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

NARCIS (Netherlands)

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

1998-01-01

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

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

Science.gov (United States)

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

2018-05-23

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

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

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.

A new methodology involving stable isotope tracer to compare short- and long- term selenium mobility in soils

Science.gov (United States)

Tolu, Julie; Thiry, Yves; Potin-gautier, Martine; Le hécho, Isabelle; Bueno, Maïté

2013-04-01

Selenium is an element of environmental concern given its dual beneficial and toxic character to animal and human health. Its radioactive isotope 79Se, a fission product of 235U, is considered critical in safety assessment of nuclear waste repositories in case of leakage and hypothetical soil contamination. Therefore, Se species transformations and interactions with soil components have to be clearly understood to predict its dispersion in the biosphere (e.g., accumulation in soils, migration to waters, transfer to living organisms). While natural Se interactions with soils run over centuries to millennia time scales, transformations and partitioning are generally studied with short-term experiments (often inferior to 1 month) after Se addition. The influence of slower, long-term processes involved in Se speciation and mobility in soils is thus not properly accounted for. We tested if using ambient Se would be relevant for long-term risk assessment while added Se would be more representative of short-term contamination impact. For that purpose, we developed a new methodology to trace the differential reactivity of ambient and spiked Se at trace level (µg kg-1) in soils. It combined the use of a stable isotopically enriched tracer with our previous published analytical method based on specific extractions and HPLC-ICP-MS to determine trace Se species partition in different soil phases. Given that soil extracts contains very high concentrations of various elements interfering Se (e.g., Fe, Cl, Br), the ICP-MS parameters and mathematical corrections were optimized to cope with such interferences. Following optimization, three correct and accurate (<2%) isotope ratios were obtained with 77Se, 78Se, 80Se and 82Se. The optimized method was then applied to an arable and a forest soil submitted to an aging process (drying/wetting cycles) during three months, to which 77Se(IV) was previously added. The results showed that ambient Se was at steady state in terms of water

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

DEFF Research Database (Denmark)

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

2008-01-01

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

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

Prediction of Sea Surface Temperature Using Long Short-Term Memory

Science.gov (United States)

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

2017-10-01

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

Human short-term spatial memory: precision predicts capacity.

Science.gov (United States)

Banta Lavenex, Pamela; Boujon, Valérie; Ndarugendamwo, Angélique; Lavenex, Pierre

2015-03-01

Here, we aimed to determine the capacity of human short-term memory for allocentric spatial information in a real-world setting. Young adults were tested on their ability to learn, on a trial-unique basis, and remember over a 1-min interval the location(s) of 1, 3, 5, or 7 illuminating pads, among 23 pads distributed in a 4m×4m arena surrounded by curtains on three sides. Participants had to walk to and touch the pads with their foot to illuminate the goal locations. In contrast to the predictions from classical slot models of working memory capacity limited to a fixed number of items, i.e., Miller's magical number 7 or Cowan's magical number 4, we found that the number of visited locations to find the goals was consistently about 1.6 times the number of goals, whereas the number of correct choices before erring and the number of errorless trials varied with memory load even when memory load was below the hypothetical memory capacity. In contrast to resource models of visual working memory, we found no evidence that memory resources were evenly distributed among unlimited numbers of items to be remembered. Instead, we found that memory for even one individual location was imprecise, and that memory performance for one location could be used to predict memory performance for multiple locations. Our findings are consistent with a theoretical model suggesting that the precision of the memory for individual locations might determine the capacity of human short-term memory for spatial information. Copyright © 2015 Elsevier Inc. All rights reserved.

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

Directory of Open Access Journals (Sweden)

Adam Mikus

2018-06-01

Full Text Available Technology driven interventions provide us with an increasing amount of fine-grained data about the patient. This data includes regular ecological momentary assessments (EMA but also response times to EMA questions by a user. When observing this data, we see a huge variation between the patterns exhibited by different patients. Some are more stable while others vary a lot over time. This poses a challenging problem for the domain of artificial intelligence and makes on wondering whether it is possible to predict the future mental state of a patient using the data that is available. In the end, these predictions could potentially contribute to interventions that tailor the feedback to the user on a daily basis, for example by warning a user that a fall-back might be expected during the next days, or by applying a strategy to prevent the fall-back from occurring in the first place.In this work, we focus on short term mood prediction by considering the adherence and usage data as an additional predictor. We apply recurrent neural networks to handle the temporal aspects best and try to explore whether individual, group level, or one single predictive model provides the highest predictive performance (measured using the root mean squared error (RMSE. We use data collected from patients from five countries who used the ICT4Depression/MoodBuster platform in the context of the EU E-COMPARED project. In total, we used the data from 143 patients (with between 9 and 425days of EMA data who were diagnosed with a major depressive disorder according to DSM-IV.Results show that we can make predictions of short term mood change quite accurate (ranging between 0.065 and 0.11. The past EMA mood ratings proved to be the most influential while adherence and usage data did not improve prediction accuracy. In general, group level predictions proved to be the most promising, however differences were not significant.Short term mood prediction remains a difficult task

Using predictive uncertainty analysis to optimise tracer test design and data acquisition

Science.gov (United States)

Wallis, Ilka; Moore, Catherine; Post, Vincent; Wolf, Leif; Martens, Evelien; Prommer, Henning

2014-07-01

Tracer injection tests are regularly-used tools to identify and characterise flow and transport mechanisms in aquifers. Examples of practical applications are manifold and include, among others, managed aquifer recharge schemes, aquifer thermal energy storage systems and, increasingly important, the disposal of produced water from oil and shale gas wells. The hydrogeological and geochemical data collected during the injection tests are often employed to assess the potential impacts of injection on receptors such as drinking water wells and regularly serve as a basis for the development of conceptual and numerical models that underpin the prediction of potential impacts. As all field tracer injection tests impose substantial logistical and financial efforts, it is crucial to develop a solid a-priori understanding of the value of the various monitoring data to select monitoring strategies which provide the greatest return on investment. In this study, we demonstrate the ability of linear predictive uncertainty analysis (i.e. “data worth analysis”) to quantify the usefulness of different tracer types (bromide, temperature, methane and chloride as examples) and head measurements in the context of a field-scale aquifer injection trial of coal seam gas (CSG) co-produced water. Data worth was evaluated in terms of tracer type, in terms of tracer test design (e.g., injection rate, duration of test and the applied measurement frequency) and monitoring disposition to increase the reliability of injection impact assessments. This was followed by an uncertainty targeted Pareto analysis, which allowed the interdependencies of cost and predictive reliability for alternative monitoring campaigns to be compared directly. For the evaluated injection test, the data worth analysis assessed bromide as superior to head data and all other tracers during early sampling times. However, with time, chloride became a more suitable tracer to constrain simulations of physical transport

VAN method of short-term earthquake prediction shows promise

Science.gov (United States)

Uyeda, Seiya

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

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

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.

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

Four Examples of Short-Term and Imminent Prediction of Earthquakes

Science.gov (United States)

zeng, zuoxun; Liu, Genshen; Wu, Dabin; Sibgatulin, Victor

2014-05-01

We show here 4 examples of short-term and imminent prediction of earthquakes in China last year. They are Nima Earthquake(Ms5.2), Minxian Earthquake(Ms6.6), Nantou Earthquake (Ms6.7) and Dujiangyan Earthquake (Ms4.1) Imminent Prediction of Nima Earthquake(Ms5.2) Based on the comprehensive analysis of the prediction of Victor Sibgatulin using natural electromagnetic pulse anomalies and the prediction of Song Song and Song Kefu using observation of a precursory halo, and an observation for the locations of a degasification of the earth in the Naqu, Tibet by Zeng Zuoxun himself, the first author made a prediction for an earthquake around Ms 6 in 10 days in the area of the degasification point (31.5N, 89.0 E) at 0:54 of May 8th, 2013. He supplied another degasification point (31N, 86E) for the epicenter prediction at 8:34 of the same day. At 18:54:30 of May 15th, 2013, an earthquake of Ms5.2 occurred in the Nima County, Naqu, China. Imminent Prediction of Minxian Earthquake (Ms6.6) At 7:45 of July 22nd, 2013, an earthquake occurred at the border between Minxian and Zhangxian of Dingxi City (34.5N, 104.2E), Gansu province with magnitude of Ms6.6. We review the imminent prediction process and basis for the earthquake using the fingerprint method. 9 channels or 15 channels anomalous components - time curves can be outputted from the SW monitor for earthquake precursors. These components include geomagnetism, geoelectricity, crust stresses, resonance, crust inclination. When we compress the time axis, the outputted curves become different geometric images. The precursor images are different for earthquake in different regions. The alike or similar images correspond to earthquakes in a certain region. According to the 7-year observation of the precursor images and their corresponding earthquake, we usually get the fingerprint 6 days before the corresponding earthquakes. The magnitude prediction needs the comparison between the amplitudes of the fingerpringts from the same

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

International Nuclear Information System (INIS)

Chen, Kuilin; Yu, Jie

2014-01-01

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

Perceived stress and anhedonia predict short-and long-term weight change, respectively, in healthy adults.

Science.gov (United States)

Ibrahim, Mostafa; Thearle, Marie S; Krakoff, Jonathan; Gluck, Marci E

2016-04-01

Perceived stress; emotional eating; anhedonia; depression and dietary restraint, hunger, and disinhibition have been studied as risk factors for obesity. However, the majority of studies have been cross-sectional and the directionality of these relationships remains unclear. In this longitudinal study, we assess their impact on future weight change. Psychological predictors of weight change in short- (6month) and long-term (>1year) periods were studied in 65 lean and obese individuals in two cohorts. Subjects participated in studies of food intake and metabolism that did not include any type of medication or weight loss interventions. They completed psychological questionnaires at baseline and weight change was monitored at follow-up visits. At six months, perceived stress predicted weight gain (r(2)=0.23, P=0.02). There was a significant interaction (r(2)=.38, P=0.009) between perceived stress and positive emotional eating, such that higher scores in both predicted greater weight gain, while those with low stress but high emotional eating scores lost weight. For long-term, higher anhedonia scores predicted weight gain (r(2)=0.24, P=0.04). Depression moderated these effects such that higher scores in both predicted weight gain but higher depression and lower anhedonia scores predicted weight loss. There are different behavioral determinants for short- and long-term weight change. Targeting perceived stress may help with short-term weight loss while depression and anhedonia may be better targets for long-term weight regulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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

2017-05-01

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

Development of in-vessel source term analysis code, tracer

International Nuclear Information System (INIS)

Miyagi, K.; Miyahara, S.

1996-01-01

Analyses of radionuclide transport in fuel failure accidents (generally referred to source terms) are considered to be important especially in the severe accident evaluation. The TRACER code has been developed to realistically predict the time dependent behavior of FPs and aerosols within the primary cooling system for wide range of fuel failure events. This paper presents the model description, results of validation study, the recent model advancement status of the code, and results of check out calculations under reactor conditions. (author)

Short Term Prediction of PM10 Concentrations Using Seasonal Time Series Analysis

Directory of Open Access Journals (Sweden)

Hamid Hazrul Abdul

2016-01-01

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

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.

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.

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

International Nuclear Information System (INIS)

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

2004-01-01

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

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

Science.gov (United States)

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

2018-05-01

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

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

Directory of Open Access Journals (Sweden)

K. Chen

2016-06-01

Full Text Available Short-term precipitation commonly occurs in south part of China, which brings intensive precipitation in local region for very short time. Massive water would cause the intensive flood inside of city when precipitation amount beyond the capacity of city drainage system. Thousands people’s life could be influenced by those short-term disasters and the higher city managements are required to facing these challenges. How to predict the occurrence of heavy precipitation accurately is one of the worthwhile scientific questions in meteorology. According to recent studies, the accuracy of short-term precipitation prediction based on numerical simulation model still remains low reliability, in some area where lack of local observations, the accuracy may be as low as 10%. The methodology for short term precipitation occurrence prediction still remains a challenge. In this paper, a machine learning method based on SVM was presented to predict short-term precipitation occurrence by using FY2-G satellite imagery and ground in situ observation data. The results were validated by traditional TS score which commonly used in evaluation of weather prediction. The results indicate that the proposed algorithm can present overall accuracy up to 90% for one-hour to six-hour forecast. The result implies the prediction accuracy could be improved by using machine learning method combining with satellite image. This prediction model can be further used to evaluated to predicted other characteristics of weather in Shenzhen in future.

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

DEFF Research Database (Denmark)

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

2012-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2008-08-15

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

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

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

Science.gov (United States)

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

2012-01-29

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

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

International Nuclear Information System (INIS)

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

2011-01-01

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

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

Science.gov (United States)

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

2014-07-01

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

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 ...

Discrete fracture modelling for the Stripa tracer validation experiment predictions

International Nuclear Information System (INIS)

Dershowitz, W.; Wallmann, P.

1992-02-01

Groundwater flow and transport through three-dimensional networks of discrete fractures was modeled to predict the recovery of tracer from tracer injection experiments conducted during phase 3 of the Stripa site characterization and validation protect. Predictions were made on the basis of an updated version of the site scale discrete fracture conceptual model used for flow predictions and preliminary transport modelling. In this model, individual fractures were treated as stochastic features described by probability distributions of geometric and hydrologic properties. Fractures were divided into three populations: Fractures in fracture zones near the drift, non-fracture zone fractures within 31 m of the drift, and fractures in fracture zones over 31 meters from the drift axis. Fractures outside fracture zones are not modelled beyond 31 meters from the drift axis. Transport predictions were produced using the FracMan discrete fracture modelling package for each of five tracer experiments. Output was produced in the seven formats specified by the Stripa task force on fracture flow modelling. (au)

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

DEFF Research Database (Denmark)

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

2012-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2011-01-15

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2003-08-01

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

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-09-01

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

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)

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

Directory of Open Access Journals (Sweden)

Rui Xue

2015-01-01

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

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

Science.gov (United States)

von Allmen, David Yoh; Wurmitzer, Karoline; Martin, Ernst; Klaver, Peter

2013-07-01

Although the hippocampus had been traditionally thought to be exclusively involved in long-term memory, recent studies raised controversial explanations why hippocampal activity emerged during short-term memory tasks. For example, it has been argued that long-term memory processes might contribute to performance within a short-term memory paradigm when memory capacity has been exceeded. It is still unclear, though, whether neural activity in the hippocampus predicts visual short-term memory (VSTM) performance. To investigate this question, we measured BOLD activity in 21 healthy adults (age range 19-27 yr, nine males) while they performed a match-to-sample task requiring processing of object-location associations (delay period  =  900 ms; set size conditions 1, 2, 4, and 6). Based on individual memory capacity (estimated by Cowan's K-formula), two performance groups were formed (high and low performers). Within whole brain analyses, we found a robust main effect of "set size" in the posterior parietal cortex (PPC). In line with a "set size × group" interaction in the hippocampus, a subsequent Finite Impulse Response (FIR) analysis revealed divergent hippocampal activation patterns between performance groups: Low performers (mean capacity  =  3.63) elicited increased neural activity at set size two, followed by a drop in activity at set sizes four and six, whereas high performers (mean capacity  =  5.19) showed an incremental activity increase with larger set size (maximal activation at set size six). Our data demonstrated that performance-related neural activity in the hippocampus emerged below capacity limit. In conclusion, we suggest that hippocampal activity reflected successful processing of object-location associations in VSTM. Neural activity in the PPC might have been involved in attentional updating. Copyright © 2013 Wiley Periodicals, Inc.

Short-term landfill methane emissions dependency on wind.

Science.gov (United States)

Delkash, Madjid; Zhou, Bowen; Han, Byunghyun; Chow, Fotini K; Rella, Chris W; Imhoff, Paul T

2016-09-01

Short-term (2-10h) variations of whole-landfill methane emissions have been observed in recent field studies using the tracer dilution method for emissions measurement. To investigate the cause of these variations, the tracer dilution method is applied using 1-min emissions measurements at Sandtown Landfill (Delaware, USA) for a 2-h measurement period. An atmospheric dispersion model is developed for this field test site, which is the first application of such modeling to evaluate atmospheric effects on gas plume transport from landfills. The model is used to examine three possible causes of observed temporal emissions variability: temporal variability of surface wind speed affecting whole landfill emissions, spatial variability of emissions due to local wind speed variations, and misaligned tracer gas release and methane emissions locations. At this site, atmospheric modeling indicates that variation in tracer dilution method emissions measurements may be caused by whole-landfill emissions variation with wind speed. Field data collected over the time period of the atmospheric model simulations corroborate this result: methane emissions are correlated with wind speed on the landfill surface with R(2)=0.51 for data 2.5m above ground, or R(2)=0.55 using data 85m above ground, with emissions increasing by up to a factor of 2 for an approximately 30% increase in wind speed. Although the atmospheric modeling and field test are conducted at a single landfill, the results suggest that wind-induced emissions may affect tracer dilution method emissions measurements at other landfills. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

International Nuclear Information System (INIS)

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

2012-01-01

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

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 fluid, heat, and solute transport in deep 'georeservoirs' likely to become 'EGS': some challenges to ICDP hydrogeologists who might like using artificial tracers

Science.gov (United States)

Ghergut, Julia; Behrens, Horst; Huenges, Ernst; Rose, Peter; Sauter, Martin

2014-05-01

-georeservoir characterization and/or short- to mid-term process monitoring during reservoir operation: - if those tests have been successful to a certain extent, it was primarily owing to ascertainedly conservative tracer transport behavior; - if those tests have been of limited success, it was because of lack of reactive tracer species with well-defined, and reasonable properties (reasonable means: sensitive to 'something', but not to 'everything' that may 'happen' within the target georeservoir). If the artificial-tracer-based quantification of deep-georeservoir hydrogeology and of induced (short- to mid-term) transport processes therein is to become a task for some future ICDP projects, they will need to effectively address this dilemma. Further, if EGS, and especially the petrothermal type shall be on the agenda, then SW tests will be 'unavoidable'. Finally, if the most is to be made out of a SW test, then tailored reactive tracer pairs (Tomich et al. 1973, Ghergut et al. 2013) are a must: not just reactive, not just retarded, but: conservative alongside with reactive, and with contrasting retardation behavior between product and reactant. Selected references: Harms U, Koeberl C, Zoback M, eds (2005) Continental Scientific Drilling: A Decade of Progress, and Challenges for the Future. Springer, 366 pp. Harms U, Wiersberg T (2013) Conference on ICDP's New Science Plan. Scientific Drilling, 15: 77. Huenges E, Jung R (2004) Technologies for the Utilisation of Enhanced Geothermal Systems (www.bgr.de/ veransta/renewables_2004/presentations_DGP/Block1Introduction_pdf/2_Huenges_Jung.pdf) Jung R (2013) EGS - Goodbye or Back to the Future. Chapter 5, dx.doi.org/10.5772/56458 (www.intechopen.com/ books/effective-and-sustainable-hydraulic-fracturing) Moeck I (2013) Classification of geothermal plays according to geological habitats. IGA Academy Report 0101-2013 (www.geothermal-energy.org/iga_service_gmbh/projects/ifc_project/workshop_izmir.html) Robinson B A (1985) Non-reactive and chemically

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

Science.gov (United States)

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

2017-12-01

Air pollutant concentration forecasting is an effective method of protecting public health by providing an early warning against harmful air pollutants. However, existing methods of air pollutant concentration prediction fail to effectively model long-term dependencies, and most neglect spatial correlations. In this paper, a novel long short-term memory neural network extended (LSTME) model that inherently considers spatiotemporal correlations is proposed for air pollutant concentration prediction. Long short-term memory (LSTM) layers were used to automatically extract inherent useful features from historical air pollutant data, and auxiliary data, including meteorological data and time stamp data, were merged into the proposed model to enhance the performance. Hourly PM 2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm) concentration data collected at 12 air quality monitoring stations in Beijing City from Jan/01/2014 to May/28/2016 were used to validate the effectiveness of the proposed LSTME model. Experiments were performed using the spatiotemporal deep learning (STDL) model, the time delay neural network (TDNN) model, the autoregressive moving average (ARMA) model, the support vector regression (SVR) model, and the traditional LSTM NN model, and a comparison of the results demonstrated that the LSTME model is superior to the other statistics-based models. Additionally, the use of auxiliary data improved model performance. For the one-hour prediction tasks, the proposed model performed well and exhibited a mean absolute percentage error (MAPE) of 11.93%. In addition, we conducted multiscale predictions over different time spans and achieved satisfactory performance, even for 13-24 h prediction tasks (MAPE = 31.47%). Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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

Science.gov (United States)

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

2016-03-01

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

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

Directory of Open Access Journals (Sweden)

Haimin Yang

2017-01-01

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

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

Science.gov (United States)

Yang, Haimin; Pan, Zhisong; Tao, Qing

2017-01-01

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

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

International Nuclear Information System (INIS)

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

2017-01-01

Air pollutant concentration forecasting is an effective method of protecting public health by providing an early warning against harmful air pollutants. However, existing methods of air pollutant concentration prediction fail to effectively model long-term dependencies, and most neglect spatial correlations. In this paper, a novel long short-term memory neural network extended (LSTME) model that inherently considers spatiotemporal correlations is proposed for air pollutant concentration prediction. Long short-term memory (LSTM) layers were used to automatically extract inherent useful features from historical air pollutant data, and auxiliary data, including meteorological data and time stamp data, were merged into the proposed model to enhance the performance. Hourly PM 2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm) concentration data collected at 12 air quality monitoring stations in Beijing City from Jan/01/2014 to May/28/2016 were used to validate the effectiveness of the proposed LSTME model. Experiments were performed using the spatiotemporal deep learning (STDL) model, the time delay neural network (TDNN) model, the autoregressive moving average (ARMA) model, the support vector regression (SVR) model, and the traditional LSTM NN model, and a comparison of the results demonstrated that the LSTME model is superior to the other statistics-based models. Additionally, the use of auxiliary data improved model performance. For the one-hour prediction tasks, the proposed model performed well and exhibited a mean absolute percentage error (MAPE) of 11.93%. In addition, we conducted multiscale predictions over different time spans and achieved satisfactory performance, even for 13–24 h prediction tasks (MAPE = 31.47%). - Highlights: • Regional air pollutant concentration shows an obvious spatiotemporal correlation. • Our prediction model presents superior performance. • Climate data and metadata can significantly

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

Science.gov (United States)

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

2017-07-15

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

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

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…

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

DEFF Research Database (Denmark)

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

2017-01-01

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

Stacking Ensemble Learning for Short-Term Electricity Consumption Forecasting

Directory of Open Access Journals (Sweden)

Federico Divina

2018-04-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2010-12-15

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

Dynamical prediction and pattern mapping in short-term load forecasting

Energy Technology Data Exchange (ETDEWEB)

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

2008-01-15

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

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

Science.gov (United States)

Zhang, J; Nawata, K

2018-05-01

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

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

Science.gov (United States)

Murray, Alexandra M; Nobre, Anna C; Stokes, Mark G

2011-05-01

Visual short-term memory (VSTM) is limited in capacity. Therefore, it is important to encode only visual information that is most likely to be relevant to behaviour. Here we asked which aspects of selective biasing of VSTM encoding predict subsequent memory-based performance. We measured EEG during a selective VSTM encoding task, in which we varied parametrically the memory load and the precision of recall required to compare a remembered item to a subsequent probe item. On half the trials, a spatial cue indicated that participants only needed to encode items from one hemifield. We observed a typical sequence of markers of anticipatory spatial attention: early attention directing negativity (EDAN), anterior attention directing negativity (ADAN), late directing attention positivity (LDAP); as well as of VSTM maintenance: contralateral delay activity (CDA). We found that individual differences in preparatory brain activity (EDAN/ADAN) predicted cue-related changes in recall accuracy, indexed by memory-probe discrimination sensitivity (d'). Importantly, our parametric manipulation of memory-probe similarity also allowed us to model the behavioural data for each participant, providing estimates for the quality of the memory representation and the probability that an item could be retrieved. We found that selective encoding primarily increased the probability of accurate memory recall; that ERP markers of preparatory attention predicted the cue-related changes in recall probability. Copyright © 2011. Published by Elsevier Ltd.

Predictions of tracer transport in interwell tracer tests at the C-Hole complex. Yucca Mountain site characterization project report milestone 4077

International Nuclear Information System (INIS)

Reimus, P.W.

1996-09-01

This report presents predictions of tracer transport in interwell tracer tests that are to be conducted at the C-Hole complex at the Nevada Test Site on behalf of the Yucca Mountain Site Characterization Project. The predictions are used to make specific recommendations about the manner in which the tracer test should be conducted to best satisfy the needs of the Project. The objective of he tracer tests is to study flow and species transport under saturated conditions in the fractured tuffs near Yucca Mountain, Nevada, the site of a potential high-level nuclear waste repository. The potential repository will be located in the unsaturated zone within Yucca Mountain. The saturated zone beneath and around the mountain represents the final barrier to transport to the accessible environment that radionuclides will encounter if they breach the engineered barriers within the repository and the barriers to flow and transport provided by the unsaturated zone. Background information on the C-Holes is provided in Section 1.1, and the planned tracer testing program is discussed in Section 1.2

Prediction of long-term creep curves

International Nuclear Information System (INIS)

Oikawa, Hiroshi; Maruyama, Kouichi

1992-01-01

This paper aims at discussing how to predict long-term irradiation enhanced creep properties from short-term tests. The predictive method based on the θ concept was examined by using creep data of ferritic steels. The method was successful in predicting creep curves including the tertiary creep stage as well as rupture lifetimes. Some material constants involved in the method are insensitive to the irradiation environment, and their values obtained in thermal creep are applicable to irradiation enhanced creep. The creep mechanisms of most engineering materials definitely change at the athermal yield stress in the non-creep regime. One should be aware that short-term tests must be carried out at stresses lower than the athermal yield stress in order to predict the creep behavior of structural components correctly. (orig.)

Continuous administration of short-lived radioisotope tracers and the analogous Laplace transform

International Nuclear Information System (INIS)

Orr, J.S.

1979-01-01

Short-lived radioactive tracers are used because of the low radiation dose to patients. Another advantage finding increasing use, however, is that the equilibrium activities achieved by continuous administration to a steady state contain kinetic information. This is not the case with long-lived isotopes. The derivation of quantitative kinetic information in the form of rate constants or flows requires the formulation of a model of the system being studied. Several approaches to this have been published based on a model of single compartments with simultaneous arrival of tracer. To deal with more realistic models a method is proposed which uses the analogy between the procedure of continuous administration of short-lived tracer and the Laplace transform. This analogy permits all the theorems of Laplace transform theory to be applied to the analysis of measured activities. The basis of the analogy is explained and examples are given of its application to a number of models which represent actual physiology more realistically than single compartment models. In these applications the transformed equations representing the model, with measured values of activity inserted for each transform, are solved to derive the rate constants. This is different from the use of Laplace transforms where the constant coefficients are known and the initial value problem is solved to find the behaviour of the variables. (author)

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.

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

Science.gov (United States)

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

2016-09-01

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

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

Directory of Open Access Journals (Sweden)

César Hernández-Hernández

2017-06-01

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

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

Science.gov (United States)

Leclercq, Anne-Lise; Majerus, Steve

2010-03-01

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

Statistically Based Morphodynamic Modeling of Tracer Slowdown

Science.gov (United States)

Borhani, S.; Ghasemi, A.; Hill, K. M.; Viparelli, E.

2017-12-01

Tracer particles are used to study bedload transport in gravel-bed rivers. One of the advantages associated with using of tracer particles is that they allow for direct measures of the entrainment rates and their size distributions. The main issue in large scale studies with tracer particles is the difference between tracer stone short term and long term behavior. This difference is due to the fact that particles undergo vertical mixing or move to less active locations such as bars or even floodplains. For these reasons the average virtual velocity of tracer particle decreases in time, i.e. the tracer slowdown. In summary, tracer slowdown can have a significant impact on the estimation of bedload transport rate or long term dispersal of contaminated sediment. The vast majority of the morphodynamic models that account for the non-uniformity of the bed material (tracer and not tracer, in this case) are based on a discrete description of the alluvial deposit. The deposit is divided in two different regions; the active layer and the substrate. The active layer is a thin layer in the topmost part of the deposit whose particles can interact with the bed material transport. The substrate is the part of the deposit below the active layer. Due to the discrete representation of the alluvial deposit, active layer models are not able to reproduce tracer slowdown. In this study we try to model the slowdown of tracer particles with the continuous Parker-Paola-Leclair morphodynamic framework. This continuous, i.e. not layer-based, framework is based on a stochastic description of the temporal variation of bed surface elevation, and of the elevation specific particle entrainment and deposition. Particle entrainment rates are computed as a function of the flow and sediment characteristics, while particle deposition is estimated with a step length formulation. Here we present one of the first implementation of the continuum framework at laboratory scale, its validation against

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

Directory of Open Access Journals (Sweden)

Rudolf Scitovski

2012-12-01

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

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

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

Science.gov (United States)

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

2017-06-01

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

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.

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

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

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

Science.gov (United States)

Hanson, Jack; Yang, Yuedong; Paliwal, Kuldip; Zhou, Yaoqi

2017-03-01

Capturing long-range interactions between structural but not sequence neighbors of proteins is a long-standing challenging problem in bioinformatics. Recently, long short-term memory (LSTM) networks have significantly improved the accuracy of speech and image classification problems by remembering useful past information in long sequential events. Here, we have implemented deep bidirectional LSTM recurrent neural networks in the problem of protein intrinsic disorder prediction. The new method, named SPOT-Disorder, has steadily improved over a similar method using a traditional, window-based neural network (SPINE-D) in all datasets tested without separate training on short and long disordered regions. Independent tests on four other datasets including the datasets from critical assessment of structure prediction (CASP) techniques and >10 000 annotated proteins from MobiDB, confirmed SPOT-Disorder as one of the best methods in disorder prediction. Moreover, initial studies indicate that the method is more accurate in predicting functional sites in disordered regions. These results highlight the usefulness combining LSTM with deep bidirectional recurrent neural networks in capturing non-local, long-range interactions for bioinformatics applications. SPOT-disorder is available as a web server and as a standalone program at: http://sparks-lab.org/server/SPOT-disorder/index.php . j.hanson@griffith.edu.au or yuedong.yang@griffith.edu.au or yaoqi.zhou@griffith.edu.au. Supplementary data is available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-01-15

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

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

International Nuclear Information System (INIS)

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

2017-01-01

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

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

Science.gov (United States)

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

2018-03-01

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

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

Science.gov (United States)

ElSaid, AbdElRahman Ahmed

This thesis examines building viable Recurrent Neural Networks (RNN) using Long Short Term Memory (LSTM) neurons to predict aircraft engine vibrations. The different networks are trained on a large database of flight data records obtained from an airline containing flights that suffered from excessive vibration. RNNs can provide a more generalizable and robust method for prediction over analytical calculations of engine vibration, as analytical calculations must be solved iteratively based on specific empirical engine parameters, and this database contains multiple types of engines. Further, LSTM RNNs provide a "memory" of the contribution of previous time series data which can further improve predictions of future vibration values. LSTM RNNs were used over traditional RNNs, as those suffer from vanishing/exploding gradients when trained with back propagation. The study managed to predict vibration values for 1, 5, 10, and 20 seconds in the future, with 2.84% 3.3%, 5.51% and 10.19% mean absolute error, respectively. These neural networks provide a promising means for the future development of warning systems so that suitable actions can be taken before the occurrence of excess vibration to avoid unfavorable situations during flight.

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

Directory of Open Access Journals (Sweden)

Jinxing Shen

2013-01-01

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

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)

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.

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

OpenAIRE

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

2017-01-01

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

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.

Audit of long-term and short-term liabilities

Directory of Open Access Journals (Sweden)

Korinko M.D.

2017-03-01

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

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

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Make BJ

2015-01-01

properties of predictive variables. Results: The best predictors of an exacerbation in the next 6 months were more COPD maintenance medications prior to the trial, higher mean daily reliever use, more exacerbations during the previous year, lower forced expiratory volume in 1 second/forced vital capacity ratio, and female sex. Using these risk variables, we developed a score to predict short-term (6-month risk of COPD exacerbations (SCOPEX. Budesonide/formoterol reduced future exacerbation risk more than formoterol or as-needed short-acting ß2-agonist (salbutamol. Conclusion: SCOPEX incorporates easily identifiable patient characteristics and can be readily applied in clinical practice to target therapy to reduce COPD exacerbations in patients at the highest risk. Keywords: chronic obstructive pulmonary disease, exacerbation, model, predictor, inhaled corticosteroids, bronchodilators 

Predictive value of tracer studies for 131I treatment in hyperthyroid cats

International Nuclear Information System (INIS)

Broome, M.R.; Turrel, J.M.; Hays, M.T.

1988-01-01

In 76 cats with hyperthyroidism, peak thyroidal radioiodine ( 131 I) uptakes and effective half-lives were determined after administration of tracer and therapeutic activities of 131 I. In 6 additional hyperthyroid cats, only peak thyroidal uptakes after administration of tracer and therapeutic activities of 131 I were determined. Good correlation was found between peak thyroidal uptakes of tracer and therapeutic 131 I; however, only fair correlation was observed between effective half-lives. In 79% of the cats, the effective half-life for therapeutic 131 I was longer than that for tracer 131 I. After administration of therapeutic activity of 131 I, monoexponential and biphasic decay curves were observed in 51 and 16 cats, respectively. Using therapeutic kinetic data, radiation doses to the thyroid gland were calculated retrospectively on the basis of 2 methods for determining the activity of 131 I administered: (1) actual administration of tracer-compensated activity and (2) hypothetic administration of uniform activity (3 mCi). Because of the good predictive ability of tracer kinetic data for the therapeutic kinetic data, the tracer-compensated radiation doses came significantly (P = 0.008) closer to the therapeutic goal than did the uniform-activity doses. In addition, the use of tracer kinetic information reduced the extent of the tendency for consistently high uniform-activity doses. A manual method for acquiring tracer kinetic data was developed and was an acceptable alternative to computerized techniques. Adoption of this method gives individuals and institutions with limited finances the opportunity to characterize the iodine kinetics in cats before proceeding with administration of therapeutic activities of 131 I

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-10-15

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

Short-term forecasting model for aggregated regional hydropower generation

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Science.gov (United States)

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

Few instruments capture symptoms that predict cardiac events in the short-term. This study examines the ability of the McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey to predict acute cardiac events within 3 months of administration and to identify the prodromal symptoms most associated with short-term risk in women without known coronary heart disease. The McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey was administered to 1,097 women referred to a cardiologist for initial coronary heart disease evaluation. Logistic regression models were used to examine prodromal symptoms individually and in combination to identify the subset of symptoms most predictive of an event within 3 months. Fifty-one women had an early cardiac event. In bivariate analyses, 4 of 30 prodromal symptoms were significantly associated with event occurrence within 90 days. In adjusted analyses, women reporting arm pain or discomfort and unusual fatigue were more likely (OR, 4.67; 95% CI, 2.08-10.48) to have a cardiac event than women reporting neither. The McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey may assist in predicting short-term coronary heart disease events in women without known coronary heart disease. Copyright © 2017 Jacobs Institute of Women's Health. All rights reserved.

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

International Nuclear Information System (INIS)

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

2016-01-01

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

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

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TIAN Yan

2015-03-01

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

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

OpenAIRE

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

2011-01-01

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

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.

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

KAUST Repository

Radwan, Ahmed Gomaa

2014-06-18

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

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

KAUST Repository

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

2014-01-01

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

The PER (Preoperative Esophagectomy Risk) Score: A Simple Risk Score to Predict Short-Term and Long-Term Outcome in Patients with Surgically Treated Esophageal Cancer.

Science.gov (United States)

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

2016-02-01

Esophageal resection in patients with esophageal cancer (EC) is still associated with high mortality and morbidity rates. We aimed to develop a simple preoperative risk score for the prediction of short-term and long-term outcomes for patients with EC treated by esophageal resection. In total, 498 patients suffering from esophageal carcinoma, who underwent esophageal resection, were included in this retrospective cohort study. Three preoperative esophagectomy risk (PER) groups were defined based on preoperative functional evaluation of different organ systems by validated tools (revised cardiac risk index, model for end-stage liver disease score, and pulmonary function test). Clinicopathological parameters, morbidity, and mortality as well as disease-free survival (DFS) and overall survival (OS) were correlated to the PER score. The PER score significantly predicted the short-term outcome of patients with EC who underwent esophageal resection. PER 2 and PER 3 patients had at least double the risk of morbidity and mortality compared to PER 1 patients. Furthermore, a higher PER score was associated with shorter DFS (P PER score was identified as an independent predictor of tumor recurrence (hazard ratio [HR] 2.1; P PER score allows preoperative objective allocation of patients with EC into different risk categories for morbidity, mortality, and long-term outcomes. Thus, multicenter studies are needed for independent validation of the PER score.

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...

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 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.

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)

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.

Short-term wind power prediction

DEFF Research Database (Denmark)

Joensen, Alfred K.

2003-01-01

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

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

Science.gov (United States)

Schmidt, Mathias V; Trümbach, Dietrich; Weber, Peter; Wagner, Klaus; Scharf, Sebastian H; Liebl, Claudia; Datson, Nicole; Namendorf, Christian; Gerlach, Tamara; Kühne, Claudia; Uhr, Manfred; Deussing, Jan M; Wurst, Wolfgang; Binder, Elisabeth B; Holsboer, Florian; Müller, Marianne B

2010-12-15

Increased vulnerability to aversive experiences is one of the main risk factors for stress-related psychiatric disorders as major depression. However, the molecular bases of vulnerability, on the one hand, and stress resilience, on the other hand, are still not understood. Increasing clinical and preclinical evidence suggests a central involvement of the glutamatergic system in the pathogenesis of major depression. Using a mouse paradigm, modeling increased stress vulnerability and depression-like symptoms in a genetically diverse outbred strain, and we tested the hypothesis that differences in AMPA receptor function may be linked to individual variations in stress vulnerability. Vulnerable and resilient animals differed significantly in their dorsal hippocampal AMPA receptor expression and AMPA receptor binding. Treatment with an AMPA receptor potentiator during the stress exposure prevented the lasting effects of chronic social stress exposure on physiological, neuroendocrine, and behavioral parameters. In addition, spatial short-term memory, an AMPA receptor-dependent behavior, was found to be predictive of individual stress vulnerability and response to AMPA potentiator treatment. Finally, we provide evidence that genetic variations in the AMPA receptor subunit GluR1 are linked to the vulnerable phenotype. Therefore, we propose genetic variations in the AMPA receptor system to shape individual stress vulnerability. Those individual differences can be predicted by the assessment of short-term memory, thereby opening up the possibility for a specific treatment by enhancing AMPA receptor function.

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

NARCIS (Netherlands)

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

2009-01-01

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

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

Science.gov (United States)

Jarrold, C; Baddeley, A D

2001-10-01

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

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.

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

Science.gov (United States)

Diehl, Charlotte; Rees, Jonas; Bohner, Gerd

2012-01-01

We combine evolutionary and sociocultural accounts of sexual harassment, proposing that sexuality-related and hostility-related motives lead to different types of harassment. Specifically, men's short-term mating orientation (STMO) was hypothesized to predict only unwanted sexual attention but not gender harassment, whereas men's hostile sexism (HS) was hypothesized to predict both unwanted sexual attention and gender harassment. As part of an alleged computer-chat task, 100 male students could send sexualized personal remarks (representing unwanted sexual attention), sexist jokes (representing gender harassment), or nonharassing material to an attractive female target. Independently, participants' STMO, HS, and sexual harassment myth acceptance (SHMA) were assessed. Correlational and path analyses revealed that STMO specifically predicted unwanted sexual attention, whereas HS predicted both unwanted sexual attention and gender harassment. Furthermore, SHMA fully mediated the effect of HS on gender harassment, but did not mediate effects of STMO or HS on unwanted sexual attention. Results are discussed in relation to motivational explanations for sexual harassment and antiharassment interventions. © 2012 Wiley Periodicals, Inc.

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

International Nuclear Information System (INIS)

Lihn, M.L.

1989-03-01

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

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

Science.gov (United States)

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

2018-05-17

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

Using environmental tracer data to identify deep-aquifer, long-term flow patterns and recharge distributions in the Surat Basin, Queensland, Australia

Science.gov (United States)

Siade, A. J.; Suckow, A. O.; Morris, R.; Raiber, M.; Prommer, H.

2017-12-01

The calibration of regional groundwater flow models, including those investigating coal-seam gas (CSG) impacts in the Surat Basin, Australia, are not typically constrained using environmental tracers, although the use of such data can potentially provide significant reductions in predictive uncertainties. These additional sources of information can also improve the conceptualisation of flow systems and the quantification of groundwater fluxes. In this study, new multi-tracer data (14C, 39Ar, 81Kr, and 36Cl) were collected for the eastern recharge areas of the basin and within the deeper Hutton and Precipice Sandstone formations to complement existing environmental tracer data. These data were used to better understand the recharge mechanisms, recharge rates and the hydraulic properties associated with deep aquifer systems in the Surat Basin. Together with newly acquired pressure data documenting the response to the large-scale reinjection of highly treated CSG co-produced water, the environmental tracer data helped to improve the conceptualisation of the aquifer system, forming the basis for a more robust quantification of the long-term impacts of CSG-related activities. An existing regional scale MODFLOW-USG groundwater flow model of the area was used as the basis for our analysis of existing and new observation data. A variety of surrogate modelling approaches were used to develop simplified models that focussed on the flow and transport behaviour of the deep aquifer systems. These surrogate models were able to represent sub-system behaviour in terms of flow, multi-environmental tracer transport and the observed large-scale hydrogeochemical patterns. The incorporation of the environmental tracer data into the modelling framework provide an improved understanding of the flow regimes of the deeper aquifer systems as well as valuable information on how to reduce uncertainties in hydraulic properties where there is little or no historical observations of hydraulic

Viruses as groundwater tracers: using ecohydrology to characterize short travel times in aquifers

Science.gov (United States)

Hunt, Randall J.; Borchardt, Mark A.; Bradbury, Kenneth R.

2014-01-01

Viruses are attractive tracers of short (population over time; therefore, the virus snapshot shed in the fecal wastes of an infected population at a specific point in time can serve as a marker for tracking virus and groundwater movement. The virus tracing approach and an example application are described to illustrate their ability to characterize travel times in high-groundwater velocity settings, and provide insight unavailable from standard hydrogeologic approaches. Although characterization of preferential flowpaths does not usually characterize the majority of other travel times occurring in the groundwater system (e.g., center of plume mass; tail of the breakthrough curve), virus approaches can trace very short times of transport, and thus can fill an important gap in our current hydrogeology toolbox.

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

Science.gov (United States)

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

2009-06-10

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

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

Science.gov (United States)

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

2013-01-01

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

Modelling tracer transport in fractured rock at Stripa

International Nuclear Information System (INIS)

Herbert, A.

1992-01-01

We present the results of a modelling study, making predictions for tracer transport experiments carried out within the H-zone feature in the Stripa mine. We use a direct fracture network approach to represent the system of interconnected flow-conducting fractures comprising this zone. It is a highly fractured granite, and our fracture-network models include up to 60000 fractures. We have had to develop efficient algorithms to calculate the flow and transport through these networks; these techniques are described and justified. The first stage of modelling addressed two saline injection experiments. The results of these were known to us and so in addition to 'predicting' the results of these experiments, we used them to calibrate a flow model of the experimental site. This model was then used to make true 'blind' predictions for a set of tracer experiments carried out in the natural head-field, caused by an open drift. Where our flow model was good, our predictions were found to be very accurate, explaining the dispersion in the tracer breakthrough in terms of the fracture network geometry. Discrepancies for experiments in less well characterised regions of the H-zone are presented, and we suggest that the errors in these predictions are a consequence of the inaccuracies of the flow-field. We have demonstrated the use of large-scale fracture network modelling. It has proved very successful, and made very accurate predictions of field experiments carried out at the Stripa mine. The measured dispersion of tracers can be accounted for by the geometry of the fracture network flow system. (14 refs.) (au)

Error analysis of short term wind power prediction models

International Nuclear Information System (INIS)

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

2011-01-01

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

Error analysis of short term wind power prediction models

Energy Technology Data Exchange (ETDEWEB)

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

2011-04-15

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

Journal: Efficient Hydrologic Tracer-Test Design for Tracer ...

Science.gov (United States)

Hydrological tracer testing is the most reliable diagnostic technique available for the determination of basic hydraulic and geometric parameters necessary for establishing operative solute-transport processes. Tracer-test design can be difficult because of a lack of prior knowledge of the basic hydraulic and geometric parameters desired and the appropriate tracer mass to release. A new efficient hydrologic tracer-test design (EHTD) methodology has been developed to facilitate the design of tracer tests by root determination of the one-dimensional advection-dispersion equation (ADE) using a preset average tracer concentration which provides a theoretical basis for an estimate of necessary tracer mass. The method uses basic measured field parameters (e.g., discharge, distance, cross-sectional area) that are combined in functional relatipnships that descrive solute-transport processes related to flow velocity and time of travel. These initial estimates for time of travel and velocity are then applied to a hypothetical continuous stirred tank reactor (CSTR) as an analog for the hydrological-flow system to develop initial estimates for tracer concentration, tracer mass, and axial dispersion. Application of the predicted tracer mass with the hydraulic and geometric parameters in the ADE allows for an approximation of initial sample-collection time and subsequent sample-collection frequency where a maximum of 65 samples were determined to be necessary for descri

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

Directory of Open Access Journals (Sweden)

MI Chang-hong

2016-02-01

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

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

Science.gov (United States)

Ni, X. Y.; Huang, H.; Du, W. P.

2017-02-01

The PM2.5 problem is proving to be a major public crisis and is of great public-concern requiring an urgent response. Information about, and prediction of PM2.5 from the perspective of atmospheric dynamic theory is still limited due to the complexity of the formation and development of PM2.5. In this paper, we attempted to realize the relevance analysis and short-term prediction of PM2.5 concentrations in Beijing, China, using multi-source data mining. A correlation analysis model of PM2.5 to physical data (meteorological data, including regional average rainfall, daily mean temperature, average relative humidity, average wind speed, maximum wind speed, and other pollutant concentration data, including CO, NO2, SO2, PM10) and social media data (microblog data) was proposed, based on the Multivariate Statistical Analysis method. The study found that during these factors, the value of average wind speed, the concentrations of CO, NO2, PM10, and the daily number of microblog entries with key words 'Beijing; Air pollution' show high mathematical correlation with PM2.5 concentrations. The correlation analysis was further studied based on a big data's machine learning model- Back Propagation Neural Network (hereinafter referred to as BPNN) model. It was found that the BPNN method performs better in correlation mining. Finally, an Autoregressive Integrated Moving Average (hereinafter referred to as ARIMA) Time Series model was applied in this paper to explore the prediction of PM2.5 in the short-term time series. The predicted results were in good agreement with the observed data. This study is useful for helping realize real-time monitoring, analysis and pre-warning of PM2.5 and it also helps to broaden the application of big data and the multi-source data mining methods.

Key aspects of stratospheric tracer modeling using assimilated winds

Directory of Open Access Journals (Sweden)

B. Bregman

2006-01-01

horizontal dispersion is not necessarily an indication of poor wind quality, as observations indicate. Moreover, the generally applied air parcel dispersion calculations should be interpreted with care, given the strong sensitivity of dispersion with altitude. The results in this study provide a guideline for stratospheric tracer modeling using assimilated winds. They further demonstrate significant progress in the use of assimilated meteorology in chemistry-transport models, relevant for both short- and long-term integrations.

The suitability of short-term measurements of radon in the built environment

International Nuclear Information System (INIS)

Denman, A.R.; Groves-Kirkby, C.J.; Phillips, P.S.; Crockett, R.G.M.; Woolridge, A.C.

2008-01-01

Although domestic and workplace radon concentration levels often show marked diurnal/short-term variation, overall health risk is determined by the long-term average level, and many national protocols advocate the use of long exposure periods, usually three months, to assess long-term risk. Simple passive measurement techniques, e.g. track-etch, activated charcoal and electret, can, however, provide reasonably accurate determinations with exposures as short as one week, and there is pressure from users and stake holders for assessments within this time period. We report evaluation of the effectiveness of one-week, one-month and three-month exposures over a period of one year in a designated Radon Affected Area in the United Kingdom (UK). Although short-term exposures did not compromise measurement accuracy, short-term radon variability rendered one-week measurements less reliable in predicting annual average radon levels via the conventional methodology. Analysis permitted estimation of the maximum and minimum short-term measured domestic radon concentrations at which there was 95% probability of the predicted annual average being below or above the UK Action Level of 200 Bq·m -3 respectively. Between these limits, the short-term result is equivocal, requiring repetition, and the 'equivocal range' for one-week measurements is significantly wider than for three-month exposures. In any geographical area, domestic radon concentrations are distributed log normally, with many properties having low average levels; a small number exhibit excessive levels, and this distribution must be considered when defining exposures for a radon measurement programme. In low-radon areas, where 1% of houses might exceed the Action Level, a one-week assessment will find that fewer outcomes are equivocal. For high-radon areas, with 20% or more houses over the Action Level, more than 50% of one-week outcomes will be equivocal, requiring repeats. The results of this work will be presented

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

Science.gov (United States)

De Vet, Emely; Nelissen, Rob M A; Zeelenberg, Marcel; De Ridder, Denise T D

2013-05-01

Although psychological theories outline that it might be beneficial to set more challenging goals, people attempting to lose weight are generally recommended to set modest weight loss goals. The present study explores whether the amount of weight loss individuals strive for is associated with more positive psychological and behavioral outcomes. Hereto, 447 overweight and obese participants trying to lose weight completed two questionnaires with a 2-month interval. Many participants set goals that could be considered unrealistically high. However, higher weight loss goals did not predict dissatisfaction but predicted more effort in the weight loss attempt, as well as more self-reported short-term weight loss when baseline commitment and motivation were controlled for.

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

Science.gov (United States)

Castro, J; Toro, J; Cruz, M

2000-01-01

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

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

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.

EGS in sedimentary basins: sensitivity of early-flowback tracer signals to induced-fracture parameters

Science.gov (United States)

Karmakar, Shyamal; Ghergut, Julia; Sauter, Martin

2015-04-01

Artificial-fracture design, and fracture characterization during or following stimulation treatment is a central aspect of many EGS ('enhanced' or 'engineered' geothermal system) projects. During the creation or stimulation of an EGS, the injection of fluids, followed by flowback and production stages offers the opportunity for conducting various tracer tests in a single-well (SW) configuration, and given the typical operational and time limitations associated with such tests, along with the need to assess treatment success in real time, investigators mostly favour using short-time tracer-test data, rather than awaiting long-term 'tailings' of tracer signals. Late-time tracer signals from SW injection-flowback and production tests have mainly been used for the purpose of multiple-fracture inflow profiling in multi-layer reservoirs [1]. However, the potential of using SW short-term tracer signals for fracture characterization [2, 3] remained little explored as yet. Dealing with short-term flowback signals, we face a certain degree of parameter interplay, leading to ambiguity in fracture parameter inversion from the measured signal of a single tracer. This ambiguity can, to a certain extent, be overcome by - combining different sources of information (lithostratigraphy, and hydraulic monitoring) in order to constrain the variation range of hydrogeologic parameters (matrix and fracture permeability and porosity, fracture size), - using different types of tracers, such as conservative tracer pairs with contrasting diffusivity, or tracers pairs with contrasting sorptivity onto target surfaces. Fracture height is likely to be constrained by lithostratigraphy, while fracture length is supposed to be determinable from hydraulic monitoring (pressure recordings); the flowback rate can be assumed as a known (measurable) quantity during individual-fracture flowback. This leaves us with one or two unknown parameters to be determined from tracer signals: - the transport

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

International Nuclear Information System (INIS)

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

2002-01-01

Three parametric statistical models have been fully validated for cancer of the larynx for the prediction of long-term 15, 20 and 25 year cancer-specific survival fractions when short-term follow-up data was available for just 1-2 years after the end of treatment of the last patient. In all groups of cases the treatment period was only 5 years. Three disease stage groups were studied, T1N0, T2N0 and T3N0. The models are the Standard Lognormal (SLN) first proposed by Boag (1949 J. R. Stat. Soc. Series B 11 15-53) but only ever fully validated for cancer of the cervix, Mould and Boag (1975 Br. J. Cancer 32 529-50), and two new models which have been termed Tobacco Cancer Risk (TCR) and Absolute Cancer Cure (ACC). In each, the frequency distribution of survival times of defined groups of cancer deaths is lognormally distributed: larynx only (SLN), larynx and lung (TCR) and all cancers (ACC). All models each have three unknown parameters but it was possible to estimate a value for the lognormal parameter S a priori. By reduction to two unknown parameters the model stability has been improved. The material used to validate the methodology consisted of case histories of 965 patients, all treated during the period 1944-1968 by Dr Manuel Lederman of the Royal Marsden Hospital, London, with follow-up to 1988. This provided a follow-up range of 20- 44 years and enabled predicted long-term survival fractions to be compared with the actual survival fractions, calculated by the Kaplan and Meier (1958 J. Am. Stat. Assoc. 53 457-82) method. The TCR and ACC models are better than the SLN model and for a maximum short-term follow-up of 6 years, the 20 and 25 year survival fractions could be predicted. Therefore the numbers of follow-up years saved are respectively 14 years and 19 years. Clinical trial results using the TCR and ACC models can thus be analysed much earlier than currently possible. Absolute cure from cancer was also studied, using not only the prediction models which

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

Science.gov (United States)

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

2011-01-01

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

Self-concept and quality of object relations as predictors of outcome in short- and long-term psychotherapy.

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Lindfors, Olavi; Knekt, Paul; Heinonen, Erkki; Virtala, Esa

2014-01-01

Quality of object relations and self-concept reflect clinically relevant aspects of personality functioning, but their prediction as suitability factors for psychotherapies of different lengths has not been compared. This study compared their prediction on psychiatric symptoms and work ability in short- and long-term psychotherapy. Altogether 326 patients, 20-46 years of age, with mood and/or anxiety disorder, were randomized to short-term (solution-focused or short-term psychodynamic) psychotherapy and long-term psychodynamic psychotherapy. The Quality of Object Relations Scale (QORS) and the Structural Analysis of Social Behavior (SASB) self-concept questionnaire were measured at baseline, and their prediction on outcome during the 3-year follow-up was assessed by the Symptom Check List Global Severity Index and the Anxiety Scale, the Beck Depression Inventory and by the Work Ability Index, Social Adjustment Scale work subscale and the Perceived Psychological Functioning scale. Negative self-concept strongly and self-controlling characteristics modestly predicted better 3-year outcomes in long-term therapy, after faster early gains in short-term therapy. Patients with a more positive or self-emancipating self-concept, or more mature object relations, experienced more extensive benefits after long-term psychotherapy. The importance of length vs. long-term therapy technique on the differences found is not known. Patients with mild to moderate personality pathology, indicated by poor self-concept, seem to benefit more from long-term than short-term psychotherapy, in reducing risk of depression. Long-term therapy may also be indicated for patients with relatively good psychological functioning. More research is needed on the relative importance of these characteristics in comparison with other patient-related factors. © 2013 Published by Elsevier B.V.

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

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

2014-01-01

Experiments were conducted to test a modern exemplar-familiarity model on its ability to account for both short-term and long-term probe recognition within the same memory-search paradigm. Also, making connections to the literature on attention and visual search, the model was used to interpret differences in probe-recognition performance across…

Short-term 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.

Statistical short-term earthquake prediction.

Science.gov (United States)

Kagan, Y Y; Knopoff, L

1987-06-19

A statistical procedure, derived from a theoretical model of fracture growth, is used to identify a foreshock sequence while it is in progress. As a predictor, the procedure reduces the average uncertainty in the rate of occurrence for a future strong earthquake by a factor of more than 1000 when compared with the Poisson rate of occurrence. About one-third of all main shocks with local magnitude greater than or equal to 4.0 in central California can be predicted in this way, starting from a 7-year database that has a lower magnitude cut off of 1.5. The time scale of such predictions is of the order of a few hours to a few days for foreshocks in the magnitude range from 2.0 to 5.0.

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

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

2011-01-01

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

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

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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.

A fuzzy inference model for short-term load forecasting

International Nuclear Information System (INIS)

Mamlook, Rustum; Badran, Omar; Abdulhadi, Emad

2009-01-01

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

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.

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

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Klos, Coen L; Safar, Bashar; Hunt, Steven R; Wise, Paul E; Birnbaum, Elisa H; Mutch, Matthew G; Fleshman, James W; Dharmarajan, Sekhar

2014-08-01

The Accordion severity grading system is a novel system to score the severity of postoperative complications in a standardized fashion. This study aims to demonstrate the validity of the Accordion system in colorectal surgery by correlating severity grades with short-term outcomes after right colectomy for colon cancer. This is a retrospective cohort review of patients who underwent right colectomy for cancer between January 1, 2002, and January 31, 2007, at a single tertiary care referral center. Complications were categorized according to the Accordion severity grading system: grades 1 (mild), 2 (moderate), 3-5 (severe), and 6 (death). Outcome measures were hospital stay, 30-d readmission rate and 1-y survival. Correlation between Accordion grades and outcome measures is reflected by Spearman rho (ρ). One-year survival was obtained per Kaplan-Meier method and compared by logrank test for trend. Significance was set at P ≤ 0.05. Overall, 235 patients underwent right colectomy for cancer of which 122 (51.9%) had complications. In total, 52 (43%) had an Accordion grade 1 complication; 44 (36%) grade 2; four (3%) grade 3; 11 (9%) grade 4; seven (6%) grade 5; and four (3%) grade 6. There was significant correlation between Accordion grades and hospital stay (ρ = 0.495, P trend in 1-y survival as complication severity by Accordion grade increased (P = 0.02). The Accordion grading system is a useful tool to estimate short-term outcomes after right colectomy for cancer. High-grade Accordion complications are associated with longer hospital stay and increased risk of readmission and mortality. Published by Elsevier Inc.

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

Science.gov (United States)

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

2018-01-01

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

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.

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

DEFF Research Database (Denmark)

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

2013-01-01

Forecast-based flow prediction in drainage systems can be used to implement real-time control of drainage systems. This study compares two different types of rainfall forecast - a radar rainfall extrapolation-based nowcast model and a numerical weather prediction model. The models are applied...... performance of the system is found using the radar nowcast for the short lead times and the weather model for larger lead times....

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

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

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

Science.gov (United States)

Sperber, Richard D.

1976-01-01

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

The use of synthetic colloids in tracer transport experiments in saturated rock fractures

International Nuclear Information System (INIS)

Reimus, P.W.

1995-08-01

Studies of groundwater flow and contaminant transport in saturated, fractured geologic media are of great interest to researchers studying the potential long-term storage of hazardous wastes in or near such media. A popular technique for conducting such studies is to introduce tracers having different chemical and physical properties into a system and then observe the tracers at one or more downstream locations, inferring flow and transport mechanisms from the breakthrough characteristics of the different tracers. Many tracer studies have been conducted in saturated, fractured media to help develop and/or refine models capable of predicting contaminant transport over large scales in such media

Reassessment of primed constant-infusion tracer method to measure urea kinetics

International Nuclear Information System (INIS)

Jahoor, F.; Wolfe, R.R.

1987-01-01

The validity of the primed constant-infusion tracer technique to make short-term measurements of urea production rates (R/sub a/) in humans in a physiological steady state and during disruption of steady state was evaluated. Four subjects received a primed constant infusion (P/I = 560 min) of [ 13 C]urea for 8 h. A plateau in urea enrichment was reached after 2 h and maintained throughout. When [ 13 C]- and [ 18 O]urea were simultaneously infused into four subjects at P/I ratios of 560:1 and 360:1, respectively, both tracers reached plateau enrichment at the same time (2-4 h). The enrichment at plateau was a function of the infusion rate rather than the priming dose, and calculated urea R/sub a/ was the same with either prime. In five additional experiments the technique responded acutely to a physiological perturbation (alanine infusion) in a dose-dependent manner. The results confirm that this technique is appropriate for short-term measurements of urea R/sub a/, and the requirement for accuracy in estimating the priming dose is not impractically stringent

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

International Nuclear Information System (INIS)

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

2016-01-01

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

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

Science.gov (United States)

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

2017-07-01

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

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

Science.gov (United States)

Magen, Hagit; Emmanouil, Tatiana-Aloi; McMains, Stephanie A.; Kastner, Sabine; Treisman, Anne

2009-01-01

Limits to the capacity of visual short-term memory (VSTM) indicate a maximum storage of only 3 or 4 items. Recently, it has been suggested that activity in a specific part of the brain, the posterior parietal cortex (PPC), is correlated with behavioral estimates of VSTM capacity and might reflect a capacity-limited store. In three experiments that…

The Value of Median Nerve Sonography as a Predictor for Short- and Long-Term Clinical Outcomes in Patients with Carpal Tunnel Syndrome: A Prospective Long-Term Follow-Up Study.

Directory of Open Access Journals (Sweden)

Alexander Marschall

Full Text Available To investigate the prognostic value of B-mode and Power Doppler (PD ultrasound of the median nerve for the short- and long-term clinical outcomes of patients with carpal tunnel syndrome (CTS.Prospective study of 135 patients with suspected CTS seen 3 times: at baseline, then at short-term (3 months and long-term (15-36 months follow-up. At baseline, the cross-sectional area (CSA of the median nerve was measured with ultrasound at 4 levels on the forearm and wrist. PD signals were graded semi-quantitatively (0-3. Clinical outcomes were evaluated at each visit with the Boston Questionnaire (BQ and the DASH Questionnaire, as well as visual analogue scales for the patient's assessment of pain (painVAS and physician's global assessment (physVAS. The predictive values of baseline CSA and PD for clinical outcomes were determined with multivariate logistic regression models.Short-term and long-term follow-up data were available for 111 (82.2% and 105 (77.8% patients, respectively. There was a final diagnosis of CTS in 84 patients (125 wrists. Regression analysis revealed that the CSA, measured at the carpal tunnel inlet, predicted short-term clinical improvement according to BQ in CTS patients undergoing carpal tunnel surgery (OR 1.8, p = 0.05, but not in patients treated conservatively. Neither CSA nor PD assessments predicted short-term improvement of painVAS, physVAS or DASH, nor was any of the ultrasound parameters useful for the prediction of long-term clinical outcomes.Ultrasound assessment of the median nerve at the carpal tunnel inlet may predict short-term clinical improvement in CTS patients undergoing carpal tunnel release, but long-term outcomes are unrelated to ultrasound findings.

The Demonstration of Short-Term Consolidation.

Science.gov (United States)

Jolicoeur, Pierre; Dell'Acqua, Roberto

1998-01-01

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

Short-Term 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.

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

DEFF Research Database (Denmark)

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

2016-01-01

from the RADAR/JAPAN study to predict the effect of atrasentan on renal and heart failure outcomes. METHODS: We performed a post-hoc analysis of the RADAR/JAPAN randomized clinical trials in which 211 patients with type-2 diabetes and nephropathy were randomly assigned to atrasentan 0.75 mg/day, 1......BACKGROUND: A recent phase II clinical trial (Reducing Residual Albuminuria in Subjects with Diabetes and Nephropathy with AtRasentan trial and an identical trial in Japan (RADAR/JAPAN)) showed that the endothelin A receptor antagonist atrasentan lowers albuminuria, blood pressure, cholesterol......, hemoglobin, and increases body weight in patients with type 2 diabetes and nephropathy. We previously developed an algorithm, the Parameter Response Efficacy (PRE) score, which translates short-term drug effects into predictions of long-term effects on clinical outcomes. DESIGN: We used the PRE score on data...

Clinical Significance of the Prognostic Nutritional Index for Predicting Short- and Long-Term Surgical Outcomes After Gastrectomy: A Retrospective Analysis of 7781 Gastric Cancer Patients.

Science.gov (United States)

Lee, Jee Youn; Kim, Hyoung-Il; Kim, You-Na; Hong, Jung Hwa; Alshomimi, Saeed; An, Ji Yeong; Cheong, Jae-Ho; Hyung, Woo Jin; Noh, Sung Hoon; Kim, Choong-Bai

2016-05-01

To evaluate the predictive and prognostic significance of the prognostic nutritional index (PNI) in a large cohort of gastric cancer patients who underwent gastrectomy.Assessing a patient's immune and nutritional status, PNI has been reported as a predictive marker for surgical outcomes in various types of cancer.We retrospectively reviewed data from a prospectively maintained database of 7781 gastric cancer patients who underwent gastrectomy from January 2001 to December 2010 at a single center. From this data, we analyzed clinicopathologic characteristics, PNI, and short- and long-term surgical outcomes for each patient. We used the PNI value for the 10th percentile (46.70) of the study cohort as a cut-off for dividing patients into low and high PNI groups.Regarding short-term outcomes, multivariate analysis showed a low PNI (odds ratio [OR] = 1.505, 95% CI = 1.212-1.869, P cancer recurrence.

Tracer a application in marine outfall studies

International Nuclear Information System (INIS)

Genders, S.

1979-01-01

The applicability of radioactive and fluorescent tracers for field studies to predict or investigate waste water transport and dispersion from marine outfalls is evaluated. The application of either instantaneous or continuous tracer release, 'in situ' detection of tracers and data processing are considered. The necessity of a combined use of tracer techniques and conventional hydrographic methods for a statistical prediction of transport and dillution of waste water are pointed out. A procedure to determine an outlet distance from the coast, which satisfy bathing water criteria is outlined. (M.A.) [pt

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...

The roles of self-efficacy and motivation in the prediction of short- and long-term adherence to exercise among patients with coronary heart disease.

Science.gov (United States)

Slovinec D'Angelo, Monika E; Pelletier, Luc G; Reid, Robert D; Huta, Veronika

2014-11-01

Poor adherence to regular exercise is a documented challenge among people with heart disease. Identifying key determinants of exercise adherence and distinguishing between the processes driving short- and long-term adherence to regular exercise is a valuable endeavor. The purpose of the present study was to test a model of exercise behavior change, which incorporates motivational orientations and self-efficacy for exercise behavior, in the prediction of short- and long-term exercise adherence. Male and female patients (N = 801) hospitalized for coronary heart disease were recruited from 3 tertiary care cardiac centers and followed for a period of 1 year after hospital discharge. A prospective, longitudinal design was used to examine the roles of motivation and self-efficacy (measured at recruitment and at 2 and 6 months after discharge) in the prediction of exercise behavior at 6 and 12 months. Baseline measures of exercise and clinical and demographic covariates were included in the analyses. Structural equation modeling showed that both autonomous motivation and self-efficacy were important determinants of short-term (6-month) exercise behavior regulation, but that only autonomous motivation remained a significant predictor of long-term (12-month) exercise behavior. Self-efficacy partially mediated the relationship between motivation for exercise and 6-month exercise behavior. This research confirmed the roles of autonomous motivation and self-efficacy in the health behavior change process and emphasized the key function of autonomous motivation in exercise maintenance. Theoretical and cardiac rehabilitation program applications of this research are discussed. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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

Science.gov (United States)

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

2014-07-01

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

Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration

Energy Technology Data Exchange (ETDEWEB)

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

2017-08-23

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

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.

Short-term memory across eye blinks.

Science.gov (United States)

Irwin, David E

2014-01-01

The effect of eye blinks on short-term memory was examined in two experiments. On each trial, participants viewed an initial display of coloured, oriented lines, then after a retention interval they viewed a test display that was either identical or different by one feature. Participants kept their eyes open throughout the retention interval on some blocks of trials, whereas on others they made a single eye blink. Accuracy was measured as a function of the number of items in the display to determine the capacity of short-term memory on blink and no-blink trials. In separate blocks of trials participants were instructed to remember colour only, orientation only, or both colour and orientation. Eye blinks reduced short-term memory capacity by approximately 0.6-0.8 items for both feature and conjunction stimuli. A third, control, experiment showed that a button press during the retention interval had no effect on short-term memory capacity, indicating that the effect of an eye blink was not due to general motoric dual-task interference. Eye blinks might instead reduce short-term memory capacity by interfering with attention-based rehearsal processes.

Short-term memory and dual task performance

Science.gov (United States)

Regan, J. E.

1982-01-01

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

Association between early attention-deficit/hyperactivity symptoms and current verbal and visuo-spatial short-term memory.

Science.gov (United States)

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

2013-01-01

Deficits in short-term memory are common in adolescents with attention-deficit/hyperactivity disorder (ADHD), but their current ADHD symptoms cannot well predict their short-term performance. Taking a developmental perspective, we wanted to clarify the association between ADHD symptoms at early childhood and short-term memory in late childhood and adolescence. The participants included 401 patients with a clinical diagnosis of DSM-IV ADHD, 213 siblings, and 176 unaffected controls aged 8-17 years (mean age, 12.02 ± 2.24). All participants and their mothers were interviewed using the Chinese Kiddie Epidemiologic version of the Schedule for Affective Disorders and Schizophrenia to obtain information about ADHD symptoms and other psychiatric disorders retrospectively, at an earlier age first, then currently. The participants were assessed with the Wechsler Intelligence Scale for Children--3rd edition, including Digit Span, and the Spatial working memory task of the Cambridge Neuropsychological Test Automated Battery. Multi-level regression models were used for data analysis. Although crude analyses revealed that inattention, hyperactivity, and impulsivity symptoms significantly predicted deficits in short-term memory, only inattention symptoms had significant effects (all pshort-term memory at the current assessment. Therefore, our findings suggest that earlier inattention symptoms are associated with impaired verbal and visuo-spatial short-term memory at a later development stage. Impaired short-term memory in adolescence can be detected earlier by screening for the severity of inattention in childhood. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

International Nuclear Information System (INIS)

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

2016-01-01

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

Short-term 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 Memory as an Additional Predictor of School Achievement for Immigrant Children?

Science.gov (United States)

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

2004-01-01

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

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

Science.gov (United States)

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

2013-04-01

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

From probabilistic forecasts to statistical scenarios of short-term wind power production

DEFF Research Database (Denmark)

Pinson, Pierre; Papaefthymiou, George; Klockl, Bernd

2009-01-01

on the development of the forecast uncertainty through forecast series. However, this additional information may be paramount for a large class of time-dependent and multistage decision-making problems, e.g. optimal operation of combined wind-storage systems or multiple-market trading with different gate closures......Short-term (up to 2-3 days ahead) probabilistic forecasts of wind power provide forecast users with highly valuable information on the uncertainty of expected wind generation. Whatever the type of these probabilistic forecasts, they are produced on a per horizon basis, and hence do not inform....... This issue is addressed here by describing a method that permits the generation of statistical scenarios of short-term wind generation that accounts for both the interdependence structure of prediction errors and the predictive distributions of wind power production. The method is based on the conversion...

Short-term incentive schemes for hospital managers

Directory of Open Access Journals (Sweden)

Lucas Malambe

2013-10-01

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

Short-Term Intercultural Psychotherapy: Ethnographic Inquiry

Science.gov (United States)

Seeley, Karen M.

2004-01-01

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

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...

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

Science.gov (United States)

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

2017-07-03

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

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

Science.gov (United States)

Bakun, W.H.

1988-01-01

Aside from the goal of better understanding the Parkfield earthquake cycle, it is the intention of the U.S Geological Survey to attempt to issue a warning shortly before the anticipated earthquake. Although short-term earthquake warnings are not yet generally feasible, the wealth of information available for the previous significant Parkfield earthquakes suggests that if the next earthquake follows the pattern of "characteristic" Parkfield shocks, such a warning might be possible. Focusing on earthquake precursors reported for the previous  "characteristic" shocks, particulary the 1934 and 1966 events, the USGS developed a plan* in late 1985 on which to base earthquake warnings for Parkfield and has assisted State, county, and local officials in the Parkfield area to prepare a coordinated, reasonable response to a warning, should one be issued. 

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

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

DEFF Research Database (Denmark)

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

2012-01-01

Forecast based flow prediction in drainage systems can be used to implement real time control of drainage systems. This study compares two different types of rainfall forecasts – a radar rainfall extrapolation based nowcast model and a numerical weather prediction model. The models are applied...... performance of the system is found using the radar nowcast for the short leadtimes and weather model for larger lead times....

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

Science.gov (United States)

Binamé, Florence; Poncelet, Martine

2016-01-01

Recent theories of short-term memory (STM) distinguish between item information, which reflects the temporary activation of long-term representations stored in the language system, and serial-order information, which is encoded in a specific representational system that is independent of the language network. Some studies examining the…

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

Directory of Open Access Journals (Sweden)

Geethanjali SELVARETNAM

2014-11-01

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

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

In situ gaseous tracer diffusion experiments and predictive modeling at the Greater Confinement Disposal Test

International Nuclear Information System (INIS)

Olson, M.C.

1985-07-01

The Greater Confinement Disposal Test (GCDT) at the Nevada Test Site is a research project investigating the feasibility of augered shaft disposal of low-level radioactive waste considered unsuitable for shallow land burial. The GCDT contains environmentally mobile and high-specific-activity sources. Research is focused on providing a set of analytically derived hydrogeologic parameters and an empirical database for application in a multiphase, two-dimensional, transient, predictive performance model. Potential contaminant transport processes at the GCDT are identified and their level of significance is detailed. Nonisothermal gaseous diffusion through alluvial sediments is considered the primary waste migration process. Volatile organic tracers are released in the subsurface and their migration is monitored in situ to determine media effective diffusion coefficients, tortuosity, and sorption-corrected porosity terms. The theoretical basis for volatile tracer experiments is presented. Treatment of thermal and liquid flow components is discussed, as is the basis for eliminating several negligible transport processes. Interpretive techniques include correlation, power spectra, and least squares analysis, a graphical analytical solution, and inverse numerical modeling. Model design and application to the GCDT are discussed. GCDT structural, analytical, and computer facilities are detailed. The status of the current research program is reviewed, and temperature and soil moisture profiles are presented along with results of operational tests on the analytical system. 72 refs., 39 figs., 2 tabs

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)

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 Review on Predicting Fouling in RO Desalination

Directory of Open Access Journals (Sweden)

Alejandro Ruiz-García

2017-10-01

Full Text Available Reverse Osmosis (RO membrane fouling is one of the main challenges that membrane manufactures, the scientific community and industry professionals have to deal with. The consequences of this inevitable phenomenon have a negative effect on the performance of the desalination system. Predicting fouling in RO systems is key to evaluating the long-term operating conditions and costs. Much research has been done on fouling indices, methods, techniques and prediction models to estimate the influence of fouling on the performance of RO systems. This paper offers a short review evaluating the state of industry knowledge in the development of fouling indices and models in membrane systems for desalination in terms of use and applicability. Despite major efforts in this field, there are gaps in terms of effective methods and models for the estimation of fouling in full-scale RO desalination plants. In existing models applied to full-scale RO desalination plants, neither the spacer geometry of membranes, nor the efficiency and frequency of chemical cleanings are considered.

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

Directory of Open Access Journals (Sweden)

Kristina M Visscher

2007-03-01

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

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

Science.gov (United States)

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

2007-03-01

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

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

International Nuclear Information System (INIS)

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

2016-01-01

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

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.

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

Science.gov (United States)

Jedlovec, Gary J.; Molthan, Andrew; Zavodsky, Bradley T.; Case, Jonathan L.; LaFontaine, Frank J.; Srikishen, Jayanthi

2010-01-01

The NASA Short-term Prediction Research and Transition Center (SPoRT)'s new "Weather in a Box" resources will provide weather research and forecast modeling capabilities for real-time application. Model output will provide additional forecast guidance and research into the impacts of new NASA satellite data sets and software capabilities. By combining several research tools and satellite products, SPoRT can generate model guidance that is strongly influenced by unique NASA contributions.

Generation of statistical scenarios of short-term wind power production

DEFF Research Database (Denmark)

Pinson, Pierre; Papaefthymiou, George; Klockl, Bernd

2007-01-01

Short-term (up to 2-3 days ahead) probabilistic forecasts of wind power provide forecast users with a paramount information on the uncertainty of expected wind generation. Whatever the type of these probabilistic forecasts, they are produced on a per horizon basis, and hence do not inform...... on the development of the forecast uncertainty through forecast series. This issue is addressed here by describing a method that permits to generate statistical scenarios of wind generation that accounts for the interdependence structure of prediction errors, in plus of respecting predictive distributions of wind...

Predicting short and long-term exercise intentions and behaviour in patients with coronary artery disease: A test of protection motivation theory.

Science.gov (United States)

Tulloch, Heather; Reida, Robert; D'Angeloa, Monika Slovinec; Plotnikoff, Ronald C; Morrina, Louise; Beatona, Louise; Papadakisa, Sophia; Pipe, Andrew

2009-03-01

The purpose of this study was to examine the utility of protection motivation theory (PMT) in the prediction of exercise intentions and behaviour in the year following hospitalisation for coronary artery disease (CAD). Patients with documented CAD (n = 787), recruited at hospital discharge, completed questionnaires measuring PMT's threat (i.e. perceived severity and vulnerability) and coping (i.e. self-efficacy, response efficacy) appraisal constructs at baseline, 2 and 6 months, and exercise behaviour at baseline, 6 and 12 months post-hospitalisation. Structural equation modelling showed that the PMT model of exercise at 6 months had a good fit with the empirical data. Self-efficacy, response efficacy, and perceived severity predicted exercise intentions, which, in turn predicted exercise behaviour. Overall, the PMT variables accounted for a moderate amount of variance in exercise intentions (23%) and behaviour (20%). In contrast, the PMT model was not reliable for predicting exercise behaviour at 12 months post-hospitalisation. The data provided support for PMT applied to short-term, but not long-term, exercise behaviour among patients with CAD. Health education should concentrate on providing positive coping messages to enhance patients' confidence regarding exercise and their belief that exercise provides health benefits, as well as realistic information about disease severity.

Compilation and analyses of results from cross-hole tracer tests with conservative tracers

Energy Technology Data Exchange (ETDEWEB)

Hjerne, Calle; Nordqvist, Rune; Harrstroem, Johan (Geosigma AB (Sweden))

2010-09-15

Radionuclide transport in hydrogeological formations is one of the key factors for the safety analysis of a future repository of nuclear waste. Tracer tests have therefore been an important field method within the SKB investigation programmes at several sites since the late 1970's. This report presents a compilation and analyses of results from cross-hole tracer tests with conservative tracers performed within various SKB investigations. The objectives of the study are to facilitate, improve and reduce uncertainties in predictive tracer modelling and to provide supporting information for SKB's safety assessment of a final repository of nuclear waste. More specifically, the focus of the report is the relationship between the tracer mean residence time and fracture hydraulic parameters, i.e. the relationship between mass balance aperture and fracture transmissivity, hydraulic diffusivity and apparent storativity. For 74 different combinations of pumping and injection section at six different test sites (Studsvik, Stripa, Finnsjoen, Aespoe, Forsmark, Laxemar), estimates of mass balance aperture from cross-hole tracer tests as well as transmissivity were extracted from reports or in the SKB database Sicada. For 28 of these combinations of pumping and injection section, estimates of hydraulic diffusivity and apparent storativity from hydraulic interference tests were also found. An empirical relationship between mass balance aperture and transmissivity was estimated, although some uncertainties for individual data exist. The empirical relationship between mass balance aperture and transmissivity presented in this study deviates considerably from other previously suggested relationships, such as the cubic law and transport aperture as suggested by /Dershowitz and Klise 2002/, /Dershowitz et al. 2002/ and /Dershowitz et al. 2003/, which also is discussed in this report. No clear and direct empirical relationship between mass balance aperture and hydraulic

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-07-26

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

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

Science.gov (United States)

Molthan, Andrew L.; Burks, Jason E.; McGrath, Kevin M.; Jedlovec, Gary J.

2012-01-01

NASA s Short-term Prediction Research and Transition (SPoRT) Center supports the transition of unique NASA and NOAA research activities to the operational weather forecasting community. SPoRT emphasizes real-time analysis and prediction out to 48 hours. SPoRT partners with NOAA s National Weather Service (NWS) Weather Forecast Offices (WFOs) and National Centers to improve current products, demonstrate future satellite capabilities and explore new data assimilation techniques. Recently, the SPoRT Center has been involved in several activities related to disaster response, in collaboration with NOAA s National Weather Service, NASA s Applied Sciences Disasters Program, and other partners.

A comparison of measurements and calculations for the Stripa tracer experiments

International Nuclear Information System (INIS)

Hodgkinson, D.P.; Copper, N.S.

1992-03-01

This paper presents a comparison of measurements and predictions for migration of tracers from boreholes to the validation drift and to other boreholes in the Site Characterisation and Validation (SCV) block. The comparison was carried out on behalf of the Stripa task force on fracture flow modelling. The paper summarises the radar/saline tracer experiments, the tracer migration experiment observations and reviews the fracture flow and tracer transport modelling approaches and predictions made by AEA Technology, Fracflow Consultants, Golder Associates and Lawrence Berkeley Laboratory. The predictions are compared with the observed breakthrough curves on the basis of the validation process and criteria defined by the task force. The results of all four modelling groups met the validation criteria, with the predictions of the tracer breakthrough concentrations and times being within an order of magnitude of the observations. Also the AEA and Golder approaches allow the spatial distribution of tracer breakthrough into the validation drift to be predicted and these predictions also showed reasonable accuracy. The successful completion of this project demonstrates the feasibility of discrete fracture flow and tracer transport modelling. (36 refs.) (au)

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...

Labeling of hepatic glycogen after short- and long-term stimulation of glycogen synthesis in rats injected with 3H-galactose

International Nuclear Information System (INIS)

Michaels, J.E.; Garfield, S.A.; Hung, J.T.; Cardell, R.R. Jr.

1990-01-01

The effects of short- and long-term stimulation of glycogen synthesis elicited by dexamethasone were studied by light (LM) and electron (EM) microscopic radioautography (RAG) and biochemical analysis. Adrenalectomized rats were fasted overnight and pretreated for short- (3 hr) or long-term (14 hr) periods with dexamethasone prior to intravenous injection of tracer doses of 3H-galactose. Analysis of LM-RAGs from short-term rats revealed that about equal percentages (44%) of hepatocytes became heavily or lightly labeled 1 hr after labeling. The percentage of heavily labeled cells increased slightly 6 hr after labeling, and unlabeled glycogen became apparent in some hepatocytes. The percentage of heavily labeled cells had decreased somewhat 12 hr after labeling, and more unlabeled glycogen was evident. In the long-term rats 1 hr after labeling, a higher percentage of heavily labeled cells (76%) was observed compared to short-term rats, and most glycogen was labeled. In spite of the high amount of labeling seen initially, the percentage of heavily labeled hepatocytes had decreased considerably to 55% by 12 hr after injection; and sparsely labeled and unlabeled glycogen was prevalent. The EM-RAGs of both short- and long-term rats were similar. Silver grains were associated with glycogen patches 1 hr after labeling; 12 hr after labeling, the glycogen patches had enlarged; and label, where present, was dispersed over the enlarged glycogen clumps. Analysis of DPM/mg tissue corroborated the observed decrease in label 12 hr after administration in the long-term animals. The loss of label observed 12 hr after injection in the long-term pretreated rats suggests that turnover of glycogen occurred during this interval despite the net accumulation of glycogen that was visible morphologically and evident from biochemical measurement

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

Directory of Open Access Journals (Sweden)

Dinh V.T.

2018-01-01

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

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

Science.gov (United States)

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

2018-05-01

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

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...

Short-term prediction of local wind conditions

DEFF Research Database (Denmark)

Landberg, L.

2001-01-01

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

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

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

Science.gov (United States)

Molecular Thresholds for Early Key Events in Liver Tumorgensis: PhthalateCase StudyTriangleShort-term changes in molecular profiles are a central component of strategies to model health effects of environmental chemicals such as phthalates, for which there is widespread human exp...

The prediction of the level of personality organization on reduction of psychiatric symptoms and improvement of work ability in short- versus long-term psychotherapies during a 5-year follow-up.

Science.gov (United States)

Knekt, Paul; Lindfors, Olavi; Keinänen, Matti; Heinonen, Erkki; Virtala, Esa; Härkänen, Tommi

2017-09-01

How level of personality organization (LPO) predicts psychiatric symptoms and work ability in short- versus long-term psychotherapies is poorly known. We investigated the importance of the LPO on the benefits of short-term versus long-term psychotherapies. A cohort study based on 326 outpatients with mood or anxiety disorder was allocated to long-term (LPP) and short-term (SPP) psychodynamic psychotherapy, and solution-focused therapy (SFT). The LPO was assessed by interview at baseline and categorized into neuroses and higher level borderline. Outcome was assessed at baseline and 4-9 times during a 5-year follow-up, using self-report and interview-based measures of symptoms and work ability. For patients receiving SPP, improvement in work ability, symptom reduction, and the remission rate were more considerable in patients with neuroses than in higher level borderline patients, whereas LPP or SFT showed no notable differences in effectiveness in the two LPO groups. In patients with neuroses, improvement was more considerable in the short-term therapy groups during the first year of follow-up, and in higher level borderline patients LPP was more effective after 3 years of follow-up. The remission rate, defined as both symptom reduction and lack of auxiliary treatment, was higher in LPP than in SPP for both the LPO groups considered. In neuroses, short-term psychotherapy was associated with a more rapid reduction of symptoms and increase in work ability, whereas LPP was more effective for longer follow-ups in both LPO groups. Further large-scale studies are needed. Level of personality organization is relevant for selection between short- and long-term psychotherapies. Short-term therapy gives faster benefits for neurotic patients but not for patients with higher level borderline personality organization. Sustained remission from symptoms is more probable after long-term than short-term therapy. © 2016 The British Psychological Society.

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-12-15

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

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

USING PERFLUOROCARBON TRACERS FOR VERIFICATION OF CAP AND COVER SYSTEMS PERFORMANCE

International Nuclear Information System (INIS)

HEISER, J.; SULLIVAN, T.

2001-01-01

The Department of Energy (DOE) Environmental Management (EM) office has committed itself to an accelerated cleanup of its national facilities. The goal is to have much of the DOE legacy waste sites remediated by 2006. This includes closure of several sites (e.g., Rocky Flats and Fernald). With the increased focus on accelerated cleanup, there has been considerable concern about long-term stewardship issues in general, and verification and long-term monitoring (LTM) of caps and covers, in particular. Cap and cover systems (covers) are vital remedial options that will be extensively used in meeting these 2006 cleanup goals. Every buried waste site within the DOE complex will require some form of cover system. These covers are expected to last from 100 to 1000 years or more. The stakeholders can be expected to focus on system durability and sustained performance. DOE EM has set up a national committee of experts to develop a long-term capping (LTC) guidance document. Covers are subject to subsidence, erosion, desiccation, animal intrusion, plant root infiltration, etc., all of which will affect the overall performance of the cover. Very little is available in terms of long-term monitoring other than downstream groundwater or surface water monitoring. By its very nature, this can only indicate that failure of the cover system has already occurred and contaminants have been transported away from the site. This is unacceptable. Methods that indicate early cover failure (prior to contaminant release) or predict approaching cover failure are needed. The LTC committee has identified predictive monitoring technologies as a high priority need for DOE, both for new covers as well as existing covers. The same committee identified a Brookhaven National Laboratory (BNL) technology as one approach that may be capable of meeting the requirements for LTM. The Environmental Research and Technology Division (ERTD) at BNL developed a novel methodology for verifying and monitoring

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.

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

Science.gov (United States)

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

2014-11-01

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

Representation of tropical deep convection in atmospheric models – Part 2: Tracer transport

Directory of Open Access Journals (Sweden)

C. R. Hoyle

2011-08-01

Full Text Available The tropical transport processes of 14 different models or model versions were compared, within the framework of the SCOUT-O3 (Stratospheric-Climate Links with Emphasis on the Upper Troposphere and Lower Stratosphere project. The tested models range from the regional to the global scale, and include numerical weather prediction (NWP, chemical transport, and chemistry-climate models. Idealised tracers were used in order to prevent the model's chemistry schemes from influencing the results substantially, so that the effects of modelled transport could be isolated. We find large differences in the vertical transport of very short-lived tracers (with a lifetime of 6 h within the tropical troposphere. Peak convective outflow altitudes range from around 300 hPa to almost 100 hPa among the different models, and the upper tropospheric tracer mixing ratios differ by up to an order of magnitude. The timing of convective events is found to be different between the models, even among those which source their forcing data from the same NWP model (ECMWF. The differences are less pronounced for longer lived tracers, however they could have implications for modelling the halogen burden of the lowermost stratosphere through transport of species such as bromoform, or short-lived hydrocarbons into the lowermost stratosphere. The modelled tracer profiles are strongly influenced by the convective transport parameterisations, and different boundary layer mixing parameterisations also have a large impact on the modelled tracer profiles. Preferential locations for rapid transport from the surface into the upper troposphere are similar in all models, and are mostly concentrated over the western Pacific, the Maritime Continent and the Indian Ocean. In contrast, models do not indicate that upward transport is highest over western Africa.

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

Directory of Open Access Journals (Sweden)

Qiang Shang

2016-08-01

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

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

Science.gov (United States)

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

2018-06-01

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

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

Science.gov (United States)

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

2015-08-01

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

Short-term predictions in forex trading

Science.gov (United States)

Muriel, A.

2004-12-01

Using a kinetic equation that is used to model turbulence (Physica A, 1985-1988, Physica D, 2001-2003), we redefine variables to model the time evolution of the foreign exchange rates of three major currencies. We display live and predicted data for one period of trading in October, 2003.

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

DEFF Research Database (Denmark)

Tastu, Julija

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

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

Prediction of Short- and Medium-term Efficacy of Biosimilar Infliximab Therapy. Do Trough Levels and Antidrug Antibody Levels or Clinical And Biochemical Markers Play the More Important Role?

Science.gov (United States)

Gonczi, Lorant; Vegh, Zsuzsanna; Golovics, Petra Anna; Rutka, Mariann; Gecse, Krisztina Barbara; Bor, Renata; Farkas, Klaudia; Szamosi, Tamás; Bene, László; Gasztonyi, Beáta; Kristóf, Tünde; Lakatos, László; Miheller, Pál; Palatka, Károly; Papp, Mária; Patai, Árpád; Salamon, Ágnes; Tóth, Gábor Tamás; Vincze, Áron; Biro, Edina; Lovasz, Barbara Dorottya; Kurti, Zsuzsanna; Szepes, Zoltan; Molnár, Tamás; Lakatos, Péter L

2017-06-01

Biosimilar infliximab CT-P13 received European Medicines Agency [EMA] approval in June 2013 for all indications of the originator product. In the present study, we aimed to evaluate the predictors of short- and medium-term clinical outcome in patients treated with the biosimilar infliximab at the participating inflammatory bowel disease [IBD] centres in Hungary. Demographic data were collected and a harmonised monitoring strategy was applied. Clinical and biochemical activities were evaluated at Weeks 14, 30, and 54. Trough level [TL] and anti-drug antibody [ADA] concentrations were measured by enzyme-linked immunosorbent assay [ELISA] [LT-005, Theradiag, France] at baseline at 14, 30 and 54 weeks and in two centres at Weeks 2 and 6. A total of 291 consecutive IBD patients (184 Crohn's disease [CD] and 107 ulcerative colitis [UC]) were included. In UC, TLs at Week 2 predicted both clinical response and remission at Weeks 14 and 30 (clinical response/remission at Week 14: area under the curve [AUC] = 0.81, p < 0.001, cut-off: 11.5 μg/ml/AUC = 0.79, p < 0.001, cut-off: 15.3μg/ml; clinical response/remission at Week 30: AUC = 0.79, p = 0.002, cut-off: 11.5 μg/ml/AUC = 0.74, p = 0.006, cut-off: 14.5 μg/ml), whereas ADA positivity at Week 14 was inversely associated with clinical response at Week 30 [58.3% vs 84.8% ,p = 0.04]. Previous anti-tumour necrosis factor [TNF] exposure was inversely associated with short-term clinical remission [Week 2: 18.8% vs 47.8%, p = 0.03, at Week 6: 38.9% vs 69.7%, p = 0.013, at Week 14: 37.5% vs 2.5%, p = 0.06]. In CD, TLs at Week 2 predicted short-term [Week 14 response/remission, AUCTLweek2 = 0.715-0.721, p = 0.05/0.005] but not medium-term clinical efficacy. In addition, early ADA status by Week 14 [p = 0.04-0.05 for Weeks 14 and 30], early clinical response [p < 0.001 for Weeks 30/54] and normal C-reactive protein [CRP] at Week 14 [p = 0.005-0.0001] and previous anti-TNF exposure [p = 0.03-0.0001 for Weeks 14, 30, and 54] were

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.

Tracers of air-sea gas exchange

International Nuclear Information System (INIS)

Liss, P.S.

1988-01-01

The flux of gas across the air-sea interface is determined by the product of the interfacial concentration difference driving the exchange and a rate constant, often termed the transfer velocity. The concentration-difference term is generally obtained by direct measurement, whereas more indirect approaches are required to estimate the transfer velocity and its variation as a function of controlling parameters such as wind and sea state. Radioactive tracers have proved particularly useful in the estimation of air-sea transfer velocities and, recently, stable purposeful tracers have also started to be used. In this paper the use of the following tracers to determine transfer velocities at the sea surface is discussed: natural and bomb-produced 14 C, dissolved oxygen, 222 Rn and sulphur hexafluoride. Other topics covered include the relation between transfer velocity and wind speed as deduced from tracer and wind-tunnel studies, and the discrepancy between transfer velocities determined by using tracers and from eddy correlation measurements in the atmosphere. (author)

Women's fertility across the cycle increases the short-term attractiveness of creative intelligence.

Science.gov (United States)

Haselton, Martie G; Miller, Geoffrey F

2006-03-01

Male provisioning ability may have evolved as a "good dad" indicator through sexual selection, whereas male creativity may have evolved partly as a "good genes" indicator. If so, women near peak fertility (midcycle) should prefer creativity over wealth, especially in short-term mating. Forty-one normally cycling women read vignettes describing creative but poor men vs. uncreative but rich men. Women's estimated fertility predicted their short-term (but not long-term) preference for creativity over wealth, in both their desirability ratings of individual men (r=.40, p<.01) and their forced-choice decisions between men (r=.46, p<.01). These preliminary results are consistent with the view that creativity evolved at least partly as a good genes indicator through mate choice.

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

OpenAIRE

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

2003-01-01

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

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.

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.

Distinct electrophysiological indices of maintenance in auditory and visual short-term memory.

Science.gov (United States)

Lefebvre, Christine; Vachon, François; Grimault, Stephan; Thibault, Jennifer; Guimond, Synthia; Peretz, Isabelle; Zatorre, Robert J; Jolicœur, Pierre

2013-11-01

We compared the electrophysiological correlates for the maintenance of non-musical tones sequences in auditory short-term memory (ASTM) to those for the short-term maintenance of sequences of coloured disks held in visual short-term memory (VSTM). The visual stimuli yielded a sustained posterior contralateral negativity (SPCN), suggesting that the maintenance of sequences of coloured stimuli engaged structures similar to those involved in the maintenance of simultaneous visual displays. On the other hand, maintenance of acoustic sequences produced a sustained negativity at fronto-central sites. This component is named the Sustained Anterior Negativity (SAN). The amplitude of the SAN increased with increasing load in ASTM and predicted individual differences in the performance. There was no SAN in a control condition with the same auditory stimuli but no memory task, nor one associated with visual memory. These results suggest that the SAN is an index of brain activity related to the maintenance of representations in ASTM that is distinct from the maintenance of representations in VSTM. © 2013 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

Qiu, Yunfei; Li, Xizhong; Zheng, Wei; Hu, Qinghe; Wei, Zhanmeng; Yue, Yaqin

2017-08-01

The climate changes have great impact on the residents’ electricity consumption, so the study on the impact of climatic factors on electric power load is of significance. In this paper, the effects of the data of temperature, rainfall and wind of smart city on short-term power load is studied to predict power load. The authors studied the relation between power load and daily temperature, rainfall and wind in the 31 days of January of one year. In the research, the authors used the Matlab neural network toolbox to establish the combinational forecasting model. The authors trained the original input data continuously to get the internal rules inside the data and used the rules to predict the daily power load in the next January. The prediction method relies on the accuracy of weather forecasting. If the weather forecasting is different from the actual weather, we need to correct the climatic factors to ensure accurate prediction.

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.

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 ...

Tracer simulation using a global general circulation model: Results from a midlatitude instantaneous source experiment

International Nuclear Information System (INIS)

Mahlman, J.D.; Moxim, W.J.

1978-01-01

An 11-level general circulation model with seasonal variation is used to perform an experiment on the dispersion of passive tracers. Specially constructed time-dependent winds from this model are used as input to a separate tracer model. The methodologies employed to construct the tracer model are described.The experiment presented is the evolution of a hypothetical instantaneous source of tracer on 1 Janaury with maximum initial concentration at 65 mb, 36 0 N, 180 0 E. The tracer is assumed to have no sources or sinks in the stratosphere, but is subject to removal processes in the lower troposphere.The experimental results reveal a number of similarities to observed tracer behavior, including the average poleward-downward slope of mixing ratio isopleths, strong tracer gradients across the tropopause, intrusion of tracer into the Southern Hemisphere lower stratosphere, and the long-term interhemispheric exchange rate. The model residence times show behavior intermediate to those exhibited for particulate radioactive debris and gaseous C 14 O 2 . This suggests that caution should be employed when either radioactive debris or C 14 O 2 data are used to develop empirical models for prediction of gaseous tracers which are efficiently removed in the troposphere.In this experiment, the tracer mixing ratio and potential vorticity evolve to very high correlations. Mechanisms for this correlation are discussed. The zonal mean tracer balances exhibit complex behavior among the various transport terms. At early stages, the tracer evolution is dominated by eddy effects. Later, a very large degree of self-cancellation between mean cell and eddy effects is observed. During seasonal transitions, however, this self-cancellation diminishes markedly, leading to significant changes in the zonal mean tracer distribution. A possible theoretical explanation is presented

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.

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

Science.gov (United States)

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

2016-09-01

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

Long residence times - bad tracer tests?

Science.gov (United States)

Ghergut, Julia; Behrens, Horst; Sauter, Martin

2015-04-01

Tracer tests conducted at geothermal well doublets or triplets in the Upper Rhine Rift Valley [1] all face, with very few exceptions so far, one common issue: lack of conclusive tracer test results, or tracer signals still undetectable for longer than one or two years after tracer injection. While the reasons for this surely differ from site to site (Riehen, Landau, Insheim, Bruchsal, ...), its effects on how the usefulness of tracer tests is perceived by the non-tracer community are pretty much the same. The 'poor-signal' frustration keeps nourishing two major 'alternative' endeavours : (I) design and execute tracer tests in single-well injection-withdrawal (push-pull), 'instead of' inter-well flow-path tracing configurations; (II) use 'novel' tracer substances instead of the 'old' ones which have 'obviously failed'. Frustration experienced with most inter-well tracer tests in the Upper Rhine Rift Valley has also made them be regarded as 'maybe useful for EGS' ('enhanced', or 'engineered' geothermal systems, whose fluid RTD typically include a major share of values below one year), but 'no longer worthwhile a follow-up sampling' in natural, large-scale hydrothermal reservoirs. We illustrate some of these arguments with the ongoing Bruchsal case [2]. The inter-well tracer test conducted at Bruchsal was (and still is!) aimed at assessing inter-well connectivity, fluid residence times, and characterizing the reservoir structure [3]. Fluid samples taken at the geothermal production well after reaching a fluid turnover of about 700,000 m3 showed tracer concentrations in the range of 10-8 Minj per m3, in the liquid phase of each sample (Minj being the total quantity of tracer injected as a short pulse at the geothermal re-injection well). Tracer signals might actually be higher, owing to tracer amounts co-precipitated and/or adsorbed onto the solid phase whose accumulation in the samples was unavoidable (due to pressure relief and degassing during the very sampling

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

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)

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...

Stable isotope tracers and exercise physiology: past, present and future.

Science.gov (United States)

Wilkinson, Daniel J; Brook, Matthew S; Smith, Kenneth; Atherton, Philip J

2017-05-01

Stable isotope tracers have been invaluable assets in physiological research for over 80 years. The application of substrate-specific stable isotope tracers has permitted exquisite insight into amino acid, fatty-acid and carbohydrate metabolic regulation (i.e. incorporation, flux, and oxidation, in a tissue-specific and whole-body fashion) in health, disease and response to acute and chronic exercise. Yet, despite many breakthroughs, there are limitations to 'substrate-specific' stable isotope tracers, which limit physiological insight, e.g. the need for intravenous infusions and restriction to short-term studies (hours) in controlled laboratory settings. In recent years significant interest has developed in alternative stable isotope tracer techniques that overcome these limitations, in particular deuterium oxide (D 2 O or heavy water). The unique properties of this tracer mean that through oral administration, the turnover and flux through a number of different substrates (muscle proteins, lipids, glucose, DNA (satellite cells)) can be monitored simultaneously and flexibly (hours/weeks/months) without the need for restrictive experimental control. This makes it uniquely suited for the study of 'real world' human exercise physiology (amongst many other applications). Moreover, using D 2 O permits evaluation of turnover of plasma and muscle proteins (e.g. dynamic proteomics) in addition to metabolomics (e.g. fluxomics) to seek molecular underpinnings, e.g. of exercise adaptation. Here, we provide insight into the role of stable isotope tracers, from substrate-specific to novel D 2 O approaches, in facilitating our understanding of metabolism. Further novel potential applications of stable isotope tracers are also discussed in the context of integration with the snowballing field of 'omic' technologies. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

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

Science.gov (United States)

Norris, Dennis

2017-09-01

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

Fast Weight Long Short-Term Memory

OpenAIRE

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

2018-01-01

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

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

Science.gov (United States)

Angelier, Frédéric; Parenteau, Charline; Trouvé, Colette; Angelier, Nicole

2016-12-01

Although the transfer of wild animals to captivity is crucial for conservation purposes, this process is often challenging because some species or individuals do not adjust well to captive conditions. Chronic stress has been identified as a major concern for animals held on long-term captivity. Surprisingly, the first hours or days of captivity have been relatively overlooked. However, they are certainly very stressful, because individuals are being transferred to a totally novel and confined environment. To ensure the success of conservation programmes, it appears crucial to better understand the proximate causes of interspecific and interindividual variability in the sensitivity to these first hours of captivity. In that respect, the study of stress hormones is relevant, because the hormonal stress response may help to assess whether specific individuals or species adjust, or not, to such captive conditions ('the stress response-adjustment to captivity hypothesis'). We tested this hypothesis in rock pigeons by measuring their corticosterone stress response and their ability to adjust to short-term captivity (body mass loss and circulating corticosterone levels after a day of captivity). We showed that an increased corticosterone stress response is associated with a lower ability to adjust to short-term captivity (i.e. higher body mass loss and circulating corticosterone levels). Our study suggests, therefore, that a low physiological sensitivity to stress may be beneficial for adjusting to captivity. Future studies should now explore whether the stress response can be useful to predict the ability of individuals from different populations or species to not only adjust to short-term but also long-term captivity.

A 82Br tracer study of coastal groundwater movement at Hat Head, NSW

International Nuclear Information System (INIS)

Hughes, C.; Stone, D.

2003-01-01

At Hat Head, NSW, on the eastern Australian coast, a radioisotope tracer study of groundwater flow in response to tidal forcing was conducted adjacent to a tidal creek. Using radiotracer, 82 Br, groundwater movement was tracked in-situ over 5 days on two occasions encompassing both neap and spring tide conditions. The tracer was injected into one borehole and gamma counts monitored from an adjacent borehole using NaI(Th) detectors. This technique maps the path of the slow moving tracer without sampling and allows the net groundwater movement to be distinguished from short term tidally driven fluxes. During the neap tide period net groundwater movement of 0.1 m/d was observed with horizontal tidal fluctuations in the order of 0.04 m. This contrasts with the tidally dominated spring tide period where net groundwater movement was negligible but tidally driven fluctuations of up to 0.13 m were observed

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

Science.gov (United States)

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

2011-12-01

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

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

Short-Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm

Directory of Open Access Journals (Sweden)

Jianzhou Wang

2015-01-01

Full Text Available This paper develops an effectively intelligent model to forecast short-term wind speed series. A hybrid forecasting technique is proposed based on recurrence plot (RP and optimized support vector regression (SVR. Wind caused by the interaction of meteorological systems makes itself extremely unsteady and difficult to forecast. To understand the wind system, the wind speed series is analyzed using RP. Then, the SVR model is employed to forecast wind speed, in which the input variables are selected by RP, and two crucial parameters, including the penalties factor and gamma of the kernel function RBF, are optimized by various optimization algorithms. Those optimized algorithms are genetic algorithm (GA, particle swarm optimization algorithm (PSO, and cuckoo optimization algorithm (COA. Finally, the optimized SVR models, including COA-SVR, PSO-SVR, and GA-SVR, are evaluated based on some criteria and a hypothesis test. The experimental results show that (1 analysis of RP reveals that wind speed has short-term predictability on a short-term time scale, (2 the performance of the COA-SVR model is superior to that of the PSO-SVR and GA-SVR methods, especially for the jumping samplings, and (3 the COA-SVR method is statistically robust in multi-step-ahead prediction and can be applied to practical wind farm applications.

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

Directory of Open Access Journals (Sweden)

Juan Du

2018-05-01

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

Use of sulfur hexafluoride and perfluorocarbon tracers in plutonium storage containers for leak detection

International Nuclear Information System (INIS)

Kung, J.K.

1998-05-01

This study involves an investigation of the feasibility of a tracer-based leak detection system for long-term interim plutonium storage. In particular, a protocol has been developed based on the use of inert tracers with varying concentrations in order to open-quotes fingerprintclose quotes or open-quotes tagclose quotes specific containers. A particular combination of tracers at specific ratios could be injected into the free volume of each container, allowing for the detection of leaks as well as determination of the location of leaking containers. Based on plutonium storage considerations, sulfur hexafluoride and four perfluorocarbon tracers were selected and should allow a wide range of viable fingerprinting combinations. A open-quotes high-lowclose quotes protocol which uses two distinct chromatographic peak areas or concentration levels, is recommended. Combinations of air exchange rates, detection durations, and detectability limits are examined in order to predict minimum tracer concentrations required for injection in storage containers

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

OpenAIRE

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

2009-01-01

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

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1999-03-01

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

Operative factors associated with short-term outcome in horses with large colon volvulus: 47 cases from 2006 to 2013.

Science.gov (United States)

Gonzalez, L M; Fogle, C A; Baker, W T; Hughes, F E; Law, J M; Motsinger-Reif, A A; Blikslager, A T

2015-05-01

There is an important need for objective parameters that accurately predict the outcome of horses with large colon volvulus. To evaluate the predictive value of a series of histomorphometric parameters on short-term outcome, as well as the impact of colonic resection on horses with large colon volvulus. Retrospective cohort study. Adult horses admitted to the Equine and Farm Animal Veterinary Center at North Carolina State University, Peterson and Smith and Chino Valley Equine Hospitals between 2006 and 2013 that underwent an exploratory coeliotomy, diagnosed with large colon volvulus of ≥360 degrees, where a pelvic flexure biopsy was obtained, and that recovered from general anaesthesia, were selected for inclusion in the study. Logistic regression was used to determine associations between signalment, histomorphometric measurements of interstitium-to-crypt ratio, degree of haemorrhage, percentage loss of luminal and glandular epithelium, as well as colonic resection with short-term outcome (discharge from the hospital). Pelvic flexure biopsies from 47 horses with large colon volvulus were evaluated. Factors that were significantly associated with short-term outcome on univariate logistic regression were Thoroughbred breed (P = 0.04), interstitium-to-crypt ratio >1 (P = 0.02) and haemorrhage score ≥3 (P = 0.005). Resection (P = 0.92) was not found to be associated significantly with short-term outcome. No combined factors increased the likelihood of death in forward stepwise logistic regression modelling. A digitally quantified measurement of haemorrhage area strengthened the association of haemorrhage with nonsurvival in cases of large colon volvulus. Histomorphometric measurements of interstitium-to-crypt ratio and degree of haemorrhage predict short-term outcome in cases of large colon volvulus. Resection was not associated with short-term outcome in horses selected for this study. Accurate quantification of mucosal haemorrhage at the time of surgery may

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.

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

Science.gov (United States)

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

2015-04-01

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

Familiarity speeds up visual short-term memory consolidation.

Science.gov (United States)

Xie, Weizhen; Zhang, Weiwei

2017-06-01

Existing long-term memory (LTM) can boost the number of retained representations over a short delay in visual short-term memory (VSTM). However, it is unclear whether and how prior LTM affects the initial process of transforming fragile sensory inputs into durable VSTM representations (i.e., VSTM consolidation). The consolidation speed hypothesis predicts faster consolidation for familiar relative to unfamiliar stimuli. Alternatively, the perceptual boost hypothesis predicts that the advantage in perceptual processing of familiar stimuli should add a constant boost for familiar stimuli during VSTM consolidation. To test these competing hypotheses, the present study examined how the large variance in participants' prior multimedia experience with Pokémon affected VSTM for Pokémon. In Experiment 1, the amount of time allowed for VSTM consolidation was manipulated by presenting consolidation masks at different intervals after the onset of to-be-remembered Pokémon characters. First-generation Pokémon characters that participants were more familiar with were consolidated faster into VSTM as compared with recent-generation Pokémon characters that participants were less familiar with. These effects were absent in participants who were unfamiliar with both generations of Pokémon. Although familiarity also increased the number of retained Pokémon characters when consolidation was uninterrupted but still incomplete due to insufficient encoding time in Experiment 1, this capacity effect was absent in Experiment 2 when consolidation was allowed to complete with sufficient encoding time. Together, these results support the consolidation speed hypothesis over the perceptual boost hypothesis and highlight the importance of assessing experimental effects on both processing and representation aspects of VSTM. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Tracer dating and ocean ventilation

International Nuclear Information System (INIS)

Thiele, G.; Sarmiento, J.L.

1990-01-01

The interpretation of transient tracer observations depends on difficult to obtain information on the evolution in time of the tracer boundary conditions and interior distributions. Recent studies have attempted to circumvent this problem by making use of a derived quantity, age, based on the simultaneous distribution of two complementary tracers, such as tritium and its daughter, helium 3. The age is defined with reference to the surface such that the boundary condition takes on a constant value of zero. The authors use a two-dimensional model to explore the circumstances under which such a combination of conservation equations for two complementary tracers can lead to a cancellation of the time derivative terms. An interesting aspect of this approach is that mixing can serve as a source or sink of tracer based age. The authors define an idealized ventilation age tracer that is conservative with respect to mixing, and they explore how its behavior compares with that of the tracer-based ages over a range of advective and diffusive parameters

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…

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

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…

Improving Transit Predictions of Known Exoplanets with TERMS

Directory of Open Access Journals (Sweden)

Mahadevan S.

2011-02-01

Full Text Available Transiting planet discoveries have largely been restricted to the short-period or low-periastron distance regimes due to the bias inherent in the geometric transit probability. Through the refinement of planetary orbital parameters, and hence reducing the size of transit windows, long-period planets become feasible targets for photometric follow-up. Here we describe the TERMS project that is monitoring these host stars at predicted transit times.

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.

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

NARCIS (Netherlands)

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

1997-01-01

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

A novel economy reflecting short-term load forecasting approach

International Nuclear Information System (INIS)

Lin, Cheng-Ting; Chou, Li-Der

2013-01-01

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

Short-Term Reciprocity in Late Parent-Child Relationships

Science.gov (United States)

Leopold, Thomas; Raab, Marcel

2011-01-01

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

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

OpenAIRE

Logvinova, Veronika

2015-01-01

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

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

Multiple-tracer tests for contaminant transport process identification in saturated municipal solid waste

International Nuclear Information System (INIS)

Woodman, N.D.; Rees-White, T.C.; Stringfellow, A.M.; Beaven, R.P.; Hudson, A.P.

2015-01-01

Highlights: • Multiple tracers were applied to saturated MSW to test dual-porosity properties. • Lithium demonstrated to be non-conservative as a tracer. • 260 mm diameter column too small to test transport properties of MSW. • The classical advection-dispersion mode was rejected due to high dispersivity. • Characteristic diffusion times did not vary with the tracer. - Abstract: Two column tests were performed in conditions emulating vertical flow beneath the leachate table in a biologically active landfill to determine dominant transport mechanisms occurring in landfills. An improved understanding of contaminant transport process in wastes is required for developing better predictions about potential length of the long term aftercare of landfills, currently measured in timescales of centuries. Three tracers (lithium, bromide and deuterium) were used. Lithium did not behave conservatively. Given that lithium has been used extensively for tracing in landfill wastes, the tracer itself and the findings of previous tests which assume that it has behaved conservatively may need revisiting. The smaller column test could not be fitted with continuum models, probably because the volume of waste was below a representative elemental volume. Modelling compared advection-dispersion (AD), dual porosity (DP) and hybrid AD–DP models. Of these models, the DP model was found to be the most suitable. Although there is good evidence to suggest that diffusion is an important transport mechanism, the breakthrough curves of the different tracers did not differ from each other as would be predicted based on the free-water diffusion coefficients. This suggested that solute diffusion in wastes requires further study

Multiple-tracer tests for contaminant transport process identification in saturated municipal solid waste

Energy Technology Data Exchange (ETDEWEB)

Woodman, N.D., E-mail: n.d.woodman@soton.ac.uk; Rees-White, T.C.; Stringfellow, A.M.; Beaven, R.P.; Hudson, A.P.

2015-04-15

Highlights: • Multiple tracers were applied to saturated MSW to test dual-porosity properties. • Lithium demonstrated to be non-conservative as a tracer. • 260 mm diameter column too small to test transport properties of MSW. • The classical advection-dispersion mode was rejected due to high dispersivity. • Characteristic diffusion times did not vary with the tracer. - Abstract: Two column tests were performed in conditions emulating vertical flow beneath the leachate table in a biologically active landfill to determine dominant transport mechanisms occurring in landfills. An improved understanding of contaminant transport process in wastes is required for developing better predictions about potential length of the long term aftercare of landfills, currently measured in timescales of centuries. Three tracers (lithium, bromide and deuterium) were used. Lithium did not behave conservatively. Given that lithium has been used extensively for tracing in landfill wastes, the tracer itself and the findings of previous tests which assume that it has behaved conservatively may need revisiting. The smaller column test could not be fitted with continuum models, probably because the volume of waste was below a representative elemental volume. Modelling compared advection-dispersion (AD), dual porosity (DP) and hybrid AD–DP models. Of these models, the DP model was found to be the most suitable. Although there is good evidence to suggest that diffusion is an important transport mechanism, the breakthrough curves of the different tracers did not differ from each other as would be predicted based on the free-water diffusion coefficients. This suggested that solute diffusion in wastes requires further study.

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.

Role of self-efficacy and social support in short-term recovery after total hip replacement: a prospective cohort study.

Science.gov (United States)

Brembo, Espen Andreas; Kapstad, Heidi; Van Dulmen, Sandra; Eide, Hilde

2017-04-11

Despite the overall success of total hip replacement (THR) in patients with symptomatic osteoarthritis (OA), up to one-quarter of patients report suboptimal recovery. The aim of this study was to determine whether social support and general self-efficacy predict variability in short-term recovery in a Norwegian cohort. We performed secondary analysis of a prospective multicenter study of 223 patients who underwent THR for OA in 2003-2004. The total score of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) at 3 months after surgery was used as the recovery variable. We measured self-efficacy using the General Self-Efficacy Scale (GSES) and social support with the Social Provisions Scale (SPS). Preoperative and postoperative scores were compared using Wilcoxon tests. The Mann-Whitney U test compared scores between groups that differed in gender and age. Spearman's rho correlation coefficients were used to evaluate associations between selected predictor variables and the recovery variable. We performed univariate and multiple linear regression analyses to identify independent variables and their ability to predict short-term recovery after THR. The median preoperative WOMAC score was 58.3 before and 23.9 after surgery. The mean absolute change was 31.9 (standard deviation [SD] 17.0) and the mean relative change was 54.8% (SD 26.6). Older age, female gender, higher educational level, number of comorbidities, baseline WOMAC score, self-efficacy, and three of six individual provisions correlated significantly with short-term recovery after THR and predicted the variability in recovery in the univariate regression model. In multiple regression models, baseline WOMAC was the most consistent predictor of short-term recovery: a higher preoperative WOMAC score predicted worse short-term recovery (β = 0.44 [0.29, 0.59]). Higher self-efficacy predicted better recovery (β = -0.44 [-0.87, -0.02]). Reliable alliance was a significant predictor

Using Forecasting to Predict Long-Term Resource Utilization for Web Services

Science.gov (United States)

Yoas, Daniel W.

2013-01-01

Researchers have spent years understanding resource utilization to improve scheduling, load balancing, and system management through short-term prediction of resource utilization. Early research focused primarily on single operating systems; later, interest shifted to distributed systems and, finally, into web services. In each case researchers…

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

Science.gov (United States)

Lague, D.; Davy, P.

2008-12-01

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

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.

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.

Predictors of survival and ability to wean from short-term mechanical circulatory support device following acute myocardial infarction complicated by cardiogenic shock.

Science.gov (United States)

Garan, A Reshad; Eckhardt, Christina; Takeda, Koji; Topkara, Veli K; Clerkin, Kevin; Fried, Justin; Masoumi, Amirali; Demmer, Ryan T; Trinh, Pauline; Yuzefpolskaya, Melana; Naka, Yoshifumi; Burkhoff, Dan; Kirtane, Ajay; Colombo, Paolo C; Takayama, Hiroo

2017-11-01

Cardiogenic shock following acute myocardial infarction (AMI-CS) portends a poor prognosis. Short-term mechanical circulatory support devices (MCSDs) provide hemodynamic support for patients with cardiogenic shock but predictors of survival and the ability to wean from short-term MCSDs remain largely unknown. All patients > 18 years old treated at our institution with extra-corporeal membrane oxygenation or short-term surgical ventricular assist device for AMI-CS were studied. We collected acute myocardial infarction details with demographic and hemodynamic variables. Primary outcomes were survival to discharge and recovery from MCSD (i.e. survival without heart replacement therapy including durable ventricular assist device or heart transplant). One hundred and twenty-four patients received extra-corporeal membrane oxygenation or short-term surgical ventricular assist device following acute myocardial infarction from 2007 to 2016; 89 received extra-corporeal membrane oxygenation and 35 short-term ventricular assist device. Fifty-five (44.4%) died in the hospital and 69 (55.6%) survived to discharge. Twenty-six (37.7%) required heart replacement therapy (four transplant, 22 durable ventricular assist device) and 43 (62.3%) were discharged without heart replacement therapy. Age and cardiac index at MCSD implantation were predictors of survival to discharge; patients over 60 years with cardiac index <1.5 l/min per m 2 had a low likelihood of survival. The angiographic result after revascularization predicted recovery from MCSD (odds ratio 9.00, 95% confidence interval 2.45-32.99, p=0.001), but 50% of those optimally revascularized still required heart replacement therapy. Cardiac index predicted recovery from MCSD among this group (odds ratio 4.06, 95% confidence interval 1.45-11.55, p=0.009). Among AMI-CS patients requiring short-term MCSDs, age and cardiac index predict survival to discharge. Angiographic result and cardiac index predict ventricular recovery but 50

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

Science.gov (United States)

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

2016-02-01

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

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

DEFF Research Database (Denmark)

Blank, N; Diderichsen, Finn

1995-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2000-07-14

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

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.

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

Science.gov (United States)

Kemps, Eva; Andrade, Jackie

2012-05-01

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

Prospective testing of Coulomb short-term earthquake forecasts

Science.gov (United States)

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

2009-12-01

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

Synthesis of tracers using automated radiochemistry and robotics

International Nuclear Information System (INIS)

Dannals, R.F.

1992-07-01

Synthesis of high specific activity radiotracers labeled with short-lived positron-emitting radionuclides for positron emission tomography (PET) often requires handling large initial quantities of radioactivity. High specific activities are required when preparing tracers for use in PET studies of neuroreceptors. A fully automated approach for tracer synthesis is highly desirable. This proposal involves the development of a system for the Synthesis of Tracers using Automated Radiochemistry and Robotics (STARR) for this purpose. While the long range objective of the proposed research is the development of a totally automated radiochemistry system for the production of major high specific activity 11 C-radiotracers for use in PET, the specific short range objectives are the automation of 11 C-methyl iodide ( 11 CH 3 I) production via an integrated approach using both radiochemistry modular labstations and robotics, and the extension of this automated capability to the production of several radiotracers for PET (initially, 11 C-methionine, 3-N-[ 11 C-methyl]spiperone, and [ 11 C]-carfentanil)

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

Science.gov (United States)

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

2016-01-01

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

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...

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…

Visual short term memory related brain activity predicts mathematical abilities.

Science.gov (United States)

Boulet-Craig, Aubrée; Robaey, Philippe; Lacourse, Karine; Jerbi, Karim; Oswald, Victor; Krajinovic, Maja; Laverdière, Caroline; Sinnett, Daniel; Jolicoeur, Pierre; Lippé, Sarah

2017-07-01

Previous research suggests visual short-term memory (VSTM) capacity and mathematical abilities are significantly related. Moreover, both processes activate similar brain regions within the parietal cortex, in particular, the intraparietal sulcus; however, it is still unclear whether the neuronal underpinnings of VSTM directly correlate with mathematical operation and reasoning abilities. The main objective was to investigate the association between parieto-occipital brain activity during the retention period of a VSTM task and performance in mathematics. The authors measured mathematical abilities and VSTM capacity as well as brain activity during memory maintenance using magnetoencephalography (MEG) in 19 healthy adult participants. Event-related magnetic fields (ERFs) were computed on the MEG data. Linear regressions were used to estimate the strength of the relation between VSTM related brain activity and mathematical abilities. The amplitude of parieto-occipital cerebral activity during the retention of visual information was related to performance in 2 standardized mathematical tasks: mathematical reasoning and calculation fluency. The findings show that brain activity during retention period of a VSTM task is associated with mathematical abilities. Contributions of VSTM processes to numerical cognition should be considered in cognitive interventions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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...

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.

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...

Tracers and Tracer Testing: Design, Implementation, Tracer Selection, and Interpretation Methods

Energy Technology Data Exchange (ETDEWEB)

G. Michael Shook; Shannon L.; Allan Wylie

2004-01-01

Conducting a successful tracer test requires adhering to a set of steps. The steps include identifying appropriate and achievable test goals, identifying tracers with the appropriate properties, and implementing the test as designed. When these steps are taken correctly, a host of tracer test analysis methods are available to the practitioner. This report discusses the individual steps required for a successful tracer test and presents methods for analysis. The report is an overview of tracer technology; the Suggested Reading section offers references to the specifics of test design and interpretation.

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.

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

CSIR Research Space (South Africa)

Anele, AO

2017-11-01

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

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.

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

International Nuclear Information System (INIS)

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

2017-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-01-15

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

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.

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

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

Science.gov (United States)

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

2017-07-15

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

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...

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

Science.gov (United States)

Schultz, L. A.; Smith, M. R.; Fuell, K.; Stano, G. T.; LeRoy, A.; Berndt, E.

2015-12-01

Instruments aboard the Joint Polar Satellite System (JPSS) series of satellites will provide imagery and other data sets relevant to operational weather forecasts. To prepare current and future weather forecasters in application of these data sets, Proving Ground activities have been established that demonstrate future JPSS capabilities through use of similar sensors aboard NASA's Terra and Aqua satellites, and the S-NPP mission. As part of these efforts, NASA's Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, Alabama partners with near real-time providers of S-NPP products (e.g., NASA, UW/CIMSS, UAF/GINA, etc.) to demonstrate future capabilities of JPSS. This includes training materials and product distribution of multi-spectral false color composites of the visible, near-infrared, and infrared bands of MODIS and VIIRS. These are designed to highlight phenomena of interest to help forecasters digest the multispectral data provided by the VIIRS sensor. In addition, forecasters have been trained on the use of the VIIRS day-night band, which provides imagery of moonlit clouds, surface, and lights emitted by human activities. Hyperspectral information from the S-NPP/CrIS instrument provides thermodynamic profiles that aid in the detection of extremely cold air aloft, helping to map specific aviation hazards at high latitudes. Hyperspectral data also support the estimation of ozone concentration, which can highlight the presence of much drier stratospheric air, and map its interaction with mid-latitude or tropical cyclones to improve predictions of their strengthening or decay. Proving Ground activities are reviewed, including training materials and methods that have been provided to forecasters, and forecaster feedback on these products that has been acquired through formal, detailed assessment of their applicability to a given forecast threat or task. Future opportunities for collaborations around the delivery of training are proposed

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

Tracer gas dispersion in ducts-study of a new compact device using arrays of sonic micro jets

Energy Technology Data Exchange (ETDEWEB)

Silva, A.R. [Instituto Nacional de Engenharia e Tecnologia Industrial (INETI), Lisboa (Portugal); Afonso, C.F. [Faculdade de Engenharia, Universidade do Porto Departmento de Mecanica e Gestao Industrial, Porto (Portugal)

2004-07-01

One of the most feasible ways to measure duct airflows is by tracer gas techniques, especially for complex situations when the duct lengths are short as well as their access, which makes extremely difficult or impossible other methods to be implemented. One problem associated with the implementation of tracer gas technique when the ducts lengths are short is due to the impossibility of achieving complete mixing of the tracer with airflow and its sampling. In this work, the development of a new device for the injection of tracer gas in ducts is discussed as well as a new tracer-sampling device. The developed injection device has a compact tubular shape, with magnetic fixation to be easy to apply in duct walls. An array of sonic micro jets in counter current direction, with the possibility of angular movement according to its main axle ensures a complete mixing of the tracer in very short distances. The tracer-sampling device, with a very effective integration function, feeds the sampling system for analysis. Both devices were tested in a wind tunnel of approximately 21 m total length. The tests distances between injection and integration device considered were: X/Dh = 22; X/Dh = 4; X/Dh 2; and X/Dh = 1. For very short distances of X/Dh = 2 and X/Dh = 1, semi-empirical expressions were needed. A good reproducibility of airflow rate values was obtained. These preliminary tests showed that the practical implementation of tracer gas techniques in HVAC systems for measuring airflow rates with a very short mixing distance is possible with the devices developed. (author)

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...

Short-Term Forecasting of Electric Loads Using Nonlinear Autoregressive Artificial Neural Networks with Exogenous Vector Inputs

Directory of Open Access Journals (Sweden)

Jaime Buitrago

2017-01-01

Full Text Available Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural networks (ANN with exogenous multi-variable input (NARX. The proposed implementation of the network is new: the neural network is trained in open-loop using actual load and weather data, and then, the network is placed in closed-loop to generate a forecast using the predicted load as the feedback input. Unlike the existing short-term load forecasting methods using ANNs, the proposed method uses its own output as the input in order to improve the accuracy, thus effectively implementing a feedback loop for the load, making it less dependent on external data. Using the proposed framework, mean absolute percent errors in the forecast in the order of 1% have been achieved, which is a 30% improvement on the average error using feedforward ANNs, ARMAX and state space methods, which can result in large savings by avoiding commissioning of unnecessary power plants. The New England electrical load data are used to train and validate the forecast prediction.

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.

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.

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

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

Science.gov (United States)

Carluccio, Giuseppe; Bruno, Mary; Collins, Christopher M

2016-05-01

Present a novel method for rapid prediction of temperature in vivo for a series of pulse sequences with differing levels and distributions of specific energy absorption rate (SAR). After the temperature response to a brief period of heating is characterized, a rapid estimate of temperature during a series of periods at different heating levels is made using a linear heat equation and impulse-response (IR) concepts. Here the initial characterization and long-term prediction for a complete spine exam are made with the Pennes' bioheat equation where, at first, core body temperature is allowed to increase and local perfusion is not. Then corrections through time allowing variation in local perfusion are introduced. The fast IR-based method predicted maximum temperature increase within 1% of that with a full finite difference simulation, but required less than 3.5% of the computation time. Even higher accelerations are possible depending on the time step size chosen, with loss in temporal resolution. Correction for temperature-dependent perfusion requires negligible additional time and can be adjusted to be more or less conservative than the corresponding finite difference simulation. With appropriate methods, it is possible to rapidly predict temperature increase throughout the body for actual MR examinations. © 2015 Wiley Periodicals, Inc.

Short-term load forecasting of power system

Science.gov (United States)

Xu, Xiaobin

2017-05-01

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

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)

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

Directory of Open Access Journals (Sweden)

Yuan-Kang Wu

2014-01-01

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

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.

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.

In-vessel source term analysis code TRACER version 2.3. User's manual

International Nuclear Information System (INIS)

Toyohara, Daisuke; Ohno, Shuji; Hamada, Hirotsugu; Miyahara, Shinya

2005-01-01

A computer code TRACER (Transport Phenomena of Radionuclides for Accident Consequence Evaluation of Reactor) version 2.3 has been developed to evaluate species and quantities of fission products (FPs) released into cover gas during a fuel pin failure accident in an LMFBR. The TRACER version 2.3 includes new or modified models shown below. a) Both model: a new model for FPs release from fuel. b) Modified model for FPs transfer from fuel to bubbles or sodium coolant. c) Modified model for bubbles dynamics in coolant. Computational models, input data and output data of the TRACER version 2.3 are described in this user's manual. (author)

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

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

Science.gov (United States)

Sheremata, Summer L; Shomstein, Sarah

2017-08-01

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

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

Directory of Open Access Journals (Sweden)

Lai Hong Simon Chiu

2014-03-01

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

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.

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

NARCIS (Netherlands)

Geerts, E; Bouhuys, N

1998-01-01

It was hypothesized that personality factors determine the short-term outcome of depression, and that they may do this via non-verbal interpersonal interactions and via cognitive interpretations of non-verbal behaviour. Twenty-six hospitalized depressed patients entered the study. Personality

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 Prediction Research and Transition (SPoRT) Center: Transitioning Satellite Data to Operations

Science.gov (United States)

Zavodsky, Bradley

2012-01-01

The Short-term Prediction Research and Transition (SPoRT) Center located at NASA Marshall Space Flight Center has been conducting testbed activities aimed at transitioning satellite products to National Weather Service operational end users for the last 10 years. SPoRT is a NASA/NOAA funded project that has set the bar for transition of products to operational end users through a paradigm of understanding forecast challenges and forecaster needs, displaying products in end users decision support systems, actively assessing the operational impact of these products, and improving products based on forecaster feedback. Aiming for quality partnerships rather than a large quantity of data users, SPoRT has become a community leader in training operational forecasters on the use of up-and-coming satellite data through the use of legacy instruments and proxy data. Traditionally, SPoRT has supplied satellite imagery and products from NASA instruments such as the Moderate-resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS). However, recently, SPoRT has been funded by the GOES-R and Joint Polar Satellite System (JPSS) Proving Grounds to accelerate the transition of selected imagery and products to help improve forecaster awareness of upcoming operational data from the Visible Infrared Imager Radiometer Suite (VIIRS), Cross-track Infrared Sounder (CrIS), Advanced Baseline Imager (ABI), and Geostationary Lightning Mapper (GLM). This presentation provides background on the SPoRT Center, the SPoRT paradigm, and some example products that SPoRT is excited to work with forecasters to evaluate.

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

Science.gov (United States)

Xu, Shiluo; Niu, Ruiqing

2018-02-01

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

Noaa chlorofluorocarbon tracer program air and seawater measurements: 1986-1989. Data file

International Nuclear Information System (INIS)

Wisegarver, D.P.; Bullister, J.L.; Gammon, R.H.; Menzia, F.A.; Kelly, K.C.

1993-04-01

The NOAA Chlorofluorocarbon (CFC) Tracer Program at PMEL has been measuring the growing burden of these anthropogenic gases in the thermocline waters of the Pacific Ocean since 1980. The central goals of the NOAA CFC Tracer Program are to document the transient invasion of the CFC tracers into the Pacific Ocean, by means of repeat occupations of key hydrographic sections at 5-year intervals, and to interpret these changing distributions in terms of coupled ocean-atmosphere models. Studies are underway to use the CFC observations in model-validation studies, and to help develop predictive capabilities on the decade-to-century timescale. The report includes measurements of trichlorofluoromethane (CFC-11) and dichlorodifluoromethane (CFC-12) dissolved in seawater samples collected in the Pacific Ocean by the NOAA CFC Tracer Program on six cruises during the period of 1986-1989. Measurements of depth, pressure, salinity, temperature, and dissolved oxygen are included with the CFC data. Measurements of CFC-11 and CFC-12 in air samples collected along the cruise tracks are also included in the report. Data from the report are also available from the authors in digital format

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.

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.

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.

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...

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

International Nuclear Information System (INIS)

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

2006-01-01

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

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.

Impacts of short-term heatwaves on sun-induced chlorophyll fluorescence(SiF) in temperate tree species

Science.gov (United States)

Wang, F.; Gu, L.; Guha, A.; Han, J.; Warren, J.

2017-12-01

The current projections for global climate change forecast an increase in the intensity and frequency of extreme climatic events, such as droughts and short-term heat waves. Understanding the effects of short-term heat wave on photosynthesis process is of critical importance to predict global impacts of extreme weather event on vegetation. The diurnal and seasonal characteristics of SIF emitted from natural vegetation, e.g., forest and crop, have been studied at the ecosystem-scale, regional-scale and global-scale. However, the detailed response of SIF from different plant species under extremely weather event, especially short-term heat wave, have not been reported. The purpose of this study was to study the response of solar-induced chlorophyll fluorescence, gas exchange and continuous fluorescence at leaf scale for different temperate tree species. The short-term heatwave experiment was conducted using plant growth chamber (CMP6050, Conviron Inc., Canada). We developed an advanced spectral fitting method to obtain the plant SIF in the plant growth chamber. We compared SIF variation among different wavelength and chlorophyll difference among four temperate tree species. The diurnal variation of SIF signals at leaf-scales for temperate tree species are different under heat stress. The SIF response at leaf-scales and their difference for four temperate tree species are different during a cycle of short-term heatwave stress. We infer that SIF be used as a measure of heat tolerance for temperate tree species.

Sentence Comprehension in Adolescents with down Syndrome and Typically Developing Children: Role of Sentence Voice, Visual Context, and Auditory-Verbal Short-Term Memory.

Science.gov (United States)

Miolo, Giuliana; Chapman, Robins S.; Sindberg, Heidi A.

2005-01-01

The authors evaluated the roles of auditory-verbal short-term memory, visual short-term memory, and group membership in predicting language comprehension, as measured by an experimental sentence comprehension task (SCT) and the Test for Auditory Comprehension of Language--Third Edition (TACL-3; E. Carrow-Woolfolk, 1999) in 38 participants: 19 with…

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...

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

DEFF Research Database (Denmark)

Jensen, David Getreuer

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

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

Potential study of bed filtration characteristics in impressed boreholes by radon tracer technique

International Nuclear Information System (INIS)

Litvinov, A.A.; Pinkenzon, D.B.; Makarov, M.S.; Vinarskij, M.S.

1977-01-01

Potential study of bed filtration characteristics in impressed boreholes by radon tracer method is shown. Effects recorded by radon tracer result from gamma radiation of short-living radon decay daughter products. During filtration of tracer through punched holes, cement stone, and rocks the products are deposited and cause a local effect for 2-3 hours. There is a shortage of short-living products in filtrated radon liquid and for some time (which is necessary for production of notable quantity of new decay products) it is practically not a gamma emitter. It is shown that the feature of effect formation governs the technique for well logging as well as interpretation of the results obtained

Memory timeline: Brain ERP C250 (not P300) is an early biomarker of short-term storage.

Science.gov (United States)

Chapman, Robert M; Gardner, Margaret N; Mapstone, Mark; Dupree, Haley M; Antonsdottir, Inga M

2015-04-16

Brain event-related potentials (ERPs) offer a quantitative link between neurophysiological activity and cognitive performance. ERPs were measured while young adults performed a task that required storing a relevant stimulus in short-term memory. Using principal components analysis, ERP component C250 (maximum at 250 ms post-stimulus) was extracted from a set of ERPs that were separately averaged for various task conditions, including stimulus relevancy and stimulus sequence within a trial. C250 was more positive in response to task-specific stimuli that were successfully stored in short-term memory. This relationship between C250 and short-term memory storage of a stimulus was confirmed by a memory probe recall test where the behavioral recall of a stimulus was highly correlated with its C250 amplitude. ERP component P300 (and its subcomponents of P3a and P3b, which are commonly thought to represent memory operations) did not show a pattern of activation reflective of storing task-relevant stimuli. C250 precedes the P300, indicating that initial short-term memory storage may occur earlier than previously believed. Additionally, because C250 is so strongly predictive of a stimulus being stored in short-term memory, C250 may provide a strong index of early memory operations. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Prognostic factors of the short-term outcomes of patients with hepatitis B virus-associated acute-on-chronic liver failure.

Science.gov (United States)

Lei, Qing; Ao, Kangjian; Zhang, Yinhua; Ma, Deqiang; Ding, Deping; Ke, Changzheng; Chen, Yue; Luo, Jie; Meng, Zhongji

2017-11-01

To investigate the impact of the baseline status of patients with hepatitis B virus-associated acute-on-chronic liver failure on short-term outcomes. A retrospective study was conducted that included a total of 138 patients with hepatitis B virus-associated acute-on-chronic liver failure admitted to the Department of Infectious Diseases, Taihe Hospital, Hubei University of Medicine, from November 2013 to October 2016. The patients were divided into a poor prognosis group (74 patients) and a good prognosis group (64 patients) based on the disease outcome. General information, clinical indicators and prognostic scores of the patients' baseline status were analyzed, and a prediction model was established accordingly. Elder age, treatment with artificial liver support systems and the frequency of such treatments, high levels of white blood cells, neutrophils, neutrophil count/lymphocyte count ratio, alanine aminotransferase, gamma-glutamyl transferase, total bilirubin, urea, and prognostic scores as well as low levels of albumin and sodium were all significantly associated with the short-term outcomes of hepatitis B virus-associated acute-on-chronic liver failure. The predictive model showed that logit (p) = 3.068 + 1.003 × neutrophil count/lymphocyte count ratio - 0.892 × gamma-glutamyl transferase - 1.138 × albumin - 1.364 × sodium + 1.651 × artificial liver support therapy. The neutrophil count/lymphocyte count ratio and serum levels of gamma-glutamyl transferase, albumin and sodium were independent risk factors predicting short-term outcomes of hepatitis B virus-associated acute-on-chronic liver failure, and the administration of multiple treatments with artificial liver support therapy during the early stage is conducive to improved short-term outcomes.

Intact organism, short-term studies using 11C

International Nuclear Information System (INIS)

Spence, R.D.; Sharpe, P.J.H.

1991-01-01

Experimental investigation of biochemical pathways and biophysical mechanisms is difficult because in many cases more than one pathway or mechanism is involved. Ideally, a physiological tracer should be used to follow the uptake, transport, and assimilation of materials such as carbon and nitrogen to characterize the movements and mechanisms of physiological processes. Real-time measurements of net photosynthesis and dark respiration of plants have been possible since the development of the infrared gas analyzer (IRGA), allowing the intensive investigation of mechanisms and dynamics of CO 2 assimilation in green plants. Comparable research on the movement of carbon within the plant, however, requires another technique that allows real-time observations of carbon transport. This chapter describes how the short-lived radioisotope 11 C can be used to conduct plant physiological studies that are difficult or impossible to make using other isotopes such as 14 C

Three-Dimensional modelling of the long-term variability of tracer transport in the Asian Summer Monsoon anticyclone

Science.gov (United States)

Taverna, Giorgio; Chipperfield, Martyn; Feng, Wuhu; Pope, Richard; Hossaini, Ryan; Forster, Piers

2017-04-01

The Asian Monsoon is an important region for the transport of gases from the troposphere to the stratosphere. Recent work by many groups has focused on quantifying processes which contribute to coupling in the upper troposphere - lower stratosphere (UTLS), including transport during the Asian Summer Monsoon (ASM). Troposphere-to-stratosphere transport in this region has been the focus of a number of recent campaigns, including the EU "StratoClim campaign" in Kalamata, Greece, 2016. Anthropogenic compounds such as CO Very Short-Lived Substances (VSLS), which destroy stratospheric ozone, and sulphur compounds, which maintain the stratospheric aerosol layer, are among the important species involved in large convective systems transport such as the ASM. An important question for halogenated VSLS is whether ASM-associated transport can take place on timescales which are short relative to their chemical lifetimes of days to months. This talk will present results of the TOMCAT/SLIMCAT off-line 3-D chemical transport model to investigate these issues using moderate-resolution simulations (2.8°x2.8°, 60 levels from surface to 60 km). The model is forced by ECMWF ERA-Interim reanalyses. A 1979-2016 simulation was run using artificial and idealized tracers with parametrized loss rates, lifetimes and emissions. These types of tracer have already been successfully used to study the transport of VSLS from surface through the TTL. The interannual variability of the transport inside and through the ASM anticyclone and related confinement will be shown and quantified. Comparisons will be made with in-situ and remote satellite data, where possible.

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...

Long-Term Prediction of Satellite Orbit Using Analytical Method

Directory of Open Access Journals (Sweden)

Jae-Cheol Yoon

1997-12-01

Full Text Available A long-term prediction algorithm of geostationary orbit was developed using the analytical method. The perturbation force models include geopotential upto fifth order and degree and luni-solar gravitation, and solar radiation pressure. All of the perturbation effects were analyzed by secular variations, short-period variations, and long-period variations for equinoctial elements such as the semi-major axis, eccentricity vector, inclination vector, and mean longitude of the satellite. Result of the analytical orbit propagator was compared with that of the cowell orbit propagator for the KOREASAT. The comparison indicated that the analytical solution could predict the semi-major axis with an accuarcy of better than ~35meters over a period of 3 month.

An Analysis of Short- Term Overreaction to Stock Market News: Iranian Evidence

OpenAIRE

Masoumeh Naderi; Sasan Mekanik

2012-01-01

In Financial markets information is in the form of signs, news and different predictions coming from inside or outside of the company which makes reactions and as a result changes in stock prices. Such as increase and decrease over the limit or long period of times. However, this behavior is non-rational behavior of market which can be a rational response to perceived uncertainty that is understood by investors. We investigate the stock market short –term overreaction. The Aim of this project...

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

Directory of Open Access Journals (Sweden)

Shervin Assari

2016-09-01

Full Text Available Objectives: Despite the well-established association between self-rated health and mortality, research findings have been inconsistent regarding how men and women differ on this link. Using a national sample in the United States, this study compared American male and female older adults for the predictive role of baseline self-rated health on the short-term risk of mortality. Methods: This longitudinal study followed 1500 older adults (573 men (38.2% and 927 women (61.8% aged 66 years or older for 3 years from 2001 to 2004. The main predictor of interest was self-rated health, which was measured using a single item in 2001. The outcome was the risk of all-cause mortality during the 3-year follow-up period. Demographic factors (race and age, socio-economic factors (education and marital status, and health behaviors (smoking and drinking were covariates. Gender was the focal moderator. We ran logistic regression models in the pooled sample and also stratified by gender, with self-rated health treated as either nominal variables, poor compared to other levels (i.e. fair, good, or excellent or excellent compared to other levels (i.e. good, fair, or poor, or an ordinal variable. Results: In the pooled sample, baseline self-rated health predicted mortality risk, regardless of how the variable was treated. We found a significant interaction between gender and poor self-rated health, indicating a stronger effect of poor self-rated health on mortality risk for men compared to women. Gender did not interact with excellent self-rated health on mortality. Conclusion: Perceived poor self-rated health better reflects risk of mortality over a short period of time for older men compared to older women. Clinicians may need to take poor self-rated health of older men very seriously. Future research should test whether the differential predictive validity of self-rated health based on gender is due to a different meaning of poor self-rated health for older men

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 ...

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…

Tracer filamentation at an unstable ocean front

Science.gov (United States)

Feng, Yen Chia; Mahadevan, Amala; Thiffeault, Jean-Luc; Yecko, Philip

2017-11-01

A front, where two bodies of ocean water with different physical properties meet, can become unstable and lead to a flow with high strain rate and vorticity. Phytoplankton and other oceanic tracers are stirred into filaments by such flow fields, as can often be seen in satellite imagery. The stretching and folding of a tracer by a two-dimensional flow field has been well studied. In the ocean, however, the vertical shear of horizontal velocity is typically two orders of magnitude larger than the horizontal velocity gradient. Theoretical calculations show that vertical shear alters the way in which horizontal strain affects the tracer, resulting in thin, sloping structures in the tracer field. Using a non-hydrostatic ocean model of an unstable ocean front, we simulate tracer filamentation to identify the effect of vertical shear on the deformation of the tracer. In a complementary laboratory experiment, we generate a simple, vertically sheared strain flow and use dye and particle image velocimetry to quantify the filamentary structures in terms of the strain and shear. We identify how vertical shear alters the tracer filaments and infer how the evolution of tracers in the ocean will differ from the idealized two-dimensional paradigm. Support of NSF DMS-1418956 is acknowledged.

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.

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

Science.gov (United States)

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

2017-12-01

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

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.

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.

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 ...

Attentional control constrains visual short-term memory: Insights from developmental and individual differences

Science.gov (United States)

Astle, D.E.; Nobre, A.C.; Scerif, G.

2014-01-01

The mechanisms by which attentional control biases mnemonic representations have attracted much interest but remain poorly understood. As attention and memory develop gradually over childhood and variably across individuals, assessing how participants of different ages and ability attend to mnemonic contents can elucidate their interplay. In Experiment 1, 7-, 10-year-olds and adults were asked to report whether a probe item had been part of a previously presented four-item array. The initial array could either be uncued, preceded (“pre-cued”) or followed (“retro-cued”) by a spatial cue orienting attention to one of the potential item locations. Performance across groups was significantly improved by both cue types and individual differences in children’s retrospective attentional control predicted their visual short-term and working memory span, whereas their basic ability to remember in the absence of cues did not. Experiment 2 imposed a variable delay between the array and the subsequent orienting cue. Cueing benefits were greater in adults compared to 10-year-olds, but they persisted even when cues followed the array by nearly 3 seconds, suggesting that orienting operated on durable short-term representations for both age groups. The findings indicate that there are substantial developmental and individual differences in the ability to control attention to memory and that in turn these differences constrain visual short-term memory capacity. PMID:20680889

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.

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.

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.

Tumoral tracers

International Nuclear Information System (INIS)

Camargo, E.E.

1979-01-01

Direct tumor tracers are subdivided in the following categories:metabolite tracers, antitumoral tracers, radioactive proteins and cations. Use of 67 Ga-citrate as a clinically important tumoral tracer is emphasized and gallium-67 whole-body scintigraphy is discussed in detail. (M.A.) [pt

Long-Term Survival Prediction for Coronary Artery Bypass Grafting: Validation of the ASCERT Model Compared With The Society of Thoracic Surgeons Predicted Risk of Mortality.

Science.gov (United States)

Lancaster, Timothy S; Schill, Matthew R; Greenberg, Jason W; Ruaengsri, Chawannuch; Schuessler, Richard B; Lawton, Jennifer S; Maniar, Hersh S; Pasque, Michael K; Moon, Marc R; Damiano, Ralph J; Melby, Spencer J

2018-05-01

The recently developed American College of Cardiology Foundation-Society of Thoracic Surgeons (STS) Collaboration on the Comparative Effectiveness of Revascularization Strategy (ASCERT) Long-Term Survival Probability Calculator is a valuable addition to existing short-term risk-prediction tools for cardiac surgical procedures but has yet to be externally validated. Institutional data of 654 patients aged 65 years or older undergoing isolated coronary artery bypass grafting between 2005 and 2010 were reviewed. Predicted survival probabilities were calculated using the ASCERT model. Survival data were collected using the Social Security Death Index and institutional medical records. Model calibration and discrimination were assessed for the overall sample and for risk-stratified subgroups based on (1) ASCERT 7-year survival probability and (2) the predicted risk of mortality (PROM) from the STS Short-Term Risk Calculator. Logistic regression analysis was performed to evaluate additional perioperative variables contributing to death. Overall survival was 92.1% (569 of 597) at 1 year and 50.5% (164 of 325) at 7 years. Calibration assessment found no significant differences between predicted and actual survival curves for the overall sample or for the risk-stratified subgroups, whether stratified by predicted 7-year survival or by PROM. Discriminative performance was comparable between the ASCERT and PROM models for 7-year survival prediction (p validated for prediction of long-term survival after coronary artery bypass grafting in all risk groups. The widely used STS PROM performed comparably as a predictor of long-term survival. Both tools provide important information for preoperative decision making and patient counseling about potential outcomes after coronary artery bypass grafting. Copyright © 2018 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

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.

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...

Radionuclides as tracers

International Nuclear Information System (INIS)

Ganatra, R.D.

1992-01-01

Importance of radioisotopes in medicine is because of their two characteristics: their biological behaviour is identical to their stable counterparts, and because they are radioactive their emissions can be detected by a suitable instrument. All isotopes of iodine will behave in the same way and will concentrate in the thyroid gland. There is no way of detecting the stable, natural iodine in the thyroid gland, but the presence of radioactive iodine can be detected externally in vivo by a detector. Thus, the radioactive iodine becomes a tracer, a sport of a spy, which mimics the behaviour of natural iodine and relays information to a detector. The radioactive tracers are popular because of the ease with which they can be detected in vivo and the fact that the measurement of their presence in the body can be in quantitative terms. The measurement can be very accurate and sensitive. Whenever the measurements can be done in vivo, the information is obtained in dynamic terms, as it is happening, as if the physiological events become transparent

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

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.

Predicting Kenya Short Rains Using the Indian Ocean SST

Science.gov (United States)

Peng, X.; Albertson, J. D.; Steinschneider, S.

2017-12-01

The rainfall over the Eastern Africa is charaterized by the typical bimodal monsoon system. Literatures have shown that the monsoon system is closely connected with the large-scale atmospheric motion which is believed to be driven by sea surface temperature anomalies (SSTA). Therefore, we may make use of the predictability of SSTA in estimating future Easter Africa monsoon. In this study, we tried predict the Kenya short rains (Oct, Nov and Dec rainfall) based on the Indian Ocean SSTA. The Least Absolute Shrinkage and Selection Operator (LASSO) regression is used to avoid over-fitting issues. Models for different lead times are trained using a 28-year training set (2006-1979) and are tested using a 10-year test set (2007-2016). Satisfying prediciton skills are achieved at relatively long lead times (i.e., 8 and 10 months) in terms of correlation coefficient and sign accuracy. Unlike some of the previous work, the prediction models are obtained from a data-driven method. Limited predictors are selected for each model and can be used in understanding the underlying physical connection. Still, further investigation is needed since the sampling variability issue cannot be excluded due to the limited sample size.

Variation in Parasympathetic Dysregulation Moderates Short-term Memory Problems in Childhood Attention-Deficit/Hyperactivity Disorder.

Science.gov (United States)

Ward, Anthony R; Alarcón, Gabriela; Nigg, Joel T; Musser, Erica D

2015-11-01

Although attention deficit/hyperactivity disorder (ADHD) is associated with impairment in working memory and short-term memory, up to half of individual children with ADHD perform within a normative range. Heterogeneity in other ADHD-related mechanisms, which may compensate for or combine with cognitive weaknesses, is a likely explanation. One candidate is the robustness of parasympathetic regulation (as indexed by respiratory sinus arrhythmia; RSA). Theory and data suggest that a common neural network is likely tied to both heart-rate regulation and certain cognitive functions (including aspects of working and short-term memory). Cardiac-derived indices of parasympathetic reactivity were collected during short-term memory (STM) storage and rehearsal tasks from 243 children (116 ADHD, 127 controls). ADHD was associated with lower STM performance, replicating previous work. In addition, RSA reactivity moderated the association between STM and ADHD - both as a category and a dimension - independent of comorbidity. Specifically, conditional effects revealed that high levels of withdrawal interacted with weakened STM but high levels of augmentation moderated a positive association predicting ADHD. Thus, variations in parasympathetic reactivity may help explain neuropsychological heterogeneity in ADHD.

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...

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)

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

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...

Nitrogen assimilation and short term retention in a nutrient-rich tidal freshwater marsh – a whole ecosystem 15N enrichment study

Directory of Open Access Journals (Sweden)

B. Gribsholt

2007-01-01

Full Text Available An intact tidal freshwater marsh system (3477 m2 was labelled by adding 15N-ammonium as a tracer to the flood water inundating the ecosystem. The appearance and retention of 15N-label in different marsh components (leaves, roots, sediment, leaf litter and invertebrate fauna was followed over 15 days. This allowed us to elucidate the direct assimilation and dependence on creek-water nitrogen on a relatively short term and provided an unbiased assessment of the relative importance of the various compartments within the ecosystem. Two separate experiments were conducted, one in spring/early summer (May 2002 when plants were young and building up biomass; the other in late summer (September 2003 when macrophytes were in a flowering or early senescent state. Nitrogen assimilation rate (per hour inundated was >3 times faster in May compared to September. On both occasions, however, the results clearly revealed that the less conspicuous compartments such as leaf litter and ruderal vegetations are more important in nitrogen uptake and retention than the prominent reed (Phragmites australis meadows. Moreover, short-term nitrogen retention in these nutrient rich marshes occurs mainly via microbial pathways associated with the litter and sediment. Rather than direct uptake by macrophytes, it is the large reactive surface area provided by the tidal freshwater marsh vegetation that is most crucial for nitrogen transformation, assimilation and short term retention in nutrient rich tidal freshwater marshes. Our results clearly revealed the dominant role of microbes in initial nitrogen retention in marsh ecosystems.

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.)

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 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.

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.

Accurate assessment of exposure using tracer gas measurements

DEFF Research Database (Denmark)

Kierat, Wojciech; Bivolarova, Mariya; Zavrl, Eva

2018-01-01

analyzers with short and long response times, respectively. The tracer gas concentration was characterized by the mean, standard deviation and 95th percentile values. The results revealed that the measurement time needed to determine, with sufficient accuracy, these parameters decreased substantially...

Recover Act. Verification of Geothermal Tracer Methods in Highly Constrained Field Experiments

Energy Technology Data Exchange (ETDEWEB)

Becker, Matthew W. [California State University, Long Beach, CA (United States)

2014-05-16

The prediction of the geothermal system efficiency is strong linked to the character of the flow system that connects injector and producer wells. If water flow develops channels or “short circuiting” between injection and extraction wells thermal sweep is poor and much of the reservoir is left untapped. The purpose of this project was to understand how channelized flow develops in fracture geothermal reservoirs and how it can be measured in the field. We explored two methods of assessing channelization: hydraulic connectivity tests and tracer tests. These methods were tested at a field site using two verification methods: ground penetrating radar (GPR) images of saline tracer and heat transfer measurements using distributed temperature sensing (DTS). The field site for these studies was the Altona Flat Fractured Rock Research Site located in northeastern New York State. Altona Flat Rock is an experimental site considered a geologic analog for some geothermal reservoirs given its low matrix porosity. Because soil overburden is thin, it provided unique access to saturated bedrock fractures and the ability image using GPR which does not effectively penetrate most soils. Five boreholes were drilled in a “five spot” pattern covering 100 m2 and hydraulically isolated in a single bedding plane fracture. This simple system allowed a complete characterization of the fracture. Nine small diameter boreholes were drilled from the surface to just above the fracture to allow the measurement of heat transfer between the fracture and the rock matrix. The focus of the hydraulic investigation was periodic hydraulic testing. In such tests, rather than pumping or injection in a well at a constant rate, flow is varied to produce an oscillating pressure signal. This pressure signal is sensed in other wells and the attenuation and phase lag between the source and receptor is an indication of hydraulic connection. We found that these tests were much more effective than constant

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

Directory of Open Access Journals (Sweden)

Yu Liu

Full Text Available The prediction of the short-term quantitative precipitation nowcasting (QPN from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC; the Horn-Schunck optical-flow scheme (PHS; and the Pyramid Lucas-Kanade Optical Flow method (PPLK, which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6. The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

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

Science.gov (United States)

Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei

2015-01-01

The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

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.

Short and long term efficiencies of debris risk reduction measures: Application to a European LEO mission

Science.gov (United States)

Lang, T.; Kervarc, R.; Bertrand, S.; Carle, P.; Donath, T.; Destefanis, R.; Grassi, L.; Tiboldo, F.; Schäfer, F.; Kempf, S.; Gelhaus, J.

2015-01-01

Recent numerical studies indicate that the low Earth orbit (LEO) debris environment has reached a point such that even if no further space launches were conducted, the Earth satellite population would remain relatively constant for only the next 50 years or so. Beyond that, the debris population would begin to increase noticeably, due to the production of collisional debris (Liou and Johnson, 2008). Measures to be enforced play thus a major role to preserve an acceptable space mission risk and ensure sustainable space activities. The identification of such measures and the quantification of their efficiency over time for LEO missions is of prime concern in the decision-making process, as it has been investigated for the last few decades by the Inter-Agency Space Debris Coordination Committee (IADC). This paper addresses the final results of a generic methodology and the characteristics of a tool developed to assess the efficiency of the risk reduction measures identified for the Sentinel-1 (S1) mission. This work is performed as part of the 34-month P2-ROTECT project (Prediction, Protection & Reduction of OrbiTal Exposure to Collision Threats), funded by the European Union within the Seventh Framework Programme. Three ways of risk reduction have been investigated, both in short and long-term, namely: better satellite protection, better conjunction prediction, and cleaner environment. According to our assumptions, the S1 mission vulnerability evaluations in the long term (from 2093 to 2100) show that full compliance to the mitigation measures leads to a situation twice safer than that induced by an active debris removal of 5 objects per year in a MASTER2009 Business-As-Usual context. Because these measures have visible risk reduction effects in the long term, complementary measures with short response time are also studied. In the short term (from 2013 to 2020), a better prediction of the conjunctions is more efficient than protecting the satellite S1 itself. By

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

Science.gov (United States)

Heki, K.; He, L.

2017-12-01

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

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.

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2009-07-15

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

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

Science.gov (United States)

Prastuti, M.; Suhartono; Salehah, NA

2018-04-01

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

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.

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

Directory of Open Access Journals (Sweden)

Chengshi Tian

2018-03-01

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

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.…

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 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

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…

Working memory training improves visual short-term memory capacity.

Science.gov (United States)

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

2016-01-01

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

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.

Pro B-type natriuretic peptide plasma value: a new criterion for the prediction of short- and long-term outcomes after transcatheter aortic valve implantation.

Science.gov (United States)

López-Otero, Diego; Trillo-Nouche, Ramiro; Gude, Francisco; Cid-Álvarez, Belen; Ocaranza-Sanchez, Raimundo; Alvarez, Melisa Santas; Lear, Pamela V; Gonzalez-Juanatey, José R

2013-09-30

To determine the prognostic value of pro B-type natriuretic peptide (pro-BNP) to predict mortality after transcatheter aortic valve implantation (TAVI). Logistic EuroSCORE (LES) overestimates observed mortality after TAVI. A new risk score specific to TAVI is needed to accurately assess mortality and outcome. Eighty-five patients were included. Indications for TAVI were nonoperable or surgically high-risk patients (LES>20%). Pro-BNP was measured 24h before the procedure. Cox proportional hazards model was used to evaluate clinical factors. The predictive accuracy of these Cox models was determined by using time-dependent receiver operating characteristic (ROC) curves. Pro-BNP levels (log-transformed) were significantly higher in non-survivors than in survivors at 30 days (3.36 ± 0.43 vs. 3.81 ± 0.43, p<0.004) and at the end of follow-up (3.34 ± 0.42 vs. 3.63 ± 0.48, p<0.011). Multivariate analysis revealed that only increased log pro-BNP levels were associated with higher mortality rate at short [hazard ratio (HR) (95% confidence intervals (CI)]=5.35 (1.74-16.5), p=0.003] and long-term follow-ups [HR=11 (CI: 1.51-81.3), p=0.018]. LES was not associated with increased mortality at either time point [HR=1.03 (CI: 0.95-1.10), p=0.483 and HR=1.03 (CI: 0.98-1.07), p=0.230, respectively]. At 30, 90, 180, and 365 days, the c-index was 0.72 for log pro-BNP and 0.63 for LES (p=0.044). Pre-procedure log transform of plasma pro-BNP levels are an independent and strong predictor of short- and long-term outcomes after TAVI and are more discriminatory than LES. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.