigeon visual short-term memory directly compared to primates.

Science.gov (United States)

Wright, Anthony A; Elmore, L Caitlin

2016-02-01

Three pigeons were trained to remember arrays of 2-6 colored squares and detect which of two squares had changed color to test their visual short-term memory. Procedures (e.g., stimuli, displays, viewing times, delays) were similar to those used to test monkeys and humans. Following extensive training, pigeons performed slightly better than similarly trained monkeys, but both animal species were considerably less accurate than humans with the same array sizes (2, 4 and 6 items). Pigeons and monkeys showed calculated memory capacities of one item or less, whereas humans showed a memory capacity of 2.5 items. Despite the differences in calculated memory capacities, the pigeons' memory results, like those from monkeys and humans, were all well characterized by an inverse power-law function fit to d' values for the five display sizes. This characterization provides a simple, straightforward summary of the fundamental processing of visual short-term memory (how visual short-term memory declines with memory load) that emphasizes species similarities based upon similar functional relationships. By closely matching pigeon testing parameters to those of monkeys and humans, these similar functional relationships suggest similar underlying processes of visual short-term memory in pigeons, monkeys and humans. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Laparoscopic vs open approach for transverse colon cancer. A systematic review and meta-analysis of short and long term outcomes.

Science.gov (United States)

Athanasiou, Christos D; Robinson, Jonathan; Yiasemidou, Marina; Lockwood, Sonia; Markides, Georgios A

2017-05-01

Transverse colon malignancies have been excluded from all randomized controlled trials comparing laparoscopic against open colectomies, potentially due to the advanced laparoscopic skills required for dissecting around the middle colic vessels and the associated morbidity. Concerns have been expressed that the laparoscopic approach may compromise the oncological clearance in transverse colon cancer. This study aimed to comprehensively compare the laparoscopic (LPA) to the open (OPA) approach by performing a meta-analysis of long and short term outcomes. Medline, Embase, Cochrane library, Scopus and Web of Knowledge databases were interrogated. Selected studies were critically appraised and the short-term morbidity and long term oncological outcomes were meta-analyzed. Sensitivity analysis according to the quality of the study, type of procedure (laparoscopic vs laparoscopically assisted) and level of lymphadenectomy was performed. Statistical heterogeneity and publication bias were also investigated. Eleven case control trials (1415 patients) were included in the study. There was no difference between the LPA and the OPA in overall survival [Hazard Ratio (HR) = 0.83 (0.56, 1.22); P = 0.34], disease free survival (p = 0.20), local recurrence (p = 0.81) or distant metastases (p = 0.24). LPA was found to have longer operative time [Weighted mean difference (WMD) = 45.00 (29.48, 60.52); P transverse colon cancer. Copyright © 2017 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Fuel consumption: short term and long term price impacts per population type

International Nuclear Information System (INIS)

2011-01-01

This report presents assessments of the price sensitivity of household fuel consumption. After a literature review on price-elasticity assessments and the use of pseudo-panels, the investigation analyses the deciding factors of the household fuel expense and its evolution between 1985 and 2006. It proposes a short term price-elasticity assessment based on the most recent survey, and also proposes price-elasticity assessments for sub-populations, notably in terms of income level or location (rural or urban areas)

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

International Nuclear Information System (INIS)

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

2011-01-01

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

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 memory in networks of dissociated cortical neurons.

Science.gov (United States)

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

2013-01-30

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

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.

Dimension-based attention in visual short-term memory.

Science.gov (United States)

Pilling, Michael; Barrett, Doug J K

2016-07-01

We investigated how dimension-based attention influences visual short-term memory (VSTM). This was done through examining the effects of cueing a feature dimension in two perceptual comparison tasks (change detection and sameness detection). In both tasks, a memory array and a test array consisting of a number of colored shapes were presented successively, interleaved by a blank interstimulus interval (ISI). In Experiment 1 (change detection), the critical event was a feature change in one item across the memory and test arrays. In Experiment 2 (sameness detection), the critical event was the absence of a feature change in one item across the two arrays. Auditory cues indicated the feature dimension (color or shape) of the critical event with 80 % validity; the cues were presented either prior to the memory array, during the ISI, or simultaneously with the test array. In Experiment 1, the cue validity influenced sensitivity only when the cue was given at the earliest position; in Experiment 2, the cue validity influenced sensitivity at all three cue positions. We attributed the greater effectiveness of top-down guidance by cues in the sameness detection task to the more active nature of the comparison process required to detect sameness events (Hyun, Woodman, Vogel, Hollingworth, & Luck, Journal of Experimental Psychology: Human Perception and Performance, 35; 1140-1160, 2009).

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

Science.gov (United States)

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

2016-03-01

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

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

International Nuclear Information System (INIS)

Mazighi, Ahmed El Hachemi

2004-01-01

Traditionally guided by long-term contracts, the international natural gas trade is experiencing new methods of operating, based on the short term and more flexibility. Today, indeed, the existence of uncommitted quantities of natural gas, combined with gas price discrepancies among different regions of the world, gives room for the expansion of the spot-trading of gas. The main objective of this paper is to discuss three fundamental risks related to the short-term trading of natural gas: volume risk, price risk and infrastructure risk. The defenders of globalisation argue that the transition from the long-term to the short-term trading of natural gas is mainly a question of access to gas reserves, decreasing costs of gas liquefaction, the building of liquefied natural gas (LNG) fleets and regasification facilities and third-party access to the infrastructure. This process needs to be as short as possible, so that the risks related to the transition process will disappear rapidly. On the other hand, the detractors of globalisation put the emphasis on the complexity of the gas value chain and on the fact that eliminating long-term contracts increases the risks inherent to the international natural gas business. In this paper, we try to untangle and assess the risks related to the short-term trading of natural gas. Our main conclusions are: the short-term trading of gas is far from riskless; volume risk requires stock-building in both consuming and producing countries; price risk, through the high volatility for gas, induces an increase in options prices; there is no evidence to suggest that money-lenders' appetite for financing gas infrastructure projects will continue in a short-term trading system. This would be a threat to consumers' security of supply. (Author)

Short term depression unmasks the ghost frequency.

Directory of Open Access Journals (Sweden)

Tjeerd V Olde Scheper

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

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

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

THE INTEGRATED SHORT-TERM STATISTICAL SURVEYS: EXPERIENCE OF NBS IN MOLDOVA

Directory of Open Access Journals (Sweden)

Oleg CARA

2012-07-01

Full Text Available The users’ rising need for relevant, reliable, coherent, timely data for the early diagnosis of the economic vulnerability and of the turning points in the business cycles, especially during a financial and economic crisis, asks for a prompt answer, coordinated by statistical institutions. High quality short term statistics are of special interest for the emerging market economies, such as the Moldavian one, being extremely vulnerable when facing economic recession. Answering to the challenges of producing a coherent and adequate image of the economic activity, by using the system of indicators and definitions efficiently applied at the level of the European Union, the National Bureau of Statistics (NBS of the Republic of Moldova has launched the development process of an integrated system of short term statistics (STS based on the advanced international experience.Thus, in 2011, BNS implemented the integrated statistical survey on STS based on consistent concepts, harmonized with the EU standards. The integration of the production processes, which were previously separated, is based on a common technical infrastructure, standardized procedures and techniques for data production. The achievement of this complex survey with holistic approach has allowed the consolidation of the statistical data quality, comparable at European level and the signifi cant reduction of information burden on business units, especially of small size.The reformation of STS based on the integrated survey has been possible thanks to the consistent methodological and practical support given to NBS by the National Institute of Statistics (INS of Romania, for which we would like to thank to our Romanian colleagues.

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.

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

Directory of Open Access Journals (Sweden)

Holger Hoppe

2012-05-01

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

Short- and Long-Term Effects of Adolescent Alcohol Access: Evidence from Denmark

DEFF Research Database (Denmark)

Gupta, Nabanita Datta; Nilsson, Anton

We exploit changes in minimum legal alcohol purchasing ages in Denmark in order to estimate effects on short- and long-term health outcomes, as well as on human capital formation. Employing a difference-in-differences approach for immediate outcomes and a “regression kink design” for long......-term outcomes, we bring comprehensive evidence on the health and education effects of three reforms, which affected alcohol availability along different dimensions and margins – 1) establishing an off-premise alcohol purchase age of 15 (1998), 2) raising the off-premise alcohol purchase age to 16 (2004), and 3......) increasing the purchase age of beverages exceeding 16.5% in alcohol content from 16 to 18 (2011). Our findings show significant short-term effects of the first and third reforms in terms of reducing injuries and alcohol-related conditions, and some long-term effects of the first reform in terms of reducing...

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.

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.

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

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 ...

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 Simplified Short Term Load Forecasting Method Based on Sequential Patterns

DEFF Research Database (Denmark)

Kouzelis, Konstantinos; Bak-Jensen, Birgitte; Mahat, Pukar

2014-01-01

Load forecasting is an essential part of a power system both for planning and daily operation purposes. As far as the latter is concerned, short term load forecasting has been broadly used at the transmission level. However, recent technological advancements and legislation have facilitated the i...... in comparison with an ARIMA model....

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...

Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition

OpenAIRE

Li, Xiangang; Wu, Xihong

2014-01-01

Long short-term memory (LSTM) based acoustic modeling methods have recently been shown to give state-of-the-art performance on some speech recognition tasks. To achieve a further performance improvement, in this research, deep extensions on LSTM are investigated considering that deep hierarchical model has turned out to be more efficient than a shallow one. Motivated by previous research on constructing deep recurrent neural networks (RNNs), alternative deep LSTM architectures are proposed an...

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

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...

The many faces of working memory and short-term storage.

Science.gov (United States)

Cowan, Nelson

2017-08-01

The topic of working memory (WM) is ubiquitous in research on cognitive psychology and on individual differences. According to one definition, it is a small amount of information kept in a temporary state of heightened accessibility; it is used in most types of communication and problem solving. Short-term storage has been defined as the passive (i.e., non-attention-based, nonstrategic) component of WM or, alternatively, as a passive store separate from an attention-based WM. Here I note that much confusion has been created by the use by various investigators of many, subtly different definitions of WM and short-term storage. The definitions are sometimes made explicit and sometimes implied. As I explain, the different definitions may have stemmed from the use of a wide variety of techniques to explore WM, along with differences in theoretical orientation. By delineating nine previously used definitions of WM and explaining how additional ones may emerge from combinations of these nine, I hope to improve scientific discourse on WM. The potential advantages of clarity about definitions of WM and short-term storage are illustrated with respect to several ongoing research controversies.

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

Science.gov (United States)

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

2017-12-01

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

Reinsurance by short-term reinsurers in South Africa

Directory of Open Access Journals (Sweden)

Fernhout, C. L. R.

2016-02-01

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

Short- and long-term memory: differential involvement of neurotransmitter systems and signal transduction cascades

Directory of Open Access Journals (Sweden)

MÔNICA R.M. VIANNA

2000-09-01

Full Text Available Since William James (1890 first distinguished primary from secondary memory, equivalent to short- and long-term memory, respectively, it has been assumed that short-term memory processes are in charge of cognition while long-term memory is being consolidated. From those days a major question has been whether short-term memory is merely a initial phase of long-term memory, or a separate phenomena. Recent experiments have shown that many treatments with specific molecular actions given into the hippocampus and related brain areas after one-trial avoidance learning can effectively cancel short-term memory without affecting long-term memory formation. This shows that short-term memory and long-term memory involve separate mechanisms and are independently processed. Other treatments, however, influence both memory types similarly, suggesting links between both at the receptor and at the post-receptor level, which should not be surprising as they both deal with nearly the same sensorimotor representations. This review examines recent advances in short- and long-term memory mechanisms based on the effect of intra-hippocampal infusion of drugs acting upon neurotransmitter and signal transduction systems on both memory types.

Short-Term and Long-Term Effects of an Exercise-Based Patient Education Programme in People with Multiple Sclerosis: A Pilot Study

Directory of Open Access Journals (Sweden)

Christina Lutz

2017-01-01

Full Text Available Background. Although people with Multiple Sclerosis (pwMS benefit from physical exercise, they still show reduced physical activity and exercise behaviour. This study aimed to investigate short- and long-term effects of an exercise-based patient education programme (ePEP that focuses on empowering pwMS to a sustainable and self-regulated exercise training management. Methods. Fourteen pwMS were randomly assigned to immediate experimental group (EG-I: n=8 and waitlist-control group (EG-W: n=6 and attended biweekly in a six-week ePEP. All participants were measured for walking ability, quality of life, fatigue, and self-efficacy towards physical exercise before and after the ePEP, after 12 weeks, and one year after baseline. Short-term effects were analysed in a randomised control trial and long-term effects of all ePEP participants (EG-I + EG-W = EG-all in a quasi-experimental design. Results. Only functional gait significantly improved in EG-I compared to EG-W (p=0.008, r=-0.67. Moderate to large effects were found in EG-all for walking ability. Not significant, however, relevant changes were detected for quality of life and fatigue. Self-efficacy showed no changes. Conclusion. The ePEP seems to be a feasible option to empower pwMS to a self-regulated and sustainable exercise training management shown in long-term walking improvements.

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

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

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

Science.gov (United States)

Kulhánek, Tomáš; Kofránek, Jiří; Mateják, Marek

2014-11-01

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

A hybrid wavelet transform based short-term wind speed forecasting approach.

Science.gov (United States)

Wang, Jujie

2014-01-01

It is important to improve the accuracy of wind speed forecasting for wind parks management and wind power utilization. In this paper, a novel hybrid approach known as WTT-TNN is proposed for wind speed forecasting. In the first step of the approach, a wavelet transform technique (WTT) is used to decompose wind speed into an approximate scale and several detailed scales. In the second step, a two-hidden-layer neural network (TNN) is used to predict both approximated scale and detailed scales, respectively. In order to find the optimal network architecture, the partial autocorrelation function is adopted to determine the number of neurons in the input layer, and an experimental simulation is made to determine the number of neurons within each hidden layer in the modeling process of TNN. Afterwards, the final prediction value can be obtained by the sum of these prediction results. In this study, a WTT is employed to extract these different patterns of the wind speed and make it easier for forecasting. To evaluate the performance of the proposed approach, it is applied to forecast Hexi Corridor of China's wind speed. Simulation results in four different cases show that the proposed method increases wind speed forecasting accuracy.

The epidemiology of long- and short-term cancer survivors

DEFF Research Database (Denmark)

Jarlbæk, Lene; Christensen, Linda; Bruera, Eduardo

2014-01-01

Introduction. In this study, we present data from a population-based cohort of incident cancer patients separated in long- and short-term survivors. Our aim was to procure denominators for use in the planning of rehabilitation and palliative care programs. Material and methods. A registry......-linkage cohort study. All cancer patients, diagnosed from 1993 to 2003 from a 470 000 large population, were followed individually from diagnosis to death or until 31 December 2008. Long-term survivors lived five years or more after the time of the cancer diagnosis (TOCD). Short-term survivors died less than...... and sex. Two-year crude cancer survival seems as a clinically relevant cut point for characterizing potential "denominators" for rehabilitation or palliative care programs. From this cohort of incident cancer patients, and using two-year survival as a cut point, it could be estimated that 54% would...

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.

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.

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…

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

OpenAIRE

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

2014-01-01

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

Drought analysis and short-term forecast in the Aison River Basin (Greece

Directory of Open Access Journals (Sweden)

S. Kavalieratou

2012-05-01

Full Text Available A combined regional drought analysis and forecast is elaborated and applied to the Aison River Basin (Greece. The historical frequency, duration and severity were estimated using the standardized precipitation index (SPI computed on variable time scales, while short-term drought forecast was investigated by means of 3-D loglinear models. A quasi-association model with homogenous diagonal effect was proposed to fit the observed frequencies of class transitions of the SPI values computed on the 12-month time scale. Then, an adapted submodel was selected for each data set through the backward elimination method. The analysis and forecast of the drought class transition probabilities were based on the odds of the expected frequencies, estimated by these submodels, and the respective confidence intervals of these odds. The parsimonious forecast models fitted adequately the observed data. Results gave a comprehensive insight on drought behavior, highlighting a dominant drought period (1988–1991 with extreme drought events and revealing, in most cases, smooth drought class transitions. The proposed approach can be an efficient tool in regional water resources management and short-term drought warning, especially in irrigated districts.

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…

An Optimized Prediction Intervals Approach for Short Term PV Power Forecasting

Directory of Open Access Journals (Sweden)

Qiang Ni

2017-10-01

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

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…

Fragile visual short-term memory is an object-based and location-specific store.

Science.gov (United States)

Pinto, Yaïr; Sligte, Ilja G; Shapiro, Kimron L; Lamme, Victor A F

2013-08-01

Fragile visual short-term memory (FM) is a recently discovered form of visual short-term memory. Evidence suggests that it provides rich and high-capacity storage, like iconic memory, yet it exists, without interference, almost as long as visual working memory. In the present study, we sought to unveil the functional underpinnings of this memory storage. We found that FM is only completely erased when the new visual scene appears at the same location and consists of the same objects as the to-be-recalled information. This result has two important implications: First, it shows that FM is an object- and location-specific store, and second, it suggests that FM might be used in everyday life when the presentation of visual information is appropriately designed.

Comparative study of short- and long-term indoor radon measurements

Energy Technology Data Exchange (ETDEWEB)

Al-Jarallah, M.I. [Department of Physics, King Fahd University of Petroleum and Minerals, Dhahran 31261 (Saudi Arabia)], E-mail: mibrahim@kfupm.edu.sa; Fazal-ur-Rehman,; Abdalla, Khalid [Department of Physics, King Fahd University of Petroleum and Minerals, Dhahran 31261 (Saudi Arabia)

2008-08-15

Short-term indoor radon measurements are used widely. Therefore, it is interesting to find out a correlation between these measurements and long-term measurements which reflect a better average radon concentration of individual measurement. To find the correlation between the two measurements of indoor radon concentrations at low radon levels, a study was carried out at 34 locations of King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia using active and passive methods. In the short-term active method, a radon gas analyzer (AlphaGUARD) was used for a duration of 24 h in each measurement. In the long-term passive method, CR-39 based radon dosimeters were utilized for a period of 6 months, from January 2006 to June 2006. The short-term active measurements showed that the average, minimum and maximum radon concentrations were 19, 8 and 58Bqm{sup -3}, respectively, with a standard deviation of 8.6Bqm{sup -3}. The long-term passive measurements showed that the average, minimum and maximum radon concentrations were 25, 10 and 67Bqm{sup -3}, respectively, with a standard deviation of 12Bqm{sup -3}. The two measurements showed a poor correlation (R{sup 2}=0.38). The long-term measurements showed on the average higher concentrations by a factor of 1.3.

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.

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

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.

Functional diversity of Collembola is reduced in soils subjected to short-term, but not long-term, geothermal warming

DEFF Research Database (Denmark)

Holmstrup, Martin; Ehlers, Bodil K.; Slotsbo, Stine

2018-01-01

the extent of such effects in long-term field-based experiments. In this study we make use of both recent (short-term) and long-term geothermal warming of Icelandic soils to examine the responses of Collembola, an ecologically important group of soil invertebrates, to warming. 2. On the basis of metabolic...

Probabilistic short-term volcanic hazard in phases of unrest: A case study for tephra fallout

Science.gov (United States)

Selva, Jacopo; Costa, Antonio; Sandri, Laura; Macedonio, Giovanni; Marzocchi, Warner

2014-12-01

During volcanic crises, volcanologists estimate the impact of possible imminent eruptions usually through deterministic modeling of the effects of one or a few preestablished scenarios. Despite such an approach may bring an important information to the decision makers, the sole use of deterministic scenarios does not allow scientists to properly take into consideration all uncertainties, and it cannot be used to assess quantitatively the risk because the latter unavoidably requires a probabilistic approach. We present a model based on the concept of Bayesian event tree (hereinafter named BET_VH_ST, standing for Bayesian event tree for short-term volcanic hazard), for short-term near-real-time probabilistic volcanic hazard analysis formulated for any potential hazardous phenomenon accompanying an eruption. The specific goal of BET_VH_ST is to produce a quantitative assessment of the probability of exceedance of any potential level of intensity for a given volcanic hazard due to eruptions within restricted time windows (hours to days) in any area surrounding the volcano, accounting for all natural and epistemic uncertainties. BET_VH_ST properly assesses the conditional probability at each level of the event tree accounting for any relevant information derived from the monitoring system, theoretical models, and the past history of the volcano, propagating any relevant epistemic uncertainty underlying these assessments. As an application example of the model, we apply BET_VH_ST to assess short-term volcanic hazard related to tephra loading during Major Emergency Simulation Exercise, a major exercise at Mount Vesuvius that took place from 19 to 23 October 2006, consisting in a blind simulation of Vesuvius reactivation, from the early warning phase up to the final eruption, including the evacuation of a sample of about 2000 people from the area at risk. The results show that BET_VH_ST is able to produce short-term forecasts of the impact of tephra fall during a rapidly

Prosodic Similarity Effects in Short-Term Memory in Developmental Dyslexia.

Science.gov (United States)

Goswami, Usha; Barnes, Lisa; Mead, Natasha; Power, Alan James; Leong, Victoria

2016-11-01

Children with developmental dyslexia are characterized by phonological difficulties across languages. Classically, this 'phonological deficit' in dyslexia has been investigated with tasks using single-syllable words. Recently, however, several studies have demonstrated difficulties in prosodic awareness in dyslexia. Potential prosodic effects in short-term memory have not yet been investigated. Here we create a new instrument based on three-syllable words that vary in stress patterns, to investigate whether prosodic similarity (the same prosodic pattern of stressed and unstressed syllables) exerts systematic effects on short-term memory. We study participants with dyslexia and age-matched and younger reading-level-matched typically developing controls. We find that all participants, including dyslexic participants, show prosodic similarity effects in short-term memory. All participants exhibited better retention of words that differed in prosodic structure, although participants with dyslexia recalled fewer words accurately overall compared to age-matched controls. Individual differences in prosodic memory were predicted by earlier vocabulary abilities, by earlier sensitivity to syllable stress and by earlier phonological awareness. To our knowledge, this is the first demonstration of prosodic similarity effects in short-term memory. The implications of a prosodic similarity effect for theories of lexical representation and of dyslexia are discussed. © 2016 The Authors. Dyslexia published by John Wiley & Sons Ltd. © 2016 The Authors. Dyslexia published by John Wiley & Sons Ltd.

What are the short-term and long-term effects of occupation-focused and occupation-based occupational therapy in the home on older adults' occupational performance?

DEFF Research Database (Denmark)

Nielsen, Tove Lise; Petersen, Kirsten Schultz; Nielsen, Claus Vinther

2016-01-01

critically appraised 13 of 995 detected papers. Extracted data were presented and summarised descriptively. Results Eight high-quality papers showed that occupation-focused and occupation-based occupational therapy using cognitive, behavioural and environmental strategies may significantly improve......Abstract Title What are the short-term and long-term effects of occupation-focused and occupation-based occupational therapy in the home on older adults’ occupational performance? A systematic review Background There is a lack of evidence-based knowledge about the effectiveness of home......-based occupational therapy for older adults aimed at improving occupational performance by practicing activities and tasks. Aim This review synthesizes and discusses evidence for the effectiveness of occupation-focused and occupation-based occupational therapy for older adults at home. Material and methods Peer...

Short term scheduling of multiple grid-parallel PEM fuel cells for microgrid applications

Energy Technology Data Exchange (ETDEWEB)

El-Sharkh, M.Y.; Rahman, A.; Alam, M.S. [Dept. of Electrical and Computer Engineering, University of South Alabama, Mobile, AL 36688 (United States)

2010-10-15

This paper presents a short term scheduling scheme for multiple grid-parallel PEM fuel cell power plants (FCPPs) connected to supply electrical and thermal energy to a microgrid community. As in the case of regular power plants, short term scheduling of FCPP is also a cost-based optimization problem that includes the cost of operation, thermal power recovery, and the power trade with the local utility grid. Due to the ability of the microgrid community to trade power with the local grid, the power balance constraint is not applicable, other constraints like the real power operating limits of the FCPP, and minimum up and down time are therefore used. To solve the short term scheduling problem of the FCPPs, a hybrid technique based on evolutionary programming (EP) and hill climbing technique (HC) is used. The EP is used to estimate the optimal schedule and the output power from each FCPP. The HC technique is used to monitor the feasibility of the solution during the search process. The short term scheduling problem is used to estimate the schedule and the electrical and thermal power output of five FCPPs supplying a maximum power of 300 kW. (author)

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.

Mechanism for optimization of signal-to-noise ratio of dopamine release based on short-term bidirectional plasticity.

Science.gov (United States)

Da Cunha, Claudio; McKimm, Eric; Da Cunha, Rafael M; Boschen, Suelen L; Redgrave, Peter; Blaha, Charles D

2017-07-15

Repeated electrical stimulation of dopamine (dopamine) fibers can cause variable effects on further dopamine release; sometimes there are short-term decreases while in other cases short-term increases have been reported. Previous studies have failed to discover what factors determine in which way dopamine neurons will respond to repeated stimulation. The aim of the present study was therefore to investigate what determines the direction and magnitude of this particular form of short-term plasticity. Fixed potential amperometry was used to measure dopamine release in the nucleus accumbens in response to two trains of electrical pulses administered to the ventral tegmental area of anesthetized mice. When the pulse trains were of equal magnitude we found that low magnitude stimulation was associated with short-term suppression and high magnitude stimulation with short-term facilitation of dopamine release. Secondly, we found that the magnitude of the second pulse train was critical for determining the sign of the plasticity (suppression or facilitation), while the magnitude of the first pulse train determined the extent to which the response to the second train was suppressed or facilitated. This form of bidirectional plasticity might provide a mechanism to enhance signal-to-noise ratio of dopamine neurotransmission. Copyright © 2017 Elsevier B.V. All rights reserved.

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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...

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.

Dispositional optimism as predictor of outcome in short- and long-term psychotherapy.

Science.gov (United States)

Heinonen, Erkki; Heiskanen, Tiia; Lindfors, Olavi; Härkäpää, Kristiina; Knekt, Paul

2017-09-01

Dispositional optimism predicts various beneficial outcomes in somatic health and treatment, but has been little studied in psychotherapy. This study investigated whether an optimistic disposition differentially predicts patients' ability to benefit from short-term versus long-term psychotherapy. A total of 326 adult outpatients with mood and/or anxiety disorder were randomized into short-term (solution-focused or short-term psychodynamic) or long-term psychodynamic therapy and followed up for 3 years. Dispositional optimism was assessed by patients at baseline with the self-rated Life Orientation Test (LOT) questionnaire. Outcome was assessed at baseline and seven times during the follow-up, in terms of depressive (BDI, HDRS), anxiety (SCL-90-ANX, HARS), and general psychiatric symptoms (SCL-90-GSI), all seven follow-up points including patients' self-reports and three including interview-based measures. Lower dispositional optimism predicted faster symptom reduction in short-term than in long-term psychotherapy. Higher optimism predicted equally rapid and eventually greater benefits in long-term, as compared to short-term, psychotherapy. Weaker optimism appeared to predict sustenance of problems early in long-term therapy. Stronger optimism seems to best facilitate engaging in and benefiting from a long-term therapy process. Closer research might clarify the psychological processes responsible for these effects and help fine-tune both briefer and longer interventions to optimize treatment effectiveness for particular patients and their psychological qualities. Weaker dispositional optimism does not appear to inhibit brief therapy from effecting symptomatic recovery. Patients with weaker optimism do not seem to gain added benefits from long-term therapy, but instead may be susceptible to prolonged psychiatric symptoms in the early stages of long-term therapy. © 2016 The British Psychological Society.

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...

Differential Gene Expression Profiling of Enriched Human Spermatogonia after Short- and Long-Term Culture

Directory of Open Access Journals (Sweden)

Sabine Conrad

2014-01-01

Full Text Available This study aimed to provide a molecular signature for enriched adult human stem/progenitor spermatogonia during short-term (<2 weeks and long-term culture (up to more than 14 months in comparison to human testicular fibroblasts and human embryonic stem cells. Human spermatogonia were isolated by CD49f magnetic activated cell sorting and collagen−/laminin+ matrix binding from primary testis cultures obtained from ten adult men. For transcriptomic analysis, single spermatogonia-like cells were collected based on their morphology and dimensions using a micromanipulation system from the enriched germ cell cultures. Immunocytochemical, RT-PCR and microarray analyses revealed that the analyzed populations of cells were distinct at the molecular level. The germ- and pluripotency-associated genes and genes of differentiation/spermatogenesis pathway were highly expressed in enriched short-term cultured spermatogonia. After long-term culture, a proportion of cells retained and aggravated the “spermatogonial” gene expression profile with the expression of germ and pluripotency-associated genes, while in the majority of long-term cultured cells this molecular profile, typical for the differentiation pathway, was reduced and more genes related to the extracellular matrix production and attachment were expressed. The approach we provide here to study the molecular status of in vitro cultured spermatogonia may be important to optimize the culture conditions and to evaluate the germ cell plasticity in the future.

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.

A new cascade NN based method to short-term load forecast in deregulated electricity market

International Nuclear Information System (INIS)

Kouhi, Sajjad; Keynia, Farshid

2013-01-01

Highlights: • We are proposed a new hybrid cascaded NN based method and WT to short-term load forecast in deregulated electricity market. • An efficient preprocessor consist of normalization and shuffling of signals is presented. • In order to select the best inputs, a two-stage feature selection is presented. • A new cascaded structure consist of three cascaded NNs is used as forecaster. - Abstract: Short-term load forecasting (STLF) is a major discussion in efficient operation of power systems. The electricity load is a nonlinear signal with time dependent behavior. The area of electricity load forecasting has still essential need for more accurate and stable load forecast algorithm. To improve the accuracy of prediction, a new hybrid forecast strategy based on cascaded neural network is proposed for STLF. This method is consists of wavelet transform, an intelligent two-stage feature selection, and cascaded neural network. The feature selection is used to remove the irrelevant and redundant inputs. The forecast engine is composed of three cascaded neural network (CNN) structure. This cascaded structure can be efficiently extract input/output mapping function of the nonlinear electricity load data. Adjustable parameters of the intelligent feature selection and CNN is fine-tuned by a kind of cross-validation technique. The proposed STLF is tested on PJM and New York electricity markets. It is concluded from the result, the proposed algorithm is a robust forecast method

Short-term effects of a rights-based sexuality education curriculum for high-school students: a cluster-randomized trial.

Science.gov (United States)

Constantine, Norman A; Jerman, Petra; Berglas, Nancy F; Angulo-Olaiz, Francisca; Chou, Chih-Ping; Rohrbach, Louise A

2015-03-26

An emerging model for sexuality education is the rights-based approach, which unifies discussions of sexuality, gender norms, and sexual rights to promote the healthy sexual development of adolescents. A rigorous evaluation of a rights-based intervention for a broad population of adolescents in the U.S. has not previously been published. This paper evaluates the immediate effects of the Sexuality Education Initiative (SEI) on hypothesized psychosocial determinants of sexual behavior. A cluster-randomized trial was conducted with ninth-grade students at 10 high schools in Los Angeles. Classrooms at each school were randomized to receive either a rights-based curriculum or basic sex education (control) curriculum. Surveys were completed by 1,750 students (N = 934 intervention, N = 816 control) at pretest and immediate posttest. Multilevel regression models examined the short-term effects of the intervention on nine psychosocial outcomes, which were hypothesized to be mediators of students' sexual behaviors. Compared with students who received the control curriculum, students receiving the rights-based curriculum demonstrated significantly greater knowledge about sexual health and sexual health services, more positive attitudes about sexual relationship rights, greater communication about sex and relationships with parents, and greater self-efficacy to manage risky situations at immediate posttest. There were no significant differences between the two groups for two outcomes, communication with sexual partners and intentions to use condoms. Participation in the rights-based classroom curriculum resulted in positive, statistically significant effects on seven of nine psychosocial outcomes, relative to a basic sex education curriculum. Longer-term effects on students' sexual behaviors will be tested in subsequent analyses. ClinicalTrials.gov NCT02009046.

Short and long-term lifestyle coaching approaches used to address diverse participant barriers to weight loss and physical activity adherence.

Science.gov (United States)

Venditti, Elizabeth M; Wylie-Rosett, Judith; Delahanty, Linda M; Mele, Lisa; Hoskin, Mary A; Edelstein, Sharon L

2014-02-12

Individual barriers to weight loss and physical activity goals in the Diabetes Prevention Program, a randomized trial with 3.2 years average treatment duration, have not been previously reported. Evaluating barriers and the lifestyle coaching approaches used to improve adherence in a large, diverse participant cohort can inform dissemination efforts. Lifestyle coaches documented barriers and approaches after each session (mean session attendance = 50.3 ± 21.8). Subjects were 1076 intensive lifestyle participants (mean age = 50.6 years; mean BMI = 33.9 kg/m²; 68% female, 48% non-Caucasian). Barriers and approaches used to improve adherence were ranked by the percentage of the cohort for whom they applied. Barrier groupings were also analyzed in relation to baseline demographic characteristics. Top weight loss barriers reported were problems with self-monitoring (58%); social cues (58%); holidays (54%); low activity (48%); and internal cues (thought/mood) (44%). Top activity barriers were holidays (51%); time management (50%); internal cues (30%); illness (29%), and motivation (26%). The percentage of the cohort having any type of barrier increased over the long-term intervention period. A majority of the weight loss barriers were significantly associated with younger age, greater obesity, and non-Caucasian race/ethnicity (p-values vary). Physical activity barriers, particularly thought and mood cues, social cues and time management, physical injury or illness and access/weather, were most significantly associated with being female and obese (p  90% long term) and regularly reviewed self-monitoring skills. More costly approaches were used infrequently during the first 16 sessions (≤10%) but increased over 3.2 years. Behavioral problem solving approaches have short and long term dissemination potential for many kinds of participant barriers. Given minimal resources, increased attention to training lifestyle coaches in the consistent use of these

Short-term Consumer Benefits of Dynamic Pricing

OpenAIRE

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

2011-01-01

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

Laboratory and Field-Based Evaluation of Short-Term Effort with Maximal Intensity in Individuals with Intellectual Disabilities

Directory of Open Access Journals (Sweden)

Lencse-Mucha Judit

2015-12-01

Full Text Available Results of previous studies have not indicated clearly which tests should be used to assess short-term efforts of people with intellectual disabilities. Thus, the aim of the present study was to evaluate laboratory and field-based tests of short-term effort with maximal intensity of subjects with intellectual disabilities. Twenty four people with intellectual disability, who trained soccer, participated in this study. The 30 s Wingate test and additionally an 8 s test with maximum intensity were performed on a bicycle ergometer. The fatigue index, maximal and mean power, relative maximal and relative mean power were measured. Overall, nine field-based tests were conducted: 5, 10 and 20 m sprints, a 20 m shuttle run, a seated medicine ball throw, a bent arm hang test, a standing broad jump, sit-ups and a hand grip test. The reliability of the 30 s and 8 s Wingate tests for subjects with intellectual disability was confirmed. Significant correlation was observed for mean power between the 30 s and 8 s tests on the bicycle ergometer at a moderate level (r >0.4. Moreover, significant correlations were indicated between the results of laboratory tests and field tests, such as the 20 m sprint, the 20 m shuttle run, the standing long jump and the medicine ball throw. The strongest correlation was in the medicine ball throw. The 30 s Wingate test is a reliable test assessing maximal effort in subjects with intellectual disability. The results of this research confirmed that the 8 s test on a bicycle ergometer had a moderate correlation with the 30 s Wingate test in this population, thus, this comparison needs further investigation to examine alternativeness of the 8 s to 30 s Wingate tests. The non-laboratory tests could be used to indirectly assess performance in short-term efforts with maximal intensity.

Laboratory and Field-Based Evaluation of Short-Term Effort with Maximal Intensity in Individuals with Intellectual Disabilities

Science.gov (United States)

Lencse-Mucha, Judit; Molik, Bartosz; Marszałek, Jolanta; Kaźmierska-Kowalewska, Kalina; Ogonowska-Słodownik, Anna

2015-01-01

Results of previous studies have not indicated clearly which tests should be used to assess short-term efforts of people with intellectual disabilities. Thus, the aim of the present study was to evaluate laboratory and field-based tests of short-term effort with maximal intensity of subjects with intellectual disabilities. Twenty four people with intellectual disability, who trained soccer, participated in this study. The 30 s Wingate test and additionally an 8 s test with maximum intensity were performed on a bicycle ergometer. The fatigue index, maximal and mean power, relative maximal and relative mean power were measured. Overall, nine field-based tests were conducted: 5, 10 and 20 m sprints, a 20 m shuttle run, a seated medicine ball throw, a bent arm hang test, a standing broad jump, sit-ups and a hand grip test. The reliability of the 30 s and 8 s Wingate tests for subjects with intellectual disability was confirmed. Significant correlation was observed for mean power between the 30 s and 8 s tests on the bicycle ergometer at a moderate level (r >0.4). Moreover, significant correlations were indicated between the results of laboratory tests and field tests, such as the 20 m sprint, the 20 m shuttle run, the standing long jump and the medicine ball throw. The strongest correlation was in the medicine ball throw. The 30 s Wingate test is a reliable test assessing maximal effort in subjects with intellectual disability. The results of this research confirmed that the 8 s test on a bicycle ergometer had a moderate correlation with the 30 s Wingate test in this population, thus, this comparison needs further investigation to examine alternativeness of the 8 s to 30 s Wingate tests. The non-laboratory tests could be used to indirectly assess performance in short-term efforts with maximal intensity. PMID:26834874

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…

How long-term dynamics of sediment subduction controls short-term dynamics of seismicity

Science.gov (United States)

Brizzi, S.; van Zelst, I.; van Dinther, Y.; Funiciello, F.; Corbi, F.

2017-12-01

Most of the world's greatest earthquakes occur along the subduction megathrust. Weak and porous sediments have been suggested to homogenize the plate interface and thereby promote lateral rupture propagation and great earthquakes. However, the importance of sediment thickness, let alone their physical role, is not yet unequivocally established. Based on a multivariate statistical analysis of a global database of 62 subduction segments, we confirm that sediment thickness is one of the key parameters controlling the maximum magnitude a megathrust can generate. Moreover, Monte Carlo simulations highlighted that the occurrence of great earthquakes on sediment-rich subduction segments is very unlikely (p-value≪0.05) related to pure chance. To understand how sediments in the subduction channel regulate earthquake size, this study extends and demystifies multivariate, spatiotemporally limited data through numerical modeling. We use the 2D Seismo-Thermo-Mechanical modeling approach to simulate both the long- and short-term dynamics of subduction and related seismogenesis (van Dinther et al., JGR, 2013). These models solve for the conservation of mass, momentum and energy using a visco-elasto-plastic rheology with rate-dependent friction. Results show that subducted sediments have a strong influence on the long-term evolution of the convergent margin. Increasing the sediment thickness on the incoming plate from 0 to 6 km causes a decrease of slab dip from 23° to 10°. This, in addition to increased radiogenic heating, extends isotherms, thereby widening the seismogenic portion of the megathrust from 80 to 150 km. Consequently, over tens of thousands of years, we observe that the maximum moment magnitude of megathrust earthquakes increases from 8.2 to 9.2 for these shallower and warmer interfaces. In addition, we observe more and larger splay faults, which could enhance vertical seafloor displacements. These results highlight the primary role of subducted sediments in

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...

Experimental Study of Short-Term Training in Social Cognition in Pre-Schoolers

Science.gov (United States)

Houssa, Marine; Nader-Grosbois, Nathalie; Jacobs, Emilie

2014-01-01

Using an experimental approach, our study examined the differentiated effects on pre-schoolers' social cognition of two short-term social information processing (SIP) and Theory of Mind (ToM) training sessions dealing with emotions and beliefs. The links between ToM, SIP, and social adjustment or externalizing behavior were examined. 47…

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

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.

Supervised guiding long-short term memory for image caption generation based on object classes

Science.gov (United States)

Wang, Jian; Cao, Zhiguo; Xiao, Yang; Qi, Xinyuan

2018-03-01

The present models of image caption generation have the problems of image visual semantic information attenuation and errors in guidance information. In order to solve these problems, we propose a supervised guiding Long Short Term Memory model based on object classes, named S-gLSTM for short. It uses the object detection results from R-FCN as supervisory information with high confidence, and updates the guidance word set by judging whether the last output matches the supervisory information. S-gLSTM learns how to extract the current interested information from the image visual se-mantic information based on guidance word set. The interested information is fed into the S-gLSTM at each iteration as guidance information, to guide the caption generation. To acquire the text-related visual semantic information, the S-gLSTM fine-tunes the weights of the network through the back-propagation of the guiding loss. Complementing guidance information at each iteration solves the problem of visual semantic information attenuation in the traditional LSTM model. Besides, the supervised guidance information in our model can reduce the impact of the mismatched words on the caption generation. We test our model on MSCOCO2014 dataset, and obtain better performance than the state-of-the- art models.

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

International Nuclear Information System (INIS)

Yu, Feng; Xu, Xiaozhong

2014-01-01

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

Road safety performance measures and AADT uncertainty from short-term counts.

Science.gov (United States)

Milligan, Craig; Montufar, Jeannette; Regehr, Jonathan; Ghanney, Bartholomew

2016-12-01

The objective of this paper is to enable better risk analysis of road safety performance measures by creating the first knowledge base on uncertainty surrounding annual average daily traffic (AADT) estimates when the estimates are derived by expanding short-term counts with the individual permanent counter method. Many road safety performance measures and performance models use AADT as an input. While there is an awareness that the input suffers from uncertainty, the uncertainty is not well known or accounted for. The paper samples data from a set of 69 permanent automatic traffic recorders in Manitoba, Canada, to simulate almost 2 million short-term counts over a five year period. These short-term counts are expanded to AADT estimates by transferring temporal information from a directly linked nearby permanent count control station, and the resulting AADT values are compared to a known reference AADT to compute errors. The impacts of five factors on AADT error are considered: length of short-term count, number of short-term counts, use of weekday versus weekend counts, distance from a count to its expansion control station, and the AADT at the count site. The mean absolute transfer error for expanded AADT estimates is 6.7%, and this value varied by traffic pattern group from 5% to 10.5%. Reference percentiles of the error distribution show that almost all errors are between -20% and +30%. Error decreases substantially by using a 48-h count instead of a 24-h count, and only slightly by using two counts instead of one. Weekday counts are superior to weekend counts, especially if the count is only 24h. Mean absolute transfer error increases with distance to control station (elasticity 0.121, p=0.001), and increases with AADT (elasticity 0.857, proad safety performance measures that use AADT as inputs. Analytical frameworks for such analysis exist but are infrequently used in road safety because the evidence base on AADT uncertainty is not well developed. Copyright �

Short-term initiatives for enhancing cyber-safety within South African schools

Directory of Open Access Journals (Sweden)

Elmarie Kritzinger

2016-07-01

Full Text Available The rate of technological development across the globe is dramatic. The decreasing cost and increasing availability of ICT devices means that its users are no longer exclusively industry or government employees – they are now also home users. Home users integrate ICT in their daily lives for education, socialising and information gathering. However, using ICT is associated with risks and threats, such as identity theft and phishing scams. Most home users of ICT do not have the necessary information technology and Internet skills to protect themselves and their information. School learners, in particular, are not sufficiently educated on how to use technological devices safely, especially in developing countries such as South Africa. The national school curriculum in South Africa currently does not make provision for cyber-safety education, and the availability of supporting material and training for ICT teachers in South Africa is limited, resulting in a lack of knowledge and skills regarding cyber-safety. The research in hand focuses on the situation concerning cyber-safety awareness in schools and has adopted a short-term approach towards cyber-safety among teachers and school learners in South Africa until a formal long-term national approach has been implemented. This study takes a quantitative approach to investigating the current options of teachers to enhance cyber-safety among learners in their schools. The research proposes that short-term initiatives (i.e. posters can increase learners’ awareness of cyber-safety until formal cyber-safety awareness methods have been introduced.

The complexity of self-regulating food intake in weight loss maintenance. A qualitative exploration among short- and long-term weight loss maintainers

DEFF Research Database (Denmark)

Pedersen, Susanne; Sniethotta, Falko; Sainsbury, Kirby

Objective: The aim of this study was to better understand whether self-regulation of food intake in WLM differs in the challenging transition from being a short-term maintainer (having maintained without regaining less than 12 months) to a long-term maintainer (having maintained without regaining....../storing, preparing/cooking, eating, and general barriers and resources in WLM. Post-hoc coding was applied based on self-regulation strategies and self-efficacy beliefs, and thematic analysis was also applied to identify additional themes. A content analysis approach using NVivo 11 highlighted the differences...... describe and understand the self-regulatory strategies related to food intake in WLM. Methods: Individual interviews (14 female/5 male) were conducted with 9 Danish short- and 10 long-term weight loss maintainers. Initial codes were based on five themes related to food intake: planning, shopping...

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 cascaded hydroelectric system scheduling based on chaotic particle swarm optimization using improved logistic map

Science.gov (United States)

He, Yaoyao; Yang, Shanlin; Xu, Qifa

2013-07-01

In order to solve the model of short-term cascaded hydroelectric system scheduling, a novel chaotic particle swarm optimization (CPSO) algorithm using improved logistic map is introduced, which uses the water discharge as the decision variables combined with the death penalty function. According to the principle of maximum power generation, the proposed approach makes use of the ergodicity, symmetry and stochastic property of improved logistic chaotic map for enhancing the performance of particle swarm optimization (PSO) algorithm. The new hybrid method has been examined and tested on two test functions and a practical cascaded hydroelectric system. The experimental results show that the effectiveness and robustness of the proposed CPSO algorithm in comparison with other traditional algorithms.

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.

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.

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.

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)

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...

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 ...

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

International Nuclear Information System (INIS)

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

2007-01-01

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

Setting the stage for the review of the international estimate of short-term intake (IESTI) equation.

NARCIS (Netherlands)

Richter, Anke; Sieke, Christian; Reich, Hermine; Ossendorp, Bernadette C; Breysse, Nicolas; Lutze, Jason; Mahieu, Karin; Margerison, Sam; Rietveld, Anton; Sarda, Xavier; Vial, Gaelle; van der Velde-Koerts, Trijntje

2018-01-01

In the framework of setting Maximum Residue Limits (MRLs) for pesticides, both chronic and acute health risks to consumers arising from the long-term and short-term dietary exposure to pesticide residues have to be assessed. The current internationally harmonized approach for assessing the acute

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...

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.

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

Science.gov (United States)

Vicary, Staci A; Stevens, Catherine J

2014-01-01

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

Pointing towards visuospatial patterns in short-term memory: differential effects on familiarity- and recollection-based judgments.

Science.gov (United States)

Rossi-Arnaud, Clelia; Spataro, Pietro; Marques, Valeria R S; Longobardi, Emiddia

2015-03-01

Previous studies have indicated that pointing toward to-be-remembered visuospatial patterns enhances short-term memory (STM) when the presentation of pointing and no-pointing trials is mixed (Chum et al., 2007; Dodd & Shumborski, 2009; Rossi-Arnaud et al., 2012). By contrast, when presentation is blocked, pointing has inhibitory effects on memory (Dodd & Shumborski, 2009; Rossi-Arnaud et al., 2012). In the present study, we demonstrated that pointing has different effects on short-term recollection- and familiarity-based judgments, depending on the length of the visuospatial patterns (5- vs. 7-item arrays) and the interval between the encoding and test phases (2 vs. 5 s). More specifically, pointing decreased the accuracy of recollection-based judgments for 5-item arrays, but not for 7-item arrays (this negative effect did not interact with interval length). In contrast, pointing facilitated familiarity-based judgments when the interval between the study and test phases was 5 s, but not when it was 2 s (this positive effect did not interact with pattern length). We proposed that the negative effects might be accounted for by the simultaneous recruitment of attention resources in the planning and execution of pointing movements. As a consequence, executive resources are diverted from the primary memory task, resulting in a less efficient use of attention-demanding retrieval strategies, like chunking. By contrast, the positive effects on familiarity judgments might reflect the unitization of the to-be-remembered items into a single shape. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

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.

The Interdependence of Long- and Short-Term Components in Unmasked Repetition Priming: An Indication of Shared Resources.

Science.gov (United States)

Merema, Matt R; Speelman, Craig P

2015-01-01

It has been suggested that unmasked repetition priming is composed of distinct long-and short-term priming components. The current study sought to clarify the relationship between these components by examining the relationship between them. A total of 60 people (45 females, 15 males) participated in a computer-based lexical decision task designed to measure levels of short-term priming across different levels of long-term priming. The results revealed an interdependent relationship between the two components, whereby an increase in long-term priming prompted a decrease in short-term priming. Both long-term and short-term priming were accurately captured by a single power function over seven minutes post repetition, suggesting the two components may draw on the same resources. This interdependence between long- and short-term priming may serve to improve fluency in reading.

The Interdependence of Long- and Short-Term Components in Unmasked Repetition Priming: An Indication of Shared Resources.

Directory of Open Access Journals (Sweden)

Matt R Merema

Full Text Available It has been suggested that unmasked repetition priming is composed of distinct long-and short-term priming components. The current study sought to clarify the relationship between these components by examining the relationship between them. A total of 60 people (45 females, 15 males participated in a computer-based lexical decision task designed to measure levels of short-term priming across different levels of long-term priming. The results revealed an interdependent relationship between the two components, whereby an increase in long-term priming prompted a decrease in short-term priming. Both long-term and short-term priming were accurately captured by a single power function over seven minutes post repetition, suggesting the two components may draw on the same resources. This interdependence between long- and short-term priming may serve to improve fluency in reading.

Gradient decent based multi-objective cultural differential evolution for short-term hydrothermal optimal scheduling of economic emission with integrating wind power and photovoltaic power

International Nuclear Information System (INIS)

Zhang, Huifeng; Yue, Dong; Xie, Xiangpeng; Dou, Chunxia; Sun, Feng

2017-01-01

With the integration of wind power and photovoltaic power, optimal operation of hydrothermal power system becomes great challenge due to its non-convex, stochastic and complex-coupled constrained characteristics. This paper extends short-term hydrothermal system optimal model into short-term hydrothermal optimal scheduling of economic emission while considering integrated intermittent energy resources (SHOSEE-IIER). For properly solving SHOSEE-IIER problem, a gradient decent based multi-objective cultural differential evolution (GD-MOCDE) is proposed to improve the optimal efficiency of SHOSEE-IIER combined with three designed knowledge structures, which mainly enhances search ability of differential evolution in the shortest way. With considering those complex-coupled and stochastic constraints, a heuristic constraint-handling measurement is utilized to tackle with them both in coarse and fine tuning way, and probability constraint-handling procedures are taken to properly handle those stochastic constraints combined with their probability density functions. Ultimately, those approaches are implemented on five test systems, which testify the optimization efficiency of proposed GD-MOCDE and constraint-handling efficiency for system load balance, water balance and stochastic constraint-handling measurements, those obtained results reveal that the proposed GD-MOCDE can properly solve the SHOSEE-IIER problem combined with those constraint-handling approaches. - Highlights: • Gradient decent method is proposed to improve mutation operator. • Hydrothermal system is extended to hybrid energy system. • The uncertainty constraint is converted into deterministic constraint. • The results show the viability and efficiency of proposed algorithm.

Short-term memory development: differences in serial position curves between age groups and latent classes.

Science.gov (United States)

Koppenol-Gonzalez, Gabriela V; Bouwmeester, Samantha; Vermunt, Jeroen K

2014-10-01

In studies on the development of cognitive processes, children are often grouped based on their ages before analyzing the data. After the analysis, the differences between age groups are interpreted as developmental differences. We argue that this approach is problematic because the variance in cognitive performance within an age group is considered to be measurement error. However, if a part of this variance is systematic, it can provide very useful information about the cognitive processes used by some children of a certain age but not others. In the current study, we presented 210 children aged 5 to 12 years with serial order short-term memory tasks. First we analyze our data according to the approach using age groups, and then we apply latent class analysis to form latent classes of children based on their performance instead of their ages. We display the results of the age groups and the latent classes in terms of serial position curves, and we discuss the differences in results. Our findings show that there are considerable differences in performance between the age groups and the latent classes. We interpret our findings as indicating that the latent class analysis yielded a much more meaningful way of grouping children in terms of cognitive processes than the a priori grouping of children based on their ages. Copyright © 2014 Elsevier Inc. All rights reserved.

Short and long term maintenance strategy for reactor vessel head penetrations

International Nuclear Information System (INIS)

Teissier, A.; Heuze, A.

1995-01-01

This paper presents elements based on : surveys, operating inspection, theoretical studies, safety analysis, laboratory results, that enabled to determine maintenance options and short and long term strategies for processing on reactor vessel head leaks. (TEC). 1 tab

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

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

Directory of Open Access Journals (Sweden)

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.

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%

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)

Bidirectional Long Short-Term Memory Network for Vehicle Behavior Recognition

Directory of Open Access Journals (Sweden)

Jiasong Zhu

2018-06-01

Full Text Available Vehicle behavior recognition is an attractive research field which is useful for many computer vision and intelligent traffic analysis tasks. This paper presents an all-in-one behavior recognition framework for moving vehicles based on the latest deep learning techniques. Unlike traditional traffic analysis methods which rely on low-resolution videos captured by road cameras, we capture 4K ( 3840 × 2178 traffic videos at a busy road intersection of a modern megacity by flying a unmanned aerial vehicle (UAV during the rush hours. We then manually annotate locations and types of road vehicles. The proposed method consists of the following three steps: (1 vehicle detection and type recognition based on deep neural networks; (2 vehicle tracking by data association and vehicle trajectory modeling; (3 vehicle behavior recognition by nearest neighbor search and by bidirectional long short-term memory network, respectively. This paper also presents experimental results of the proposed framework in comparison with state-of-the-art approaches on the 4K testing traffic video, which demonstrated the effectiveness and superiority of the proposed method.

Frequency-specific insight into short-term memory capacity

OpenAIRE

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

2016-01-01

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

Effects of age, gender, and stimulus presentation period on visual short-term memory.

Science.gov (United States)

Kunimi, Mitsunobu

2016-01-01

This study focused on age-related changes in visual short-term memory using visual stimuli that did not allow verbal encoding. Experiment 1 examined the effects of age and the length of the stimulus presentation period on visual short-term memory function. Experiment 2 examined the effects of age, gender, and the length of the stimulus presentation period on visual short-term memory function. The worst memory performance and the largest performance difference between the age groups were observed in the shortest stimulus presentation period conditions. The performance difference between the age groups became smaller as the stimulus presentation period became longer; however, it did not completely disappear. Although gender did not have a significant effect on d' regardless of the presentation period in the young group, a significant gender-based difference was observed for stimulus presentation periods of 500 ms and 1,000 ms in the older group. This study indicates that the decline in visual short-term memory observed in the older group is due to the interaction of several factors.

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.

Fluoroscopically guided caudal epidural steroid injection for management of degenerative lumbar spinal stenosis: short-term and long-term results

Energy Technology Data Exchange (ETDEWEB)

Lee, Joon Woo; Myung, Jae Sung; Kang, Heung Sik [Seoul National University Bundang Hospital, Department of Radiology, Seong Nam, Gyeongi-do (Korea); Park, Kun Woo; Yeom, Jin S. [Seoul National University Bundang Hospital, Department of Orthopaedic Surgery, Seong Nam, Gyeongi-do (Korea); Kim, Ki-Jeong; Kim, Hyun-Jib [Seoul National University Bundang Hospital, Department of Neurosurgery, Seong Nam, Gyeongi-do (Korea)

2010-07-15

To evaluate the short-term and long-term effects of fluoroscopically guided caudal epidural steroid injection (ESI) for the management of degenerative lumbar spinal stenosis (DLSS) and to analyze outcome predictors. All patients who underwent caudal ESI in 2006 for DLSS were included in the study. Response was based on chart documentation (aggravated, no change, slightly improved, much improved, no pain). In June 2009 telephone interviews were conducted, using formatted questions including the North American Spine Society (NASS) patient satisfaction scale. For short-term and long-term effects, age difference was evaluated by the Mann-Whitney U test, and gender, duration of symptoms, level of DLSS, spondylolisthesis, and previous operations were evaluated by Fisher's exact test. Two hundred and sixteen patients (male: female = 75:141; mean age 69.2 years; range 48{proportional_to}91 years) were included in the study. Improvements (slightly improved, much improved, no pain) were seen in 185 patients (85.6%) after an initial caudal ESI and in 189 patients (87.5%) after a series of caudal ESIs. Half of the patients (89/179, 49.8%) replied positively to the NASS patient satisfaction scale (1 or 2). There were no significant outcome predictors for either the short-term or the long-term responses. Fluoroscopically guided caudal ESI was effective for the management of DLSS (especially central canal stenosis) with excellent short-term and good long-term results, without significant outcome predictors. (orig.)

Wind Power Forecasting Based on Echo State Networks and Long Short-Term Memory

DEFF Research Database (Denmark)

López, Erick; Allende, Héctor; Gil, Esteban

2018-01-01

involved. In particular, two types of RNN, Long Short-Term Memory (LSTM) and Echo State Network (ESN), have shown good results in time series forecasting. In this work, we present an LSTM+ESN architecture that combines the characteristics of both networks. An architecture similar to an ESN is proposed...

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

International Nuclear Information System (INIS)

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

2014-01-01

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

Response of rat lung tissue to short-term hyperoxia: a proteomic approach.

Science.gov (United States)

Spelten, Oliver; Wetsch, Wolfgang A; Wrettos, Georg; Kalenka, Armin; Hinkelbein, Jochen

2013-11-01

An inspiratory oxygen fraction of 1.0 is often required to avoid hypoxia both in many pre- and in-hospital situations. On the other hand, hyperoxia may lead to deleterious consequences (cell growth inhibition, inflammation, and apoptosis) for numerous tissues including the lung. Whereas clinical effects of hyperoxic lung injury are well known, its impact on the expression of lung proteins has not yet been evaluated sufficiently. The aim of this study was to analyze time-dependent alterations of protein expression in rat lung tissue after short-term normobaric hyperoxia (NH). After approval of the local ethics committee for animal research, N = 36 Wistar rats were randomized into six different groups: three groups with NH with exposure to 100 % oxygen for 3 h and three groups with normobaric normoxia (NN) with exposure to room air (21 % oxygen). After the end of the experiments, lungs were removed immediately (NH0 and NN0), after 3 days (NH3 and NN3) and after 7 days (NH7 and NN7). Lung lysates were analyzed by two-dimensional gel electrophoresis (2D-GE) followed by peptide mass fingerprinting using mass spectrometry. Statistical analysis was performed with Delta 2D (DECODON GmbH, Greifswald, Germany; ANOVA, Bonferroni correction, p pO2 was significantly higher in NH-groups compared to NN-groups (581 ± 28 vs. 98 ± 12 mmHg; p < 0.01), all other physiological parameters did not differ. Expression of 14 proteins were significantly altered: two proteins were up-regulated and 12 proteins were down-regulated. Even though NH was comparatively short termed, significant alterations in lung protein expression could be demonstrated up to 7 days after hyperoxia. The identified proteins indicate an association with cell growth inhibition, regulation of apoptosis, and approval of structural cell integrity.

Examining Preservice Teachers' Classroom Management Decisions in Three Case-Based Teaching Approaches

Science.gov (United States)

Cevik, Yasemin Demiraslan; Andre, Thomas

2013-01-01

This study was aimed at comparing the impact of three types of case-based approaches (worked example, faded work example, and case-based reasoning) on preservice teachers' decision making and reasoning skills related to realistic classroom management situations. Participants in this study received a short-term implementation of one of these three…

Short-Term Robustness of Production Management Systems : New Methodology

NARCIS (Netherlands)

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

2000-01-01

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

Differences in health status between long-term and short-term benzodiazepine users.

NARCIS (Netherlands)

Zandstra, S.M.; Furer, J.W.; Lisdonk, E.H. van de; Bor, J.H.J.; Zitman, F.G.; Weel, C. van

2002-01-01

BACKGROUND: Despite generally accepted advice to keep treatment short, benzodiazepines are often prescibed for more than six months. Prevention of long-term benzodiazepine use could be facilitated by the utilisation of risk indicators for long-term use. However, the characteristics of long-term

The roles of long-term phonotactic and lexical prosodic knowledge in phonological short-term memory.

Science.gov (United States)

Tanida, Yuki; Ueno, Taiji; Lambon Ralph, Matthew A; Saito, Satoru

2015-04-01

Many previous studies have explored and confirmed the influence of long-term phonological representations on phonological short-term memory. In most investigations, phonological effects have been explored with respect to phonotactic constraints or frequency. If interaction between long-term memory and phonological short-term memory is a generalized principle, then other phonological characteristics-that is, suprasegmental aspects of phonology-should also exert similar effects on phonological short-term memory. We explored this hypothesis through three immediate serial-recall experiments that manipulated Japanese nonwords with respect to lexical prosody (pitch-accent type, reflecting suprasegmental characteristics) as well as phonotactic frequency (reflecting segmental characteristics). The results showed that phonotactic frequency affected the retention not only of the phonemic sequences, but also of pitch-accent patterns, when participants were instructed to recall both the phoneme sequence and accent pattern of nonwords. In addition, accent pattern typicality influenced the retention of the accent pattern: Typical accent patterns were recalled more accurately than atypical ones. These results indicate that both long-term phonotactic and lexical prosodic knowledge contribute to phonological short-term memory performance.

Visual Short-Term Memory Complexity

DEFF Research Database (Denmark)

Sørensen, Thomas Alrik

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

SHORT-TERM MEMORY IS INDEPENDENT OF BRAIN PROTEIN SYNTHESIS

Energy Technology Data Exchange (ETDEWEB)

Davis, Hasker P.; Rosenzweig, Mark R.; Jones, Oliver W.

1980-09-01

Male Swiss albino CD-1 mice given a single injection of a cerebral protein synthesis inhibitor, anisomycin (ANI) (1 mg/animal), 20 min prior to single trial passive avoidance training demonstrated impaired retention at tests given 3 hr, 6 hr, 1 day, and 7 days after training. Retention was not significantly different from saline controls when tests were given 0.5 or 1.5 hr after training. Prolonging inhibition of brain protein synthesis by giving either 1 or 2 additional injections of ANI 2 or 2 and 4 hr after training did not prolong short-term retention performance. The temporal development of impaired retention in ANI treated mice could not be accounted for by drug dosage, duration of protein synthesis inhibition, or nonspecific sickness at test. In contrast to the suggestion that protein synthesis inhibition prolongs short-term memory (Quinton, 1978), the results of this experiment indicate that short-term memory is not prolonged by antibiotic drugs that inhibit cerebral protein synthesis. All evidence seems consistent with the hypothesis that short-term memory is protein synthesis independent and that the establishment of long-term memory depends upon protein synthesis during or shortly after training. Evidence for a role of protein synthesis in memory maintenance is discussed.

Impaired short-term memory for pitch in congenital amusia.

Science.gov (United States)

Tillmann, Barbara; Lévêque, Yohana; Fornoni, Lesly; Albouy, Philippe; Caclin, Anne

2016-06-01

Congenital amusia is a neuro-developmental disorder of music perception and production. The hypothesis is that the musical deficits arise from altered pitch processing, with impairments in pitch discrimination (i.e., pitch change detection, pitch direction discrimination and identification) and short-term memory. The present review article focuses on the deficit of short-term memory for pitch. Overall, the data discussed here suggest impairments at each level of processing in short-term memory tasks; starting with the encoding of the pitch information and the creation of the adequate memory trace, the retention of the pitch traces over time as well as the recollection and comparison of the stored information with newly incoming information. These impairments have been related to altered brain responses in a distributed fronto-temporal network, associated with decreased connectivity between these structures, as well as in abnormalities in the connectivity between the two auditory cortices. In contrast, amusic participants׳ short-term memory abilities for verbal material are preserved. These findings show that short-term memory deficits in congenital amusia are specific to pitch, suggesting a pitch-memory system that is, at least partly, separated from verbal memory. This article is part of a Special Issue entitled SI: Auditory working memory. Copyright © 2015 Elsevier B.V. All rights reserved.

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

Energy Technology Data Exchange (ETDEWEB)

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

1990-10-01

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

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

International Nuclear Information System (INIS)

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

1990-10-01

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

The uranium industry: long-term planning for short-term competition

International Nuclear Information System (INIS)

Vottero, X.; Georges Capus, G.

2001-01-01

Long term planning for short term competition Today, uranium producers face new challenges in terms of both production (new regulatory, environmental and social constraints) and market conditions (new sources of uranium supply, very low prices and tough competition). In such a context, long-term planning is not just a prerequisite to survive in the nuclear fuel cycle industry. In fact, it also contributes to sustaining nuclear electricity generation facing fierce competition from other energy sources in increasingly deregulated markets. Firstly, the risk of investing in new mining projects in western countries is growing because, on the one hand, of very erratic market conditions and, on the other hand, of increasingly lengthy, complex and unpredictable regulatory conditions. Secondly, the supply of other sources of uranium (uranium derived from nuclear weapons, uranium produced in CIS countries, ...) involve other risks, mainly related to politics and commercial restrictions. Consequently, competitive uranium supply requires not only technical competence but also financial strength and good marketing capabilities in order to anticipate long-term market trends, in terms of both demand and supply. It also requires taking into account new parameters such as politics, environment, regulations, etc. Today, a supplier dedicated to the sustainable production of nuclear electricity must manage a broad range of long-term risks inherent to the procurement of uranium. Taking into account all these parameters in a context of short-term, fast-changing market is a great challenge for the future generation. World Uranium Civilian Supply and Demand. (authors)

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.

[Short-term and long-term fetal heart rate variability after amnioinfusion treatment of oligohydramnios complicated pregnancy].

Science.gov (United States)

Machalski, T; Sikora, J; Bakon, I; Magnucki, J; Grzesiak-Kubica, E; Szkodny, E

2001-12-01

Results of computerised analysis of cardiotocograms obtained in the group of 21 pregnancies complicated by idiopathic oligohydramnios are presented in the study. Amnioinfusion procedures were administered serially in local anesthesia with ultrasound and colour Doppler control on the base of oligohydramnios criteria by Phelan. The analysis was based on KOMPOR software created by ITAM Zabrze based on PC computer connected to Hewlett-Packard Series 50A cardiotocograph. Significant short-term variability increase just after amnioinfusion procedure from 5.55 ms to 8.24 ms and after 24 hours up to 7.25 ms was found, while significant long-term variability values changes were not observed.

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.

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.

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.

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....

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.

An accident diagnosis algorithm using long short-term memory

Directory of Open Access Journals (Sweden)

Jaemin Yang

2018-05-01

Full Text Available Accident diagnosis is one of the complex tasks for nuclear power plant (NPP operators. In abnormal or emergency situations, the diagnostic activity of the NPP states is burdensome though necessary. Numerous computer-based methods and operator support systems have been suggested to address this problem. Among them, the recurrent neural network (RNN has performed well at analyzing time series data. This study proposes an algorithm for accident diagnosis using long short-term memory (LSTM, which is a kind of RNN, which improves the limitation for time reflection. The algorithm consists of preprocessing, the LSTM network, and postprocessing. In the LSTM-based algorithm, preprocessed input variables are calculated to output the accident diagnosis results. The outputs are also postprocessed using softmax to determine the ranking of accident diagnosis results with probabilities. This algorithm was trained using a compact nuclear simulator for several accidents: a loss of coolant accident, a steam generator tube rupture, and a main steam line break. The trained algorithm was also tested to demonstrate the feasibility of diagnosing NPP accidents. Keywords: Accident Diagnosis, Long Short-term Memory, Recurrent Neural Network, Softmax

INCAP - Applying short-term flexibility to control inventories

OpenAIRE

Lödding , Hermann; Lohmann , Steffen

2011-01-01

Abstract Inventory Based Capacity Control (INCAP) is a very simple method that allows inventory levels to be effectively controlled by using short-term capacity flexibility in make-to-stock settings. Moreover, INCAP can be used for finished goods inventories as well as for semi-finished goods inventories. The basic idea is to define upper and lower inventory limits and to adjust capacities if the inventory level reaches either limit. Should the inventory fall below the lower limit,...

Very Short-term Nonparametric Probabilistic Forecasting of Renewable Energy Generation - with Application to Solar Energy

DEFF Research Database (Denmark)

Golestaneh, Faranak; Pinson, Pierre; Gooi, Hoay Beng

2016-01-01

Due to the inherent uncertainty involved in renewable energy forecasting, uncertainty quantification is a key input to maintain acceptable levels of reliability and profitability in power system operation. A proposal is formulated and evaluated here for the case of solar power generation, when only...... approach to generate very short-term predictive densities, i.e., for lead times between a few minutes to one hour ahead, with fast frequency updates. We rely on an Extreme Learning Machine (ELM) as a fast regression model, trained in varied ways to obtain both point and quantile forecasts of solar power...... generation. Four probabilistic methods are implemented as benchmarks. Rival approaches are evaluated based on a number of test cases for two solar power generation sites in different climatic regions, allowing us to show that our approach results in generation of skilful and reliable probabilistic forecasts...

Chiral approach to nuclear matter: Role of explicit short-range NN-terms

International Nuclear Information System (INIS)

Fritsch, S.; Kaiser, N.

2004-01-01

We extend a recent chiral approach to nuclear matter by including the most general (momentum-independent) NN-contact interaction. Iterating this two-parameter contact vertex with itself and with one-pion exchange the emerging energy per particle exhausts all terms possible up to and including fourth order in the small momentum expansion. Two (isospin-dependent) cut-offs Λ 0,1 are introduced to regularize the (linear) divergences of some three-loop in-medium diagrams. The equation of state of pure neutron matter, anti E n (k n ), can be reproduced very well up to quite high neutron densities of ρ n =0.5 fm -3 by adjusting the strength of a repulsive nn-contact interaction. Binding and saturation of isospin-symmetric nuclear matter is a generic feature of our perturbative calculation. Fixing the maximum binding energy per particle to - anti E(k f0 )=15.3 MeV we find that any possible equilibrium density ρ 0 lies below ρ 0 max =0.191 fm -3 . The additional constraint from the neutron matter equation of state leads however to a somewhat too low saturation density of ρ 0 =0.134 fm -3 . We also investigate the effects of the NN-contact interaction on the complex single-particle potential U(p,k f )+iW(p,k f ). We find that the effective nucleon mass at the Fermi surface is bounded from below by M * (k f0 ) ≥1.4 M. This property keeps the critical temperature of the liquid-gas phase transition at somewhat too high values T c ≥21 MeV. The downward bending of the asymmetry energy A(k f ) above nuclear-matter saturation density is a generic feature of the approximation to fourth order. We furthermore investigate the effects of the NN-contact interaction on the (vector-∇ρ) 2 -term in the nuclear energy density functional E[ρ,τ]. Altogether, there is within this complete fourth-order calculation no ''magic'' set of adjustable short-range parameters with which one could reproduce simultaneously and accurately all semi-empirical properties of nuclear matter. In

The importance of short-term off-target effects in estimating the long-term renal and cardiovascular protection of angiotensin receptor blockers

DEFF Research Database (Denmark)

Smink, P A; Miao, Y; Eijkemans, M J C

2014-01-01

Angiotensin receptor blockers (ARBs) have multiple effects that may contribute to their efficacy on renal/cardiovascular outcomes. We developed and validated a risk score that incorporated short-term changes in multiple risk markers to predict the ARB effect on renal/cardiovascular outcomes.......98), in addition to being markedly more accurate than predicted RRRs based on changes in single markers. The score was validated in an independent ARB trial. Predictions of long-term renal/cardiovascular ARB effects are more accurate when considering short-term changes in multiple risk markers, challenging the use...

Short-term variability of Johor River discharge based on wavelet analysis

Science.gov (United States)

Ahmad, N.; Kamaruddin, S. A.; Heryansyah, A.

2015-02-01

River discharge provides a direct measure of water quantity and availability of water for specific uses. It also provides the basis for understanding river basin processes and is essential for interpreting and understanding river flow characteristics. This study investigates the temporal variability of river discharge records of Johor River. Wavelet analysis of discharge records for 30 years was carried out to characterize the river flow variability. Our results indicate that Johor River discharge data shows a significant short-term variability of between 0.6 to 2.5 years.

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

Directory of Open Access Journals (Sweden)

Morken Gunnar

2011-03-01

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

Ultra-Short-Term Heart Rate Variability is Sensitive to Training Effects in Team Sports Players.

Science.gov (United States)

Nakamura, Fabio Y; Flatt, Andrew A; Pereira, Lucas A; Ramirez-Campillo, Rodrigo; Loturco, Irineu; Esco, Michael R

2015-09-01

The aim of this study was to test the possibility of the ultra-short-term lnRMSSD (measured in 1-min post-1-min stabilization period) to detect training induced adaptations in futsal players. Twenty-four elite futsal players underwent HRV assessments pre- and post-three or four weeks preseason training. From the 10-min HRV recording period, lnRMSSD was analyzed in the following time segments: 1) from 0-5 min (i.e., stabilization period); 2) from 0-1 min; 1-2 min; 2-3 min; 3-4 min; 4-5 min and; 3) from 5-10 min (i.e., criterion period). The lnRMSSD was almost certainly higher (100/00/00) using the magnitude-based inference in all periods at the post- moment. The correlation between changes in ultra-short-term lnRMSSD (i.e., 0-1 min; 1-2 min; 2-3 min; 3-4 min; 4-5 min) and lnRMSSDCriterion ranged between 0.45-0.75, with the highest value (p = 0.75; 90% CI: 0.55 - 0.85) found between ultra-short-term lnRMDSSD at 1-2 min and lnRMSSDCriterion. In conclusion, lnRMSSD determined in a short period of 1-min is sensitive to training induced changes in futsal players (based on the very large correlation to the criterion measure), and can be used to track cardiac autonomic adaptations. Key pointsThe ultra-short-term (1 min) natural log of the root-mean-square difference of successive normal RR intervals (lnRMSSD) is sensitive to training effects in futsal playersThe ultra-short-term lnRMSSD may simplify the assessment of the cardiac autonomic changes in the field compared to the traditional and lengthier (10 min duration) analysisCoaches are encouraged to implement the ultra-short-term heart rate variability in their routines to monitor team sports athletes.

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

Directory of Open Access Journals (Sweden)

Jiancang Zhuang

2012-07-01

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

Comparison of Sugammadex and Neostigmine in Short Term Surgery

Directory of Open Access Journals (Sweden)

Fatih Koc

2014-03-01

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

Short-term memory for scenes with affective content

OpenAIRE

Maljkovic, Vera; Martini, Paolo

2005-01-01

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

Short term load forecasting using neuro-fuzzy networks

Energy Technology Data Exchange (ETDEWEB)

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

2005-07-01

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

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-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

Ethnicity-specific birthweight distributions improve identification of term newborns at risk for short-term morbidity.

Science.gov (United States)

Hanley, Gillian E; Janssen, Patricia A

2013-11-01

We aimed to determine whether ethnicity-specific birthweight distributions more accurately identify newborns at risk for short-term neonatal morbidity associated with small for gestational age (SGA) birth than population-based distributions not stratified on ethnicity. We examined 100,463 singleton term infants born to parents in Washington State between Jan. 1, 2006, and Dec. 31, 2008. Using multivariable logistic regression models, we compared the ability of an ethnicity-specific growth distribution and a population-based growth distribution to predict which infants were at increased risk for Apgar score distributions had the highest rates of each of the adverse outcomes assessed-more than double those of infants only considered SGA by the population-based standards. When controlling for mother's age, parity, body mass index, education, gestational age, mode of delivery, and marital status, newborns considered SGA by ethnicity-specific birthweight distributions were between 2 and 7 times more likely to suffer from the adverse outcomes listed above than infants who were not SGA. In contrast, newborns considered SGA by population-based birthweight distributions alone were at no higher risk of any adverse outcome except hypothermia (adjusted odds ratio, 2.76; 95% confidence interval, 1.68-4.55) and neonatal intensive care unit admission (adjusted odds ratio, 1.40; 95% confidence interval, 1.18-1.67). Ethnicity-specific birthweight distributions were significantly better at identifying the infants at higher risk of short-term neonatal morbidity, suggesting that their use could save resources and unnecessary parental anxiety. Copyright © 2013 Mosby, Inc. All rights reserved.

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

Verbal short-term memory and vocabulary learning in polyglots.

Science.gov (United States)

Papagno, C; Vallar, G

1995-02-01

Polyglot and non-polyglot Italian subjects were given tests assessing verbal (phonological) and visuo-spatial short-term and long-term memory, general intelligence, and vocabulary knowledge in their native language. Polyglots had a superior level of performance in verbal short-term memory tasks (auditory digit span and nonword repetition) and in a paired-associate learning test, which assessed the subjects' ability to acquire new (Russian) words. By contrast, the two groups had comparable performance levels in tasks assessing general intelligence, visuo-spatial short-term memory and learning, and paired-associate learning of Italian words. These findings, which are in line with neuropsychological and developmental evidence, as well as with data from normal subjects, suggest a close relationship between the capacity of phonological memory and the acquisition of foreign languages.

The stimulation of hematosis on short-term and prolong irradiation

International Nuclear Information System (INIS)

Tukhtaev, T.M.

1978-01-01

This book studies the stimulation of hematosis on short-term and prolong irradiation, pathogenetic mechanisms of lesion and reconstruction of hematosis at critical radiation sickness, action hematosis stimulators in short-term irradiation conditions

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

Science.gov (United States)

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

2018-06-01

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

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.

Short-Term Synaptic Plasticity Regulation in Solution-Gated Indium-Gallium-Zinc-Oxide Electric-Double-Layer Transistors.

Science.gov (United States)

Wan, Chang Jin; Liu, Yang Hui; Zhu, Li Qiang; Feng, Ping; Shi, Yi; Wan, Qing

2016-04-20

In the biological nervous system, synaptic plasticity regulation is based on the modulation of ionic fluxes, and such regulation was regarded as the fundamental mechanism underlying memory and learning. Inspired by such biological strategies, indium-gallium-zinc-oxide (IGZO) electric-double-layer (EDL) transistors gated by aqueous solutions were proposed for synaptic behavior emulations. Short-term synaptic plasticity, such as paired-pulse facilitation, high-pass filtering, and orientation tuning, was experimentally emulated in these EDL transistors. Most importantly, we found that such short-term synaptic plasticity can be effectively regulated by alcohol (ethyl alcohol) and salt (potassium chloride) additives. Our results suggest that solution gated oxide-based EDL transistors could act as the platforms for short-term synaptic plasticity emulation.

Cellular activation of hypothalamic hypocretin/orexin neurons facilitates short-term spatial memory in mice.

Science.gov (United States)

Aitta-Aho, Teemu; Pappa, Elpiniki; Burdakov, Denis; Apergis-Schoute, John

2016-12-01

The hypothalamic hypocretin/orexin (HO) system holds a central role in the regulation of several physiological functions critical for food-seeking behavior including mnemonic processes for effective foraging behavior. It is unclear however whether physiological increases in HO neuronal activity can support such processes. Using a designer rM3Ds receptor activation approach increasing HO neuronal activity resulted in improved short-term memory for novel locations. When tested on a non-spatial novelty object recognition task no significant difference was detected between groups indicating that hypothalamic HO neuronal activation can selectively facilitate short-term spatial memory for potentially supporting memory for locations during active exploration. Copyright © 2016 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2017-08-01

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

A short-term, comprehensive, yoga-based lifestyle intervention is efficacious in reducing anxiety, improving subjective well-being and personality

Directory of Open Access Journals (Sweden)

Raj Kumar Yadav

2012-01-01

Full Text Available Objective: To assess the efficacy of a short-term comprehensive yoga-based lifestyle intervention in reducing anxiety, improving subjective well-being and personality. Materials and Methods: The study is a part of an ongoing larger study at a tertiary care hospital. Participants (n=90 included patients with chronic diseases attending a 10-day, yoga-based lifestyle intervention program for prevention and management of chronic diseases, and healthy controls (n=45 not attending any such intervention. Primary Outcome Measures: Change in state and trait anxiety questionnaire (STAI-Y; 40 items, subjective well-being inventory (SUBI; 40 items, and neuroticism extraversion openness to experience five factor personality inventory revised (NEO-FF PI-R; 60 items at the end of intervention. Results: Following intervention, the STAI-Y scores reduced significantly (P0.01 at Day 10 versus Day 1. Similarly NEO-FF PI-R scores improved significantly (P<0.001 at Day 10 versus Day 1. Control group showed an increase in STAI-Y while SUBI and NEO-FF PI-R scores remained comparable at Day 10 versus Day 1. Conclusions: The observations suggest that a short-term, yoga-based lifestyle intervention may significantly reduce anxiety and improve subjective well-being and personality in patients with chronic diseases.

Learning From Short Text Streams With Topic Drifts.

Science.gov (United States)

Li, Peipei; He, Lu; Wang, Haiyan; Hu, Xuegang; Zhang, Yuhong; Li, Lei; Wu, Xindong

2017-09-18

Short text streams such as search snippets and micro blogs have been popular on the Web with the emergence of social media. Unlike traditional normal text streams, these data present the characteristics of short length, weak signal, high volume, high velocity, topic drift, etc. Short text stream classification is hence a very challenging and significant task. However, this challenge has received little attention from the research community. Therefore, a new feature extension approach is proposed for short text stream classification with the help of a large-scale semantic network obtained from a Web corpus. It is built on an incremental ensemble classification model for efficiency. First, more semantic contexts based on the senses of terms in short texts are introduced to make up of the data sparsity using the open semantic network, in which all terms are disambiguated by their semantics to reduce the noise impact. Second, a concept cluster-based topic drifting detection method is proposed to effectively track hidden topic drifts. Finally, extensive studies demonstrate that as compared to several well-known concept drifting detection methods in data stream, our approach can detect topic drifts effectively, and it enables handling short text streams effectively while maintaining the efficiency as compared to several state-of-the-art short text classification approaches.

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.

Category Specific Knowledge Modulate Capacity Limitations of Visual Short-Term Memory

DEFF Research Database (Denmark)

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

2016-01-01

We explore whether expertise can modulate the capacity of visual short-term memory, as some seem to argue that training affects capacity of short-term memory [13] while others are not able to find this modulation [12]. We extend on a previous study [3] demonstrating expertise effects by investiga...... are in line with the theoretical interpretation that visual short-term memory reflects the sum of the reverberating feedback loops to representations in long-term memory.......We explore whether expertise can modulate the capacity of visual short-term memory, as some seem to argue that training affects capacity of short-term memory [13] while others are not able to find this modulation [12]. We extend on a previous study [3] demonstrating expertise effects......), and expert observers (Japanese university students). For both the picture and the letter condition we find no performance difference in memory capacity, however, in the critical hiragana condition we demonstrate a systematic difference relating expertise differences between the groups. These results...

Social cognitive markers of short-term clinical outcome in first-episode psychosis.

Science.gov (United States)

Montreuil, Tina; Bodnar, Michael; Bertrand, Marie-Claude; Malla, Ashok K; Joober, Ridha; Lepage, Martin

2010-07-01

In psychotic disorders, impairments in cognition have been associated with both clinical and functional outcome, while deficits in social cognition have been associated with functional outcome. As an extension to a recent report on neurocognition and short-term clinical outcome in first-episode psychosis (FEP), the current study explored whether social cognitive deficits could also identify poor short-term clinical outcome among FEP patients. We defined the social-cognition domain based on the scores from the Hinting Task and the Four Factor Tests of Social Intelligence. Data were collected in 45 FEP patients and 26 healthy controls. The patients were divided into good- and poor-outcome groups based on clinical data at six months following initiation of treatment. Social cognition was compared among 27 poor-outcome, 18 good-outcome, and 26 healthy-control participants. Outcome groups significantly differed in the social cognition domain (z-scores: poor outcome=-2.0 [SD=1.4]; good outcome=-1.0 [SD=1.0]; p=0.005), with both groups scoring significantly lower than the control group (psocial cognition appears to be compromised in all FEP patients compared to healthy controls. More interestingly, significant differences in social cognitive impairments exist between good and poor short-term clinical outcome groups, with the largest effect found in the Cartoon Predictions subtest.

Short term benefits for laparoscopic colorectal resection.

Science.gov (United States)

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

2005-07-20

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

Short-term carbon partitioning fertilizer responses vary among two full-sib loblolly pine clones

Science.gov (United States)

Jeremy P. Stovall; John R. Seiler; Thomas R. Fox

2012-01-01

We investigated the effects of fertilizer application on the partitioning of gross primary productivity (GPP) between contrasting full-sib clones of Pinus taeda (L.). Our objective was to determine if fertilizer growth responses resulted from similar short-term changes to partitioning. A modeling approach incorporating respiratory carbon (C) fluxes,...

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 robustness of production management systems

NARCIS (Netherlands)

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

1998-01-01

Short-term performance of a production management system for make-to-stock factories may be quantified through the service rate per shift; long-term performance through the average monthly work in process (WIP). This may yield, for example, that WIP is minimized, while the probability of the service

Potentials of short term and long term cryopreserved sperm of the ...

African Journals Online (AJOL)

To service the growing demand for male African giant catfish (Clarias gariepinus) broodstock for aquaculture in Nigeria, and to conserve valuable genetic resources, we improved both short-term (in deep freezer at -35°C) and long-term cryopreservation (in liquid nitrogen at -296°C) of catfish sperm. Catfish sperm ...

Temporal grouping effects in musical short-term memory.

Science.gov (United States)

Gorin, Simon; Mengal, Pierre; Majerus, Steve

2018-07-01

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

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.

Auditory short-term memory activation during score reading.

Science.gov (United States)

Simoens, Veerle L; Tervaniemi, Mari

2013-01-01

Performing music on the basis of reading a score requires reading ahead of what is being played in order to anticipate the necessary actions to produce the notes. Score reading thus not only involves the decoding of a visual score and the comparison to the auditory feedback, but also short-term storage of the musical information due to the delay of the auditory feedback during reading ahead. This study investigates the mechanisms of encoding of musical information in short-term memory during such a complicated procedure. There were three parts in this study. First, professional musicians participated in an electroencephalographic (EEG) experiment to study the slow wave potentials during a time interval of short-term memory storage in a situation that requires cross-modal translation and short-term storage of visual material to be compared with delayed auditory material, as it is the case in music score reading. This delayed visual-to-auditory matching task was compared with delayed visual-visual and auditory-auditory matching tasks in terms of EEG topography and voltage amplitudes. Second, an additional behavioural experiment was performed to determine which type of distractor would be the most interfering with the score reading-like task. Third, the self-reported strategies of the participants were also analyzed. All three parts of this study point towards the same conclusion according to which during music score reading, the musician most likely first translates the visual score into an auditory cue, probably starting around 700 or 1300 ms, ready for storage and delayed comparison with the auditory feedback.

Short term forecasting of petroleum product demand in France

International Nuclear Information System (INIS)

Cadren, M.

1998-01-01

The analysis of petroleum product demand became a privileged thrust of research following the modifications in terms of structure and level of the petroleum markets since eighties. The greatest importance to econometrics models of Energy demand, joint works about nonstationary data, explained the development of error-correction models and the co-integration. In this context, the short term econometrics modelling of petroleum product demand does not only focus on forecasts but also on the measure of the gain acquired from using error-correction techniques and co-integration. It's filling to take the influence of technical improvement and environment pressures into account in econometrics modelling of petroleum products demand. The first part presents the evolution of Energy Demand in France and more particularly the petroleum product demand since 1986. The objective is to determine the main characteristics of each product, which will help us to analyse and validate the econometrics models. The second part focus on the recent developments in times series modelling. We study the problem of nonstationary data and expose different unit root tests. We examine the main approaches to univariate and multivariate modelling with nonstationary data and distinguish the forecasts of the latter's. The third part is intended to applications; its objective is to illustrate the theoretic developments of the second part with a comparison between the performances of different approaches (approach Box and Jenkins, Johansen approach's and structural approach). The models will be applied to the main French petroleum market. The observed asymmetrical demand behaviour is also considered. (author)

A strategic flight conflict avoidance approach based on a memetic algorithm

Directory of Open Access Journals (Sweden)

Guan Xiangmin

2014-02-01

Full Text Available Conflict avoidance (CA plays a crucial role in guaranteeing the airspace safety. The current approaches, mostly focusing on a short-term situation which eliminates conflicts via local adjustment, cannot provide a global solution. Recently, long-term conflict avoidance approaches, which are proposed to provide solutions via strategically planning traffic flow from a global view, have attracted more attentions. With consideration of the situation in China, there are thousands of flights per day and the air route network is large and complex, which makes the long-term problem to be a large-scale combinatorial optimization problem with complex constraints. To minimize the risk of premature convergence being faced by current approaches and obtain higher quality solutions, in this work, we present an effective strategic framework based on a memetic algorithm (MA, which can markedly improve search capability via a combination of population-based global search and local improvements made by individuals. In addition, a specially designed local search operator and an adaptive local search frequency strategy are proposed to improve the solution quality. Furthermore, a fast genetic algorithm (GA is presented as the global optimization method. Empirical studies using real traffic data of the Chinese air route network and daily flight plans show that our approach outperformed the existing approaches including the GA based approach and the cooperative coevolution based approach as well as some well-known memetic algorithm based approaches.

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

Directory of Open Access Journals (Sweden)

Peng Sun

2016-10-01

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

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.

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.

About the distinction between working memory and short-term memory

Directory of Open Access Journals (Sweden)

Bart eAben

2012-08-01

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

Medial temporal lobe contributions to short-term memory for faces

Science.gov (United States)

Race, Elizabeth; LaRocque, Karen F.; Keane, Margaret M.; Verfaellie, Mieke

2015-01-01

The role of the medial temporal lobes (MTL) in short-term memory (STM) remains a matter of debate. While imaging studies commonly show hippocampal activation during short-delay memory tasks, evidence from amnesic patients with MTL lesions is mixed. It has been argued that apparent STM impairments in amnesia may reflect long-term memory (LTM) contributions to performance. We challenge this conclusion by demonstrating that MTL amnesic patients show impaired delayed matching-to-sample (DMS) for faces in a task that meets both a traditional delay-based and a recently proposed distractor-based criterion for classification as a STM task. In Experiment 1, we demonstrate that our face DMS task meets the proposed distractor-based criterion for STM classification, in that extensive processing of delay-period distractor stimuli disrupts performance of healthy individuals. In Experiment 2, MTL amnesic patients with lesions extending into anterior subhippocampal cortex, but not patients with lesions limited to the hippocampus, show impaired performance on this task without distraction at delays as short as 8s, within temporal range of delay-based STM classification, in the context of intact perceptual matching performance. Experiment 3 provides support for the hypothesis that STM for faces relies on configural processing by showing that the extent to which healthy participants’ performance is disrupted by interference depends on the configural demands of the distractor task. Together, these findings are consistent with the notion that the amnesic impairment in STM for faces reflects a deficit in configural processing associated with subhippocampal cortices and provide novel evidence that the MTL supports cognition beyond the LTM domain. PMID:23937185

Medial temporal lobe contributions to short-term memory for faces.

Science.gov (United States)

Race, Elizabeth; LaRocque, Karen F; Keane, Margaret M; Verfaellie, Mieke

2013-11-01

The role of the medial temporal lobes (MTL) in short-term memory (STM) remains a matter of debate. Whereas imaging studies commonly show hippocampal activation during short-delay memory tasks, evidence from amnesic patients with MTL lesions is mixed. It has been argued that apparent STM impairments in amnesia may reflect long-term memory (LTM) contributions to performance. We challenge this conclusion by demonstrating that MTL amnesic patients show impaired delayed matching-to-sample (DMS) for faces in a task that meets both a traditional delay-based and a recently proposed distractor-based criterion for classification as an STM task. In Experiment 1, we demonstrate that our face DMS task meets the proposed distractor-based criterion for STM classification, in that extensive processing of delay-period distractor stimuli disrupts performance of healthy individuals. In Experiment 2, MTL amnesic patients with lesions extending into anterior subhippocampal cortex, but not patients with lesions limited to the hippocampus, show impaired performance on this task without distraction at delays as short as 8 s, within temporal range of delay-based STM classification, in the context of intact perceptual matching performance. Experiment 3 provides support for the hypothesis that STM for faces relies on configural processing by showing that the extent to which healthy participants' performance is disrupted by interference depends on the configural demands of the distractor task. Together, these findings are consistent with the notion that the amnesic impairment in STM for faces reflects a deficit in configural processing associated with subhippocampal cortices and provide novel evidence that the MTL supports cognition beyond the LTM domain. PsycINFO Database Record (c) 2013 APA, all rights reserved.

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

Directory of Open Access Journals (Sweden)

Jaime Lloret

2013-08-01

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

Short-Term Contract Work in Adult Education (I) and (II).

Science.gov (United States)

Hall, Dorothea; McMath, Patricia

1986-01-01

This two-part article discusses short-term project contracts for adult education staff. Part one covers implications of this trend for the service and for the staff involved. Part two looks at short-term contracts from the management viewpoint. (CH)

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 ...

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…

Working memory, short-term memory and reading proficiency in school-age children with cochlear implants.

Science.gov (United States)

Bharadwaj, Sneha V; Maricle, Denise; Green, Laura; Allman, Tamby

2015-10-01

The objective of the study was to examine short-term memory and working memory through both visual and auditory tasks in school-age children with cochlear implants. The relationship between the performance on these cognitive skills and reading as well as language outcomes were examined in these children. Ten children between the ages of 7 and 11 years with early-onset bilateral severe-profound hearing loss participated in the study. Auditory and visual short-term memory, auditory and visual working memory subtests and verbal knowledge measures were assessed using the Woodcock Johnson III Tests of Cognitive Abilities, the Wechsler Intelligence Scale for Children-IV Integrated and the Kaufman Assessment Battery for Children II. Reading outcomes were assessed using the Woodcock Reading Mastery Test III. Performance on visual short-term memory and visual working memory measures in children with cochlear implants was within the average range when compared to the normative mean. However, auditory short-term memory and auditory working memory measures were below average when compared to the normative mean. Performance was also below average on all verbal knowledge measures. Regarding reading outcomes, children with cochlear implants scored below average for listening and passage comprehension tasks and these measures were positively correlated to visual short-term memory, visual working memory and auditory short-term memory. Performance on auditory working memory subtests was not related to reading or language outcomes. The children with cochlear implants in this study demonstrated better performance in visual (spatial) working memory and short-term memory skills than in auditory working memory and auditory short-term memory skills. Significant positive relationships were found between visual working memory and reading outcomes. The results of the study provide support for the idea that WM capacity is modality specific in children with hearing loss. Based on these

Predictors of Short- and Long-Term Attrition From the Parents as Agents of Change Randomized Controlled Trial for Managing Pediatric Obesity.

Science.gov (United States)

Spence, Nicholas D; Newton, Amanda S; Keaschuk, Rachel A; Ambler, Kathryn A; Jetha, Mary M; Holt, Nicholas L; Rosychuk, Rhonda J; Spence, John C; Sharma, Arya M; Ball, Geoff D C

Attrition in pediatric weight management is a substantial problem. This study examined factors associated with short- and long-term attrition from a lifestyle and behavioral intervention for parents of children with overweight or obesity. Fifty-two families with children ages 6 to 12 years old and body mass index at or above the 85th percentile participated in a randomized controlled trial focused on parents, comparing parent-based cognitive behavioral therapy with parent-based psychoeducation for pediatric weight management. We examined program attrition using two clinical phases of the intervention: short-term and long-term attrition, modeled using the general linear model. Predictors included intervention type, child/parent weight status, sociodemographic factors, and health of the family system. Higher self-assessed health of the family system was associated with lower short-term attrition; higher percentage of intervention sessions attended by parents was associated with lower long-term attrition. Different variables were significant in our short- and long-term models. Attrition might best be conceptualized based on short- and long-term phases of clinical, parent-based interventions for pediatric weight management. Copyright © 2016 National Association of Pediatric Nurse Practitioners. Published by Elsevier Inc. All rights reserved.

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.

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...

Dissociating Measures of Consciousness from Measures of Short-Term Memory

DEFF Research Database (Denmark)

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

Often, the contents of consciousness are equated with the contents of short-term memory (or working memory), sometimes to a point where they are treated as identical entities. In the present study we aimed to investigate whether they may be modulated independently and thus dissociated from each...... if conscious content simply can be reduced to a cognitive process like short-term memory. In two experiments, we combined two different measures of short-term memory capacity to investigate how manipulations of set-size affect performance in observers with the Perceptual Awareness Scale (PAS) to measure...... conscious experience of the stimulus in every trial (Ramsøy & Overgaard, 2004; Overgaard & Sørensen, 2004). We trained observers to report their experience of a visual target stimulus on the four-point PAS scale; ranging from “no experience” to “clear experience”. To measure short-term memory we used...

Short-term fasting alters cytochrome P450-mediated drug metabolism in humans

NARCIS (Netherlands)

Lammers, Laureen A.; Achterbergh, Roos; de Vries, Emmely M.; van Nierop, F. Samuel; Klümpen, Heinz-Josef; Soeters, Maarten R.; Boelen, Anita; Romijn, Johannes A.; Mathôt, Ron A. A.

2015-01-01

Experimental studies indicate that short-term fasting alters drug metabolism. However, the effects of short-term fasting on drug metabolism in humans need further investigation. Therefore, the aim of this study was to evaluate the effects of short-term fasting (36 h) on P450-mediated drug

The role of long-term familiarity and attentional maintenance in short-term memory for timbre.

Science.gov (United States)

Siedenburg, Kai; McAdams, Stephen

2017-04-01

We study short-term recognition of timbre using familiar recorded tones from acoustic instruments and unfamiliar transformed tones that do not readily evoke sound-source categories. Participants indicated whether the timbre of a probe sound matched with one of three previously presented sounds (item recognition). In Exp. 1, musicians better recognised familiar acoustic compared to unfamiliar synthetic sounds, and this advantage was particularly large in the medial serial position. There was a strong correlation between correct rejection rate and the mean perceptual dissimilarity of the probe to the tones from the sequence. Exp. 2 compared musicians' and non-musicians' performance with concurrent articulatory suppression, visual interference, and with a silent control condition. Both suppression tasks disrupted performance by a similar margin, regardless of musical training of participants or type of sounds. Our results suggest that familiarity with sound source categories and attention play important roles in short-term memory for timbre, which rules out accounts solely based on sensory persistence.

Readiness for change and short-term outcomes of female adolescents in residential treatment for anorexia nervosa.

Science.gov (United States)

McHugh, Matthew D

2007-11-01

To determine if readiness for change (RFC) at admission predicted length of stay (LOS) and short-term outcomes among female adolescents in residential treatment for anorexia nervosa (AN). Using a prospective cohort design to collect data from participants (N = 65) at admission and discharge, Kaplan-Meier survival analysis and Cox regression tested whether RFC on admission predicted time in LOS to a favorable short-term outcome--a composite endpoint based on minimum criteria for weight gain, drive for thinness, depression, anxiety, and health-related quality of life (HRQOL). Participants with low RFC had a mean survival time to a favorable short-term outcome of 59.4 days compared to 34.1 days for those with high RFC (log rank = 8.44, df = 1, p = .003). The probability of a favorable short-term outcome was 5.30 times greater for participants with high RFC. Readiness for change is a useful predictor of a favorable short-term outcome and should be considered in the assessment profile of patients with AN. (c) 2007 by Wiley Periodicals, Inc.

Verbal and musical short-term memory: Variety of auditory disorders after stroke.

Science.gov (United States)

Hirel, Catherine; Nighoghossian, Norbert; Lévêque, Yohana; Hannoun, Salem; Fornoni, Lesly; Daligault, Sébastien; Bouchet, Patrick; Jung, Julien; Tillmann, Barbara; Caclin, Anne

2017-04-01

Auditory cognitive deficits after stroke may concern language and/or music processing, resulting in aphasia and/or amusia. The aim of the present study was to assess the potential deficits of auditory short-term memory for verbal and musical material after stroke and their underlying cerebral correlates with a Voxel-based Lesion Symptom Mapping approach (VLSM). Patients with an ischemic stroke in the right (N=10) or left (N=10) middle cerebral artery territory and matched control participants (N=14) were tested with a detailed neuropsychological assessment including global cognitive functions, music perception and language tasks. All participants then performed verbal and musical auditory short-term memory (STM) tasks that were implemented in the same way for both materials. Participants had to indicate whether series of four words or four tones presented in pairs, were the same or different. To detect domain-general STM deficits, they also had to perform a visual STM task. Behavioral results showed that patients had lower performance for the STM tasks in comparison with control participants, regardless of the material (words, tones, visual) and the lesion side. The individual patient data showed a double dissociation between some patients exhibiting verbal deficits without musical deficits or the reverse. Exploratory VLSM analyses suggested that dorsal pathways are involved in verbal (phonetic), musical (melodic), and visual STM, while the ventral auditory pathway is involved in musical STM. Copyright © 2017 Elsevier Inc. All rights reserved.

Anomaly Detection for Temporal Data using Long Short-Term Memory (LSTM)

OpenAIRE

Singh, Akash

2017-01-01

We explore the use of Long short-term memory (LSTM) for anomaly detection in temporal data. Due to the challenges in obtaining labeled anomaly datasets, an unsupervised approach is employed. We train recurrent neural networks (RNNs) with LSTM units to learn the normal time series patterns and predict future values. The resulting prediction errors are modeled to give anomaly scores. We investigate different ways of maintaining LSTM state, and the effect of using a fixed number of time steps on...

U.S.-Based Short-Term Public Health Cultural Immersion Experience for Chinese Undergraduate Students

Science.gov (United States)

Powell, Dorothy Lewis; Biederman, Donna J.

2017-01-01

A U.S. and Chinese university developed a short-term student exchange program in public/community health. The program--which consisted of lectures, seminars, field trips, cross-cultural experiences, and a synthesis excursion--resulted in high levels of program satisfaction, increased intrapersonal awareness, and skill acquisition. Program content…

Word embeddings and recurrent neural networks based on Long-Short Term Memory nodes in supervised biomedical word sense disambiguation.

Science.gov (United States)

Jimeno Yepes, Antonio

2017-09-01

Word sense disambiguation helps identifying the proper sense of ambiguous words in text. With large terminologies such as the UMLS Metathesaurus ambiguities appear and highly effective disambiguation methods are required. Supervised learning algorithm methods are used as one of the approaches to perform disambiguation. Features extracted from the context of an ambiguous word are used to identify the proper sense of such a word. The type of features have an impact on machine learning methods, thus affect disambiguation performance. In this work, we have evaluated several types of features derived from the context of the ambiguous word and we have explored as well more global features derived from MEDLINE using word embeddings. Results show that word embeddings improve the performance of more traditional features and allow as well using recurrent neural network classifiers based on Long-Short Term Memory (LSTM) nodes. The combination of unigrams and word embeddings with an SVM sets a new state of the art performance with a macro accuracy of 95.97 in the MSH WSD data set. Copyright © 2017 Elsevier Inc. All rights reserved.

Dissociating Contents of Consciousness from Contents of Short-Term Memory

DEFF Research Database (Denmark)

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

2014-01-01

The contents of consciousness and of short-term memory are hard to disentangle. As it seems intuitive that we represent attended objects in short-term memory and in experience, to many, it also seems intuitive to equate this content. Here we investigated memory resolution for orientation......” to a “clear experience” of a probed target. To assess memory resolution we used a Landolt-variation on the visual short-term memory (VSTM) resolution paradigm (e.g. Wilken & Ma, 2004). Set-sizes in the memory display were varied between 1, 2, or 4 elements. With increasing set-size we found that both...

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

International Nuclear Information System (INIS)

Zheng, Xiujuan; Fang, Huajing

2015-01-01

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

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.

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.

Emotion-based decision-making in healthy subjects: short-term effects of reducing dopamine levels.

Science.gov (United States)

Sevy, Serge; Hassoun, Youssef; Bechara, Antoine; Yechiam, Eldad; Napolitano, Barbara; Burdick, Katherine; Delman, Howard; Malhotra, Anil

2006-10-01

Converging evidences from animal and human studies suggest that addiction is associated with dopaminergic dysfunction in brain reward circuits. So far, it is unclear what aspects of addictive behaviors are related to a dopaminergic dysfunction. We hypothesize that a decrease in dopaminergic activity impairs emotion-based decision-making. To demonstrate this hypothesis, we investigated the effects of a decrease in dopaminergic activity on the performance of an emotion-based decision-making task, the Iowa gambling task (IGT), in 11 healthy human subjects. We used a double-blind, placebo-controlled, within-subject design to examine the effect of a mixture containing the branched-chain amino acids (BCAA) valine, isoleucine and leucine on prolactin, IGT performance, perceptual competency and visual aspects of visuospatial working memory, visual attention and working memory, and verbal memory. The expectancy-valence model was used to determine the relative contributions of distinct IGT components (attention to past outcomes, relative weight of wins and losses, and choice strategies) in the decision-making process. Compared to placebo, the BCAA mixture increased prolactin levels and impaired IGT performance. BCAA administration interfered with a particular component process of decision-making related to attention to more recent events as compared to more distant events. There were no differences between placebo and BCAA conditions for other aspects of cognition. Our results suggest a direct link between a reduced dopaminergic activity and poor emotion-based decision-making characterized by shortsightedness, and thus difficulties resisting short-term reward, despite long-term negative consequences. These findings have implications for behavioral and pharmacological interventions targeting impaired emotion-based decision-making in addictive disorders.

Short-term hydropower production planning by stochastic programming

DEFF Research Database (Denmark)

Fleten, Stein-Erik; Kristoffersen, Trine

2008-01-01

-term production planning a matter of spatial distribution among the reservoirs of the plant. Day-ahead market prices and reservoir inflows are, however, uncertain beyond the current operation day and water must be allocated among the reservoirs in order to strike a balance between current profits and expected......Within the framework of multi-stage mixed-integer linear stochastic programming we develop a short-term production plan for a price-taking hydropower plant operating under uncertainty. Current production must comply with the day-ahead commitments of the previous day which makes short...

Growth hormone therapy for children born small for gestational age: height gain is less dose dependent over the long term than over the short term.

Science.gov (United States)

de Zegher, Francis; Hokken-Koelega, Anita

2005-04-01

Approximately 3% of children are born small for gestational age (SGA), and approximately 10% of SGA children maintain a small body size throughout childhood and often into adult life. Among short SGA children, growth hormone (GH) therapy increases short-term growth in a dose-dependent manner; experience with long-term therapy is limited. To delineate the dose dependency of long-term height gain among short SGA children receiving GH therapy. We performed an epianalysis of the first adult height data for SGA children (n = 28) enrolled in 3 randomized trials comparing the growth-promoting efficacy of 2 continuous GH regimens (33 or 67 microg/kg per day for approximately 10 years, starting at approximately 5 years of age); in addition, we performed a meta-analysis of the adult height results published previously and those presented here. Epianalysis outcomes (n = 28) suggested that adult height increased more with a higher-dose regimen than with a lower-dose regimen. In the meta-analysis (n = 82), the higher-dose regimen was found to elicit a long-term height gain superior to that achieved with the lower-dose regimen by a mean of 0.4 SD (approximately 1 inch). Children who were shorter at the start of therapy experienced more long-term height gain. These findings confirm GH therapy as an effective and safe approach to reduce the adult height deficit that short SGA children otherwise face. In addition, the first meta-analysis indicated that height gain is less dose dependent over the long term than over the short term, at least within the dose range explored to date. For SGA children whose stature is not extremely short, current data support the use of a GH dose of approximately 33 microg/kg per day from start to adult height, particularly if treatment starts at a young age; shorter children (for example, height below -3 SD) might benefit from an approach in which short-term catch-up growth is achieved with a higher dose (> or =50 microg/kg per day) and long-term growth

The Effect of Short-Term Study Abroad Experience on American Students' Leadership Skills and Career Aspirations

Science.gov (United States)

Geyer, Alexis; Putz, Jenni; Misra, Kaustav

2017-01-01

Purpose: Building on existing study abroad literature, the purpose of this paper is to assess the impact of both short-term and long-term study abroad programs on students' leadership skills and their career aspirations. Design/methodology/approach: A sample of college students were invited to complete an electronic survey about their experiences…

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.)

Short-term and long-term effects of violent media on aggression in children and adults.

Science.gov (United States)

Bushman, Brad J; Huesmann, L Rowell

2006-04-01

To test whether the results of the accumulated studies on media violence and aggressive behavior are consistent with the theories that have evolved to explain the effects. We tested for the existence of both short-term and long-term effects for aggressive behavior. We also tested the theory-driven hypothesis that short-term effects should be greater for adults and long-term effects should be greater for children. Meta-analysis. Children younger than 18 years and adults. Violent media, including TV, movies, video games, music, and comic books. Measures of aggressive behavior, aggressive thoughts, angry feelings, physiological arousal (eg, heart rate, blood pressure), and helping behavior. Effect size estimates were combined using meta-analytic procedures. As expected, the short-term effects of violent media were greater for adults than for children whereas the long-term effects were greater for children than for adults. The results also showed that there were overall modest but significant effect sizes for exposure to media violence on aggressive behaviors, aggressive thoughts, angry feelings, arousal levels, and helping behavior. The results are consistent with the theory that short-term effects are mostly due to the priming of existing well-encoded scripts, schemas, or beliefs, which adults have had more time to encode. In contrast, long-term effects require the learning (encoding) of scripts, schemas, or beliefs. Children can encode new scripts, schemas, and beliefs via observational learning with less interference and effort than adults.

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.

The complexity of self-regulating food intake in weight loss maintenance. A qualitative study among short- and long-term weight loss maintainers

DEFF Research Database (Denmark)

Pedersen, Susanne; Sniethotta, Falko F.; Sainsbury, Kirby

2018-01-01

Rationale Whether self-regulation of food intake in weight loss maintenance (WLM) differs between being a short-term maintainer (having maintained without regaining less than 12 months) and a long-term maintainer (having maintained without regaining at least 12 months) is under-researched. Object......Rationale Whether self-regulation of food intake in weight loss maintenance (WLM) differs between being a short-term maintainer (having maintained without regaining less than 12 months) and a long-term maintainer (having maintained without regaining at least 12 months) is under......-researched. Objective The aim of this study was to explore the self-regulatory strategies and self-efficacy beliefs applied by short- and long-term maintainers to the complex set of behaviours comprising food intake in WLM, and to obtain a better understanding of their challenges in the various food-intake processes...... in WLM. Method Individual interviews (14 female/4 male) were conducted with nine Danish short- and nine long-term weight loss maintainers. The Health Action Process Approach (HAPA) was applied post-hoc to organise data and support analyses, since the approach focuses on both the cognitions (e.g., self...

Pediatric laparoscopic sleeve gastrectomy in Turkey: Short-term results.

Science.gov (United States)

Ates, Ufuk; Ergun, Ergun; Gollu, Gulnur; Sozduyar, Sumeyye; Can, Ozlem Selvi; Yagmurlu, Aydin

2018-05-01

Obesity is one of the most rapidly increasing health problems in children. Laparoscopic sleeve gastrectomy (LSG) is one of the best treatment options and is feasible and safe in children. The aim of this study was to present the short-term results of a laparoscopic sleeve gastrectomy series in children. Children who underwent LSG in 2014-2017 were included in the study. Charts were investigated retrospectively and short-term weight loss was analyzed. Patients who had surgery in 2014-2017 were included in the study. There were six girls and two boys, and the median age was 15 years (range, 11-18 years). Mean weight was 159.25 ± 19.78 kg, and mean body mass index was 61.05 ± 8.5 kg/m 2 . Mean operation time was 70 min (range, 65-90 min), mean hospital stay was 5.1 days (range, 3-7 days), and mean follow up was 19.2 months (range, 1-43 months). Of these patients, five had hypertension and were under medication and two of these five also had hyperinsulinemia. One of the five children had Bardet-Biedl syndrome and one had bronchial asthma. After operation, medication was stopped in four of the eight children. At the time of writing, six patients were doing well without postoperative complications, or the need for reoperation. Even though the follow-up period was short and the number of patients was small, LSG was a feasible and promising surgical method for morbidly obese children. A multidisciplinary approach and lifelong behavior therapy are key steps for success. © 2018 Japan Pediatric Society.

Photovoltaic systems: state of the art and short-medium term perspectives

International Nuclear Information System (INIS)

Brofferio, Sergio C.; Rota, Alberto

2006-01-01

The paper presents and discusses, from a technology and economic point of view, the characteristics, performances, issues and perspectives of the thin films and the solar concentrating photovoltaic systems in the short and medium terms. Both have well based motivations to be an evolutionary step of current wafer based Silicon systems: the former as Building Integrated Photovoltaic and the latter as high density and high power photovoltaic systems [it

Short-term planning and the life-cycle consumption puzzle

OpenAIRE

Frank Caliendo; David Aadland

2004-01-01

This paper provides a new explanation for the hump-shaped age- consumption profile observed in household data. Standard life-cycle models are based on an optimization problem that spans the entire life expectancy. Alternatively, we examine the consumption profile of an individual with a shorter planning horizon. The actual consumption profile is the envelope of a continuum of control problems because the agent’s short-term planning horizon continually slides along the time- scale, and the age...

An adaptive random search for short term generation scheduling with network constraints.

Directory of Open Access Journals (Sweden)

J A Marmolejo

Full Text Available This paper presents an adaptive random search approach to address a short term generation scheduling with network constraints, which determines the startup and shutdown schedules of thermal units over a given planning horizon. In this model, we consider the transmission network through capacity limits and line losses. The mathematical model is stated in the form of a Mixed Integer Non Linear Problem with binary variables. The proposed heuristic is a population-based method that generates a set of new potential solutions via a random search strategy. The random search is based on the Markov Chain Monte Carlo method. The main key of the proposed method is that the noise level of the random search is adaptively controlled in order to exploring and exploiting the entire search space. In order to improve the solutions, we consider coupling a local search into random search process. Several test systems are presented to evaluate the performance of the proposed heuristic. We use a commercial optimizer to compare the quality of the solutions provided by the proposed method. The solution of the proposed algorithm showed a significant reduction in computational effort with respect to the full-scale outer approximation commercial solver. Numerical results show the potential and robustness of our approach.

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.…

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

Directory of Open Access Journals (Sweden)

ChangHwan Kim

2018-03-01

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

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

Auditory-Cortex Short-Term Plasticity Induced by Selective Attention

Science.gov (United States)

Jääskeläinen, Iiro P.; Ahveninen, Jyrki

2014-01-01

The ability to concentrate on relevant sounds in the acoustic environment is crucial for everyday function and communication. Converging lines of evidence suggests that transient functional changes in auditory-cortex neurons, “short-term plasticity”, might explain this fundamental function. Under conditions of strongly focused attention, enhanced processing of attended sounds can take place at very early latencies (~50 ms from sound onset) in primary auditory cortex and possibly even at earlier latencies in subcortical structures. More robust selective-attention short-term plasticity is manifested as modulation of responses peaking at ~100 ms from sound onset in functionally specialized nonprimary auditory-cortical areas by way of stimulus-specific reshaping of neuronal receptive fields that supports filtering of selectively attended sound features from task-irrelevant ones. Such effects have been shown to take effect in ~seconds following shifting of attentional focus. There are findings suggesting that the reshaping of neuronal receptive fields is even stronger at longer auditory-cortex response latencies (~300 ms from sound onset). These longer-latency short-term plasticity effects seem to build up more gradually, within tens of seconds after shifting the focus of attention. Importantly, some of the auditory-cortical short-term plasticity effects observed during selective attention predict enhancements in behaviorally measured sound discrimination performance. PMID:24551458

Short-Term Effects of Midseason Coach Turnover on Team Performance in Soccer

Science.gov (United States)

Balduck, Anne-Line; Buelens, Marc; Philippaerts, Renaat

2010-01-01

The present study addressed the issue of short-term performance effects of midseason coach turnover in soccer. The goal of this study was to examine this effect on subsequent short-term team performance. The purposes of this study were to (a) examine whether midseason coach turnover improved results in the short term, and (b) examine how team…

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.

The Short-Term Power Load Forecasting Based on Sperm Whale Algorithm and Wavelet Least Square Support Vector Machine with DWT-IR for Feature Selection

Directory of Open Access Journals (Sweden)

Jin-peng Liu

2017-07-01

Full Text Available Short-term power load forecasting is an important basis for the operation of integrated energy system, and the accuracy of load forecasting directly affects the economy of system operation. To improve the forecasting accuracy, this paper proposes a load forecasting system based on wavelet least square support vector machine and sperm whale algorithm. Firstly, the methods of discrete wavelet transform and inconsistency rate model (DWT-IR are used to select the optimal features, which aims to reduce the redundancy of input vectors. Secondly, the kernel function of least square support vector machine LSSVM is replaced by wavelet kernel function for improving the nonlinear mapping ability of LSSVM. Lastly, the parameters of W-LSSVM are optimized by sperm whale algorithm, and the short-term load forecasting method of W-LSSVM-SWA is established. Additionally, the example verification results show that the proposed model outperforms other alternative methods and has a strong effectiveness and feasibility in short-term power load forecasting.

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

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

Directory of Open Access Journals (Sweden)

T.N. Hmylova

2008-06-01

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

FFT transformed quantitative EEG analysis of short term memory load.

Science.gov (United States)

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

2015-07-01

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

Effects of Brain-Based Learning Approach on Students' Motivation and Attitudes Levels in Science Class

Science.gov (United States)

Akyurek, Erkan; Afacan, Ozlem

2013-01-01

The purpose of the study was to examine the effect of brain-based learning approach on attitudes and motivation levels in 8th grade students' science classes. The main reason for examining attitudes and motivation levels, the effect of the short-term motivation, attitude shows the long-term effect. The pre/post-test control group research model…

An ethics curriculum for short-term global health trainees

OpenAIRE

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

2013-01-01

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

Narcissism and the Strategic Pursuit of Short-Term Mating

DEFF Research Database (Denmark)

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

2017-01-01

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

Cash Management and Short-Term Investments for Colleges and Universities.

Science.gov (United States)

Haag, Leonard H.

Effective cash management and short-term investing are discussed in this "how to" guide designed to benefit most institutions of higher education. The following premises are examined: proper compensation for effective cash management is not an expense but an investment; effective cash management and short-term investment programs do not depend on…

Language Identification in Short Utterances Using Long Short-Term Memory (LSTM) Recurrent Neural Networks.

Science.gov (United States)

Zazo, Ruben; Lozano-Diez, Alicia; Gonzalez-Dominguez, Javier; Toledano, Doroteo T; Gonzalez-Rodriguez, Joaquin

2016-01-01

Long Short Term Memory (LSTM) Recurrent Neural Networks (RNNs) have recently outperformed other state-of-the-art approaches, such as i-vector and Deep Neural Networks (DNNs), in automatic Language Identification (LID), particularly when dealing with very short utterances (∼3s). In this contribution we present an open-source, end-to-end, LSTM RNN system running on limited computational resources (a single GPU) that outperforms a reference i-vector system on a subset of the NIST Language Recognition Evaluation (8 target languages, 3s task) by up to a 26%. This result is in line with previously published research using proprietary LSTM implementations and huge computational resources, which made these former results hardly reproducible. Further, we extend those previous experiments modeling unseen languages (out of set, OOS, modeling), which is crucial in real applications. Results show that a LSTM RNN with OOS modeling is able to detect these languages and generalizes robustly to unseen OOS languages. Finally, we also analyze the effect of even more limited test data (from 2.25s to 0.1s) proving that with as little as 0.5s an accuracy of over 50% can be achieved.

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.

Short-term and long-term plasticity interaction in human primary motor cortex.

Science.gov (United States)

Iezzi, Ennio; Suppa, Antonio; Conte, Antonella; Li Voti, Pietro; Bologna, Matteo; Berardelli, Alfredo

2011-05-01

Repetitive transcranial magnetic stimulation (rTMS) over primary motor cortex (M1) elicits changes in motor evoked potential (MEP) size thought to reflect short- and long-term forms of synaptic plasticity, resembling short-term potentiation (STP) and long-term potentiation/depression (LTP/LTD) observed in animal experiments. We designed this study in healthy humans to investigate whether STP as elicited by 5-Hz rTMS interferes with LTP/LTD-like plasticity induced by intermittent and continuous theta-burst stimulation (iTBS and cTBS). The effects induced by 5-Hz rTMS and iTBS/cTBS were indexed as changes in MEP size. We separately evaluated changes induced by 5-Hz rTMS, iTBS and cTBS applied alone and those induced by iTBS and cTBS delivered after priming 5-Hz rTMS. Interactions between 5-Hz rTMS and iTBS/cTBS were investigated under several experimental conditions by delivering 5-Hz rTMS at suprathreshold and subthreshold intensity, allowing 1 and 5 min intervals to elapse between 5-Hz rTMS and TBS, and delivering one and ten 5-Hz rTMS trains. We also investigated whether 5-Hz rTMS induces changes in intracortical excitability tested with paired-pulse transcranial magnetic stimulation. When given alone, 5-Hz rTMS induced short-lasting and iTBS/cTBS induced long-lasting changes in MEP amplitudes. When M1 was primed with 10 suprathreshold 5-Hz rTMS trains at 1 min before iTBS or cTBS, the iTBS/cTBS-induced after-effects disappeared. The 5-Hz rTMS left intracortical excitability unchanged. We suggest that STP elicited by suprathreshold 5-Hz rTMS abolishes iTBS/cTBS-induced LTP/LTD-like plasticity through non-homeostatic metaplasticity mechanisms. Our study provides new information on interactions between short-term and long-term rTMS-induced plasticity in human M1. © 2011 The Authors. European Journal of Neuroscience © 2011 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Short-term water-based aerobic training promotes improvements in aerobic conditioning parameters of mature women.

Science.gov (United States)

Costa, Rochelle Rocha; Reichert, Thais; Coconcelli, Leandro; Simmer, Nicole Monticelli; Bagatini, Natália Carvalho; Buttelli, Adriana Cristine Koch; Bracht, Cláudia Gomes; Stein, Ricardo; Kruel, Luiz Fernando Martins

2017-08-01

Aging is accompanied by a decrease in aerobic capacity. Therefore, physical training has been recommended to soften the effects of advancement age. The aim of this study was to assess the effects of a short-term water-based aerobic training on resting heart rate (HR rest ), heart rate corresponding to anaerobic threshold (HR AT ), peak heart rate (HR peak ), percentage value of HR AT in relation to HR peak and test duration (TD) of mature women. Twenty-two women (65.91 ± 4.83 years) were submitted to a five-week water-based interval aerobic training. Aerobic capacity parameters were evaluated through an aquatic incremental test. After training, there was an increase in TD (16%) and HR AT percentage in relation to HR peak (4.68%), and a reduction of HR rest (9%). It is concluded that a water-based aerobic interval training prescribed through HR AT of only five weeks is able to promote improvements in aerobic capacity of mature women. Copyright © 2017 Elsevier Ltd. All rights reserved.

Short- and long-term reproducibility of radioisotopic examination of gastric emptying

Energy Technology Data Exchange (ETDEWEB)

Jonderko, K. (Silesian School of Medicine, Katowice (Poland). Dept. of Gastroenterology)

1990-01-01

Reproducibility of gastric emptying (GE) of a radiolabelled solid meal was assessed. The short-term reproducibility was evaluated on the basis of 12 paired GE examinations performed 1-3 days apart. Twelve paired GE examinations taken 3-8 months apart enabled long-term reproducibility assessment. Reproducibility of GE parameters was expressed in terms of the coefficient of variation, CV. No significant between-day variation of solid GE was found either regarding the short-term or the long-term reproducibility. Although slightly higher CV values characterized the long-term reproducibility of the GE parameters considered, the variations of the differences between repeated GE examinations did not differ significantly between short- and long-term GE reproducibility. The results obtained justify the use of radioisotopic GE measurement for the assessment of early and late results of pharmacologic or surgical management. (author).

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 impact of deep sand extraction and ecosystem-based landscaping on macrozoobenthos and sediment characteristics.

Science.gov (United States)

de Jong, Maarten F; Baptist, Martin J; Lindeboom, Han J; Hoekstra, Piet

2015-08-15

We studied short-term changes in macrozoobenthos in a 20m deep borrow pit. A boxcorer was used to sample macrobenthic infauna and a bottom sledge was used to sample macrobenthic epifauna. Sediment characteristics were determined from the boxcore samples, bed shear stress and near-bed salinity were estimated with a hydrodynamic model. Two years after the cessation of sand extraction, macrozoobenthic biomass increased fivefold in the deepest areas. Species composition changed significantly and white furrow shell (Abra alba) became abundant. Several sediment characteristics also changed significantly in the deepest parts. Macrozoobenthic species composition and biomass significantly correlated with time after cessation of sand extraction, sediment and hydrographical characteristics. Ecosystem-based landscaped sand bars were found to be effective in influencing sediment characteristics and macrozoobenthic assemblage. Significant changes in epifauna occurred in deepest parts in 2012 which coincided with the highest sedimentation rate. We recommend continuing monitoring to investigate medium and long-term impacts. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Persistent long-term facilitation at an identified synapse becomes labile with activation of short-term heterosynaptic plasticity.

Science.gov (United States)

Hu, Jiang-Yuan; Schacher, Samuel

2014-04-02

Short-term and long-term synaptic plasticity are cellular correlates of learning and memory of different durations. Little is known, however, how these two forms of plasticity interact at the same synaptic connection. We examined the reciprocal impact of short-term heterosynaptic or homosynaptic plasticity at sensorimotor synapses of Aplysia in cell culture when expressing persistent long-term facilitation (P-LTF) evoked by serotonin [5-hydroxytryptamine (5-HT)]. Short-term heterosynaptic plasticity induced by 5-HT (facilitation) or the neuropeptide FMRFa (depression) and short-term homosynaptic plasticity induced by tetanus [post-tetanic potentiation (PTP)] or low-frequency stimulation [homosynaptic depression (HSD)] of the sensory neuron were expressed in both control synapses and synapses expressing P-LTF in the absence or presence of protein synthesis inhibitors. All forms of short-term plasticity failed to significantly affect ongoing P-LTF in the absence of protein synthesis inhibitors. However, P-LTF reversed to control levels when either 5-HT or FMRFa was applied in the presence of rapamycin. In contrast, P-LTF was unaffected when either PTP or HSD was evoked in the presence of either rapamycin or anisomycin. These results indicate that synapses expressing persistent plasticity acquire a "new" baseline and functionally express short-term changes as naive synapses, but the new baseline becomes labile following selective activations-heterosynaptic stimuli that evoke opposite forms of plasticity-such that when presented in the presence of protein synthesis inhibitors produce a rapid reversal of the persistent plasticity. Activity-selective induction of a labile state at synapses expressing persistent plasticity may facilitate the development of therapies for reversing inappropriate memories.

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

Science.gov (United States)

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

2017-04-01

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

Behavioural Models of Motor Control and Short-Term Memory

OpenAIRE

Imanaka, Kuniyasu; Funase, Kozo; Yamauchi, Masaki

1995-01-01

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

Gummed-up memory: Chewing gum impairs short-term recall

OpenAIRE

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

2012-01-01

Several studies have suggested that short-term memory is generally improved by chewing gum. However, we report the first studies to show that chewing gum impairs short-term memory for both item order and item identity. Experiment 1 showed that chewing gum reduces serial recall of letter lists. Experiment 2 indicated that chewing does not simply disrupt vocal-articulatory planning required for order retention: Chewing equally impairs a matched task that required retention of list item identity...

[Development and short-term effects of a standardized patient education program for in-patient cardiologic rehabilitation].

Science.gov (United States)

Seekatz, B; Haug, G; Mosler, G; Schwaab, B; Altstidl, R; Worringen, U; Faller, H; Meng, K

2013-10-01

Patient education is an essential part in the treatment of coronary heart disease in medical rehabilitation. In the German-speaking area, no standardized and evaluated patient education program for coronary heart disease is available so far. In this paper, we demonstrate the development of a quality assured patient education program based on a health-education program of the German statutory pension insurance scheme. In a multi-level approach, an existing program was modified concerning treatment evidence, practical guidelines, theories of health and illness behavior and quality criteria for patient education as well as clinical experience and thereafter manualized. In a formative evaluation, feasibility and patient acceptance of this modified program were assessed using evaluation questionnaires of patients and trainers. Afterwards, effects of the patient education program as compared to a traditional education program were assessed on a short-term (at discharge), medium-term (6-month follow-up) and long-term (12-month follow-up) basis in a multicenter quasi-experimental control group study of patients with coronary heart disease (n=434). Results of the formative evaluation demonstrate an overall good acceptance and a good feasibility of the manualized program. Short-term results show a significant small treatment effect in the primary outcome variable patients' knowledge (p=0.001, η2 =0.028). Furthermore, small effects were also observed among some secondary outcomes, such as attitude towards medication, planning of physical activity, psychological quality of life and satisfaction with the education program. A standardized education program for patients with coronary heart disease has been developed in a systematic process based on established quality standards. Depending on the outstanding medium and long-term effects, the program may be recommended for general use in medical rehabilitation. The manual provides the prerequisites allowing for a successful

Multi-Temporal Land Cover Classification with Long Short-Term Memory Neural Networks

Science.gov (United States)

Rußwurm, M.; Körner, M.

2017-05-01

Land cover classification (LCC) is a central and wide field of research in earth observation and has already put forth a variety of classification techniques. Many approaches are based on classification techniques considering observation at certain points in time. However, some land cover classes, such as crops, change their spectral characteristics due to environmental influences and can thus not be monitored effectively with classical mono-temporal approaches. Nevertheless, these temporal observations should be utilized to benefit the classification process. After extensive research has been conducted on modeling temporal dynamics by spectro-temporal profiles using vegetation indices, we propose a deep learning approach to utilize these temporal characteristics for classification tasks. In this work, we show how long short-term memory (LSTM) neural networks can be employed for crop identification purposes with SENTINEL 2A observations from large study areas and label information provided by local authorities. We compare these temporal neural network models, i.e., LSTM and recurrent neural network (RNN), with a classical non-temporal convolutional neural network (CNN) model and an additional support vector machine (SVM) baseline. With our rather straightforward LSTM variant, we exceeded state-of-the-art classification performance, thus opening promising potential for further research.

MULTI-TEMPORAL LAND COVER CLASSIFICATION WITH LONG SHORT-TERM MEMORY NEURAL NETWORKS

Directory of Open Access Journals (Sweden)

M. Rußwurm

2017-05-01

Full Text Available Land cover classification (LCC is a central and wide field of research in earth observation and has already put forth a variety of classification techniques. Many approaches are based on classification techniques considering observation at certain points in time. However, some land cover classes, such as crops, change their spectral characteristics due to environmental influences and can thus not be monitored effectively with classical mono-temporal approaches. Nevertheless, these temporal observations should be utilized to benefit the classification process. After extensive research has been conducted on modeling temporal dynamics by spectro-temporal profiles using vegetation indices, we propose a deep learning approach to utilize these temporal characteristics for classification tasks. In this work, we show how long short-term memory (LSTM neural networks can be employed for crop identification purposes with SENTINEL 2A observations from large study areas and label information provided by local authorities. We compare these temporal neural network models, i.e., LSTM and recurrent neural network (RNN, with a classical non-temporal convolutional neural network (CNN model and an additional support vector machine (SVM baseline. With our rather straightforward LSTM variant, we exceeded state-of-the-art classification performance, thus opening promising potential for further research.

Managing long-term polycyclic aromatic hydrocarbon contaminated soils: a risk-based approach.

Science.gov (United States)

Duan, Luchun; Naidu, Ravi; Thavamani, Palanisami; Meaklim, Jean; Megharaj, Mallavarapu

2015-06-01

Polycyclic aromatic hydrocarbons (PAHs) are a family of contaminants that consist of two or more aromatic rings fused together. Soils contaminated with PAHs pose significant risk to human and ecological health. Over the last 50 years, significant research has been directed towards the cleanup of PAH-contaminated soils to background level. However, this achieved only limited success especially with high molecular weight compounds. Notably, during the last 5-10 years, the approach to remediate PAH-contaminated soils has changed considerably. A risk-based prioritization of remediation interventions has become a valuable step in the management of contaminated sites. The hydrophobicity of PAHs underlines that their phase distribution in soil is strongly influenced by factors such as soil properties and ageing of PAHs within the soil. A risk-based approach recognizes that exposure and environmental effects of PAHs are not directly related to the commonly measured total chemical concentration. Thus, a bioavailability-based assessment using a combination of chemical analysis with toxicological assays and nonexhaustive extraction technique would serve as a valuable tool in risk-based approach for remediation of PAH-contaminated soils. In this paper, the fate and availability of PAHs in contaminated soils and their relevance to risk-based management of long-term contaminated soils are reviewed. This review may serve as guidance for the use of site-specific risk-based management methods.

Examining the Contemporaneous, Short-Term, and Long-Term Effects of Secondary Exposure to Violence on Adolescent Substance Use.

Science.gov (United States)

Zimmerman, Gregory M; Kushner, Mackenzie

2017-09-01

The relationship between secondary exposure to violence-defined as witnessing violence in the home, community, or school-and adolescent substance use is well-documented. Yet, multi-wave empirical studies examining this relationship are sparse. In addition, studies have only begun to examine whether this relationship varies by the situational components of the violent event. Using data from the Project on Human Development in Chicago Neighborhoods (PHDCN), this study examines the contemporaneous, short-term, and long-term effects of secondary exposure to violence on substance use, and whether witnessing violence in which a weapon is present has a different impact on adolescent substance use than does witnessing violence without a weapon. Hierarchical logistic regression models on a racially and ethnically diverse sample of 1670 youth (51.5% female) residing in 79 neighborhoods indicated that: (1) the effects of secondary exposure to violence on alcohol and marijuana use were enduring, albeit attenuated, over time; (2) the effect of secondary exposure to violence on illicit drug use was suppressed in the short-term but significant in the long-term; (3) witnessing violence without a weapon was salient for alcohol and marijuana use at all time points; and (4) witnessing violence with a weapon impacted illicit drug use in the long-term. The results suggest that addressing the consequences of secondary exposure to violence requires prolonged intervention efforts and that the study of secondary exposure to violence requires a more nuanced approach that accounts for situational aspects of the violent event.

Effect of acoustic similarity on short-term auditory memory in the monkey.

Science.gov (United States)

Scott, Brian H; Mishkin, Mortimer; Yin, Pingbo

2013-04-01

Recent evidence suggests that the monkey's short-term memory in audition depends on a passively retained sensory trace as opposed to a trace reactivated from long-term memory for use in working memory. Reliance on a passive sensory trace could render memory particularly susceptible to confusion between sounds that are similar in some acoustic dimension. If so, then in delayed matching-to-sample, the monkey's performance should be predicted by the similarity in the salient acoustic dimension between the sample and subsequent test stimulus, even at very short delays. To test this prediction and isolate the acoustic features relevant to short-term memory, we examined the pattern of errors made by two rhesus monkeys performing a serial, auditory delayed match-to-sample task with interstimulus intervals of 1 s. The analysis revealed that false-alarm errors did indeed result from similarity-based confusion between the sample and the subsequent nonmatch stimuli. Manipulation of the stimuli showed that removal of spectral cues was more disruptive to matching behavior than removal of temporal cues. In addition, the effect of acoustic similarity on false-alarm response was stronger at the first nonmatch stimulus than at the second one. This pattern of errors would be expected if the first nonmatch stimulus overwrote the sample's trace, and suggests that the passively retained trace is not only vulnerable to similarity-based confusion but is also highly susceptible to overwriting. Copyright © 2013 Elsevier B.V. All rights reserved.

Assessing Tolerance-Based Robust Short-Term Load Forecasting in Buildings

Directory of Open Access Journals (Sweden)

Juan Prieto

2013-04-01

Full Text Available Short-term load forecasting (STLF in buildings differs from its broader counterpart in that the load to be predicted does not seem to be stationary, seasonal and regular but, on the contrary, it may be subject to sudden changes and variations on its consumption behaviour. Classical STLF methods do not react fast enough to these perturbations (i.e., they are not robust and the literature on building STLF has not yet explored this area. Hereby, we evaluate a well-known post-processing method (Learning Window Reinitialization applied to two broadly-used STLF algorithms (Autoregressive Model and Support Vector Machines in buildings to check their adaptability and robustness. We have tested the proposed method with real-world data and our results state that this methodology is especially suited for buildings with non-regular consumption profiles, as classical STLF methods are enough to model regular-profiled ones.

Short-term memory in the service of executive control functions

Directory of Open Access Journals (Sweden)

Farshad Alizadeh Mansouri

2015-12-01

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

Implicit short- and long-term memory direct our gaze in visual search.

Science.gov (United States)

Kruijne, Wouter; Meeter, Martijn

2016-04-01

Visual attention is strongly affected by the past: both by recent experience and by long-term regularities in the environment that are encoded in and retrieved from memory. In visual search, intertrial repetition of targets causes speeded response times (short-term priming). Similarly, targets that are presented more often than others may facilitate search, even long after it is no longer present (long-term priming). In this study, we investigate whether such short-term priming and long-term priming depend on dissociable mechanisms. By recording eye movements while participants searched for one of two conjunction targets, we explored at what stages of visual search different forms of priming manifest. We found both long- and short- term priming effects. Long-term priming persisted long after the bias was present, and was again found even in participants who were unaware of a color bias. Short- and long-term priming affected the same stage of the task; both biased eye movements towards targets with the primed color, already starting with the first eye movement. Neither form of priming affected the response phase of a trial, but response repetition did. The results strongly suggest that both long- and short-term memory can implicitly modulate feedforward visual processing.

Magnetic Tunnel Junction Based Long-Term Short-Term Stochastic Synapse for a Spiking Neural Network with On-Chip STDP Learning

Science.gov (United States)

Srinivasan, Gopalakrishnan; Sengupta, Abhronil; Roy, Kaushik

2016-07-01

Spiking Neural Networks (SNNs) have emerged as a powerful neuromorphic computing paradigm to carry out classification and recognition tasks. Nevertheless, the general purpose computing platforms and the custom hardware architectures implemented using standard CMOS technology, have been unable to rival the power efficiency of the human brain. Hence, there is a need for novel nanoelectronic devices that can efficiently model the neurons and synapses constituting an SNN. In this work, we propose a heterostructure composed of a Magnetic Tunnel Junction (MTJ) and a heavy metal as a stochastic binary synapse. Synaptic plasticity is achieved by the stochastic switching of the MTJ conductance states, based on the temporal correlation between the spiking activities of the interconnecting neurons. Additionally, we present a significance driven long-term short-term stochastic synapse comprising two unique binary synaptic elements, in order to improve the synaptic learning efficiency. We demonstrate the efficacy of the proposed synaptic configurations and the stochastic learning algorithm on an SNN trained to classify handwritten digits from the MNIST dataset, using a device to system-level simulation framework. The power efficiency of the proposed neuromorphic system stems from the ultra-low programming energy of the spintronic synapses.

Identity modulates short-term memory for facial emotion.

Science.gov (United States)

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

2009-12-01

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

A simulation approach for analysis of short-term security of natural gas supply in Colombia

International Nuclear Information System (INIS)

Villada, Juan; Olaya, Yris

2013-01-01

Achieving security of gas supply implies diversifying gas sources, while having enough supply, transportation, and storage capacity to meet demand peaks and supply interruptions. Devising a strategy for securing gas supply is not straightforward because gas supply depends on complex interactions of production, demand and infrastructure, and it is exposed to economic, regulatory, political, environmental and technical risks. To address this complexity, we propose a simulation approach that replicates the structure of the gas supply chain, including transportation constraints and demand fluctuations. We build and calibrate a computer model for the Colombian gas sector, and run the model to assess the impact of expanding transportation capacity and increasing market flexibility on the security of supply. Our analysis focuses on the operation and planned and proposed expansions of the transportation infrastructure because adequate regulation and development of this infrastructure can contribute to increase the security of supply in the gas sector. We find that proposed import facilities, specifically LNG import terminals at Buenaventura, increase system's security under the current market structure. - Highlights: ► We build a simulation model for analyzing natural gas trade in Colombia. ► The model captures the structure of the gas network and on market rules. ► We simulate investment decisions to increase short-term security of supply. ► Securing supply would need LNG imports and expansion of pipeline capacity.

Risk-based approach to long-term safety assessment for near surface disposal of radioactive waste in Korea

International Nuclear Information System (INIS)

Jeong, C.W.; Kim, K.I.; Lee, J.I.

2000-01-01

This paper presents the Korean regulatory approach to safety assessment consistent with probabilistic, risk-based long-term safety requirements for near surface disposal facilities. The approach is based on: (1) From the standpoint of risk limitation, normal processes and probabilistic disruptive events should be integrated in a similar manner in terms of potential exposures; and (2) The uncertainties inherent in the safety assessment should be reduced using appropriate exposure scenarios. In addition, this paper emphasizes the necessity of international guidance for quantifying potential exposures and the corresponding risks from radioactive waste disposal. (author)

Parallel Multi-Objective Genetic Algorithm for Short-Term Economic Environmental Hydrothermal Scheduling

Directory of Open Access Journals (Sweden)

Zhong-Kai Feng

2017-01-01

Full Text Available With the increasingly serious energy crisis and environmental pollution, the short-term economic environmental hydrothermal scheduling (SEEHTS problem is becoming more and more important in modern electrical power systems. In order to handle the SEEHTS problem efficiently, the parallel multi-objective genetic algorithm (PMOGA is proposed in the paper. Based on the Fork/Join parallel framework, PMOGA divides the whole population of individuals into several subpopulations which will evolve in different cores simultaneously. In this way, PMOGA can avoid the wastage of computational resources and increase the population diversity. Moreover, the constraint handling technique is used to handle the complex constraints in SEEHTS, and a selection strategy based on constraint violation is also employed to ensure the convergence speed and solution feasibility. The results from a hydrothermal system in different cases indicate that PMOGA can make the utmost of system resources to significantly improve the computing efficiency and solution quality. Moreover, PMOGA has competitive performance in SEEHTS when compared with several other methods reported in the previous literature, providing a new approach for the operation of hydrothermal systems.

Long-Term Capital Goods Importation and Minimum Wage Relationship in Turkey: Bounds Testing Approach

Directory of Open Access Journals (Sweden)

Tastan Serkan

2015-04-01

Full Text Available In order to examine the long-term relationship between capital goods importation and minimum wage, autoregressive distributed lag (ARDL bounds testing approach to the cointegration is used in the study. According to bounds test results, a cointegration relation exists between the capital goods importation and the minimum wage. Therefore an ARDL(4,0 model is estimated in order to determine the long and short term relations between variables. According to the empirical analysis, there is a positive and significant relationship between the capital goods importation and the minimum wage in Turkey in the long term. A 1% increase in the minimum wage leads to a 0.8% increase in the capital goods importation in the long term. The result is similar for short term coefficients. The relationship observed in the long term is preserved in short term, though in a lower level. In terms of error correction model, it can be concluded that error correction mechanism works as the error correction term is negative and significant. Short term deviations might be resolved with the error correction mechanism in the long term. Accordingly, approximately 75% of any deviation from equilibrium which might arise in the previous six month period will be resolved in the current six month period. This means that returning to long term equilibrium progresses rapidly.

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.

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

Directory of Open Access Journals (Sweden)

Chen Wang

2016-01-01

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

Facilitating long-term changes in student approaches to learning science.

Science.gov (United States)

Buchwitz, Brian J; Beyer, Catharine H; Peterson, Jon E; Pitre, Emile; Lalic, Nevena; Sampson, Paul D; Wakimoto, Barbara T

2012-01-01

Undergraduates entering science curricula differ greatly in individual starting points and learning needs. The fast pace, high enrollment, and high stakes of introductory science courses, however, limit students' opportunities to self-assess and modify learning strategies. The University of Washington's Biology Fellows Program (BFP) intervenes through a 20-session, premajors course that introduces students to the rigor expected of bioscience majors and assists their development as science learners. This study uses quantitative and qualitative approaches to assess whether the 2007-2009 BFP achieved its desired short- and long-term impacts on student learning. Adjusting for differences in students' high school grade point average and Scholastic Aptitude Test scores, we found that participation in the BFP was associated with higher grades in two subsequent gateway biology courses, across multiple quarters and instructors. Two to 4 yr after participating in the program, students attributed changes in how they approached learning science to BFP participation. They reported having learned to "think like a scientist" and to value active-learning strategies and learning communities. In addition, they reported having developed a sense of belonging in bioscience communities. The achievement of long-term impacts for a short-term instructional investment suggests a practical means to prepare diverse students for the rigors of science curricula.

Randomized controlled trial evaluating the temporal effects of high-intensity exercise on learning, short-term and long-term memory, and prospective memory.

Science.gov (United States)

Frith, Emily; Sng, Eveleen; Loprinzi, Paul D

2017-11-01

The broader purpose of this study was to examine the temporal effects of high-intensity exercise on learning, short-term and long-term retrospective memory and prospective memory. Among a sample of 88 young adult participants, 22 were randomized into one of four different groups: exercise before learning, control group, exercise during learning, and exercise after learning. The retrospective assessments (learning, short-term and long-term memory) were assessed using the Rey Auditory Verbal Learning Test. Long-term memory including a 20-min and 24-hr follow-up assessment. Prospective memory was assessed using a time-based procedure by having participants contact (via phone) the researchers at a follow-up time period. The exercise stimulus included a 15-min bout of progressive maximal exertion treadmill exercise. High-intensity exercise prior to memory encoding (vs. exercise during memory encoding or consolidation) was effective in enhancing long-term memory (for both 20-min and 24-h follow-up assessments). We did not observe a differential temporal effect of high-intensity exercise on short-term memory (immediate post-memory encoding), learning or prospective memory. The timing of high-intensity exercise may play an important role in facilitating long-term memory. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

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

Science.gov (United States)

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

2006-01-01

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

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 and long-term memory in early temporal lobe dysfunction.

Science.gov (United States)

Hershey, T; Craft, S; Glauser, T A; Hale, S

1998-01-01

Following medial temporal damage, mature humans are impaired in retaining new information over long delays but not short delays. The question of whether a similar dissociation occurs in children was addressed by testing children (ages 7-16) with unilateral temporal lobe epilepsy (TLE) and controls on short- and long-term memory tasks, including a spatial delayed response task (SDR). Early-onset TLE did not affect performance on short delays on SDR, but it did impair performance at the longest delay (60 s), similar to adults with unilateral medial temporal damage. In addition, early-onset TLE affected performance on pattern recall, spatial span, and verbal span with rehearsal interference. No differences were found on story recall or on a response inhibition task.

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

Science.gov (United States)

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

2015-01-01

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

Stochastic Optimal Wind Power Bidding Strategy in Short-Term Electricity Market

DEFF Research Database (Denmark)

Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte

2012-01-01

Due to the fluctuating nature and non-perfect forecast of the wind power, the wind power owners are penalized for the imbalance costs of the regulation, when they trade wind power in the short-term liberalized electricity market. Therefore, in this paper a formulation of an imbalance cost...... minimization problem for trading wind power in the short-term electricity market is described, to help the wind power owners optimize their bidding strategy. Stochastic optimization and a Monte Carlo method are adopted to find the optimal bidding strategy for trading wind power in the short-term electricity...... market in order to deal with the uncertainty of the regulation price, the activated regulation of the power system and the forecasted wind power generation. The Danish short-term electricity market and a wind farm in western Denmark are chosen as study cases due to the high wind power penetration here...

Differences in the verbal fluency, working memory and executive functions in alcoholics: Short-term vs. long-term abstainers.

Science.gov (United States)

Nowakowska-Domagała, Katarzyna; Jabłkowska-Górecka, Karolina; Mokros, Łukasz; Koprowicz, Jacek; Pietras, Tadeusz

2017-03-01

The aim of the study was to assess differences in verbal fluency, working memory and executive functions in two subgroups of alcohol-dependent patients, those undergoing short-term abstinence (STA) and those undergoing long-term abstinence (LTA), and to compare the level of cognitive functions in patients after long-term abstinence with healthy subjects. The study group consisted of 106 alcohol-dependent patients (53 immediately after drinking at least 3 days and 53 after at least one-year abstinence). The control group comprised 53 subjects, whose age, sex and education levels matched those of the patients in the experimental group. The dependence intensity was assessed using SADD and MAST scales. The neuropsychological assessment was based on the FAS Test, Stroop Test and TMT A&B Test. The results obtained for alcohol-dependent patients revealed significant disturbances of cognitive functions. Such results indicate the presence of severe frontal cerebral cortex dysfunctions. Frontal cortex dysfunctions affecting the verbal fluency and working memory subsystems and the executive functions also persisted during long-term abstinence periods. No significant correlations between the duration of dependence, quantity of alcohol consumed and efficiency of the working memory and executive functions were observed in alcohol-dependent subjects after short-term or long-term abstinence. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

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.

Visual dot interaction with short-term memory.

Science.gov (United States)

Etindele Sosso, Faustin Armel

2017-06-01

Many neurodegenerative diseases have a memory component. Brain structures related to memory are affected by environmental stimuli, and it is difficult to dissociate effects of all behavior of neurons. Here, visual cortex of mice was stimulated with gratings and dot, and an observation of neuronal activity before and after was made. Bandwidth, firing rate and orientation selectivity index were evaluated. A primary communication between primary visual cortex and short-term memory appeared to show an interesting path to train cognitive circuitry and investigate the basics mechanisms of the neuronal learning. The findings also suggested the interplay between primary visual cortex and short-term plasticity. The properties inside a visual target shape the perception and affect the basic encoding. Using visual cortex, it may be possible to train the memory and improve the recovery of people with cognitive disabilities or memory deficit.

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

Directory of Open Access Journals (Sweden)

Shiva Pouradeli

2016-12-01

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

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

Science.gov (United States)

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

2014-09-01

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

Short-Term Memory in Habituation and Dishabituation

Science.gov (United States)

Whitlow, Jesse William, Jr.

1975-01-01

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

Economics of solar energy: Short term costing

Science.gov (United States)

Klee, H.

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

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

Science.gov (United States)

Flegal, Kristin E; Reuter-Lorenz, Patricia A

2014-07-01

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

Short-term hydro generation scheduling of Three Gorges–Gezhouba cascaded hydropower plants using hybrid MACS-ADE approach

International Nuclear Information System (INIS)

Mo, Li; Lu, Peng; Wang, Chao; Zhou, Jianzhong

2013-01-01

Highlights: • MACS and ADE algorithms are hybridized as MACS-ADE method for solving STHGS problem. • An adaptive mutation is integrated into the proposed algorithm to avoid premature convergence. • MACS and ADE are run in parallel in search of better solution. • Several effective heuristic strategies are designed for dealing with various constraints of STHGS problem. - Abstract: Short-term hydro generation scheduling (STHGS) aims at determining optimal hydro generation scheduling to obtain minimum water consumption for one day or week while meeting various system constraints. In this paper, the STHGS problem is decomposed into two sub-problems: (i) unit commitment (UC) sub-problem; (ii) economic load dispatch (ELD) sub-problem. Then, we present a hybrid algorithm based on multi ant colony system (MACS) and differential evolution (DE) for solving the STHGS problem. First, MACS is used for dealing with UC sub-problem. A set of cooperating ant colonies cooperate to choose the unit state over the scheduled time horizon. Then, the adaptive differential evolution (ADE) is used to solve ELD sub-problem. MACS and ADE are run in parallel with adjusting their solutions in search of a better solution. Meanwhile, local and global pheromone updating rules in MACS and adaptive dynamic parameter adjusting strategy in DE are applied for enhancing the search ability of MACS-ADE. Finally, the proposed method is implemented to solve STHGS problem of Three Gorges–Gezhouba cascaded hydropower plants to verify the feasibility and effectiveness. Compared with other established methods, the simulation results reveal that the proposed MACS-ADE approach has the best convergence property, computational efficiency with less water consumption

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