Human short-term spatial memory: precision predicts capacity.

PubMed

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.

Nurses' short-term prediction of violence in acute psychiatric intensive care.

PubMed

Björkdahl, A; Olsson, D; Palmstierna, T

2006-03-01

To evaluate the short-term predictive capacity of the Brøset Violence Checklist (BVC) when used by nurses in a psychiatric intensive care unit. Seventy-three patients were assessed according to the BVC three times daily. Violent incidents were recorded with the Staff Observation Aggression Scale, revised version. An extended Cox proportional hazards model with multiple events and time-dependent covariates was estimated to evaluate how the highest BVC sum of the last 24 h and its separate items affect the risk for severe violence within the next 24 h. With a BVC sum of one or more, hazard for severe violence was six times higher than if the sum was zero. Four of the six separate items significantly increased the risk for severe violence with hazard ratios between 3.0 and 6.3. Risk for in-patient violence in a short-term perspective can to a high degree be predicted by nurses using the BVC.

Short-term Drought Prediction in India.

NASA Astrophysics Data System (ADS)

Shah, R.; Mishra, V.

2014-12-01

Medium range soil moisture drought forecast helps in decision making in the field of agriculture and water resources management. Part of skills in medium range drought forecast comes from precipitation. Proper evaluation and correction of precipitation forecast may improve drought predictions. Here, we evaluate skills of ensemble mean precipitation forecast from Global Ensemble Forecast System (GEFS) for medium range drought predictions over India. Climatological mean (CLIM) of historic data (OBS) are used as reference forecast to evaluate GEFS precipitation forecast. Analysis was conducted based on forecast initiated on 1st and 15th dates of each month for lead up to 7-days. Correlation and RMSE were used to estimate skill scores of accumulated GEFS precipitation forecast from lead 1 to 7-days. Volumetric indices based on the 2X2 contingency table were used to check missed and falsely predicted historic volume of daily precipitation from GEFS in different regions and at different thresholds. GEFS showed improvement in correlation of 0.44 over CLIM during the monsoon season and 0.55 during the winter season. Lower RMSE was showed by GEFS than CLIM. Ratio of RMSE in GEFS and CLIM comes out as 0.82 and 0.4 (perfect skill is at zero) during the monsoon and winter season, respectively. We finally used corrected GEFS forecast to derive the Variable Infiltration Capacity (VIC) model, which was used to develop short-term forecast of hydrologic and agricultural (soil moisture) droughts in India.

VAN method of short-term earthquake prediction shows promise

NASA Astrophysics Data System (ADS)

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 Memory: The "Storage" Component of Human Brain Responses Predicts Recall.

ERIC Educational Resources Information Center

Chapman, Robert M.; And Others

1978-01-01

Presents electrophysiological and behavioral evidence for a neural process related to storage in short-term memory. Predicting recall performance on the basis of the storage component of brain responses is presented. A list of references is also included. (HM)

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

NASA Technical Reports Server (NTRS)

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.

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

NASA Astrophysics Data System (ADS)

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.

Global velocity constrained cloud motion prediction for short-term solar forecasting

NASA Astrophysics Data System (ADS)

Chen, Yanjun; Li, Wei; Zhang, Chongyang; Hu, Chuanping

2016-09-01

Cloud motion is the primary reason for short-term solar power output fluctuation. In this work, a new cloud motion estimation algorithm using a global velocity constraint is proposed. Compared to the most used Particle Image Velocity (PIV) algorithm, which assumes the homogeneity of motion vectors, the proposed method can capture the accurate motion vector for each cloud block, including both the motional tendency and morphological changes. Specifically, global velocity derived from PIV is first calculated, and then fine-grained cloud motion estimation can be achieved by global velocity based cloud block researching and multi-scale cloud block matching. Experimental results show that the proposed global velocity constrained cloud motion prediction achieves comparable performance to the existing PIV and filtered PIV algorithms, especially in a short prediction horizon.

Four Examples of Short-Term and Imminent Prediction of Earthquakes

NASA Astrophysics Data System (ADS)

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

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

PubMed

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

NASA Astrophysics Data System (ADS)

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.

The NASA Severe Thunderstorm Observations and Regional Modeling (NASA STORM) Project

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Gatlin, Patrick N.; Lang, Timothy J.; Srikishen, Jayanthi; Case, Jonathan L.; Molthan, Andrew L.; Zavodsky, Bradley T.; Bailey, Jeffrey; Blakeslee, Richard J.; Jedlovec, Gary J.

2016-01-01

The NASA Severe Storm Thunderstorm Observations and Regional Modeling(NASA STORM) project enhanced NASA’s severe weather research capabilities, building upon existing Earth Science expertise at NASA Marshall Space Flight Center (MSFC). During this project, MSFC extended NASA’s ground-based lightning detection capacity to include a readily deployable lightning mapping array (LMA). NASA STORM also enabled NASA’s Short-term Prediction and Research Transition (SPoRT) to add convection allowing ensemble modeling to its portfolio of regional numerical weather prediction (NWP) capabilities. As a part of NASA STORM, MSFC developed new open-source capabilities for analyzing and displaying weather radar observations integrated from both research and operational networks. These accomplishments enabled by NASA STORM are a step towards enhancing NASA’s capabilities for studying severe weather and positions them for any future NASA related severe storm field campaigns.

The short- to medium-term predictive accuracy of static and dynamic risk assessment measures in a secure forensic hospital.

PubMed

Chu, Chi Meng; Thomas, Stuart D M; Ogloff, James R P; Daffern, Michael

2013-04-01

Although violence risk assessment knowledge and practice has advanced over the past few decades, it remains practically difficult to decide which measures clinicians should use to assess and make decisions about the violence potential of individuals on an ongoing basis, particularly in the short to medium term. Within this context, this study sought to compare the predictive accuracy of dynamic risk assessment measures for violence with static risk assessment measures over the short term (up to 1 month) and medium term (up to 6 months) in a forensic psychiatric inpatient setting. Results showed that dynamic measures were generally more accurate than static measures for short- to medium-term predictions of inpatient aggression. These findings highlight the necessity of using risk assessment measures that are sensitive to important clinical risk state variables to improve the short- to medium-term prediction of aggression within the forensic inpatient setting. Such knowledge can assist with the development of more accurate and efficient risk assessment procedures, including the selection of appropriate risk assessment instruments to manage and prevent the violence of offenders with mental illnesses during inpatient treatment.

NASA automatic subject analysis technique for extracting retrievable multi-terms (NASA TERM) system

NASA Technical Reports Server (NTRS)

Kirschbaum, J.; Williamson, R. E.

1978-01-01

Current methods for information processing and retrieval used at the NASA Scientific and Technical Information Facility are reviewed. A more cost effective computer aided indexing system is proposed which automatically generates print terms (phrases) from the natural text. Satisfactory print terms can be generated in a primarily automatic manner to produce a thesaurus (NASA TERMS) which extends all the mappings presently applied by indexers, specifies the worth of each posting term in the thesaurus, and indicates the areas of use of the thesaurus entry phrase. These print terms enable the computer to determine which of several terms in a hierarchy is desirable and to differentiate ambiguous terms. Steps in the NASA TERMS algorithm are discussed and the processing of surrogate entry phrases is demonstrated using four previously manually indexed STAR abstracts for comparison. The simulation shows phrase isolation, text phrase reduction, NASA terms selection, and RECON display.

Evaluation of NASA Foodbars as a standard diet for use in short-term rodent space flight studies.

PubMed

Tou, Janet; Grindeland, Richard; Barrett, Joyce; Dalton, Bonnie; Mandel, Adrian; Wade, Charles

2003-01-01

[corrected] A standard rodent diet for space flight must meet the unique conditions imposed by the space environment and must be nutritionally adequate because diet can influence the outcome of experiments. We evaluated the use of National Aeronautics and Space Administration (NASA) Foodbars as a standard space flight diet for rats. The Foodbar's semi-purified formulation permitted criteria such as nutrient consistency, high nutrient bioavailability, and flexibility of formulation to be met. Extrusion of the semi-purified diet produced Foodbars with the proper texture and a non-crumbing solid form for use in space. Treatment of Foodbar with 0.1% potassium sorbate prevented mold growth. Irradiation (15 to 25 kGy) prevented bacterial growth and, in combination with sorbate treatment, added protection against mold for shelf stability. During the development process, nutrient analyses indicated that extrusion and irradiation produces nutrient losses. Nutrients were adjusted accordingly to compensate for processing losses. Nutrient analysis of Foodbars continues to be performed routinely to monitor nutrient levels. It is important that the standard rodent diet provide nutrients that will prevent deficiency but also avoid excess that may mask physiologic changes produced by space flight. All vitamin levels in the Foodbars, except for vitamin K, conformed to or exceeded the current National Research Council (NRC) 1995 recommendations. All indispensable amino acids in Foodbar conformed to or exceeded the NRC nutrient recommendation for mouse growth and rat maintenance. However, some indispensable amino acids were slightly below recommendations for rat reproduction and growth. Short-term (18 to 20 d) animal feeding studies indicated that Foodbars are palatable, support growth, and maintain health in rats. Results indicated that NASA Rodent Foodbars meet the physical and nutritional criteria required to support rodents in the space environment and thus may be used

Evaluation of NASA Foodbars as a Standard Diet for Use in Short-Term Rodent Space Flight Studies

NASA Technical Reports Server (NTRS)

Tou, Janet; Grindeland, Richard; Barrett, Joyce; Dalton, Bonnie; Mandel, Adrian; Wade, Charles

2003-01-01

A standard rodent diet for space flight must meet the unique conditions imposed by the space environment and must be nutritionally adequate since diet can influence the outcome of experiments. This paper evaluates the use of National Aeronautics and Space Administration (NASA) developed Foodbars as a standard space flight diet for rats. The Foodbar's semi-purified formulation permits criteria such as nutrient consistency, high nutrient bioavailability and flexibility of formulation to be met. Extrusion of the semi-purified diet produces Foodbars with the proper texture and a non-crumbing solid form for use in space. Treatment of Foodbar with 0.1% potassium sorbate prevents mold growth. Irradiation (15-25 kGy) prevents bacterial growth and in combination with sorbate-treatment provides added protection against mold for shelf-stability. However, during the development process, nutrient analyses indicated that extrusion and irradiation produced nutrient losses. Nutrients were adjusted accordingly to compensate for processing losses. Nutrient analysis of Foodbars continues to be performed routinely to monitor nutrient levels. It is important that the standard rodent diet provide nutrients that will prevent deficiency but also avoid excess that may mask physiological changes produced by space flight. All vitamins levels in the Foodbars, except for vitamin K conformed to or exceeded the current NRC (1995) recommendations. All indispensable amino acids in Foodbar conformed to or exceeded the NRC nutrient recommendation for mice growth and rat maintenance. However, some indispensable amino acids were slightly below recommendations for rat reproduction/growth. Short-term (18-20 d) animal feeding studies indicated that Foodbars were palatable, supported growth and maintained health in rats. Results indicated that NASA rodent Foodbars meet both the physical and nutritional criteria required to support rodents in the space environment and thus, may be used successfully as a

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

PubMed

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 < 0.05) than non-responders at days 6, 8-11, and at the 3-month follow-up. The previously defined cut-off of > 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.

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

PubMed

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 < 0.001), and an elevated ammonia result within two days of admission (p = 0.012). When peak values for MELD were included, they were the most significant predictor of short-term mortality (p < 0.001), followed by INRdf (p = 0.006). On admission, two scoring systems that identify a subset of patients with severe alcoholic liver disease are able to predict >50 % mortality at four weeks and >80 % mortality at six months without specific treatment.

Models for short term malaria prediction in Sri Lanka

PubMed Central

Briët, Olivier JT; Vounatsou, Penelope; Gunawardena, Dissanayake M; Galappaththy, Gawrie NL; Amerasinghe, Priyanie H

2008-01-01

Background Malaria in Sri Lanka is unstable and fluctuates in intensity both spatially and temporally. Although the case counts are dwindling at present, given the past history of resurgence of outbreaks despite effective control measures, the control programmes have to stay prepared. The availability of long time series of monitored/diagnosed malaria cases allows for the study of forecasting models, with an aim to developing a forecasting system which could assist in the efficient allocation of resources for malaria control. Methods Exponentially weighted moving average models, autoregressive integrated moving average (ARIMA) models with seasonal components, and seasonal multiplicative autoregressive integrated moving average (SARIMA) models were compared on monthly time series of district malaria cases for their ability to predict the number of malaria cases one to four months ahead. The addition of covariates such as the number of malaria cases in neighbouring districts or rainfall were assessed for their ability to improve prediction of selected (seasonal) ARIMA models. Results The best model for forecasting and the forecasting error varied strongly among the districts. The addition of rainfall as a covariate improved prediction of selected (seasonal) ARIMA models modestly in some districts but worsened prediction in other districts. Improvement by adding rainfall was more frequent at larger forecasting horizons. Conclusion Heterogeneity of patterns of malaria in Sri Lanka requires regionally specific prediction models. Prediction error was large at a minimum of 22% (for one of the districts) for one month ahead predictions. The modest improvement made in short term prediction by adding rainfall as a covariate to these prediction models may not be sufficient to merit investing in a forecasting system for which rainfall data are routinely processed. PMID:18460204

CF6-6D engine short-term performance deterioration

NASA Technical Reports Server (NTRS)

Kramer, W. H.; Paas, J. E.; Smith, J. J.; Wulf, R. H.

1980-01-01

Studies conducted as part of the NASA-Lewis CF6 jet engine diagnostics program are summarized. An 82-engine sample of DC-10-10 aircraft engine checkout data that were gathered to define the extent and magnitude of CF6-6D short term performance deterioration were analyzed. These data are substantiated by the performance testing and analytical teardown of CF6-6D short term deterioration engine serial number (ESN) 451507.

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

PubMed

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.

PubMed

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.

NASA Safety and Health (Short Form). Final rule

NASA Technical Reports Server (NTRS)

2001-01-01

This final rule adopts with changes the interim rule published in the Federal Register on April 5, 2001 (65 FR 18051-18053), which amended the NASA FAR Supplement to implement a Safety and Health (Short Form) clause to address safety and occupational health in all NASA contracts above the micro-purchase threshold where the existing Safety and Health clause did not apply, and amended other safety and health clauses to be consistent with the new NASA Safety and Health (Short Form) clause.

Predicting Changes in Cultural Sensitivity among Students of Spanish during Short-Term Study Abroad

ERIC Educational Resources Information Center

Martinsen, Rob

2011-01-01

Short-term study abroad programs of less than a semester are becoming increasingly popular among undergraduate students in the United States. However, little research has examined the changes in students' cultural sensitivity through their participation in such programs or what factors may predict growth and improvement in such areas. This study…

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

NASA Astrophysics Data System (ADS)

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.

Short-term Memory as a Processing Shift

ERIC Educational Resources Information Center

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)

Extension of short-term variation study of Kangilerngata Sermia, Greenland

NASA Astrophysics Data System (ADS)

Kane, E.; Rignot, E. J.; Mouginot, J.

2017-12-01

Iceberg calving is an important but not well-understood aspect of predicting future sea level rise, mostly due to lack of observations. In this study a Gamma Portable Radar Interferometer (GPRI) was deployed for three weeks to observe short-term variations at Kangilerngata Sermia, West Greenland, with the goal of increasing observations of calving events and short-term velocity variations. A diurnal velocity cycle was measured and attributed to melt water production increasing basal lubrication. Many iceberg calving events were observed; one of which was immediately followed by a velocity increase of 35% that lasted 5 hours. We propose that this event was grounded ice and that the removal of basal drag associated with the calving allowed for acceleration of the glacier. Other calving from the region of floating ice had no effect on glacier speed. CTD data from 2008-2016 in the glacier fjord is analyzed to investigate ice-ocean interactions and the role of warm Atlantic water in glacial retreat. This work was funded by a grant from NASA Cryosphere Science and by the UC Irvine Donald Bren fund.

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

PubMed

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.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Melin, Alexander M.; Olama, Mohammed M.; Dong, Jin

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 tomore » 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.« less

Short-term Temperature Prediction Using Adaptive Computing on Dynamic Scales

NASA Astrophysics Data System (ADS)

Hu, W.; Cervone, G.; Jha, S.; Balasubramanian, V.; Turilli, M.

2017-12-01

When predicting temperature, there are specific places and times when high accuracy predictions are harder. For example, not all the sub-regions in the domain require the same amount of computing resources to generate an accurate prediction. Plateau areas might require less computing resources than mountainous areas because of the steeper gradient of temperature change in the latter. However, it is difficult to estimate beforehand the optimal allocation of computational resources because several parameters play a role in determining the accuracy of the forecasts, in addition to orography. The allocation of resources to perform simulations can become a bottleneck because it requires human intervention to stop jobs or start new ones. The goal of this project is to design and develop a dynamic approach to generate short-term temperature predictions that can automatically determines the required computing resources and the geographic scales of the predictions based on the spatial and temporal uncertainties. The predictions and the prediction quality metrics are computed using a numeric weather prediction model, Analog Ensemble (AnEn), and the parallelization on high performance computing systems is accomplished using Ensemble Toolkit, one component of the RADICAL-Cybertools family of tools. RADICAL-Cybertools decouple the science needs from the computational capabilities by building an intermediate layer to run general ensemble patterns, regardless of the science. In this research, we show how the ensemble toolkit allows generating high resolution temperature forecasts at different spatial and temporal resolution. The AnEn algorithm is run using NAM analysis and forecasts data for the continental United States for a period of 2 years. AnEn results show that temperature forecasts perform well according to different probabilistic and deterministic statistical tests.

Sensitivity of Short-Term Weather Forecasts to Assimilated AIRS Data: Implications for NPOESS Applications

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; McCarty, Will; Chou, Shih-Hung; Jedlovec, Gary

2009-01-01

The Atmospheric Infrared Sounder (AIRS) is acting as a heritage and risk reduction instrument for the Cross-track lnfrared Sounder (CrIS) to be flown aboard the NPP and NPOESS satellites. The hyperspectral nature of AIRS and CrIS provides high-quality soundings that, along with their asynoptic observation time over North America, make them attractive sources to fill the spatial and temporal data voids in upper air temperature and moisture measurements for use in data assimilation and numerical weather prediction. Observations from AlRS can be assimilated either as direct radiances or retrieved thermodynamic profiles, and the Short-Term Prediction Research and Transition (SPORT) Center at NASA's Marshall Space Flight Center has used both data types to improve short-term (0-48h), regional forecasts. The purpose of this paper is to share SPORT'S experiences using AlRS radiances and retrieved profiles in regional data assimilation activities by showing that proper handling of issues-including cloud contamination and land emissivity characterization-are necessary to produce optimal analyses and forecasts.

Comparison of different risk stratification systems in predicting short-term serious outcome of syncope patients.

PubMed

Safari, Saeed; Baratloo, Alireza; Hashemi, Behrooz; Rahmati, Farhad; Forouzanfar, Mohammad Mehdi; Motamedi, Maryam; Mirmohseni, Ladan

2016-01-01

Determining etiologic causes and prognosis can significantly improve management of syncope patients. The present study aimed to compare the values of San Francisco, Osservatorio Epidemiologico sulla Sincope nel Lazio (OESIL), Boston, and Risk Stratification of Syncope in the Emergency Department (ROSE) score clinical decision rules in predicting the short-term serious outcome of syncope patients. The present diagnostic accuracy study with 1-week follow-up was designed to evaluate the predictive values of the four mentioned clinical decision rules. Screening performance characteristics of each model in predicting mortality, myocardial infarction (MI), and cerebrovascular accidents (CVAs) were calculated and compared. To evaluate the value of each aforementioned model in predicting the outcome, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were calculated and receiver-operating curve (ROC) curve analysis was done. A total of 187 patients (mean age: 64.2 ± 17.2 years) were enrolled in the study. Mortality, MI, and CVA were seen in 19 (10.2%), 12 (6.4%), and 36 (19.2%) patients, respectively. Area under the ROC curve for OESIL, San Francisco, Boston, and ROSE models in prediction the risk of 1-week mortality, MI, and CVA was in the 30-70% range, with no significant difference among models ( P > 0.05). The pooled model did not show higher accuracy in prediction of mortality, MI, and CVA compared to others ( P > 0.05). This study revealed the weakness of all four evaluated models in predicting short-term serious outcome of syncope patients referred to the emergency department without any significant advantage for one among others.

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

PubMed

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.

PubMed

Shang, Qiang; Lin, Ciyun; Yang, Zhaosheng; Bing, Qichun; Zhou, Xiyang

2016-01-01

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.

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

PubMed Central

Lin, Ciyun; Yang, Zhaosheng; Bing, Qichun; Zhou, Xiyang

2016-01-01

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. PMID:27551829

Web-Enhanced Instruction and Learning: Findings of a Short- and Long-Term Impact Study and Teacher Use of NASA Web Resources

NASA Technical Reports Server (NTRS)

McCarthy, Marianne C.; Grabowski, Barbara L.; Koszalka, Tiffany

2003-01-01

Over a three-year period, researchers and educators from the Pennsylvania State University (PSU), University Park, Pennsylvania, and the NASA Dryden Flight Research Center (DFRC), Edwards, California, worked together to analyze, develop, implement and evaluate materials and tools that enable teachers to use NASA Web resources effectively for teaching science, mathematics, technology and geography. Two conference publications and one technical paper have already been published as part of this educational research series on Web-based instruction and learning. This technical paper, Web-Enhanced Instruction and Learning: Findings of a Short- and Long-Term Impact Study, is the culminating report in this educational research series and is based on the final report submitted to NASA. This report describes the broad spectrum of data gathered from teachers about their experiences using NASA Web resources in the classroom. It also describes participating teachers responses and feedback about the use of the NASA Web-Enhanced Learning Environment Strategies reflection tool on their teaching practices. The reflection tool was designed to help teachers merge the vast array of NASA resources with the best teaching methods, taking into consideration grade levels, subject areas and teaching preferences. The teachers described their attitudes toward technology and innovation in the classroom and their experiences and perceptions as they attempted to integrate Web resources into science, mathematics, technology and geography instruction.

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

NASA Astrophysics Data System (ADS)

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

14 CFR 1214.809 - Short-term call-up and accelerated launch.

Code of Federal Regulations, 2011 CFR

2011-01-01

... short-term call-up and accelerated launch provisions of the Shuttle policy normally are not offered to Spacelab customers. NASA will negotiate any such customer requirements on an individual basis. ...

14 CFR 1214.809 - Short-term call-up and accelerated launch.

Code of Federal Regulations, 2013 CFR

2013-01-01

... short-term call-up and accelerated launch provisions of the Shuttle policy normally are not offered to Spacelab customers. NASA will negotiate any such customer requirements on an individual basis. ...

14 CFR 1214.809 - Short-term call-up and accelerated launch.

Code of Federal Regulations, 2012 CFR

2012-01-01

... short-term call-up and accelerated launch provisions of the Shuttle policy normally are not offered to Spacelab customers. NASA will negotiate any such customer requirements on an individual basis. ...

14 CFR 1214.809 - Short-term call-up and accelerated launch.

Code of Federal Regulations, 2010 CFR

2010-01-01

... short-term call-up and accelerated launch provisions of the Shuttle policy normally are not offered to Spacelab customers. NASA will negotiate any such customer requirements on an individual basis. ...

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

PubMed Central

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. PMID:29391864

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

PubMed

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.

Comparison of different risk stratification systems in predicting short-term serious outcome of syncope patients

PubMed Central

Safari, Saeed; Baratloo, Alireza; Hashemi, Behrooz; Rahmati, Farhad; Forouzanfar, Mohammad Mehdi; Motamedi, Maryam; Mirmohseni, Ladan

2016-01-01

Background: Determining etiologic causes and prognosis can significantly improve management of syncope patients. The present study aimed to compare the values of San Francisco, Osservatorio Epidemiologico sulla Sincope nel Lazio (OESIL), Boston, and Risk Stratification of Syncope in the Emergency Department (ROSE) score clinical decision rules in predicting the short-term serious outcome of syncope patients. Materials and Methods: The present diagnostic accuracy study with 1-week follow-up was designed to evaluate the predictive values of the four mentioned clinical decision rules. Screening performance characteristics of each model in predicting mortality, myocardial infarction (MI), and cerebrovascular accidents (CVAs) were calculated and compared. To evaluate the value of each aforementioned model in predicting the outcome, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were calculated and receiver-operating curve (ROC) curve analysis was done. Results: A total of 187 patients (mean age: 64.2 ± 17.2 years) were enrolled in the study. Mortality, MI, and CVA were seen in 19 (10.2%), 12 (6.4%), and 36 (19.2%) patients, respectively. Area under the ROC curve for OESIL, San Francisco, Boston, and ROSE models in prediction the risk of 1-week mortality, MI, and CVA was in the 30–70% range, with no significant difference among models (P > 0.05). The pooled model did not show higher accuracy in prediction of mortality, MI, and CVA compared to others (P > 0.05). Conclusion: This study revealed the weakness of all four evaluated models in predicting short-term serious outcome of syncope patients referred to the emergency department without any significant advantage for one among others. PMID:27904602

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

PubMed

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 < 0.0001). The alternative 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.

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

PubMed

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.

14 CFR § 1214.809 - Short-term call-up and accelerated launch.

Code of Federal Regulations, 2014 CFR

2014-01-01

.... The short-term call-up and accelerated launch provisions of the Shuttle policy normally are not offered to Spacelab customers. NASA will negotiate any such customer requirements on an individual basis. ...

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

PubMed

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.

Can biological components predict short-term evolution in Autism Spectrum Disorders? A proof-of-concept study.

PubMed

Emberti Gialloreti, Leonardo; Benvenuto, Arianna; Battan, Barbara; Benassi, Francesca; Curatolo, Paolo

2016-07-22

The clinical and pathogenetic heterogeneity of Autism Spectrum Disorders (ASD) limits our ability to predict its short- and long-term evolution. Aim of this naturalistic study was to observe the clinical evolution of very young children with ASD for 12 months after first diagnosis, in order to identify those children who might develop a more positive trajectory and understand how a wide range of biological, clinical and familial factors can influence prognosis. Ninety-two children were characterized in terms of family history, prenatal and perinatal variables, and clinical conditions. The sample was divided into four subgroups based on the association of 22 biological, clinical and family history variables. Developmental Quotient (DQ), determined using the Psychoeducational Profile Revised (PEP-R), and symptoms severity, measured by means of the Autism Diagnostic Observation Schedule (ADOS), were evaluated at baseline (T0) and after one year (T1), while receiving treatment as usual. Changes in DQ and ADOS between baseline and follow-up and differences in the short-term evolution of the four subgroups were analyzed. At T1, 55.4 % of the children demonstrated some gains either of autistic symptomatology or of developmental skills. Mean ADOS score was 13.63 ± 3.67 at T0 and 10.85 ± 4.10 at T1 and mean DQ was 0.64 ± 0.14 at T0 and 0.66 ± 0.15 at T1. At follow-up, 33.7 % of the children showed an improvement in DQ and 37 % presented a less severe symptomatology, measured by means of ADOS. Overall, 15.2 % of the sample displayed major improvements both on developmental quotient and ADOS severity score; these children presented less EEG abnormalities and familial psychiatric disorders. The four subgroups, based on biological, clinical and familial variables, showed differing trends in terms of evolution. Categorizing very young children with ASD in terms of biological, clinical and familial variables can be instrumental in predicting short-term

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

PubMed

Vaaler, Arne E; Iversen, Valentina C; Morken, Gunnar; Fløvig, John C; Palmstierna, Tom; Linaker, Olav M

2011-03-18

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. 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. 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. 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. NCT00184119/NCT00184132.

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

NASA Astrophysics Data System (ADS)

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.

Short and long term improvements in quality of chronic care delivery predict program sustainability.

PubMed

Cramm, Jane Murray; Nieboer, Anna Petra

2014-01-01

Empirical evidence on sustainability of programs that improve the quality of care delivery over time is lacking. Therefore, this study aims to identify the predictive role of short and long term improvements in quality of chronic care delivery on program sustainability. In this longitudinal study, professionals [2010 (T0): n=218, 55% response rate; 2011 (T1): n=300, 68% response rate; 2012 (T2): n=265, 63% response rate] from 22 Dutch disease-management programs completed surveys assessing quality of care and program sustainability. Our study findings indicated that quality of chronic care delivery improved significantly in the first 2 years after implementation of the disease-management programs. At T1, overall quality, self-management support, delivery system design, and integration of chronic care components, as well as health care delivery and clinical information systems and decision support, had improved. At T2, overall quality again improved significantly, as did community linkages, delivery system design, clinical information systems, decision support and integration of chronic care components, and self-management support. Multilevel regression analysis revealed that quality of chronic care delivery at T0 (p<0.001) and quality changes in the first (p<0.001) and second (p<0.01) years predicted program sustainability. In conclusion this study showed that disease-management programs based on the chronic care model improved the quality of chronic care delivery over time and that short and long term changes in the quality of chronic care delivery predicted the sustainability of the projects. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Job satisfaction and short-term sickness absence among Dutch workers.

PubMed

Notenbomer, Annette; Roelen, Corné A M; Groothoff, Johan W

2006-06-01

Sickness absence is a considerable economic and social problem. Short-term sickness absence is known to be associated with behavioural attitudes. The correlation between sickness absence and job satisfaction has been studied infrequently and with contradictory results. This study investigated the correlation between short-term sickness absence and both global and specific job satisfaction. We defined short-term sickness absence as spells of up to 42 days. A random sample of 898 Dutch workers from a variety of economic sectors and companies received a self-report questionnaire on their first day of sick leave. The questionnaire measured global and specific job satisfaction. In our regression analysis, we controlled for the confounding factors of age, gender, educational level, perceived workload, job autonomy and decision latitude. The duration of an absence spell was defined as the amount of calendar days between sick leave and return to work. Global job satisfaction did not correlate significantly with the duration of short-term sickness absence. While increasing physical job demands predicted longer absence, increasing job autonomy and educational level predicted shorter absence. Satisfaction with colleagues predicted longer duration absence. Global job satisfaction did not correlate with the duration of short-term absence spells, but specific satisfaction with colleagues was associated with longer sickness spells.

Measuring short-term and long-term physiological stress effects by cortisol reactivity in saliva and hair.

PubMed

van Holland, Berry J; Frings-Dresen, Monique H W; Sluiter, Judith K

2012-11-01

The aims of this study were to investigate (1) the concurrent relationship between short-term and long-term stress reactivity measured by cortisol excretion and (2) the relationship of these physiological stress effects with self-reported stress and need for recovery after work (NFR). Participants were production workers in the meat-processing industry. Short-term cortisol excretion was calculated by summing 18 saliva samples, sampled over a 3-day period. Samples were delivered by 37 participants. Twenty-nine of them also supplied one hair sample of at least 3 cm in length for an analysis of long-term (3 months) cortisol excretion. All of them filled in a short questionnaire on self-reported stress and NFR. Self-reported stress was assessed by a three-item stress screener; NFR was assessed by an 11-item scale. Short-term and long-term cortisol excretion are significantly, but moderately, associated (r = 0.41, P = 0.03). Short-term and long-term cortisol excretion correlated weakly to self-reported stress and NFR (correlations varied from -0.04 to 0.21). Short-term and long-term physiological stress excretion levels are moderately associated. Physiological stress effects assessed from saliva and hair cannot be used interchangeably with self-reported stress because they only correlate weakly. To better predict long-term cortisol excretion in workers, the predictive value of short-term cortisol excretion must be evaluated in a prognostic longitudinal study in a working population.

Very-short-term wind power prediction by a hybrid model with single- and multi-step approaches

NASA Astrophysics Data System (ADS)

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

2017-05-01

Very-short-term wind power prediction (VSTWPP) has played an essential role for the operation of electric power systems. This paper aims at improving and applying a hybrid method of VSTWPP based on historical data. The hybrid method is combined by multiple linear regressions and least square (MLR&LS), which is intended for reducing prediction errors. The predicted values are obtained through two sub-processes:1) transform the time-series data of actual wind power into the power ratio, and then predict the power ratio;2) use the predicted power ratio to predict the wind power. Besides, the proposed method can include two prediction approaches: single-step prediction (SSP) and multi-step prediction (MSP). WPP is tested comparatively by auto-regressive moving average (ARMA) model from the predicted values and errors. The validity of the proposed hybrid method is confirmed in terms of error analysis by using probability density function (PDF), mean absolute percent error (MAPE) and means square error (MSE). Meanwhile, comparison of the correlation coefficients between the actual values and the predicted values for different prediction times and window has confirmed that MSP approach by using the hybrid model is the most accurate while comparing to SSP approach and ARMA. The MLR&LS is accurate and promising for solving problems in WPP.

Improving creativity performance by short-term meditation.

PubMed

Ding, Xiaoqian; Tang, Yi-Yuan; Tang, Rongxiang; Posner, Michael I

2014-03-19

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. 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. 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). Our results suggested that emotion-related creativity-promoting mechanism may be attributed to short-term meditation.

Oxygen uptake on-kinetics during six-minute walk test predicts short-term outcomes after off-pump coronary artery bypass surgery.

PubMed

Rocco, Isadora Salvador; Viceconte, Marcela; Pauletti, Hayanne Osiro; Matos-Garcia, Bruna Caroline; Marcondi, Natasha Oliveira; Bublitz, Caroline; Bolzan, Douglas William; Moreira, Rita Simone Lopes; Reis, Michel Silva; Hossne, Nelson Américo; Gomes, Walter José; Arena, Ross; Guizilini, Solange

2017-12-26

We aimed to investigate the ability of oxygen uptake kinetics to predict short-term outcomes after off-pump coronary artery bypass grafting. Fifty-two patients aged 60.9 ± 7.8 years waiting for off-pump coronary artery bypass surgery were evaluated. The 6-min walk test distance was performed pre-operatively, while simultaneously using a portable cardiopulmonary testing device. The transition of oxygen uptake kinetics from rest to exercise was recorded to calculate oxygen uptake kinetics fitting a monoexponential regression model. Oxygen uptake at steady state, constant time, and mean response time corrected by work rate were analysed. Short-term clinical outcomes were evaluated during the early post-operative of off-pump coronary artery bypass surgery. Multivariate analysis showed body mass index, surgery time, and mean response time corrected by work rate as independent predictors for short-term outcomes. The optimal mean response time corrected by work rate cut-off to estimate short-term clinical outcomes was 1.51 × 10 -3  min 2 /ml. Patients with slower mean response time corrected by work rate demonstrated higher rates of hypertension, diabetes, EuroSCOREII, left ventricular dysfunction, and impaired 6-min walk test parameters. The per cent-predicted distance threshold of 66% in the pre-operative was associated with delayed oxygen uptake kinetics. Pre-operative oxygen uptake kinetics during 6-min walk test predicts short-term clinical outcomes after off-pump coronary artery bypass surgery. From a clinically applicable perspective, a threshold of 66% of pre-operative predicted 6-min walk test distance indicated slower kinetics, which leads to longer intensive care unit and post-surgery hospital length of stay. Implications for rehabilitation Coronary artery bypass grafting is a treatment aimed to improve expectancy of life and prevent disability due to the disease progression; The use of pre-operative submaximal functional capacity test enabled the

Short-term Operation of Multi-purpose Reservoir using Model Predictive Control

NASA Astrophysics Data System (ADS)

Uysal, Gokcen; Schwanenberg, Dirk; Alvarado Montero, Rodolfo; Sensoy, Aynur; Arda Sorman, Ali

2017-04-01

Operation of water structures especially with conflicting water supply and flood mitigation objectives is under more stress attributed to growing water demand and changing hydro-climatic conditions. Model Predictive Control (MPC) based optimal control solutions has been successfully applied to different water resources applications. In this study, Feedback Control (FBC) and MPC get combined and an improved joint optimization-simulation operating scheme is proposed. Water supply and flood control objectives are fulfilled by incorporating the long term water supply objectives into a time-dependent variable guide curve policy whereas the extreme floods are attenuated by means of short-term optimization based on MPC. A final experiment is carried out to assess the lead time performance and reliability of forecasts in a hindcasting experiment with imperfect, perturbed forecasts. The framework is tested in Yuvacık Dam reservoir where the main water supply reservoir of Kocaeli City in the northwestern part of Turkey (the Marmara region) and it requires a challenging gate operation due to restricted downstream flow conditions.

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

PubMed

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 <15%, averagely 12.930%. To the best of our knowledge, it is the first time that 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.

Clinical picture and risk prediction of short-term mortality in cardiogenic shock.

PubMed

Harjola, Veli-Pekka; Lassus, Johan; Sionis, Alessandro; Køber, Lars; Tarvasmäki, Tuukka; Spinar, Jindrich; Parissis, John; Banaszewski, Marek; Silva-Cardoso, Jose; Carubelli, Valentina; Di Somma, Salvatore; Tolppanen, Heli; Zeymer, Uwe; Thiele, Holger; Nieminen, Markku S; Mebazaa, Alexandre

2015-05-01

The aim of this study was to investigate the clinical picture and outcome of cardiogenic shock and to develop a risk prediction score for short-term mortality. The CardShock study was a multicentre, prospective, observational study conducted between 2010 and 2012. Patients with either acute coronary syndrome (ACS) or non-ACS aetiologies were enrolled within 6 h from detection of cardiogenic shock defined as severe hypotension with clinical signs of hypoperfusion and/or serum lactate >2 mmol/L despite fluid resuscitation (n = 219, mean age 67, 74% men). Data on clinical presentation, management, and biochemical variables were compared between different aetiologies of shock. Systolic blood pressure was on average 78 mmHg (standard deviation 14 mmHg) and mean arterial pressure 57 (11) mmHg. The most common cause (81%) was ACS (68% ST-elevation myocardial infarction and 8% mechanical complications); 94% underwent coronary angiography, of which 89% PCI. Main non-ACS aetiologies were severe chronic heart failure and valvular causes. In-hospital mortality was 37% (n = 80). ACS aetiology, age, previous myocardial infarction, prior coronary artery bypass, confusion, low LVEF, and blood lactate levels were independently associated with increased mortality. The CardShock risk Score including these variables and estimated glomerular filtration rate predicted in-hospital mortality well (area under the curve 0.85). Although most commonly due to ACS, other causes account for one-fifth of cases with shock. ACS is independently associated with in-hospital mortality. The CardShock risk Score, consisting of seven common variables, easily stratifies risk of short-term mortality. It might facilitate early decision-making in intensive care or guide patient selection in clinical trials. NCT01374867. © 2015 The Authors. European Journal of Heart Failure © 2015 European Society of Cardiology.

Business Students' Choice of Short-Term or Long-Term Study Abroad Opportunities

ERIC Educational Resources Information Center

Fitzsimmons, Stacey R.; Flanagan, David J.; Wang, Xiaodan

2013-01-01

Recent years have seen a proliferation of short-term study abroad opportunities. Although they are both supplementing and replacing semester-long study abroad programs, research has focused primarily on semester (long-term) programs. We draw on the theory of planned behavior (TPB) to explore factors that predict why students choose long-term and…

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

PubMed Central

2011-01-01

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 PMID:21418581

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

PubMed

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.

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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 (<10days) predictions of universal time (UT1-UTC). The results of predictions are analyzed and compared with those obtained by other methods. It is shown that the accuracy of the predictions is comparable with that obtained by other prediction methods. The proposed method is able to yield an exact prediction even though only a few observations are provided. Hence it is very valuable in the case of a small size dataset since traditional methods, e.g., least-squares (LS) extrapolation, require longer data span to make a good forecast. In addition, these results can be obtained without making any assumption about an original dataset, and thus is of high reliability. Another 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.

Improving creativity performance by short-term meditation

PubMed Central

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.

PubMed

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

A first look at global flash drought: long term change and short term predictability

NASA Astrophysics Data System (ADS)

Yuan, Xing; Wang, Linying; Ji, Peng

2017-04-01

"Flash drought" became popular after the unexpected 2012 central USA drought, mainly due to its rapid development, low predictability and devastating impacts on water resources and crop yields. A pilot study by Mo and Lettenmaier (2015) found that flash drought, based on a definition of concurrent heat extreme, soil moisture deficit and evapotranspiration (ET) enhancement at pentad scale, were in decline over USA during recent 100 years. Meanwhile, a recent work indicated that the occurrence of flash drought in China was doubled during the past 30 years, where a severe flash drought in the summer of 2013 ravaged 13 provinces in southern China. As global warming increases the frequency of heat waves and accelerates the hydrological cycle, the flash drought is expected to increase in general, but its trend might also be affected by interannual to decadal climate oscillations. To consolidate the hotspots of flash drought and the effects of climate change on flash drought, a global inventory is being conducted by using multi-source observations (in-situ, satellite and reanalysis), CMIP5 historical simulations and future projections under different forcing scenarios, as well as global land surface hydrological modeling for key variables including surface air temperature, soil moisture and ET. In particular, a global picture of the flash drought distribution, the contribution of naturalized and anthropogenic forcings to global flash drought change, and the risk of global flash drought in the future, will be presented. Besides investigating the long-term change of flash drought, providing reliable early warning is also essential to developing adaptation strategies. While regional drought early warning systems have been emerging in recent decade, forecasting of flash drought is still at an exploratory stage due to limited understanding of flash drought predictability. Here, a set of sub-seasonal to seasonal (S2S) hindcast datasets are being used to assess the short term

The Surgical Apgar Score Predicts Not Only Short-Term Complications But Also Long-Term Prognosis After Esophagectomy.

PubMed

Nakagawa, Akio; Nakamura, Tetsu; Oshikiri, Taro; Hasegawa, Hiroshi; Yamamoto, Masashi; Kanaji, Shingo; Matsuda, Yoshiko; Yamashita, Kimihiro; Matsuda, Takeru; Sumi, Yasuo; Suzuki, Satoshi; Kakeji, Yoshihiro

2017-12-01

The surgical Apgar score (SAS) quantifies three intraoperative factors and predicts postoperative complications, but few reports describe its usefulness in esophagectomy, and no studies to date show its correlation with long-term prognosis after esophagectomy. This study investigated 400 cases in which esophagectomy was performed on esophageal malignant tumors at the authors' hospital from January 2007 to January 2017. In this study, SAS was defined as the sum of the scores of three parameters, namely, estimated blood loss, lowest mean arterial pressure, and lowest heart rate, with values extracted from medical records. Postoperative complications classified as Clavien-Dindo grade 3 or higher were also extracted. The study retrospectively compared the relationship of SAS to postoperative complications and survival. Univariate analysis showed that postoperative complications were significantly associated with hypertension (p = 0.017), thoracotomy (p = 0.012), and SAS ≤ 5 (p < 0.0001), and multivariate analysis showed that hypertension (p = 0.049) and SAS ≤ 5 (p < 0.0001) were significant predictive factors for complications. In the prognostic analysis, log-rank analysis showed that patients with an SAS ≤ 5 had a significantly poorer prognosis than those with a SAS > 5 (p = 0.043), especially for complications classified as clinical stage 2 or higher (p = 0.027). In the multivariate analysis, SAS ≤ 5 was identified as a significantly poor prognostic factor for complications classified as clinical stage 2 or higher (p = 0.029). In this study, SAS was useful not only for predicting short-term complications, but also as a long-term prognostic factor after esophagectomy.

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

PubMed

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

NASA Astrophysics Data System (ADS)

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.

A generic approach for the development of short-term predictions of Escherichia coli and biotoxins in shellfish

PubMed Central

Schmidt, Wiebke; Evers-King, Hayley L.; Campos, Carlos J. A.; Jones, Darren B.; Miller, Peter I.; Davidson, Keith; Shutler, Jamie D.

2018-01-01

Microbiological contamination or elevated marine biotoxin concentrations within shellfish can result in temporary closure of shellfish aquaculture harvesting, leading to financial loss for the aquaculture business and a potential reduction in consumer confidence in shellfish products. We present a method for predicting short-term variations in shellfish concentrations of Escherichia coli and biotoxin (okadaic acid and its derivates dinophysistoxins and pectenotoxins). The approach was evaluated for 2 contrasting shellfish harvesting areas. Through a meta-data analysis and using environmental data (in situ, satellite observations and meteorological nowcasts and forecasts), key environmental drivers were identified and used to develop models to predict E. coli and biotoxin concentrations within shellfish. Models were trained and evaluated using independent datasets, and the best models were identified based on the model exhibiting the lowest root mean square error. The best biotoxin model was able to provide 1 wk forecasts with an accuracy of 86%, a 0% false positive rate and a 0% false discovery rate (n = 78 observations) when used to predict the closure of shellfish beds due to biotoxin. The best E. coli models were used to predict the European hygiene classification of the shellfish beds to an accuracy of 99% (n = 107 observations) and 98% (n = 63 observations) for a bay (St Austell Bay) and an estuary (Turnaware Bar), respectively. This generic approach enables high accuracy short-term farm-specific forecasts, based on readily accessible environmental data and observations. PMID:29805719

Short-term hot hardness characteristics of rolling-element steels

NASA Technical Reports Server (NTRS)

Chevalier, J. L.; Dietrich, M. W.; Zaretsky, E. V.

1972-01-01

Short-term hot hardness studies were performed with five vacuum-melted steels at temperatures from 294 to 887 K (70 to 1140 F). Based upon a minimum Rockwell C hardness of 58, the temperature limitation on all materials studied was dependent on the initial room temperature hardness and the tempering temperature of each material. For the same room temperature hardness, the short-term hot hardness characteristics were identical and independent of material composition. An equation was developed to predict the short-term hardness at temperature as a function of initial room temperature hardness for AISI 52100, as well as the high-speed tool steels.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed Central

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 (< 2 h, 2-4 h, and > 4 h) and LT adherence (< 4 h, > 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 < 0.001). Neither ST nor LT adherence were related to demographic variables, baseline severity of untreated SDB, sleep architecture, or measures of daytime impairment. Good 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

The comparison of umbilical cord arterial blood lactate and pH values for predicting short-term neonatal outcomes.

PubMed

Einikyte, Ruta; Snieckuviene, Vilija; Ramasauskaite, Diana; Panaviene, Jurate; Paliulyte, Virginija; Opolskiene, Gina; Kazenaite, Edita

2017-12-01

Current clinical practice of assessing neonatal condition is based on evaluation of umbilical cord arterial blood pH value rather than lactate. However, evidence shows that lactate is direct and more predictive measurement than pH or at least of equal importance. This study is to assess and compare umbilical cord arterial lactate and pH values for predicting short-term neonatal outcomes. A retrospective cohort study was conducted at the tertiary level hospital, were arterial umbilical cord blood sampling was collected according to the standard procedures. Neonatal morbidity was registered if at least one of the following conditions was noted: Apgar score at 1 min after delivery was 6 or lower, resuscitation performed, including assisted ventilation and requirement of admission to neonatal intensive care unit. Mothers-newborns pairs were allocated into two groups: newborns exposed to perinatal hypoxia (group 1) and observed as healthy newborns (group 2). Receiver operating characteristics curves (ROC) were generated to assess the predictive ability of pH and lactate for the short-term neonatal outcomes. 901 neonates born at ≥37 weeks of gestation were included. Newborns exposed to perinatal hypoxia (group 1) encompassed 39 (4.3%) patients, and observed as healthy (group 2) - 862 (95.7%). Arterial umbilical cord blood pH in group 1 was 7.160 ± 0.126 as compared to 7.314 ± 0.083 in group 2; p < 0.001. Mean arterial lactate was significantly higher in group 1 than group 2 (6.423 ± 2.335 as compared to 3.600 ± 1.833; p < 0.001). The difference between areas under ROC curves representing pH and lactate was not significant (0.848 and 0.831 respectively; p = 0.6132). Umbilical cord arterial lactate and pH predicted short-term neonatal outcomes with similar efficacies. Copyright © 2017. Published by Elsevier B.V.

A new model integrating short- and long-term aging of copper added to soils

PubMed Central

Zeng, Saiqi; Li, Jumei; Wei, Dongpu

2017-01-01

Aging refers to the processes by which the bioavailability/toxicity, isotopic exchangeability, and extractability of metals added to soils decline overtime. We studied the characteristics of the aging process in copper (Cu) added to soils and the factors that affect this process. Then we developed a semi-mechanistic model to predict the lability of Cu during the aging process with descriptions of the diffusion process using complementary error function. In the previous studies, two semi-mechanistic models to separately predict short-term and long-term aging of Cu added to soils were developed with individual descriptions of the diffusion process. In the short-term model, the diffusion process was linearly related to the square root of incubation time (t1/2), and in the long-term model, the diffusion process was linearly related to the natural logarithm of incubation time (lnt). Both models could predict short-term or long-term aging processes separately, but could not predict the short- and long-term aging processes by one model. By analyzing and combining the two models, we found that the short- and long-term behaviors of the diffusion process could be described adequately using the complementary error function. The effect of temperature on the diffusion process was obtained in this model as well. The model can predict the aging process continuously based on four factors—soil pH, incubation time, soil organic matter content and temperature. PMID:28820888

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

NASA Astrophysics Data System (ADS)

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  <  0.01). Thus, this study demonstrated that CAD-generated false-positives might include valuable information, which needs to be further explored for identifying and/or developing more effective imaging markers for predicting short-term breast cancer risk.

Short-term solar activity forecasting

NASA Technical Reports Server (NTRS)

Xie-Zhen, C.; Ai-Di, Z.

1979-01-01

A method of forecasting the level of activity of every active region on the surface of the Sun within one to three days is proposed in order to estimate the possibility of the occurrence of ionospheric disturbances and proton events. The forecasting method is a probability process based on statistics. In many of the cases, the accuracy in predicting the short term solar activity was in the range of 70%, although there were many false alarms.

Short-Term Memory for Temporal Intervals: Contrasting Explanations of the Choose-Short Effect in Pigeons

ERIC Educational Resources Information Center

Pinto, Carlos; Machado, Armando

2011-01-01

To better understand short-term memory for temporal intervals, we re-examined the choose-short effect. In Experiment 1, to contrast the predictions of two models of this effect, the subjective shortening and the coding models, pigeons were exposed to a delayed matching-to-sample task with three sample durations (2, 6 and 18 s) and retention…

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

PubMed

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.

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

PubMed

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.

The Predictive Validity of the Short-Term Assessment of Risk and Treatability (START) for Multiple Adverse Outcomes in a Secure Psychiatric Inpatient Setting.

PubMed

O'Shea, Laura E; Picchioni, Marco M; Dickens, Geoffrey L

2016-04-01

The Short-Term Assessment of Risk and Treatability (START) aims to assist mental health practitioners to estimate an individual's short-term risk for a range of adverse outcomes via structured consideration of their risk ("Vulnerabilities") and protective factors ("Strengths") in 20 areas. It has demonstrated predictive validity for aggression but this is less established for other outcomes. We collated START assessments for N = 200 adults in a secure mental health hospital and ascertained 3-month risk event incidence using the START Outcomes Scale. The specific risk estimates, which are the tool developers' suggested method of overall assessment, predicted aggression, self-harm/suicidality, and victimization, and had incremental validity over the Strength and Vulnerability scales for these outcomes. The Strength scale had incremental validity over the Vulnerability scale for aggressive outcomes; therefore, consideration of protective factors had demonstrable value in their prediction. Further evidence is required to support use of the START for the full range of outcomes it aims to predict. © The Author(s) 2015.

Brain oscillatory substrates of visual short-term memory capacity.

PubMed

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.

Space technologies for short-term earthquake warning

NASA Astrophysics Data System (ADS)

Pulinets, S.

Recent theoretical and experimental studies explicitly demonstrated the ability of space technologies to identify and monitor the specific variations at near-earth space plasma, atmosphere and ground surface associated with approaching severe earthquakes (named as earthquake precursors) appearing several days (from 1 to 5) before the seismic shock over the seismically active areas. Several countries and private companies are in the stage of preparation (or already launched) the dedicated spacecrafts for monitoring of the earthquake precursors from space and for short-term earthquake prediction. The present paper intends to outline the optimal algorithm for creation of the space-borne system for the earthquake precursors monitoring and for short-term earthquake prediction. It takes into account the following considerations: Selection of the precursors in the terms of priority, taking into account their statistical and physical parameters Configuration of the spacecraft payload Configuration of the satellite constellation (orbit selection, satellite distribution, operation schedule) Proposal of different options (cheap microsatellite or comprehensive multisatellite constellation) Taking into account that the most promising are the ionospheric precursors of earthquakes, the special attention will be devoted to the radiophysical techniques of the ionosphere monitoring. The advantages and disadvantages of such technologies as vertical sounding, in-situ probes, ionosphere tomography, GPS TEC and GPS MET technologies will be considered.

Space technologies for short-term earthquake warning

NASA Astrophysics Data System (ADS)

Pulinets, S. A.

Recent theoretical and experimental studies explicitly demonstrated the ability of space technologies to identify and monitor the specific variations at near-earth space plasma, atmosphere and ground surface associated with approaching severe earthquakes (named as earthquake precursors) which appear several days (from 1 to 5) before the seismic shock over the seismically active areas. Several countries and private companies are in the stage of preparation (or already launched) the dedicated spacecrafts for monitoring of the earthquake precursors from space and for short-term earthquake prediction. The present paper intends to outline the optimal algorithm for creation of the space-borne system for the earthquake precursors monitoring and for short-term earthquake prediction. It takes into account the following: Selection of the precursors in the terms of priority, considering their statistical and physical parameters.Configuration of the spacecraft payload.Configuration of the satellite constellation (orbit selection, satellite distribution, operation schedule).Different options of the satellite systems (cheap microsatellite or comprehensive multisatellite constellation). Taking into account that the most promising are the ionospheric precursors of earthquakes, the special attention is devoted to the radiophysical techniques of the ionosphere monitoring. The advantages and disadvantages of such technologies as vertical sounding, in-situ probes, ionosphere tomography, GPS TEC and GPS MET technologies are considered.

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

PubMed

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.

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.

PubMed

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 < 0.001) and OS (P < 0.001). The PER score was identified as an independent predictor of tumor recurrence (hazard ratio [HR] 2.1; P < 0.001) and OS (HR 2.2; P < 0.001). The 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.

Atmospheric Electrical Activity and the Prospects for Improving Short-Term, Weather Forcasting

NASA Technical Reports Server (NTRS)

Goodman, Steven J.

2003-01-01

How might lightning measurements be used to improve short-term (0-24 hr) weather forecasting? We examine this question under two different prediction strategies. These include integration of lightning data into short-term forecasts (nowcasts) of convective (including severe) weather hazards and the assimilation of lightning data into cloud-resolving numerical weather prediction models. In each strategy we define specific metrics of forecast improvement and a progress assessment. We also address the conventional observing system deficiencies and potential gap-filling information that can be addressed through the use of the lightning measurement.

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

PubMed

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.

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

PubMed

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.

Development of a High Resolution Weather Forecast Model for Mesoamerica Using the NASA Ames Code I Private Cloud Computing Environment

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Case, Jonathan; Venner, Jason; Moreno-Madrinan, Max J.; Delgado, Francisco

2012-01-01

Two projects at NASA Marshall Space Flight Center have collaborated to develop a high resolution weather forecast model for Mesoamerica: The NASA Short-term Prediction Research and Transition (SPoRT) Center, which integrates unique NASA satellite and weather forecast modeling capabilities into the operational weather forecasting community. NASA's SERVIR Program, which integrates satellite observations, ground-based data, and forecast models to improve disaster response in Central America, the Caribbean, Africa, and the Himalayas.

NASA quiet short-haul research aircraft experimenters' handbook

NASA Technical Reports Server (NTRS)

Mccracken, R. C.

1980-01-01

A summary of guidelines and particulars concerning the use of the NASA-Ames Research Center Quiet Short-Haul Research Aircraft for applicable flight experiments is presented. Procedures for submitting experiment proposals are included along with guidelines for experimenter packages, an outline of experiment selection processes, a brief aircraft description, and additional information regarding support at Ames.

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

PubMed

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.

Prediction of long-term transverse creep compliance in high-temperature IM7/LaRC-RP46 composites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yuan, F.G.; Potter, B.D.

1994-12-31

An experimental study is performed which predicts long-term tensile transverse creep compliance of high-temperature IM7/LaRC-RP46 composites from short-term creep and recovery tests. The short-term tests were conducted for various stress levels at various fixed temperatures. Predictive nonlinear viscoelastic model developed by Schapery and experimental procedure were used to predict the long-term results in terms of master curve extrapolated from short-term tests.

The SPoRT-WRF: Evaluating the Impact of NASA Datasets on Convective Forecasts

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Kozlowski, Danielle; Case, Jonathan; Molthan, Andrew

2012-01-01

Short-term Prediction Research and Transition (SPoRT) seeks to improve short-term, regional weather forecasts using unique NASA products and capabilities SPoRT has developed a unique, real-time configuration of the NASA Unified Weather Research and Forecasting (WRF)WRF (ARW) that integrates all SPoRT modeling research data: (1) 2-km SPoRT Sea Surface Temperature (SST) Composite, (2) 3-km LIS with 1-km Greenness Vegetation Fraction (GVFs) (3) 45-km AIRS retrieved profiles. Transitioned this real-time forecast to NOAA's Hazardous Weather Testbed (HWT) as deterministic model at Experimental Forecast Program (EFP). Feedback from forecasters/participants and internal evaluation of SPoRT-WRF shows a cool, dry bias that appears to suppress convection likely related to methodology for assimilation of AIRS profiles Version 2 of the SPoRT-WRF will premier at the 2012 EFP and include NASA physics, cycling data assimilation methodology, better coverage of precipitation forcing, and new GVFs

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

ERIC Educational Resources Information Center

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…

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

NASA Astrophysics Data System (ADS)

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.

[Histological effects of short term endocrine therapy on prostatic cancer].

PubMed

Irisawa, C; Yoshimura, Y; Yokota, T; Yamaguchi, O; Kondou, Y; Hamasaki, T; Yamad, Y; Kurosu, S; Chiba, R

1996-07-01

The objective of this study is to investigate the pathological changes which occurred in prostatic cancer shortly after the commencement of endocrine therapy. Fourty-three patients underwent radical prostatectomy immediately after the short term endocrine therapy (treatment period was within one month) and the histological pictures of operative specimens were compared to those obtained from the pretreatment biopsy specimens. Degenerative changes of cancer cells, such as nuclear and cytoplasmic vacuole, collapse of the cytoplasm and the appearance of naked hyperchromatic nucleus were noticed after the short term endocrine therapy. Especially in the cases which were histologically evaluated to be poorly differentiated in the biopsy specimens, not only degenerative changes but also destruction of cancer nests caused by cell death were observed. The histological effects affected by short term endocrine treatment had no relation to the prognosis, but in the cases of stage D2, the pathological grade judged by post-therapeutic specimens were found to be useful for the prediction of prognosis. Endocrine therapy induces remarkable pathological changes in prostatic cancer within a very short time after beginning treatment.

Value of semen parameters, with special reference to TNF-α, in predicting the quality of boar semen after short-term storage.

PubMed

Mrkun, Janko; Kosec, Marjan; Zrimšek, Petra

2013-06-01

The aim of this study was to address the question whether changes in boar semen quality after short-term storage could be predicted on the basis of standard semen parameters and TNF-α level determined on the day of semen collection under commercial conditions. Progressive motility showed the highest positive correlation with morphology on day 0 of collection, and progressive motility on day 3 (P < 0.05) showed a negative correlation with acrosome abnormalities (P < 0.05). According to the area under receiver operating characteristics (ROC) curves (AUCs), progressive motility could also be used in predicting semen quality after 3 days of storage (AUC > 0.5; P < 0.05). TNF-α in seminal plasma is the only parameter measured on day 0 to show a significant correlation with the percentage of viable spermatozoa after 3 days of semen storage (r = 0.495, P < 0.05). ROC analysis shows that TNF-α level is helpful in discriminating viability outcome after semen storage (AUC = 0.94, P < 0.001). We can predict with 92.35% certainty that fresh semen samples with more than 150 pg/ml of TNF-α in the seminal plasma will retain more than 85% of viable spermatozoa after 3 days of storage. Thus, TNF-α can contribute to predicting the quality of short-term stored semen.

Post-fire Water Quality in the Western United States: Understanding and Predicting Short and Long-term Response

NASA Astrophysics Data System (ADS)

Hogue, T. S.; Rust, A.

2016-12-01

Fire frequency is increasing across mid-elevation forests, especially in the Northern Rockies, Sierra Nevada, southern Cascades, as well as the coastal ranges in California and southern Oregon. Numerous studies have noted increased discharge, floods and debris flows after wildfire. More recent work also shows increased water yield during dry seasons for up to ten years post-fire. However, few studies have evaluated long-term water quality response in fire-impacted watersheds. The current presentation will overview recent development of an extensive database on post-fire water quality response across the western U.S. A range of water quality parameters were gathered from 271 burned watersheds through local, state and federal agencies. Short and long-term response was evaluated for watersheds with at least 5 years of pre-fire data. Over 30 watersheds showed significant increases in NO3-, NO2-, NH3, and total nitrogen loading in the initial five years after fire and remained elevated ten years after fire. The burn severity influenced the degree of nitrogen response, where more severely burned watersheds showed higher nitrogen loading than less severely burned watersheds. Dissolved and total phosphorous showed significant increases in 32 watersheds for the first five years after fire. Dissolved ions such as calcium, magnesium, and chloride were also exported from over 32 watersheds, primarily during the first five years after fire, with the majority of impacted watersheds returning to pre-fire water quality conditions after ten years. Ongoing work includes evaluating key determinants that drive short and long-term response and developing predictive models for post-fire water quality. Watersheds impacted by wildfire are known to pose significant risks for downstream communities. Understanding short and long-term water quality change that can impact regional water supplies is critical for establishing potential treatment priorities and alternative source planning.

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

PubMed

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.

Intelligence as a predictor of outcome in short- and long-term psychotherapy.

PubMed

Knekt, Paul; Saari, Taru; Lindfors, Olavi

2014-12-30

Intelligence has been suggested as a suitability factor for short-term therapy whereas its possible effect on short-term versus long-term therapy still is unknown. The aim of this study was to compare the prediction of intelligence on the level of psychiatric symptoms and psychosocial functioning in psychotherapies of different lengths. A total of 251 outpatients from the Helsinki Psychotherapy Study, aged 20–46 years, and suffering from mood or anxiety disorders were allocated to two long-term and two short-term therapies. Intelligence was assessed at baseline with the Wechsler Adult Intelligence Scale (WAIS-R). Psychiatric symptoms and psychosocial functioning were assessed 5–10 times during a 5-year follow-up using two primary symptom measures (HDRS and HARS) and one primary measure of psychosocial functioning (GAF). Short-term therapy was more effective than long-term therapy during the first year of follow-up. During the second to fourth follow-up year no differences between short- and long-term therapies or the intelligence groups were found. At the fifth follow-up year, however, long-term psychotherapy showed a statistically significantly larger change in all three primary measures compared to short-term therapy among those with higher intelligence. No differences between therapy groups were noted in those with lower intelligence. People with higher intelligence may benefit more from long-term than from short-term psychotherapy. These findings should be confirmed.

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

PubMed Central

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-term memory. We show that native signers differ from speakers on measures of short-term memory that require maintenance of temporal order of the tested materials, but not on those in which temporal order is not required. In addition, we show that, in a recall task with free order, bilingual subjects are more likely to recall in temporal order when using English than ASL. We conclude that speakers and signers do share common short-term memory processes. However, whereas short-term memory for spoken English is predominantly organized in terms of temporal order, we argue that this dimension does not play as great a role in signers’ short-term memory. Other factors that may affect STM processes in signers are discussed. PMID:18083155

Assessment of NASA's Aircraft Noise Prediction Capability

NASA Technical Reports Server (NTRS)

Dahl, Milo D. (Editor)

2012-01-01

A goal of NASA s Fundamental Aeronautics Program is the improvement of aircraft noise prediction. This document provides an assessment, conducted from 2006 to 2009, on the current state of the art for aircraft noise prediction by carefully analyzing the results from prediction tools and from the experimental databases to determine errors and uncertainties and compare results to validate the predictions. The error analysis is included for both the predictions and the experimental data and helps identify where improvements are required. This study is restricted to prediction methods and databases developed or sponsored by NASA, although in many cases they represent the current state of the art for industry. The present document begins with an introduction giving a general background for and a discussion on the process of this assessment followed by eight chapters covering topics at both the system and the component levels. The topic areas, each with multiple contributors, are aircraft system noise, engine system noise, airframe noise, fan noise, liner physics, duct acoustics, jet noise, and propulsion airframe aeroacoustics.

Limited short-term prognostic utility of cerebral NIRS during neonatal therapeutic hypothermia.

PubMed

Shellhaas, Renée A; Thelen, Brian J; Bapuraj, Jayapalli R; Burns, Joseph W; Swenson, Aaron W; Christensen, Mary K; Wiggins, Stephanie A; Barks, John D E

2013-07-16

We evaluated the utility of amplitude-integrated EEG (aEEG) and regional oxygen saturation (rSO2) measured using near-infrared spectroscopy (NIRS) for short-term outcome prediction in neonates with hypoxic ischemic encephalopathy (HIE) treated with therapeutic hypothermia. Neonates with HIE were monitored with dual-channel aEEG, bilateral cerebral NIRS, and systemic NIRS throughout cooling and rewarming. The short-term outcome measure was a composite of neurologic examination and brain MRI scores at 7 to 10 days. Multiple regression models were developed to assess NIRS and aEEG recorded during the 6 hours before rewarming and the 6-hour rewarming period as predictors of short-term outcome. Twenty-one infants, mean gestational age 38.8 ± 1.6 weeks, median 10-minute Apgar score 4 (range 0-8), and mean initial pH 6.92 ± 0.19, were enrolled. Before rewarming, the most parsimonious model included 4 parameters (adjusted R(2) = 0.59; p = 0.006): lower values of systemic rSO2 variability (p = 0.004), aEEG bandwidth variability (p = 0.019), and mean aEEG upper margin (p = 0.006), combined with higher mean aEEG bandwidth (worse discontinuity; p = 0.013), predicted worse short-term outcome. During rewarming, lower systemic rSO2 variability (p = 0.007) and depressed aEEG lower margin (p = 0.034) were associated with worse outcome (model-adjusted R(2) = 0.49; p = 0.005). Cerebral NIRS data did not contribute to either model. During day 3 of cooling and during rewarming, loss of physiologic variability (by systemic NIRS) and invariant, discontinuous aEEG patterns predict poor short-term outcome in neonates with HIE. These parameters, but not cerebral NIRS, may be useful to identify infants suitable for studies of adjuvant neuroprotective therapies or modification of the duration of cooling and/or rewarming.

Auditory-Cortex Short-Term Plasticity Induced by Selective Attention

PubMed Central

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

Evaluation of Short-Term Bioassays to Predict Functional Impairment. Development of Hepatic Bioassays in Laboratory Animals, Directory of Institutions/Individuals.

DTIC Science & Technology

1980-10-01

Organizations Compounds Tested Morphological Tests Toxic Substances Functional Tests rR ACT Cutlue OM v.a e sif nemooery ad Identify by block number) %MITRE has...demonstrated ability to evaluate and predict hepatic impairment rvsulting from toxicant exposures. This directory is a companion to Selected Short-Term...Hepatic Toxicity Tests, which describes the available hepatic testing protocols and assesses their suitability for a screening program. This direc

Quantitative analysis of ventricular ectopic beats in short-term RR interval recordings to predict imminent ventricular tachyarrhythmia.

PubMed

Martínez-Alanis, Marisol; Ruiz-Velasco, Silvia; Lerma, Claudia

2016-12-15

Most approaches to predict ventricular tachyarrhythmias which are based on RR intervals consider only sinus beats, excluding premature ventricular complexes (PVCs). The method known as heartprint, which analyses PVCs and their characteristics, has prognostic value for fatal arrhythmias on long recordings of RR intervals (>70,000 beats). To evaluate characteristics of PVCs from short term recordings (around 1000 beats) and their prognostic value for imminent sustained tachyarrhythmia. We analyzed 132 pairs of short term RR interval recordings (one before tachyarrhythmia and one control) obtained from 78 patients. Patients were classified into two groups based on the history of accelerated heart rate (HR) (HR>90bpm) before a tachyarrhythmia episode. Heartprint indexes, such as mean coupling interval (meanCI) and the number of occurrences of the most prevalent form of PVCs (SNIB) were calculated. The predictive value of all the indexes and of the combination of different indexes was calculated. MeanCI shorter than 482ms and the occurrence of more repetitive arrhythmias (sNIB≥2.5), had a significant prognostic value for patients with accelerated heart rate: adjusted odds ratio of 2.63 (1.33-5.17) for meanCI and 2.28 (1.20-4.33) for sNIB. Combining these indexes increases the adjusted odds ratio: 10.94 (3.89-30.80). High prevalence of repeating forms of PVCs and shorter CI are potentially useful risk markers of imminent ventricular tachyarrhythmia. Knowing if a patient has history of VT/VF preceded by accelerated HR, improves the prognostic value of these risk markers. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

24 CFR 576.106 - Short-term and medium-term rental assistance.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 24 Housing and Urban Development 3 2012-04-01 2012-04-01 false Short-term and medium-term rental... and Eligible Activities § 576.106 Short-term and medium-term rental assistance. (a) General provisions... assistance may be short-term rental assistance, medium-term rental assistance, payment of rental arrears, or...

24 CFR 576.106 - Short-term and medium-term rental assistance.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 24 Housing and Urban Development 3 2013-04-01 2013-04-01 false Short-term and medium-term rental... and Eligible Activities § 576.106 Short-term and medium-term rental assistance. (a) General provisions... assistance may be short-term rental assistance, medium-term rental assistance, payment of rental arrears, or...

24 CFR 576.106 - Short-term and medium-term rental assistance.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 24 Housing and Urban Development 3 2014-04-01 2013-04-01 true Short-term and medium-term rental... and Eligible Activities § 576.106 Short-term and medium-term rental assistance. (a) General provisions... assistance may be short-term rental assistance, medium-term rental assistance, payment of rental arrears, or...

Interpersonal violence and the prediction of short-term risk of repeat suicide attempt

PubMed Central

Haglund, Axel; Lindh, Åsa U.; Lysell, Henrik; Renberg, Ellinor Salander; Jokinen, Jussi; Waern, Margda; Runeson, Bo

2016-01-01

In this multi-center cohort study, suicide attempters presenting to hospital (N = 355, 63% women) were interviewed using the Karolinska Interpersonal Violence Scale (KIVS) and followed-up by medical record review. Main outcome was non-fatal or fatal repeat suicide attempt within six months. Also, repeat attempt using a violent method was used as an additional outcome in separate analyses. Data were analyzed for the total group and for men and women separately. Repeat attempts were observed within six months in 78 persons (22%) and 21 (6%) of these used a violent method. KIVS total score of 6 or more was associated with repeat suicide attempt within six months (OR = 1.81, CI 1.08–3.02) and predicted new attempts with a sensitivity of 62% and a specificity of 53%. A three-fold increase in odds ratio was observed for repeat attempt using a violent method (OR = 3.40, CI 1.22–9.49). An association between exposure to violence in adulthood and violent reattempt was seen in women (OR = 1.38, CI 1.06–1.82). The overall conclusions are that information about interpersonal violence may help predict short-term risk for repeat suicide attempt, and that structured assessment of interpersonal violence may be of value in risk assessment after attempted suicide. PMID:27841333

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

PubMed Central

Gureckis, Todd M.; Love, Bradley C.

2009-01-01

Successful investors seeking returns, animals foraging for food, and pilots controlling aircraft all must take into account how their current decisions will impact their future standing. One challenge facing decision makers is that options that appear attractive in the short-term may not turn out best in the long run. In this paper, we explore human learning in a dynamic decision-making task which places short- and long-term rewards in conflict. Our goal in these studies was to evaluate how people’s mental representation of a task affects their ability to discover an optimal decision strategy. We find that perceptual cues that readily align with the underlying state of the task environment help people overcome the impulsive appeal of short-term rewards. Our experimental manipulations, predictions, and analyses are motivated by current work in reinforcement learning which details how learners value delayed outcomes in sequential tasks and the importance that “state” identification plays in effective learning. PMID:19427635

The Effect of Data Quality on Short-term Growth Model Projections

Treesearch

David Gartner

2005-01-01

This study was designed to determine the effect of FIA's data quality on short-term growth model projections. The data from Georgia's 1996 statewide survey were used for the Southern variant of the Forest Vegetation Simulator to predict Georgia's first annual panel. The effect of several data error sources on growth modeling prediction errors...

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

ERIC Educational Resources Information Center

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.

PubMed

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.

Global Weather Prediction and High-End Computing at NASA

NASA Technical Reports Server (NTRS)

Lin, Shian-Jiann; Atlas, Robert; Yeh, Kao-San

2003-01-01

We demonstrate current capabilities of the NASA finite-volume General Circulation Model an high-resolution global weather prediction, and discuss its development path in the foreseeable future. This model can be regarded as a prototype of a future NASA Earth modeling system intended to unify development activities cutting across various disciplines within the NASA Earth Science Enterprise.

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

ERIC Educational Resources Information Center

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.

PubMed

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.

Correlation of Noncancer Benchmark Doses in Short- and Long-Term Rodent Bioassays.

PubMed

Kratchman, Jessica; Wang, Bing; Fox, John; Gray, George

2018-05-01

This study investigated whether, in the absence of chronic noncancer toxicity data, short-term noncancer toxicity data can be used to predict chronic toxicity effect levels by focusing on the dose-response relationship instead of a critical effect. Data from National Toxicology Program (NTP) technical reports have been extracted and modeled using the Environmental Protection Agency's Benchmark Dose Software. Best-fit, minimum benchmark dose (BMD), and benchmark dose lower limits (BMDLs) have been modeled for all NTP pathologist identified significant nonneoplastic lesions, final mean body weight, and mean organ weight of 41 chemicals tested by NTP between 2000 and 2012. Models were then developed at the chemical level using orthogonal regression techniques to predict chronic (two years) noncancer health effect levels using the results of the short-term (three months) toxicity data. The findings indicate that short-term animal studies may reasonably provide a quantitative estimate of a chronic BMD or BMDL. This can allow for faster development of human health toxicity values for risk assessment for chemicals that lack chronic toxicity data. © 2017 Society for Risk Analysis.

Statistical short-term earthquake prediction.

PubMed

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?

ERIC Educational Resources Information Center

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.

PubMed

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.

ENSO Prediction in the NASA GMAO GEOS-5 Seasonal Forecasting System

NASA Astrophysics Data System (ADS)

Kovach, R. M.; Borovikov, A.; Marshak, J.; Pawson, S.; Vernieres, G.

2016-12-01

Seasonal-to-Interannual coupled forecasts are conducted in near-real time with the Goddard Earth Observing System (GEOS) Atmosphere-Ocean General Circulation Model (AOGCM). A 30-year suite of 9-month hindcasts is available, initialized with the MERRA-Ocean, MERRA-Land, and MERRA atmospheric fields. These forecasts are used to predict the timing and magnitude of ENSO and other short-term climate variability. The 2015 El Niño peaked in November 2015 and was considered a "very strong" event with the Equatorial Pacific Ocean sea-surface-temperature (SST) anomalies higher than 2.0 °C. These very strong temperature anomalies began in Sep/Oct/Nov (SON) of 2015 and persisted through Dec/Jan/Feb (DJF) of 2016. The other two very strong El Niño events recently recorded occurred in 1981/82 and 1997/98. The GEOS-5 system began predicting a very strong El Niño for SON starting with the March 2015 forecast. At this time, the GMAO forecast was an outlier in both the NMME and IRI multi-model ensemble prediction plumes. The GMAO May 2015 forecast for the November 2015 peak in temperature anomaly in the Niño3.4 region was in excellent agreement with the real event, but in May this forecast was still one of the outliers in the multi-model forecasts. The GEOS-5 May 2015 forecast also correctly predicted the weakening of the Eastern Pacific (Niño1+2) anomalies for SON. We will present a summary of the NASA GMAO GEOS-5 Seasonal Forecast System skills based on historic hindcasts. Initial conditions, prediction of ocean surface and subsurface evolution for the 2015/16 El Niño will be compared to the 1998/97 event. GEOS-5 capability to predict the precipitation, i.e. to model the teleconnection patterns associated with El Niño will also be shown. To conclude, we will highlight some new developments in the GEOS forecasting system.

Pentraxin-3 Predicts Short- and Mid-term Mortality in Patients with Sepsis and Septic Shock During Intensive Care Treatment.

PubMed

Hamed, Sonja; Behnes, Michael; Pauly, Dominic; Lepiorz, Dominic; Barre, Max; Becher, Tobias; Lang, Siegfried; Akin, Ibrahim; Borggrefe, Martin; Bertsch, Thomas; Hoffmann, Ursula

2018-06-01

The prognostic value of the acute phase protein Pentraxin 3 (PTX-3) is not well evaluated in patients with septic shock, which reveal an unacceptably high short- and long-term mortality. New Sepsis-3 definitions are not yet implemented in most biomarker studies. Therefore, this study assesses the prognostic value of PTX-3 for short- and mid-term mortality in patients with sepsis or septic shock, as defined by the latest definitions, treated at a medical intensive care unit (ICU). The study includes 213 ICU patients with clinical criteria of sepsis and septic shock. Plasma levels of PTX-3, procalcitonin (PCT) and interleukin-6 were measured on day 1, 3, and 8. All-cause mortality was followed up to 30 days and at 6 months. On all three days, PTX-3 levels were able to discriminate non-survivors from survivors at 30 days and 6 months (AUC range: 0.59 - 0.70; 95% CI: 0.52 - 0.79; p ≤ 0.02). Highest PTX-3 levels within the fourth quartiles during the first week of ICU treatment were associated with an increased mortality rate at 30 days (OR = 7; 95% CI: 2.0 - 23.5; p ≤ 0.002) and at 6 months (OR = 5; 95% CI: 2.1 - 11.4; p ≤ 0.006). Additionally, the prognostic value of PTX-3 was proven for all patients as well as in subcohorts of patients with sepsis and septic shock, according to Sepsis-3 criteria, both in univariate and multivariate analyses for 30-day and 6-months all-cause mortality, especially predicting all-cause mortality in septic shock (HRs range: 1.0 - 2.9; 95% CI: 0.3 - 5.1; p ≤ 0.03). PTX-3 offers prognostic value for the prediction of short- and mid-term all-cause mortality in patients suffering from sepsis and septic shock according to the latest Sepsis-3 criteria.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Yannan; Hou, Zhangshuan; Meng, Da

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.

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

NASA Astrophysics Data System (ADS)

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?

PubMed

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.

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

PubMed

Schievink, Bauke; de Zeeuw, Dick; Smink, Paul A; Andress, Dennis; Brennan, John J; Coll, Blai; Correa-Rotter, Ricardo; Hou, Fan Fan; Kohan, Donald; Kitzman, Dalane W; Makino, Hirofumi; Parving, Hans-Henrik; Perkovic, Vlado; Remuzzi, Giuseppe; Tobe, Sheldon; Toto, Robert; Hoekman, Jarno; Lambers Heerspink, Hiddo J

2016-05-01

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. We used the PRE score on data from the RADAR/JAPAN study to predict the effect of atrasentan on renal and heart failure outcomes. 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, 1.25 mg/day, or placebo. A PRE score was developed in a background set of completed clinical trials using multivariate Cox models. The score was applied to baseline and week-12 risk marker levels of RADAR/JAPAN participants, to predict atrasentan effects on clinical outcomes. Outcomes were defined as doubling serum creatinine or end-stage renal disease and hospitalization for heart failure. The PRE score predicted renal risk changes of -23% and -30% for atrasentan 0.75 and 1.25 mg/day, respectively. PRE scores also predicted a small non-significant increase in heart failure risk for atrasentan 0.75 and 1.25 mg/day (+2% vs. +7%). Selecting patients with >30% albuminuria reduction from baseline (responders) improved renal outcome to almost 50% risk reduction, whereas non-responders showed no renal benefit. Based on the RADAR/JAPAN study, with short-term changes in risk markers, atrasentan is expected to decrease renal risk without increased risk of heart failure. Within this population albuminuria responders appear to contribute to the predicted improvements, whereas non-responders showed no benefit

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

EPA Science Inventory

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

ERIC Educational Resources Information Center

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)

Small mammals as indicators of short-term and long-term disturbance in mixed prairie

USGS Publications Warehouse

Leis, S.A.; Leslie, David M.; Engle, David M.; Fehmi, J.S.

2008-01-01

Disturbance by military maneuvers over short and long time scales may have differential effects on grassland communities. We assessed small mammals as indicators of disturbance by military maneuvers in a mixed prairie in southern Oklahoma USA. We examined sites on two soil series, Foard and Lawton, across a gradient of disturbance intensity. A MANOVA showed that abundance of small mammals was associated (p = 0.03) with short-term (cover of vehicle tracks) disturbance but was not associated (p = 0.12) with long-term (loss of soil organic carbon, SOC) disturbance intensity. At the individual species level, Sigmodon hispidus (cotton rat) and Peromyscus maniculatus (deer mouse) occurred across all levels of disturbance and in both soil types. Only P. maniculatus abundance changed (p < 0.01) with short-term disturbance and increased by about one individual per 5% of additional track-cover. Abundance of P. maniculatus also increased (p = 0.04) by about three individuals per 1% increase in soil carbon. Chaetodipus hispidus (hispid pocket mouse) and Reithrodontomys fulvescens (fulvous harvest mouse) only occurred in single soil types limiting their potential as more general indicators. Abundance of P. maniculatus was positively related to shifts in plant species composition and likely reflected changes in vegetation structure (i.e. litter depth) and forage availability resulting from disturbance. Peromyscus maniculatus may be a useful biological indicator of ecosystem change because it responded predictably to both long-term and short-term disturbance and, when coupled with soil, plant, and disturbance history variables, can reveal land condition trends. ?? Springer Science+Business Media B.V. 2007.

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

USGS Publications Warehouse

Tangborn, Wendell V.

1980-01-01

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

Operationalizing the assessment and management of violence risk in the short-term.

PubMed

Doyle, Michael; Logan, Caroline

2012-01-01

Assessing risk of violence in the short term is crucial for managing and preventing violence, especially in institutions such as psychiatric units and prisons. Despite a lack of consensus on the definition of "short term", a number of recent tools and guidelines have been developed to aid short-term clinical decision-making. Whereas the supporting evidence for the new tools is impressive, limitations remain in terms of the focus on prediction, limited consideration of strengths, and poor integration with formulation and risk management. The Short-Term Assessment of Risk and Treatability (START) is a brief clinical guide for the dynamic assessment of risks, strengths and treatability. It focuses on short-term risks and the characteristics of the individual that, if changed, might lead to an increase or decrease in risk. The START has the potential to operationalize the structured professional judgment (SPJ) approach in order to inform the evaluation of multiple risk domains relevant to everyday psychiatric clinical practice. However, explicit guidance on integrating risk assessment, formulation and management is limited in the START and this paper describes the SPJ approach, reviews recent developments in approaches to risk, and considers how the START can be used to inform SPJ approaches and link risk assessment, formulation, and management. Copyright © 2012 John Wiley & Sons, Ltd.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

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

PubMed Central

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. PMID:18394484

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

ERIC Educational Resources Information Center

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…

Proposed Use of the NASA Ames Nebula Cloud Computing Platform for Numerical Weather Prediction and the Distribution of High Resolution Satellite Imagery

NASA Technical Reports Server (NTRS)

Limaye, Ashutosh S.; Molthan, Andrew L.; Srikishen, Jayanthi

2010-01-01

The development of the Nebula Cloud Computing Platform at NASA Ames Research Center provides an open-source solution for the deployment of scalable computing and storage capabilities relevant to the execution of real-time weather forecasts and the distribution of high resolution satellite data to the operational weather community. Two projects at Marshall Space Flight Center may benefit from use of the Nebula system. The NASA Short-term Prediction Research and Transition (SPoRT) Center facilitates the use of unique NASA satellite data and research capabilities in the operational weather community by providing datasets relevant to numerical weather prediction, and satellite data sets useful in weather analysis. SERVIR provides satellite data products for decision support, emphasizing environmental threats such as wildfires, floods, landslides, and other hazards, with interests in numerical weather prediction in support of disaster response. The Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS) has been configured for Nebula cloud computing use via the creation of a disk image and deployment of repeated instances. Given the available infrastructure within Nebula and the "infrastructure as a service" concept, the system appears well-suited for the rapid deployment of additional forecast models over different domains, in response to real-time research applications or disaster response. Future investigations into Nebula capabilities will focus on the development of a web mapping server and load balancing configuration to support the distribution of high resolution satellite data sets to users within the National Weather Service and international partners of SERVIR.

Accurate Prediction of Protein Contact Maps by Coupling Residual Two-Dimensional Bidirectional Long Short-Term Memory with Convolutional Neural Networks.

PubMed

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

2018-06-19

Accurate prediction of a protein contact map depends greatly on capturing as much contextual information as possible from surrounding residues for a target residue pair. Recently, ultra-deep residual convolutional networks were found to be state-of-the-art in the latest Critical Assessment of Structure Prediction techniques (CASP12, (Schaarschmidt et al., 2018)) for protein contact map prediction by attempting to provide a protein-wide context at each residue pair. Recurrent neural networks have seen great success in recent protein residue classification problems due to their ability to propagate information through long protein sequences, especially Long Short-Term Memory (LSTM) cells. Here we propose a novel protein contact map prediction method by stacking residual convolutional networks with two-dimensional residual bidirectional recurrent LSTM networks, and using both one-dimensional sequence-based and two-dimensional evolutionary coupling-based information. We show that the proposed method achieves a robust performance over validation and independent test sets with the Area Under the receiver operating characteristic Curve (AUC)>0.95 in all tests. When compared to several state-of-the-art methods for independent testing of 228 proteins, the method yields an AUC value of 0.958, whereas the next-best method obtains an AUC of 0.909. More importantly, the improvement is over contacts at all sequence-position separations. Specifically, a 8.95%, 5.65% and 2.84% increase in precision were observed for the top L∕10 predictions over the next best for short, medium and long-range contacts, respectively. This confirms the usefulness of ResNets to congregate the short-range relations and 2D-BRLSTM to propagate the long-range dependencies throughout the entire protein contact map 'image'. SPOT-Contact server url: http://sparks-lab.org/jack/server/SPOT-Contact/. Supplementary data is available at Bioinformatics online.

Prediction Activities at NASA's Global Modeling and Assimilation Office

NASA Technical Reports Server (NTRS)

Schubert, Siegfried

2010-01-01

The Global Modeling and Assimilation Office (GMAO) is a core NASA resource for the development and use of satellite observations through the integrating tools of models and assimilation systems. Global ocean, atmosphere and land surface models are developed as components of assimilation and forecast systems that are used for addressing the weather and climate research questions identified in NASA's science mission. In fact, the GMAO is actively engaged in addressing one of NASA's science mission s key questions concerning how well transient climate variations can be understood and predicted. At weather time scales the GMAO is developing ultra-high resolution global climate models capable of resolving high impact weather systems such as hurricanes. The ability to resolve the detailed characteristics of weather systems within a global framework greatly facilitates addressing fundamental questions concerning the link between weather and climate variability. At sub-seasonal time scales, the GMAO is engaged in research and development to improve the use of land information (especially soil moisture), and in the improved representation and initialization of various sub-seasonal atmospheric variability (such as the MJO) that evolves on time scales longer than weather and involves exchanges with both the land and ocean The GMAO has a long history of development for advancing the seasonal-to-interannual (S-I) prediction problem using an older version of the coupled atmosphere-ocean general circulation model (AOGCM). This includes the development of an Ensemble Kalman Filter (EnKF) to facilitate the multivariate assimilation of ocean surface altimetry, and an EnKF developed for the highly inhomogeneous nature of the errors in land surface models, as well as the multivariate assimilation needed to take advantage of surface soil moisture and snow observations. The importance of decadal variability, especially that associated with long-term droughts is well recognized by the

The Demonstration of Short-Term Consolidation.

ERIC Educational Resources Information Center

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)

Processing short-term and long-term information with a combination of polynomial approximation techniques and time-delay neural networks.

PubMed

Fuchs, Erich; Gruber, Christian; Reitmaier, Tobias; Sick, Bernhard

2009-09-01

Neural networks are often used to process temporal information, i.e., any kind of information related to time series. In many cases, time series contain short-term and long-term trends or behavior. This paper presents a new approach to capture temporal information with various reference periods simultaneously. A least squares approximation of the time series with orthogonal polynomials will be used to describe short-term trends contained in a signal (average, increase, curvature, etc.). Long-term behavior will be modeled with the tapped delay lines of a time-delay neural network (TDNN). This network takes the coefficients of the orthogonal expansion of the approximating polynomial as inputs such considering short-term and long-term information efficiently. The advantages of the method will be demonstrated by means of artificial data and two real-world application examples, the prediction of the user number in a computer network and online tool wear classification in turning.

Short-term load forecasting using neural network for future smart grid application

NASA Astrophysics Data System (ADS)

Zennamo, Joseph Anthony, III

Short-term load forecasting of power system has been a classic problem for a long time. Not merely it has been researched extensively and intensively, but also a variety of forecasting methods has been raised. This thesis outlines some aspects and functions of smart meter. It also presents different policies and current statuses as well as future projects and objectives of SG development in several countries. Then the thesis compares main aspects about latest products of smart meter from different companies. Lastly, three types of prediction models are established in MATLAB to emulate the functions of smart grid in the short-term load forecasting, and then their results are compared and analyzed in terms of accuracy. For this thesis, more variables such as dew point temperature are used in the Neural Network model to achieve more accuracy for better short-term load forecasting results.

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

NASA Astrophysics Data System (ADS)

Ohmi, Masataro; Mori, Hiroyuki

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

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

PubMed

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.

PubMed

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.

The impact of experimental measurement errors on long-term viscoelastic predictions. [of structural materials

NASA Technical Reports Server (NTRS)

Tuttle, M. E.; Brinson, H. F.

1986-01-01

The impact of flight error in measured viscoelastic parameters on subsequent long-term viscoelastic predictions is numerically evaluated using the Schapery nonlinear viscoelastic model. Of the seven Schapery parameters, the results indicated that long-term predictions were most sensitive to errors in the power law parameter n. Although errors in the other parameters were significant as well, errors in n dominated all other factors at long times. The process of selecting an appropriate short-term test cycle so as to insure an accurate long-term prediction was considered, and a short-term test cycle was selected using material properties typical for T300/5208 graphite-epoxy at 149 C. The process of selection is described, and its individual steps are itemized.

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

PubMed

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.

PubMed

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.

NASA thesaurus alphabetical update: Subject terms for indexing scientific and technical information

NASA Technical Reports Server (NTRS)

1971-01-01

The NASA THESAURUS - ALPHABETICAL UPDATE is an alphabetical listing of all subject terms (postable and nonpostable) that are currently approved for use in the NASA scientific and technical information system. Contained in the listing are the subject terms that were listed in the Preliminary Edition of the NASA THESAURUS and the additional subject terms that were approved during the period January 1, 1967 June 30, 1971. Complete Thesaurus structuring, including scope notes, category assignments, and cross-references, is provided for each term as appropriate.

Short-term memory and dual task performance

NASA Technical Reports Server (NTRS)

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.

Review of NASA short-haul studies

NASA Technical Reports Server (NTRS)

Kenyon, G. C.

1975-01-01

The paper summarizes the results of NASA-conducted technological and economic studies of low, medium, and high density short-haul transportation systems. Aircraft concepts considered included CTOL, RTOL, STOL, and general aviation aircraft. For low density systems, it was found that viable air service becomes possible if city pairs are at least 100 km apart and a two-way total travel demand of at least 200 daily passengers exists. Currently available aircraft were found suitable. The medium-density study showed that a 60-passenger twin engine turbofan was the best suited aircraft. For high density systems, STOL appears to be an economically viable means of reducing noise and congestion at major hub airports. Adequate runways 914 m in length or greater either already exist or could be added to most existing major hub airports.

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

PubMed

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 < 0.001) and 30-d readmission rate (ρ = 0.335, P < 0.001). There was a significant downward 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.

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

ERIC Educational Resources Information Center

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…

Interplay between Short- and Long-Term Plasticity in Cell-Assembly Formation

PubMed Central

Hiratani, Naoki; Fukai, Tomoki

2014-01-01

Various hippocampal and neocortical synapses of mammalian brain show both short-term plasticity and long-term plasticity, which are considered to underlie learning and memory by the brain. According to Hebb’s postulate, synaptic plasticity encodes memory traces of past experiences into cell assemblies in cortical circuits. However, it remains unclear how the various forms of long-term and short-term synaptic plasticity cooperatively create and reorganize such cell assemblies. Here, we investigate the mechanism in which the three forms of synaptic plasticity known in cortical circuits, i.e., spike-timing-dependent plasticity (STDP), short-term depression (STD) and homeostatic plasticity, cooperatively generate, retain and reorganize cell assemblies in a recurrent neuronal network model. We show that multiple cell assemblies generated by external stimuli can survive noisy spontaneous network activity for an adequate range of the strength of STD. Furthermore, our model predicts that a symmetric temporal window of STDP, such as observed in dopaminergic modulations on hippocampal neurons, is crucial for the retention and integration of multiple cell assemblies. These results may have implications for the understanding of cortical memory processes. PMID:25007209

Short-term prediction of chaotic time series by using RBF network with regression weights.

PubMed

Rojas, I; Gonzalez, J; Cañas, A; Diaz, A F; Rojas, F J; Rodriguez, M

2000-10-01

We propose a framework for constructing and training a radial basis function (RBF) neural network. The structure of the gaussian functions is modified using a pseudo-gaussian function (PG) in which two scaling parameters sigma are introduced, which eliminates the symmetry restriction and provides the neurons in the hidden layer with greater flexibility with respect to function approximation. We propose a modified PG-BF (pseudo-gaussian basis function) network in which the regression weights are used to replace the constant weights in the output layer. For this purpose, a sequential learning algorithm is presented to adapt the structure of the network, in which it is possible to create a new hidden unit and also to detect and remove inactive units. A salient feature of the network systems is that the method used for calculating the overall output is the weighted average of the output associated with each receptive field. The superior performance of the proposed PG-BF system over the standard RBF are illustrated using the problem of short-term prediction of chaotic time series.

Short-Term Intercultural Psychotherapy: Ethnographic Inquiry

ERIC Educational Resources Information Center

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…

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.

PubMed

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.

Capability of ischemia-modified albumin to predict serious cardiac outcomes in the short term among patients with potential acute coronary syndrome.

PubMed

Worster, Andrew; Devereaux, P J; Heels-Ansdell, Diane; Guyatt, Gordon H; Opie, John; Mookadam, Farouk; Hill, Stephen A

2005-06-21

Ischemia-modified albumin (IMA) has been suggested as a marker of cardiac ischemia. Little, however, is known about its capacity to predict short-term serious cardiac outcomes (death, myocardial infarction, congestive heart failure, serious arrhythmia, or refractory ischemic cardiac pain) in patients arriving at the emergency department with symptoms that may indicate cardiac ischemia. We screened 546 patients over a 4-week period, of whom 189 fulfilled our entry criteria by presenting to an emergency department with potential cardiac-ischemia symptoms within 6 hours after chest pain, seeing an emergency physician who chose to order a troponin I test, and having no serious cardiac outcome before the troponin result became available. We followed the study patients for 72 hours to determine if any experienced a serious cardiac outcome. We calculated the likelihood ratios (LRs) of IMA findings predicting serious cardiac outcomes that could not be diagnosed at presentation with current techniques. Of the 189 patients, 24 had a serious cardiac outcome within 72 hours after their arrival at the emergency department. The likelihood ratios for IMA measurement within 6 hours after chest pain predicting a serious cardiac outcome within the next 72 hours were 1.35 (95% confidence interval [CI] 0.315-5.79) for IMA < or = 80 U/mL and 0.98 (95% CI 0.86- 1.11) for IMA > 80 U/mL. These data suggest that in patients presenting with chest pain who have not yet experienced a serious cardiac event, IMA is a poor predictor of serious cardiac outcomes in the short term.

Short- and long-term theory-based predictors of physical activity in women who participated in a weight-management program.

PubMed

Wasserkampf, A; Silva, M N; Santos, I C; Carraça, E V; Meis, J J M; Kremers, S P J; Teixeira, P J

2014-12-01

This study analyzed psychosocial predictors of the Theory of Planned Behavior (TPB) and Self-Determination Theory (SDT) and evaluated their associations with short- and long-term moderate plus vigorous physical activity (MVPA) and lifestyle physical activity (PA) outcomes in women who underwent a weight-management program. 221 participants (age 37.6 ± 7.02 years) completed a 12-month SDT-based lifestyle intervention and were followed-up for 24 months. Multiple linear regression analyses tested associations between psychosocial variables and self-reported short- and long-term PA outcomes. Regression analyses showed that control constructs of both theories were significant determinants of short- and long-term MVPA, whereas affective and self-determination variables were strong predictors of short- and long-term lifestyle PA. Regarding short-term prediction models, TPB constructs were stronger in predicting MVPA, whereas SDT was more effective in predicting lifestyle PA. For long-term models, both forms of PA were better predicted by SDT in comparison to TPB. These results highlight the importance of comparing health behavior theories to identify the mechanisms involved in the behavior change process. Control and competence constructs are crucial during early adoption of structured PA behaviors, whereas affective and intrinsic sources of motivation are more involved in incidental types of PA, particularly in relation to behavioral maintenance. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

SMAP Data Assimilation at NASA SPoRT

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.

2016-01-01

The NASA Short-Term Prediction Research and Transition (SPoRT) Center maintains a near-real- time run of the Noah Land Surface Model within the Land Information System (LIS) at 3-km resolution. Soil moisture products from this model are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. We have implemented assimilation of soil moisture retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active/ Passive (SMAP) satellites, and are now evaluating the SMAP assimilation. The SMAP-enhanced LIS product is planned for public release by October 2016.

Use of NASA Near Real-Time and Archived Satellite Data to Support Disaster Assessment

NASA Technical Reports Server (NTRS)

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

2014-01-01

NASA's Short-term Prediction Research and Transition (SPoRT) Center partners with the NWS to provide near realtime data in support of a variety of weather applications, including disasters. SPoRT supports NASA's Applied Sciences Program: Disasters focus area by developing techniques that will aid the disaster monitoring, response, and assessment communities. SPoRT has explored a variety of techniques for utilizing archived and near real-time NASA satellite data. An increasing number of end-users - such as the NWS Damage Assessment Toolkit (DAT) - access geospatial data via a Web Mapping Service (WMS). SPoRT has begun developing open-standard Geographic Information Systems (GIS) data sets via WMS to respond to end-user needs.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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 themore » 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.« less

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

PubMed Central

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

2014-01-01

Objective 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. Method 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. Results 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%). Conclusion 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. PMID:25161816

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

ERIC Educational Resources Information Center

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…

NASA Accountability Report

NASA Technical Reports Server (NTRS)

1997-01-01

NASA is piloting fiscal year (FY) 1997 Accountability Reports, which streamline and upgrade reporting to Congress and the public. The document presents statements by the NASA administrator, and the Chief Financial Officer, followed by an overview of NASA's organizational structure and the planning and budgeting process. The performance of NASA in four strategic enterprises is reviewed: (1) Space Science, (2) Mission to Planet Earth, (3) Human Exploration and Development of Space, and (4) Aeronautics and Space Transportation Technology. Those areas which support the strategic enterprises are also reviewed in a section called Crosscutting Processes. For each of the four enterprises, there is discussion about the long term goals, the short term objectives and the accomplishments during FY 1997. The Crosscutting Processes section reviews issues and accomplishments relating to human resources, procurement, information technology, physical resources, financial management, small and disadvantaged businesses, and policy and plans. Following the discussion about the individual areas is Management's Discussion and Analysis, about NASA's financial statements. This is followed by a report by an independent commercial auditor and the financial statements.

The Mind and Brain of Short-Term Memory

PubMed Central

Jonides, John; Lewis, Richard L.; Nee, Derek Evan; Lustig, Cindy A.; Berman, Marc G.; Moore, Katherine Sledge

2014-01-01

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, with special attention to questions of capacity and how—or whether—short-term memory can be separated from long-term memory. Second, we ask how the components of that architecture enact processes of encoding, maintenance, and retrieval. Third, we describe the debate over the reason about forgetting from short-term memory, whether interference or decay is the cause. We close with a conceptual model tracing the representation of a single item through a short-term memory task, describing the biological mechanisms that might support psychological processes on a moment-by-moment basis as an item is encoded, maintained over a delay with some forgetting, and ultimately retrieved. PMID:17854286

Verbal Short-Term Memory Span in Speech-Disordered Children: Implications for Articulatory Coding in Short-Term Memory.

ERIC Educational Resources Information Center

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)

From a physical approach to earthquake prediction, towards long and short term warnings ahead of large earthquakes

NASA Astrophysics Data System (ADS)

Stefansson, R.; Bonafede, M.

2012-04-01

For 20 years the South Iceland Seismic Zone (SISZ) was a test site for multinational earthquake prediction research, partly bridging the gap between laboratory tests samples, and the huge transform zones of the Earth. The approach was to explore the physics of processes leading up to large earthquakes. The book Advances in Earthquake Prediction, Research and Risk Mitigation, by R. Stefansson (2011), published by Springer/PRAXIS, and an article in the August issue of the BSSA by Stefansson, M. Bonafede and G. Gudmundsson (2011) contain a good overview of the findings, and more references, as well as examples of partially successful long and short term warnings based on such an approach. Significant findings are: Earthquakes that occurred hundreds of years ago left scars in the crust, expressed in volumes of heterogeneity that demonstrate the size of their faults. Rheology and stress heterogeneity within these volumes are significantly variable in time and space. Crustal processes in and near such faults may be observed by microearthquake information decades before the sudden onset of a new large earthquake. High pressure fluids of mantle origin may in response to strain, especially near plate boundaries, migrate upward into the brittle/elastic crust to play a significant role in modifying crustal conditions on a long and short term. Preparatory processes of various earthquakes can not be expected to be the same. We learn about an impending earthquake by observing long term preparatory processes at the fault, finding a constitutive relationship that governs the processes, and then extrapolating that relationship into near space and future. This is a deterministic approach in earthquake prediction research. Such extrapolations contain many uncertainties. However the long time pattern of observations of the pre-earthquake fault process will help us to put probability constraints on our extrapolations and our warnings. The approach described is different from the usual

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

DOE PAGES

Seshadhri, C.; Smith, Andrew M.; Vorobeychik, Yevgeniy; ...

2016-07-05

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.

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

PubMed

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.

Short-Term Load Forecasting Based Automatic Distribution Network Reconfiguration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Huaiguang; Ding, Fei; Zhang, Yingchen

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 operatormore » 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.« less

Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Huaiguang; Ding, Fei; Zhang, Yingchen

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 operatormore » 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.« less

The NASA Seasonal-to-Interannual Prediction Project (NSIPP). [Annual Report for 2000

NASA Technical Reports Server (NTRS)

Rienecker, Michele; Suarez, Max; Adamec, David; Koster, Randal; Schubert, Siegfried; Hansen, James; Koblinsky, Chester (Technical Monitor)

2001-01-01

The goal of the project is to develop an assimilation and forecast system based on a coupled atmosphere-ocean-land-surface-sea-ice model capable of using a combination of satellite and in situ data sources to improve the prediction of ENSO and other major S-I signals and their global teleconnections. The objectives of this annual report are to: (1) demonstrate the utility of satellite data, especially surface height surface winds, air-sea fluxes and soil moisture, in a coupled model prediction system; and (2) aid in the design of the observing system for short-term climate prediction by conducting OSSE's and predictability studies.

Quiet Short-Haul Research Aircraft Joint Navy/NASA Sea Trials

NASA Technical Reports Server (NTRS)

Queen, S.; Cochrane, J.

1982-01-01

The Quiet Short-Haul Research Aircraft (QSRA) is a flight facility which Ames Research Center is using to conduct a broad program of terminal area and low-speed, propulsive-life flight research. A joint Navy/NASA flight research program used the QSRA to investigate the application of advanced propulsive-lift technology to the naval aircraft-carrier environment. Flight performance of the QSRA is presented together with the results or the joint Navy/NASA flight program. During the joint program, the QSRA operated aboard the USS Kitty Hawk for 4 days, during which numerous unarrested landings and free deck takeoffs were accomplished. These operations demonstrated that a large aircraft incorporating upper-surface-blowing, propulsive-life technology can be operated in the aircraft-carrier environment without any unusual problems.

Using Claims Data to Generate Clinical Flags Predicting Short-term Risk of Continued Psychiatric Hospitalizations

PubMed Central

Stein, Bradley D.; Pangilinan, Maria; Sorbero, Mark J; Marcus, Sue; Donahue, Sheila; Xu, Yan; Smith, Thomas E; Essock, Susan M

2014-01-01

Objective As health information technology advances, efforts to use administrative data to inform real-time treatment planning for individuals are increasing, despite few empirical studies demonstrating that such administrative data predict subsequent clinical events. Medicaid claims for individuals with frequent psychiatric hospitalizations were examined to test how well patterns of service use predict subsequent high short-term risk of continued psychiatric hospitalizations. Methods Medicaid claims files from New York and Pennsylvania were used to identify Medicaid recipients aged 18-64 with two or more inpatient psychiatric admissions during a target year ending March 31, 2009. Definitions from a quality-improvement initiative were used to identify patterns of inpatient and outpatient service use and prescription fills suggestive of clinical concerns. Generalized estimating equations and Markov models were applied to examine claims through March, 2011, to see what patterns of service use were sufficiently predictive of additional hospitalizations to be clinically useful. Results 11,801 unique individuals in New York and 1,859 in Pennsylvania identified met the cohort definition. In both Pennsylvania and New York, multiple recent hospitalizations, but not failure to use outpatient services or failure to fill medication prescriptions, were significant predictors of high risk of continued frequent hospitalizations, with odds ratios greater than 4.0. Conclusions Administrative data can be used to identify individuals at high risk of continued frequent hospitalizations. Such information could be used by payers and system administrators to authorize special services (e.g., mobile outreach) for such individuals as part of efforts to promote service engagement and prevent rapid rehospitalizations. PMID:25022360

Shared Neural Mechanisms for the Prediction of Own and Partner Musical Sequences after Short-term Piano Duet Training.

PubMed

Lappe, Claudia; Bodeck, Sabine; Lappe, Markus; Pantev, Christo

2017-01-01

Predictive mechanisms in the human brain can be investigated using markers for prediction violations like the mismatch negativity (MMN). Short-term piano training increases the MMN for melodic and rhythmic deviations in the training material. This increase occurs only when the material is actually played, not when it is only perceived through listening, suggesting that learning predictions about upcoming musical events are derived from motor involvement. However, music is often performed in concert with others. In this case, predictions about upcoming actions from a partner are a crucial part of the performance. In the present experiment, we use magnetoencephalography (MEG) to measure MMNs to deviations in one's own and a partner's musical material after both engaged in musical duet training. Event-related field (ERF) results revealed that the MMN increased significantly for own and partner material suggesting a neural representation of the partner's part in a duet situation. Source analysis using beamforming revealed common activations in auditory, inferior frontal, and parietal areas, similar to previous results for single players, but also a pronounced contribution from the cerebellum. In addition, activation of the precuneus and the medial frontal cortex was observed, presumably related to the need to distinguish between own and partner material.

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

PubMed

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.

White-matter structural connectivity predicts short-term melody and rhythm learning in non-musicians.

PubMed

Vaquero, Lucía; Ramos-Escobar, Neus; François, Clément; Penhune, Virginia; Rodríguez-Fornells, Antoni

2018-06-18

Music learning has received increasing attention in the last decades due to the variety of functions and brain plasticity effects involved during its practice. Most previous reports interpreted the differences between music experts and laymen as the result of training. However, recent investigations suggest that these differences are due to a combination of genetic predispositions with the effect of music training. Here, we tested the relationship of the dorsal auditory-motor pathway with individual behavioural differences in short-term music learning. We gathered structural neuroimaging data from 44 healthy non-musicians (28 females) before they performed a rhythm- and a melody-learning task during a single behavioural session, and manually dissected the arcuate fasciculus (AF) in both hemispheres. The macro- and microstructural organization of the AF (i.e., volume and FA) predicted the learning rate and learning speed in the musical tasks, but only in the right hemisphere. Specifically, the volume of the right anterior segment predicted the synchronization improvement during the rhythm task, the FA in the right long segment was correlated with the learning rate in the melody task, and the volume and FA of the right whole AF predicted the learning speed during the melody task. This is the first study finding a specific relation between different branches within the AF and rhythmic and melodic materials. Our results support the relevant function of the AF as the structural correlate of both auditory-motor transformations and the feedback-feedforward loop, and suggest a crucial involvement of the anterior segment in error-monitoring processes related to auditory-motor learning. These findings have implications for both the neuroscience of music field and second-language learning investigations. Copyright © 2018. Published by Elsevier Inc.

NASA's EOSDIS Near Term Challenges

NASA Technical Reports Server (NTRS)

Behnke, Jeanne

2018-01-01

Given the long-term requirements, and the rapid pace of information technology and changing expectations of the user community, the ESDIS Project has had to evolve EOSDIS continually over the past three decades. However, many challenges remain. One near-term challenge is the enormous quantity of new data that will need to be managed by the EOSDIS. With the upcoming launch of the latest NASA missions coupled with existing operational missions and field campaigns, EOSDIS can expect to handle as much as 50 petabytes of data per year. In perspective, this is twice the size of the current existing archive, which took over 21 years to collect. Another continuing challenge is the disparate requirements of a diverse science community. Maintaining rigorous long-term data preservation, supporting ease of discovery and access, incorporating user feedback, enabling reanalysis/ reprocessing, and agile integration of new data sources, continue to be the Project's objectives.

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

PubMed

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 p<0.001) in a model that included all three ADHD symptoms. After further controlling for comorbidity, age of assessment, treatment with methylphenidate, and Full-scale IQ, the severity of childhood inattention symptoms was still significantly associated with worse verbal (p = 0.008) and spatial (p ranging from 0.017 to 0.002) short-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

Predicting pathogen growth during short-term temperature abuse of raw pork, beef, and poultry products: use of an isothermal-based predictive tool.

PubMed

Ingham, Steven C; Fanslau, Melody A; Burnham, Greg M; Ingham, Barbara H; Norback, John P; Schaffner, Donald W

2007-06-01

A computer-based tool (available at: www.wisc.edu/foodsafety/meatresearch) was developed for predicting pathogen growth in raw pork, beef, and poultry meat. The tool, THERM (temperature history evaluation for raw meats), predicts the growth of pathogens in pork and beef (Escherichia coli O157:H7, Salmonella serovars, and Staphylococcus aureus) and on poultry (Salmonella serovars and S. aureus) during short-term temperature abuse. The model was developed as follows: 25-g samples of raw ground pork, beef, and turkey were inoculated with a five-strain cocktail of the target pathogen(s) and held at isothermal temperatures from 10 to 43.3 degrees C. Log CFU per sample data were obtained for each pathogen and used to determine lag-phase duration (LPD) and growth rate (GR) by DMFit software. The LPD and GR were used to develop the THERM predictive tool, into which chronological time and temperature data for raw meat processing and storage are entered. The THERM tool then predicts a delta log CFU value for the desired pathogen-product combination. The accuracy of THERM was tested in 20 different inoculation experiments that involved multiple products (coarse-ground beef, skinless chicken breast meat, turkey scapula meat, and ground turkey) and temperature-abuse scenarios. With the time-temperature data from each experiment, THERM accurately predicted the pathogen growth and no growth (with growth defined as delta log CFU > 0.3) in 67, 85, and 95% of the experiments with E. coli 0157:H7, Salmonella serovars, and S. aureus, respectively, and yielded fail-safe predictions in the remaining experiments. We conclude that THERM is a useful tool for qualitatively predicting pathogen behavior (growth and no growth) in raw meats. Potential applications include evaluating process deviations and critical limits under the HACCP (hazard analysis critical control point) system.

Short-term solar irradiance forecasting via satellite/model coupling

DOE PAGES

Miller, Steven D.; Rogers, Matthew A.; Haynes, John M.; ...

2017-12-01

The short-term (0-3 h) prediction of solar insolation for renewable energy production is a problem well-suited to satellite-based techniques. The spatial, spectral, temporal and radiometric resolution of instrumentation hosted on the geostationary platform allows these satellites to describe the current cloud spatial distribution and optical properties. These properties relate directly to the transient properties of the downwelling solar irradiance at the surface, which come in the form of 'ramps' that pose a central challenge to energy load balancing in a spatially distributed network of solar farms. The short-term evolution of the cloud field may be approximated to first order simplymore » as translational, but care must be taken in how the advection is handled and where the impacts are assigned. In this research, we describe how geostationary satellite observations are used with operational cloud masking and retrieval algorithms, wind field data from Numerical Weather Prediction (NWP), and radiative transfer calculations to produce short-term forecasts of solar insolation for applications in solar power generation. The scheme utilizes retrieved cloud properties to group pixels into contiguous cloud objects whose future positions are predicted using four-dimensional (space + time) model wind fields, selecting steering levels corresponding to the cloud height properties of each cloud group. The shadows associated with these clouds are adjusted for sensor viewing parallax displacement and combined with solar geometry and terrain height to determine the actual location of cloud shadows. For mid/high-level clouds at mid-latitudes and high solar zenith angles, the combined displacements from these geometric considerations are non-negligible. The cloud information is used to initialize a radiative transfer model that computes the direct and diffuse-sky solar insolation at both shadow locations and intervening clear-sky regions. Here, we describe the formulation of

Short-term solar irradiance forecasting via satellite/model coupling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, Steven D.; Rogers, Matthew A.; Haynes, John M.

The short-term (0-3 h) prediction of solar insolation for renewable energy production is a problem well-suited to satellite-based techniques. The spatial, spectral, temporal and radiometric resolution of instrumentation hosted on the geostationary platform allows these satellites to describe the current cloud spatial distribution and optical properties. These properties relate directly to the transient properties of the downwelling solar irradiance at the surface, which come in the form of 'ramps' that pose a central challenge to energy load balancing in a spatially distributed network of solar farms. The short-term evolution of the cloud field may be approximated to first order simplymore » as translational, but care must be taken in how the advection is handled and where the impacts are assigned. In this research, we describe how geostationary satellite observations are used with operational cloud masking and retrieval algorithms, wind field data from Numerical Weather Prediction (NWP), and radiative transfer calculations to produce short-term forecasts of solar insolation for applications in solar power generation. The scheme utilizes retrieved cloud properties to group pixels into contiguous cloud objects whose future positions are predicted using four-dimensional (space + time) model wind fields, selecting steering levels corresponding to the cloud height properties of each cloud group. The shadows associated with these clouds are adjusted for sensor viewing parallax displacement and combined with solar geometry and terrain height to determine the actual location of cloud shadows. For mid/high-level clouds at mid-latitudes and high solar zenith angles, the combined displacements from these geometric considerations are non-negligible. The cloud information is used to initialize a radiative transfer model that computes the direct and diffuse-sky solar insolation at both shadow locations and intervening clear-sky regions. Here, we describe the formulation of

Short-Term Memory and Aphasia: From Theory to Treatment

PubMed Central

Minkina, Irene; Rosenberg, Samantha; Kalinyak-Fliszar, Michelene; Martin, Nadine

2018-01-01

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. PMID:28201834

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

EPA Science Inventory

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...

Focusing on Short-Term Achievement Gains Fails to Produce Long-Term Gains

ERIC Educational Resources Information Center

Grissmer, David W.; Ober, David R.; Beekman, John A.

2014-01-01

The short-term emphasis engendered by No Child Left Behind (NCLB) has focused research predominantly on unraveling the complexities and uncertainties in assessing short-term results, rather than developing methods and assessing results over the longer term. In this paper we focus on estimating long-term gains and address questions important to…

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.

PubMed

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.

Ensemble forecasting of short-term system scale irrigation demands using real-time flow data and numerical weather predictions

NASA Astrophysics Data System (ADS)

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

2016-06-01

Irrigation demands fluctuate in response to weather variations and a range of irrigation management decisions, which creates challenges for water supply system operators. This paper develops a method for real-time ensemble forecasting of irrigation demand and applies it to irrigation command areas of various sizes for lead times of 1 to 5 days. The ensemble forecasts are based on a deterministic time series model coupled with ensemble representations of the various inputs to that model. Forecast inputs include past flow, precipitation, and potential evapotranspiration. These inputs are variously derived from flow observations from a modernized irrigation delivery system; short-term weather forecasts derived from numerical weather prediction models and observed weather data available from automatic weather stations. The predictive performance for the ensemble spread of irrigation demand was quantified using rank histograms, the mean continuous rank probability score (CRPS), the mean CRPS reliability and the temporal mean of the ensemble root mean squared error (MRMSE). The mean forecast was evaluated using root mean squared error (RMSE), Nash-Sutcliffe model efficiency (NSE) and bias. The NSE values for evaluation periods ranged between 0.96 (1 day lead time, whole study area) and 0.42 (5 days lead time, smallest command area). Rank histograms and comparison of MRMSE, mean CRPS, mean CRPS reliability and RMSE indicated that the ensemble spread is generally a reliable representation of the forecast uncertainty for short lead times but underestimates the uncertainty for long lead times.

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

PubMed

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

Short-Term Memory and Aphasia: From Theory to Treatment.

PubMed

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.

PubMed

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.

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

PubMed Central

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

2012-01-01

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

Discussion of New Approaches to Medium-Short-Term Earthquake Forecast in Practice of The Earthquake Prediction in Yunnan

NASA Astrophysics Data System (ADS)

Hong, F.

2017-12-01

After retrospection of years of practice of the earthquake prediction in Yunnan area, it is widely considered that the fixed-point earthquake precursory anomalies mainly reflect the field information. The increase of amplitude and number of precursory anomalies could help to determine the original time of earthquakes, however it is difficult to obtain the spatial relevance between earthquakes and precursory anomalies, thus we can hardly predict the spatial locations of earthquakes using precursory anomalies. The past practices have shown that the seismic activities are superior to the precursory anomalies in predicting earthquakes locations, resulting from the increased seismicity were observed before 80% M=6.0 earthquakes in Yunnan area. While the mobile geomagnetic anomalies are turned out to be helpful in predicting earthquakes locations in recent year, for instance, the forecasted earthquakes occurring time and area derived form the 1-year-scale geomagnetic anomalies before the M6.5 Ludian earthquake in 2014 are shorter and smaller than which derived from the seismicity enhancement region. According to the past works, the author believes that the medium-short-term earthquake forecast level, as well as objective understanding of the seismogenic mechanisms, could be substantially improved by the densely laying observation array and capturing the dynamic process of physical property changes in the enhancement region of medium to small earthquakes.

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

NASA Astrophysics Data System (ADS)

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

Predictors of short- and long-term avoidance in completers of inpatient group interventions for agoraphobia.

PubMed

Hoffart, Asle; Øktedalen, Tuva; Svanøe, Karol; Hedley, Liv M; Sexton, Harold

2015-08-01

Little is currently known about predictors of follow-up outcome of psychological treatment of agoraphobia. In this study, we wished to examine predictors of short- and long-term avoidance after inpatient group interventions for agoraphobia. Ninety-six (68%) of 141 agoraphobic patients (74% women) who had completed treatment in two open and one randomized controlled trial (RCT) were followed up 13 to 21 years after start of treatment. Major depression at pre-treatment predicted less short-term (up to one year after end of treatment) improvement in agoraphobic avoidance. Working and being married/cohabiting at pre-treatment predicted greater long-term (across one-year, two-year, and 13-21 years follow-up) improvement. In contrast, the duration of agoraphobia, amount of Axis I and II co-morbidity, being diagnosed with avoidant, dependent, and obsessive-compulsive personality disorder, and the use of antidepressants and benzodiazepines the month before intake to treatment, were unrelated to short-term as well as long-term outcome. As many as 31.9% of the included patients did not attend long-term follow-up and the power of the study was limited. The long time period between the two and 13-21 year follow-ups is a limitation, in which it is difficult to assess what actually happened. Although all the patients received some form of CBT, there was variability among the treatments. The only short-term predictor identified represented a clinical feature, whereas the long-term predictors represented features of the patients' life situation. The limited power of the study precludes the inference that non-significant predictors are unrelated to follow-up outcome. Copyright © 2015 Elsevier B.V. All rights reserved.

NASA Prediction of Worldwide Energy Resource High Resolution Meteorology Data For Sustainable Building Design

NASA Technical Reports Server (NTRS)

Chandler, William S.; Hoell, James M.; Westberg, David; Zhang, Taiping; Stackhouse, Paul W., Jr.

2013-01-01

A primary objective of NASA's Prediction of Worldwide Energy Resource (POWER) project is to adapt and infuse NASA's solar and meteorological data into the energy, agricultural, and architectural industries. Improvements are continuously incorporated when higher resolution and longer-term data inputs become available. Climatological data previously provided via POWER web applications were three-hourly and 1x1 degree latitude/longitude. The NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) data set provides higher resolution data products (hourly and 1/2x1/2 degree) covering the entire globe. Currently POWER solar and meteorological data are available for more than 30 years on hourly (meteorological only), daily, monthly and annual time scales. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings. A recent focus has been working with ASHRAE to assess complementing weather station data with MERRA data. ASHRAE building design parameters being investigated include heating/cooling degree days and climate zones.

Short-term predictions in forex trading

NASA Astrophysics Data System (ADS)

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.

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?

PubMed

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Drinking High Amounts of Alcohol as a Short-Term Mating Strategy: The Impact of Short-Term Mating Motivations on Young Adults' Drinking Behavior.

PubMed

Vincke, Eveline

2017-01-01

Previous research indicates that drinking large quantities of alcohol could function as a short-term mating strategy for young adults in mating situations. However, no study investigated whether this is actually the case. Therefore, in this article, the link between short-term mating motivations and drinking high amounts of alcohol is tested. First, a survey study ( N = 345) confirmed that young adults who engage in binge drinking are more short-term oriented in their mating strategy than young adults who never engage in binge drinking. Also, the more short-term-oriented young adults were in their mating strategy, the more often binge drinking behavior was conducted. In addition, an experimental study ( N = 229) empirically verified that short-term mating motivations increase young adults' drinking behavior, more so than long-term mating motivations. Results of the experiment clearly showed that young men and young women are triggered to drink more alcoholic beverages in a short-term mating situation compared to a long-term mating situation. Furthermore, the mating situation also affected young adults' perception of drinking behavior. Young adults in a short-term mating context perceived a higher amount of alcoholic beverages as heavy drinking compared to peers in a long-term mating context. These findings confirm that a high alcohol consumption functions as a short-term mating strategy for both young men and young women. Insights gained from this article might be of interest to institutions aimed at targeting youth alcohol (ab)use.

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

PubMed

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.

PubMed

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.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Huaiguang; Ding, Fei; Zhang, Yingchen

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 systemmore » 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.« less

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

NASA Astrophysics Data System (ADS)

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

PubMed Central

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

2013-01-01

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. PMID:23376550

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

PubMed

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.

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

PubMed

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.

Reliability of Long-Term Wave Conditions Predicted with Data Sets of Short Duration

DTIC Science & Technology

1985-03-01

the validity and reliability of predicted probable wave heights obtained from data of limited duration. BACKGROUND: The basic steps listed by...interest to perform the analysis outlined in steps 2 to 5, the prediction would only be reliable for up to a 3year return period. For a 5-year data set...for long-term hindcast data . The data retrieval and analysis program known as the Sea State Engineering Analysis System (SEAS) makes handling of the

Initial Evaluations of LoC Prediction Algorithms Using the NASA Vertical Motion Simulator

NASA Technical Reports Server (NTRS)

Krishnakumar, Kalmanje; Stepanyan, Vahram; Barlow, Jonathan; Hardy, Gordon; Dorais, Greg; Poolla, Chaitanya; Reardon, Scott; Soloway, Donald

2014-01-01

Flying near the edge of the safe operating envelope is an inherently unsafe proposition. Edge of the envelope here implies that small changes or disturbances in system state or system dynamics can take the system out of the safe envelope in a short time and could result in loss-of-control events. This study evaluated approaches to predicting loss-of-control safety margins as the aircraft gets closer to the edge of the safe operating envelope. The goal of the approach is to provide the pilot aural, visual, and tactile cues focused on maintaining the pilot's control action within predicted loss-of-control boundaries. Our predictive architecture combines quantitative loss-of-control boundaries, an adaptive prediction method to estimate in real-time Markov model parameters and associated stability margins, and a real-time data-based predictive control margins estimation algorithm. The combined architecture is applied to a nonlinear transport class aircraft. Evaluations of various feedback cues using both test and commercial pilots in the NASA Ames Vertical Motion-base Simulator (VMS) were conducted in the summer of 2013. The paper presents results of this evaluation focused on effectiveness of these approaches and the cues in preventing the pilots from entering a loss-of-control event.

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

PubMed

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.

An Overview of NASA SPoRT GOES-R JPSS Proving Ground Testbed Activities

NASA Technical Reports Server (NTRS)

Berndt, Emily; Stano, Geoffrey; Fuell, Kevin; Leroy, Anita; Mcgrath, Kevin; Molthan, Andrew; Schultz, Lori; Smith, Matthew; White, Kris; Schultz, Christopher;

Adaptive Data-based Predictive Control for Short Take-off and Landing (STOL) Aircraft

NASA Technical Reports Server (NTRS)

Barlow, Jonathan Spencer; Acosta, Diana Michelle; Phan, Minh Q.

2010-01-01

Data-based Predictive Control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. The characteristics of adaptive data-based predictive control are particularly appropriate for the control of nonlinear and time-varying systems, such as Short Take-off and Landing (STOL) aircraft. STOL is a capability of interest to NASA because conceptual Cruise Efficient Short Take-off and Landing (CESTOL) transport aircraft offer the ability to reduce congestion in the terminal area by utilizing existing shorter runways at airports, as well as to lower community noise by flying steep approach and climb-out patterns that reduce the noise footprint of the aircraft. In this study, adaptive data-based predictive control is implemented as an integrated flight-propulsion controller for the outer-loop control of a CESTOL-type aircraft. Results show that the controller successfully tracks velocity while attempting to maintain a constant flight path angle, using longitudinal command, thrust and flap setting as the control inputs.

Intercultural Competence in Short-Term Study Abroad

ERIC Educational Resources Information Center

Nguyen, Annie

2017-01-01

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

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

PubMed

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).

Short-Term Memory and Long-Term Memory are Still Different

PubMed Central

2017-01-01

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. PMID:28530428

Short Term Exogenic Climate Change Forcing

NASA Astrophysics Data System (ADS)

Krahenbuhl, Daniel

Several short term exogenic forcings affecting Earth's climate are but recently identified. Lunar nutation periodicity has implications for numerical meteorological prediction. Abrupt shifts in solar wind bulk velocity, particle density, and polarity exhibit correlation with terrestrial hemispheric vorticity changes, cyclonic strengthening and the intensification of baroclinic disturbances. Galactic Cosmic ray induced tropospheric ionization modifies cloud microphysics, and modulates the global electric circuit. This dissertation is constructed around three research questions: (1): What are the biweekly declination effects of lunar gravitation upon the troposphere? (2): How do United States severe weather reports correlate with heliospheric current sheet crossings? and (3): How does cloud cover spatially and temporally vary with galactic cosmic rays? Study 1 findings show spatial consistency concerning lunar declination extremes upon Rossby longwaves. Due to the influence of Rossby longwaves on synoptic scale circulation, our results could theoretically extend numerical meteorological forecasting. Study 2 results indicate a preference for violent tornadoes to occur prior to a HCS crossing. Violent tornadoes (EF3+) are 10% more probable to occur near, and 4% less probable immediately after a HCS crossing. The distribution of hail and damaging wind reports do not mirror this pattern. Polarity is critical for the effect. Study 3 results confirm anticorrelation between solar flux and low-level marine-layer cloud cover, but indicate substantial regional variability between cloud cover altitude and GCRs. Ultimately, this dissertation serves to extend short term meteorological forecasting, enhance climatological modeling and through analysis of severe violent weather and heliospheric events, protect property and save lives.

In Search of Decay in Verbal Short-Term Memory

PubMed Central

Berman, Marc G.; Jonides, John; Lewis, Richard L.

2014-01-01

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 interference in short-term memory in a task that rules out the use of rehearsal processes. In this article the authors present a series of studies using a novel paradigm to address this problem directly, by interrogating the operation of decay and interference in short-term memory without rehearsal confounds. The results of these studies indicate that short-term memories are subject to very small decay effects with the mere passage of time but that interference plays a much larger role in their degradation. The authors discuss the implications of these results for existing models of memory decay and interference. PMID:19271849

In search of decay in verbal short-term memory.

PubMed

Berman, Marc G; Jonides, John; Lewis, Richard L

2009-03-01

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 interference in short-term memory in a task that rules out the use of rehearsal processes. In this article the authors present a series of studies using a novel paradigm to address this problem directly, by interrogating the operation of decay and interference in short-term memory without rehearsal confounds. The results of these studies indicate that short-term memories are subject to very small decay effects with the mere passage of time but that interference plays a much larger role in their degradation. The authors discuss the implications of these results for existing models of memory decay and interference. (c) 2009 APA, all rights reserved

A Process for Assessing NASA's Capability in Aircraft Noise Prediction Technology

NASA Technical Reports Server (NTRS)

Dahl, Milo D.

2008-01-01

An acoustic assessment is being conducted by NASA that has been designed to assess the current state of the art in NASA s capability to predict aircraft related noise and to establish baselines for gauging future progress in the field. The process for determining NASA s current capabilities includes quantifying the differences between noise predictions and measurements of noise from experimental tests. The computed noise predictions are being obtained from semi-empirical, analytical, statistical, and numerical codes. In addition, errors and uncertainties are being identified and quantified both in the predictions and in the measured data to further enhance the credibility of the assessment. The content of this paper contains preliminary results, since the assessment project has not been fully completed, based on the contributions of many researchers and shows a select sample of the types of results obtained regarding the prediction of aircraft noise at both the system and component levels. The system level results are for engines and aircraft. The component level results are for fan broadband noise, for jet noise from a variety of nozzles, and for airframe noise from flaps and landing gear parts. There are also sample results for sound attenuation in lined ducts with flow and the behavior of acoustic lining in ducts.

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

PubMed

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.

Short-term hot-hardness characteristics of five case hardened steels

NASA Technical Reports Server (NTRS)

Anderson, N. E.; Zaretsky, E. V.

1975-01-01

Short-term hot-hardness studies were performed with carburized and hardened AISI 8620, CBS 1000, CBS 1000M, CBS 600, and Vasco X-2 steels. Case and core hardness measurements were made at temperatures from 294 to 811 K (70 to 1000 F). The data were compared with data for high-speed tool steels and AISI 52100. The materials tested can be ranked as follows in order of decreasing hot-hardness retention: (1) Vasco X-2; equivalent to through-hardened tool steels up to 644 K (700 F) above which Vasco X-2 is inferior; (2) CBS 1000, (3) CBS 1000M; (4) CBS 6000; better hardness retention at elevated temperatures than through-hardened AISI 52100; and (5) AISI 8620. For the carburized steels, the change in hardness with temperature of the case and core are similar for a given material. The short-term hot hardness of these materials can be predicted with + or - 1 point Rockwell C.

A Single Brief Burst Induces GluR1-Dependent Associative Short-Term Potentiation: A Potential Mechanism for Short-Term Memory

ERIC Educational Resources Information Center

Erickson, Martha A.; Maramara, Lauren A.; Lisman, John

2010-01-01

Recent work showed that short-term memory (STM) is selectively reduced in GluR1 knockout mice. This raises the possibility that a form of synaptic modification dependent on GluR1 might underlie STM. Studies of synaptic plasticity have shown that stimuli too weak to induce long-term potentiation induce short-term potentiation (STP), a phenomenon…

Simulation of short-term electric load using an artificial neural network

NASA Astrophysics Data System (ADS)

Ivanin, O. A.

2018-01-01

While solving the task of optimizing operation modes and equipment composition of small energy complexes or other tasks connected with energy planning, it is necessary to have data on energy loads of a consumer. Usually, there is a problem with obtaining real load charts and detailed information about the consumer, because a method of load-charts simulation on the basis of minimal information should be developed. The analysis of work devoted to short-term loads prediction allows choosing artificial neural networks as a most suitable mathematical instrument for solving this problem. The article provides an overview of applied short-term load simulation methods; it describes the advantages of artificial neural networks and offers a neural network structure for electric loads of residential buildings simulation. The results of modeling loads with proposed method and the estimation of its error are presented.

Short-term bioassay of complex organic mixtures. Part II. Mutagenicity testing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Epler, J.L.; Clark, B.R.; Ho, C.

1978-01-01

The feasibility of using short-term mutagenicity assays to predict the potential biohazard of various crude and complex test materials has been examined in a coupled chemical and biological approach. The principal focus of the research has involved the preliminary chemical characterizatiion and preparation for bioassay, followed by testing in the Salmonella histidine reversion assay system. The mutagenicity tests are intended to act as predictors of profound long-range health effects such as mutagenesis and/or carcinogenesis; act as a mechanism to rapidly isolate and identify a hazardous agent in a complex mixture; and function as a measure of biological activity correlating baselinemore » data with changes in process conditions. Since complex mixtures can be fractionated and approached in these short-term assays, information reflecting on the actual compounds responsible for the biological effect may be accumulated.« less

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

NASA Astrophysics Data System (ADS)

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.

State of Jet Noise Prediction-NASA Perspective

NASA Technical Reports Server (NTRS)

Bridges, James E.

2008-01-01

This presentation covers work primarily done under the Airport Noise Technical Challenge portion of the Supersonics Project in the Fundamental Aeronautics Program. To provide motivation and context, the presentation starts with a brief overview of the Airport Noise Technical Challenge. It then covers the state of NASA s jet noise prediction tools in empirical, RANS-based, and time-resolved categories. The empirical tools, requires seconds to provide a prediction of noise spectral directivity with an accuracy of a few dB, but only for axisymmetric configurations. The RANS-based tools are able to discern the impact of three-dimensional features, but are currently deficient in predicting noise from heated jets and jets with high speed and require hours to produce their prediction. The time-resolved codes are capable of predicting resonances and other time-dependent phenomena, but are very immature, requiring months to deliver predictions without unknown accuracies and dependabilities. In toto, however, when one considers the progress being made it appears that aeroacoustic prediction tools are soon to approach the level of sophistication and accuracy of aerodynamic engineering tools.

Verbal Short-Term Memory Reflects the Organization of Long-Term Memory: Further Evidence from Short-Term Memory for Emotional Words

ERIC Educational Resources Information Center

Majerus, Steve; D'Argembeau, Arnaud

2011-01-01

Many studies suggest that long-term lexical-semantic knowledge is an important determinant of verbal short-term memory (STM) performance. This study explored the impact of emotional valence on word immediate serial recall as a further lexico-semantic long-term memory (LTM) effect on STM. This effect is particularly interesting for the study of…

Three Models for Short-Term Study Abroad

ERIC Educational Resources Information Center

Sachau, Daniel; Brasher, Niel; Fee, Scott

2010-01-01

Nearly 250,000 U.S. college students participate in study abroad programs each year. A growing proportion of students are participating in short-term study abroad programs. Despite the large number of students in these programs, there are relatively few articles that describe how to start or manage a short-term, business-related, study abroad…

Auralization Architectures for NASA?s Next Generation Aircraft Noise Prediction Program

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Lopes, Leonard V.; Burley, Casey L.; Aumann, Aric R.

2013-01-01

Aircraft community noise is a significant concern due to continued growth in air traffic, increasingly stringent environmental goals, and operational limitations imposed by airport authorities. The assessment of human response to noise from future aircraft can only be afforded through laboratory testing using simulated flyover noise. Recent work by the authors demonstrated the ability to auralize predicted flyover noise for a state-of-the-art reference aircraft and a future hybrid wing body aircraft concept. This auralization used source noise predictions from NASA's Aircraft NOise Prediction Program (ANOPP) as input. The results from this process demonstrated that auralization based upon system noise predictions is consistent with, and complementary to, system noise predictions alone. To further develop and validate the auralization process, improvements to the interfaces between the synthesis capability and the system noise tools are required. This paper describes the key elements required for accurate noise synthesis and introduces auralization architectures for use with the next-generation ANOPP (ANOPP2). The architectures are built around a new auralization library and its associated Application Programming Interface (API) that utilize ANOPP2 APIs to access data required for auralization. The architectures are designed to make the process of auralizing flyover noise a common element of system noise prediction.

Embolization of renal angiomyolipomas: short-term and long-term outcomes, complications, and tumor shrinkage.

PubMed

Lee, Shen-Yang; Hsu, Hsiang-Hao; Chen, Yung-Chang; Huang, Chen-Chih; Wong, Yon-Cheong; Wang, Li-Jen; Chuang, Cheng-Keng; Yang, Chih-Wei

2009-11-01

This study retrospectively evaluated outcomes, complications, and tumor shrinkage in renal angiomyolipomas after transcatheter arterial embolization (TAE). All renal angiomyolipoma patients who underwent TAE between August 2000 and December 2008 and had short-term (term (>6 months) follow-up images were evaluated. Complications and tumor relapse after TAE were reviewed. The sizes of embolized tumors were measured to calculate size reductions and reduction rates after TAE. Differences in tumor size, size reduction, and reduction rate between different time points (pre-TAE, short-term follow-up, and long-term follow-up) and groups (completely and incompletely embolized) were determined. Eleven renal angiomyolipoma patients who had undergone TAE were included. Seven (63.6%) patients had postembolization syndrome and one had abscess formation following TAE. Two patients had a tumor relapse (18.2%). The mean tumor size was 8.57+/-2.66 cm on pre-TAE images. The mean size reduction was 3.1 cm (33.3%) and 3.8 cm (43.0%) at short-term and long-term follow-up. Tumor sizes differed significantly between pre-TAE and short-term (p=0.004) or long-term images (p=0.022) but not between short-term and long-term images (p=0.059). Results stratified by the completeness of embolization indicate that only the short-term size reduction rate differed significantly (p=0.025), while the long-term reduction rate and short- and long-term follow-up tumor size and size reduction were comparable between the two groups. In conclusion, selective TAE is effective for tumor shrinkage in most renal angiomyolipomas, with acceptable complication and relapse rates. Tumor shrinkage occurring within 6 months after TAE may reflect the long-term effect of TAE.

Role of calcitonin gene-related peptide in cardioprotection of short-term and long-term exercise preconditioning.

PubMed

Sun, Xiao-Juan; Pan, Shan-Shan

2014-07-01

To examine the role of calcitonin gene-related peptide (CGRP) in cardioprotection of short-term and long-term exercise preconditioning (EP). Male Sprague-Dawley rats were, respectively, subjected to continuous intermittent treadmill training 3 days or 3 weeks as short-term or long-term EP protocols. The myocardial injury induced by isoproterenol (ISO) was performed 24 hours after short-term and long-term EP. The myocardial injury was evaluated in terms of the serum cardiac troponin levels and the hematoxylin-basic fuchsin-picric acid staining. Additionally, serum CGRP levels, CGRP expression in the dorsal root ganglion (DRG), and heart were analyzed as possible mechanisms to explain short-term and long-term EP-induced cardioprotection. Both short-term and long-term EP markedly attenuated the isoproterenol-induced myocardial ischemia with lower serum cardiac troponin levels. Short-term EP does not alter serum CGRP levels and CGRP expression in the DRG and heart. Long-term EP significantly increases serum CGRP levels and CGRP expression in the DRG and heart. The results indicate that short-term EP does not increase the synthesis and release of CGRP. Therefore, the cardioprotective effect of short-term EP does not involve CGRP adaptation. Furthermore, long-term EP increases CGRP synthesis in the DRG and promotes CGRP release in the blood and heart. Hence, CGRP may play an important role in the cardioprotective effect of long-term EP.

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

PubMed

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

Slave to the Rhythm: Experimental Tests of a Model for Verbal Short-Term Memory and Long-Term Sequence Learning

ERIC Educational Resources Information Center

Hitch, Graham J.; Flude, Brenda; Burgess, Neil

2009-01-01

Three experiments tested predictions of a neural network model of phonological short-term memory that assumes separate representations for order and item information, order being coded via a context-timing signal [Burgess, N., & Hitch, G. J. (1999). Memory for serial order: A network model of the phonological loop and its timing. "Psychological…

22 CFR 71.11 - Short-term full diet program.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 22 Foreign Relations 1 2013-04-01 2013-04-01 false Short-term full diet program. 71.11 Section 71.... Nationals Incarcerated Abroad § 71.11 Short-term full diet program. (a) Eligibility criteria. A prisoner is considered eligible for the short-term full diet program under the following general criteria: (1) The...

22 CFR 71.11 - Short-term full diet program.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 22 Foreign Relations 1 2014-04-01 2014-04-01 false Short-term full diet program. 71.11 Section 71.... Nationals Incarcerated Abroad § 71.11 Short-term full diet program. (a) Eligibility criteria. A prisoner is considered eligible for the short-term full diet program under the following general criteria: (1) The...

22 CFR 71.11 - Short-term full diet program.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 22 Foreign Relations 1 2012-04-01 2012-04-01 false Short-term full diet program. 71.11 Section 71.... Nationals Incarcerated Abroad § 71.11 Short-term full diet program. (a) Eligibility criteria. A prisoner is considered eligible for the short-term full diet program under the following general criteria: (1) The...

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

PubMed

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

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

PubMed

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.

The economic impact of NASA R and D spending

NASA Technical Reports Server (NTRS)

Evans, M. K.

1976-01-01

The economic impact of R and D spending, particularly NASA R and D spending, on the U. S. economy was evaluated. The crux of the methodology and hence the results revolve around the fact that it was necessary to consider both the demand effects of increased spending and the supply effects of a higher rate of technological growth and a larger total productive capacity. The demand effects are primarily short-run in nature, while the supply effects do not begin to have a significant effect on aggregate economic activity until the fifth year after increased expenditures have taken place. The short-term economic impact of alternative levels of NASA expenditures for 1975 was first examined. The long-term economic impact of increased levels of NASA R and D spending over a sustained period was then evaluated.

Familiarity speeds up visual short-term memory consolidation.

PubMed

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).

NASA's Contribution to Water Research, Applications and Capacity Building in the America's

NASA Astrophysics Data System (ADS)

Toll, D. L.; Searby, N. D.; Doorn, B.; Lawford, R. G.; Entin, J. K.; Mohr, K. I.; Lee, C.; NASA International Water Team

2013-05-01

NASA's water research, applications and capacity building activities use satellites and models to contribute to regional water information and solutions for the Americas. Free and open exchange of Earth data observations and products helps engage and improve integrated observation networks and enables national and multi-national regional water cycle research and applications. NASA satellite and modeling products provide a huge volume of valuable data extending back over 50 years across a broad range of spatial (local to global) and temporal (hourly to decadal) scales and include many products that are available in near real time (see earthdata.nasa.gov). In addition, NASA's work in hydrologic predictions are valuable for: 1) short-term and hourly data that is critical for flood and landslide warnings; 2) mid-term predictions of days to weeks useful for reservoir planning and water allocation, and 3) long term seasonal to decadal forecasts helpful for agricultural and irrigation planning, land use planning, and water infrastructure development and planning. To further accomplish these objectives NASA works to actively partner with public and private groups (e.g. federal agencies, universities, NGO's, and industry) in the U.S. and internationally to ensure the broadest use of its satellites and related information and products and to collaborate with regional end users who know the regions and their needs best. Through these data, policy and partnering activities, NASA addresses numerous water issues including water scarcity, the extreme events of drought and floods, and water quality so critical to the Americas. This presentation will outline and describe NASA's water related research, applications and capacity building programs' efforts to address the Americas' critical water challenges. This will specifically include water activities in NASA's programs in Terrestrial Hydrology (e.g., land-atmosphere feedbacks and improved stream flow estimation), Water Resources

In Search of Decay in Verbal Short-Term Memory

ERIC Educational Resources Information Center

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

NASA Astrophysics Data System (ADS)

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

Abdominal Pain (Stomach Pain), Short-Term

MedlinePlus

... Long-term Abdominal Pain (Stomach Pain), Short-term Ankle Problems Breast Problems in Men Breast Problems in Women Chest Pain in Infants and Children Chest Pain, Acute Chest Pain, Chronic Cold and Flu Cough Diarrhea ...

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

PubMed

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 (p<0.003). Moreover, outcome groups differed significantly only on the Cartoon Predictions subtest (z-scores: poor outcome=-2.7 [SD=2.7]; good outcome=-0.7 [SD=1.8]; p=0.001) among the five subtests used. Overall, social cognition appears to be compromised in all FEP patients compared to healthy controls. More interestingly, significant differences in social cognitive impairments exist between good and poor short-term clinical outcome groups, with the largest effect found in the Cartoon Predictions subtest.

Short- and Long-Term Consequences of Adolescent Work.

ERIC Educational Resources Information Center

Mihalic, Sharon Wofford; Elliott, Delbert

1997-01-01

Examines the short- and long-term consequences of working during adolescence. Responses from 1,725 adolescents reveal that the negative short-term effects are in the domains of school, family and friend bonding, beliefs, and substance use. The long-term beneficial effect is that the duration of early work helps employability in adulthood. (GR)

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

ERIC Educational Resources Information Center

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…

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

PubMed Central

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

2017-01-01

Abstract Motivation: 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. Results: 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. Availability and implementation: The source code can be downloaded from https://github.com/minxueric/ismb2017_lstm. Contact: tingchen@tsinghua.edu.cn or ruijiang

Economics of solar energy: Short term costing

NASA Astrophysics Data System (ADS)

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.

Increased Short-Term Variability of the QT Interval in Professional Soccer Players: Possible Implications for Arrhythmia Prediction

PubMed Central

Lengyel, Csaba; Orosz, Andrea; Hegyi, Péter; Komka, Zsolt; Udvardy, Anna; Bosnyák, Edit; Trájer, Emese; Pavlik, Gábor; Tóth, Miklós; Wittmann, Tibor; Papp, Julius Gy.; Varró, András; Baczkó, István

2011-01-01

Background Sudden cardiac death in competitive athletes is rare but it is significantly more frequent than in the normal population. The exact cause is seldom established and is mostly attributed to ventricular fibrillation. Myocardial hypertrophy and slow heart rate, both characteristic changes in top athletes in response to physical conditioning, could be associated with increased propensity for ventricular arrhythmias. We investigated conventional ECG parameters and temporal short-term beat-to-beat variability of repolarization (STVQT), a presumptive novel parameter for arrhythmia prediction, in professional soccer players. Methods Five-minute 12-lead electrocardiograms were recorded from professional soccer players (n = 76, all males, age 22.0±0.61 years) and age-matched healthy volunteers who do not participate in competitive sports (n = 76, all males, age 22.0±0.54 years). The ECGs were digitized and evaluated off-line. The temporal instability of beat-to-beat heart rate and repolarization were characterized by the calculation of short-term variability of the RR and QT intervals. Results Heart rate was significantly lower in professional soccer players at rest (61±1.2 vs. 72±1.5/min in controls). The QT interval was prolonged in players at rest (419±3.1 vs. 390±3.6 in controls, p<0.001). QTc was significantly longer in players compared to controls calculated with Fridericia and Hodges correction formulas. Importantly, STVQT was significantly higher in players both at rest and immediately after the game compared to controls (4.8±0.14 and 4.3±0.14 vs. 3.5±0.10 ms, both p<0.001, respectively). Conclusions STVQT is significantly higher in professional soccer players compared to age-matched controls, however, further studies are needed to relate this finding to increased arrhythmia propensity in this population. PMID:21526208

Short-term annoyance from nocturnal aircraft noise exposure: results of the NORAH and STRAIN sleep studies.

PubMed

Quehl, Julia; Müller, Uwe; Mendolia, Franco

2017-11-01

The German Aerospace Center (DLR) investigated in the NORAH sleep study the association between a distinct change in nocturnal aircraft noise exposure due to the introduction of a night curfew (11:00 p.m.-5:00 a.m.) at Frankfurt Airport and short-term annoyance reactions of residents in the surrounding community. Exposure-response curves were calculated by random effects logistic regression to evaluate the aircraft noise-related parameters (1) number of overflights and (2) energy equivalent noise level L ASeq for the prediction of short-term annoyance. Data of the NORAH sleep study were compared with the STRAIN sleep study which was conducted by DLR near Cologne-Bonn Airport in 2001/2002 (N = 64), representing a steady-state/low-rate change. The NORAH sleep study was based on questionnaire surveys with 187 residents living in the vicinity of Frankfurt Airport. Noise-induced short-term annoyance and related non-acoustical variables were assessed. Nocturnal aircraft noise exposure was measured inside the residents' home. A statistically significant rise in the portion of annoyed residents with increasing number of overflights was found. Similarly, the portion of annoyed subjects increased with rising L ASeq . Importance of the frequency of fly-overs for the prediction of annoyance reactions was emphasized. The annoyance probability was significantly higher in the NORAH than in the STRAIN sleep study. Results confirm the importance of both acoustical parameters for the prediction of short-term annoyance due to nocturnal aircraft noise. Quantitative annoyance models that were derived at steady-state/low-rate change airports cannot be directly applied to airports that underwent a distinct change in operational and noise exposure patterns.

Short-Term Reciprocity in Late Parent-Child Relationships

ERIC Educational Resources Information Center

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…

NASA Thesaurus. Volumes 1 and 2; Hierarchical Listing with Definitions; Rotated Term Display

NASA Technical Reports Server (NTRS)

2012-01-01

The NASA Thesaurus contains the authorized subject terms by which the documents in the NASA STI Databases are indexed and retrieved. The scope of this controlled vocabulary includes not only aerospace engineering, but all supporting areas of engineering and physics, the natural space sciences (astronomy, astrophysics, planetary science), Earth sciences, and to some extent, the biological sciences. Volume 1 - Hierarchical Listing With Definitions contains over 18,400 subject terms, 4,300 definitions, and more than 4,500 USE cross references. The Hierarchical Listing presents full hierarchical structure for each term along with 'related term' lists, and can serve as an orthographic authority. Volume 2 - Rotated Term Display is a ready-reference tool which provides over 52,700 additional 'access points' to the thesaurus terminology. It contains the postable and nonpostable terms found in the Hierarchical Listing arranged in a KWIC (key-word-in-context) index. This CD-ROM version of the NASA Thesaurus is in PDF format and is updated to the current year of purchase.

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

PubMed Central

Parenteau, Charline; Trouvé, Colette; Angelier, Nicole

2016-01-01

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. PMID:28083117

Decay uncovered in nonverbal short-term memory.

PubMed

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.

Space Age Tools for Effective Water Management: NASA's Contribution Today and Tomorrow

NASA Technical Reports Server (NTRS)

Laymon, Candice R.

2010-01-01

This slide presentation reviews NASA's responses to Earth's hydrological needs as part of the Earth Science Mission. The mission's assets are the 20 operational missions, 6 in development and 5 under study. There is a view of the four space missions that are designed to assist in gathering information about hydrometeorology, explaining briefly what each does. There is also information about the airborne science instruments that also gather information to assist in improving our knowledge of hydrology and improving the short term (i.e., 0-24 hr) weather predictions at regional and local scales.

Meteorological regimes for the classification of aerospace air quality predictions for NASA-Kennedy Space Center

NASA Technical Reports Server (NTRS)

Stephens, J. B.; Sloan, J. C.

1976-01-01

A method is described for developing a statistical air quality assessment for the launch of an aerospace vehicle from the Kennedy Space Center in terms of existing climatological data sets. The procedure can be refined as developing meteorological conditions are identified for use with the NASA-Marshall Space Flight Center Rocket Exhaust Effluent Diffusion (REED) description. Classical climatological regimes for the long range analysis can be narrowed as the synoptic and mesoscale structure is identified. Only broad synoptic regimes are identified at this stage of analysis. As the statistical data matrix is developed, synoptic regimes will be refined in terms of the resulting eigenvectors as applicable to aerospace air quality predictions.

Short-term Action Intentions Overrule Long-Term Semantic Knowledge

ERIC Educational Resources Information Center

van Elk, M.; van Schie, H.T.; Bekkering, H.

2009-01-01

In the present study, we investigated whether the preparation of an unusual action with an object (e.g. bringing a cup towards the eye) could selectively overrule long-term semantic representations. In the first experiment it was found that unusual action intentions activated short-term semantic goal representations, rather than long-term…

Seismic Coupling of Short-Period Wind Noise Through Mars' Regolith for NASA's InSight Lander

NASA Astrophysics Data System (ADS)

Teanby, N. A.; Stevanović, J.; Wookey, J.; Murdoch, N.; Hurley, J.; Myhill, R.; Bowles, N. E.; Calcutt, S. B.; Pike, W. T.

2017-10-01

NASA's InSight lander will deploy a tripod-mounted seismometer package onto the surface of Mars in late 2018. Mars is expected to have lower seismic activity than the Earth, so minimisation of environmental seismic noise will be critical for maximising observations of seismicity and scientific return from the mission. Therefore, the seismometers will be protected by a Wind and Thermal Shield (WTS), also mounted on a tripod. Nevertheless, wind impinging on the WTS will cause vibration noise, which will be transmitted to the seismometers through the regolith (soil). Here we use a 1:1-scale model of the seismometer and WTS, combined with field testing at two analogue sites in Iceland, to determine the transfer coefficient between the two tripods and quantify the proportion of WTS vibration noise transmitted through the regolith to the seismometers. The analogue sites had median grain sizes in the range 0.3-1.0 mm, surface densities of 1.3-1.8 g cm^{-3}, and an effective regolith Young's modulus of 2.5^{+1.9}_{-1.4} MPa. At a seismic frequency of 5 Hz the measured transfer coefficients had values of 0.02-0.04 for the vertical component and 0.01-0.02 for the horizontal component. These values are 3-6 times lower than predicted by elastic theory and imply that at short periods the regolith displays significant anelastic behaviour. This will result in reduced short-period wind noise and increased signal-to-noise. We predict the noise induced by turbulent aerodynamic lift on the WTS at 5 Hz to be ˜2×10^{-10} ms^{-2} Hz^{-1/2} with a factor of 10 uncertainty. This is at least an order of magnitude lower than the InSight short-period seismometer noise floor of 10^{-8} ms^{-2} Hz^{-1/2}.

Design and Delivery of Professional Development Through Partnerships: Long-Term, Short-Term, and Everything In-Between

NASA Astrophysics Data System (ADS)

Urquhart, M. L.; Curry, B.; Hairston, M. R.

2009-12-01

Professional development for teachers can take a variety of forms, each with unique challenges and needs. At the University of Texas at Dallas (UTD), we have leveraged partnerships between multiple groups including the Masters of Arts in Teaching program in Science Education, the joint US Air Force/NASA CINDI mission, an ionospheric explorer built at UTD, and the UTD Regional Collaborative for Excellence in Science Teaching. Each effort models, and in the case of the later two has created, inquiry-based lessons around Earth-systems science. A space science mission, currently in low Earth orbit aboard the Air Force satellite C/NOFS, provides real world connections to classroom science, scientific data and visualizations, and funding to support delivery of professional development in short courses and workshops at teacher conferences. Workshops and short course in turn often serve to recruit teachers into our longer-term programs. Long-term professional development programs such as the Collaborative provide opportunities to test curriculum and teacher learning, an interface to high-quality sustained efforts within talented communities of teachers, and much more. From the birth of our CINDI Educational Outreach program to the Collaborative project that produced geoscience kit-based modules and associated professional development adopted throughout the state of Texas, we will share highlights of our major professional development initiatives and how our partnerships have enabled us to better serve the needs of K-12 teachers expected to deliver geoscience and space science content in their classrooms.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

ERIC Educational Resources Information Center

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?

NASA Astrophysics Data System (ADS)

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.

PubMed

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

NASA Astrophysics Data System (ADS)

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.

PubMed

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.

PubMed

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.

NASA's future Earth observation plans

NASA Astrophysics Data System (ADS)

Neeck, Steven P.; Paules, Granville E.; McCuistion Ramesh, J. D.

2004-11-01

NASA's Science Mission Directorate, working with its domestic and international partners, provides accurate, objective scientific data and analysis to advance our understanding of Earth system processes. Learning more about these processes will enable improved prediction capability for climate, weather, and natural hazards. Earth interactions occur on a continuum of spatial and temporal scales ranging from short-term weather to long-term climate, and from local and regional to global. Quantitatively describing these changes means precisely measuring from space scores of biological and geophysical parameters globally. New missions that SMD will launch in the coming decade will complement the first series of the Earth Observing System. These next generation systematic measurement missions are being planned to extend or enhance the record of science-quality data necessary for understanding and predicting global change. These missions include the NPOESS Preparatory Project, Ocean Surface Topography Mission, Global Precipitation Measurement, Landsat Data Continuity Mission, and an aerosol polarimetry mission called Glory. New small explorer missions will make first of a kind Earth observations. The Orbiting Carbon Observatory will measure sources and sinks of carbon to help the Nation and the world formulate effective strategies to constrain the amount of this greenhouse gas in the atmosphere. Aquarius will measure ocean surface salinity which is key to ocean circulation in the North Atlantic that produces the current era's mild climate in northern Europe. HYDROS will measure soil moisture globally. Soil moisture is critical to agriculture and to managing fresh water resources. NASA continues to design, develop and launch the Nation's civilian operational environmental satellites, in both polar and geostationary orbits, by agreement with the National Oceanic and Atmospheric Administration (NOAA). NASA plans to develop an advanced atmospheric sounder, GIFTS, for

Evaluating NASA Technology Programs in Terms of Private Sector Impacts

NASA Technical Reports Server (NTRS)

Greenberg, J. S.

1984-01-01

NASA is currently developing spacecraft technology for application to NASA scientific missions, military missions and commercial missions which are part of or form the basis of private sector business ventures. The justification of R&D programs that lead to spacecraft technology improvements encompasses the establishment of the benefits in terms of improved scientific knowledge that may result from new and/or improved NASA science missions, improved cost effectiveness of NASA and DOD missions and new or improved services that may be offered by the private sector (for example communications satellite services). It is with the latter of these areas that attention will be focused upon. In particular, it is of interest to establish the economic value of spacecraft technology improvements to private sector communications satellite business ventures. It is proposed to assess the value of spacecraft technology improvements in terms of the changes in cash flow and present value of cash flows, that may result from the use of new and/or improved spacecraft technology for specific types of private sector communications satellite missions (for example domestic point-to-point communication or direct broadcasting). To accomplish this it is necessary to place the new and/or improved technology within typical business scenarios and estimate the impacts of technical performance upon business and financial performance.

The NASA-LeRC wind turbine sound prediction code

NASA Technical Reports Server (NTRS)

Viterna, L. A.

1981-01-01

Since regular operation of the DOE/NASA MOD-1 wind turbine began in October 1979 about 10 nearby households have complained of noise from the machine. Development of the NASA-LeRC with turbine sound prediction code began in May 1980 as part of an effort to understand and reduce the noise generated by MOD-1. Tone sound levels predicted with this code are in generally good agreement with measured data taken in the vicinity MOD-1 wind turbine (less than 2 rotor diameters). Comparison in the far field indicates that propagation effects due to terrain and atmospheric conditions may be amplifying the actual sound levels by about 6 dB. Parametric analysis using the code has shown that the predominant contributions to MOD-1 rotor noise are: (1) the velocity deficit in the wake of the support tower; (2) the high rotor speed; and (3) off column operation.

Short-Term Memory; An Annotated Bibliography. Supplement 1.

ERIC Educational Resources Information Center

Fisher, Dennis F.

A compilation of 165 references dealing with short term memory, this bibliography supplements "Short-Term Memory: An Annotated Bibliography" (August 1968). The time period covered is predominantly June 1968 to June 1969. Such aspects and topics as psychometrics, motivation, human engineering, vision, auditory perception, verbal and nonverbal…

Short- and long-term eating habit modification predicts weight change in overweight, postmenopausal women: results from the WOMAN study.

PubMed

Barone Gibbs, Bethany; Kinzel, Laura S; Pettee Gabriel, Kelley; Chang, Yue-Fang; Kuller, Lewis H

2012-09-01

Standard behavioral obesity treatment produces poor long-term results. Focusing on healthy eating behaviors rather than energy intake may be an alternative strategy. In addition, important behaviors might differ for short- vs long-term weight control. Our aim was to describe and compare associations between changes in eating behaviors and weight after 6 and 48 months. We performed secondary analysis of data collected during a randomized weight-loss intervention trial with 48-month follow-up. We studied 481 overweight and obese postmenopausal women enrolled in the Women on the Move through Activity and Nutrition (WOMAN) Study. We measured changes in weight from baseline to 6 and 48 months. Linear regression models were used to examine the associations between 6- and 48-month changes in eating habits assessed by the Conner Diet Habit Survey and changes in weight. Analyses were conducted in the combined study population and stratified by randomization group. At 6 months in the combined population, weight loss was independently associated with decreased desserts (P<0.001), restaurant eating (P=0.042), sugar-sweetened beverages (P=0.009), and fried foods (P<0.001), and increased fish consumption (P=0.003). Results were similar in intervention participants; only reduced desserts and fried foods associated with weight loss in controls. At 48 months in the combined population, weight loss was again associated with decreased desserts (P=0.003) and sugar-sweetened beverages (P=0.011), but also decreased meats/cheeses (P=0.024) and increased fruits/vegetables (P<0.001). Decreased meats/cheeses predicted weight loss in intervention participants; desserts, sugar-sweetened beverages, and fruits/vegetables were independently associated in controls. Changes in eating behaviors were associated with weight change, although important behaviors differed for short- and long-term weight change and by randomization group. Future studies should determine whether interventions targeting

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

NASA Astrophysics Data System (ADS)

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.

PubMed

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.

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.

PubMed

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 <0.001), old age, male sex, high body mass index, medical comorbidity, total gastrectomy, and combined resection to be independent predictors of postoperative complications. Among these, only low PNI (OR = 4.279, 95% CI = 1.760-10.404, P = 0.001) and medical comorbidity were independent predictors of postoperative mortality. For long-term outcomes, low PNI was a poor prognostic factor for overall survival, but not recurrence (overall survival: hazard ratio [HR] = 1.383, 95% CI = 1.221-1.568, P < 0.001; recurrence-free survival: HR = 1.142, 95% CI = 0.985-1.325, P = 0.078).PNI can be used to predict patients at increased risk of postoperative morbidity and mortality. Although PNI was an independent prognostic factor for overall survival, the index was not associated with cancer recurrence.

Prospective testing of Coulomb short-term earthquake forecasts

NASA Astrophysics Data System (ADS)

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

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

PubMed

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.

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

PubMed Central

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. PMID:27875581

Student Outcomes Associated with Short-Term and Semester Study Abroad Programs

ERIC Educational Resources Information Center

Coker, Jeffrey Scott; Heiser, Evan; Taylor, Laura

2018-01-01

This five-year study of graduating seniors at Elon University (n = 1,858) compared student outcomes measured by the National Survey of Student Engagement across five study abroad groups: no study abroad, semester, short-term (three-week), two short-terms, and semester plus short-term. Both short-term and semester programs were positively…

Complex network structure influences processing in long-term and short-term memory.

PubMed

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

2012-07-01

Complex networks describe how entities in systems interact; the structure of such networks is argued to influence processing. One measure of network structure, clustering coefficient, C, measures the extent to which neighbors of a node are also neighbors of each other. Previous psycholinguistic experiments found that the C of phonological word-forms influenced retrieval from the mental lexicon (that portion of long-term memory dedicated to language) during the on-line recognition and production of spoken words. In the present study we examined how network structure influences other retrieval processes in long- and short-term memory. In a false-memory task-examining long-term memory-participants falsely recognized more words with low- than high-C. In a recognition memory task-examining veridical memories in long-term memory-participants correctly recognized more words with low- than high-C. However, participants in a serial recall task-examining redintegration in short-term memory-recalled lists comprised of high-C words more accurately than lists comprised of low-C words. These results demonstrate that network structure influences cognitive processes associated with several forms of memory including lexical, long-term, and short-term.

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

PubMed Central

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

2014-01-01

Summary Reasons for performing the study There is an important need for objective parameters that accurately predict the outcome of horses with large colon volvulus. Objectives 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. Study Design Retrospective cohort study Methods Adult horses admitted to the Equine and Farm Animal Veterinary Center at North Carolina State University, Peterson & Smith and Chino Valley Equine Hospitals between 2006–2013 undergoing an exploratory celiotomy, 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 interstitial: 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). Results 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), interstitial: crypt ratio >1 (P = 0.02) and haemorrhage score ≥3 (P = 0.005). Resection (P = 0.92) was not found to be significantly associated with short-term outcome. No combined factors increased the likelihood of death in forward stepwise logistic regression modelling. A digitally quantified haemorrhage area measurement strengthened the association of haemorrhage with non-survival in cases of large colon volvulus. Conclusions Histomorphometric measurements of interstitial: 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

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

ERIC Educational Resources Information Center

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.

PubMed

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).

NASA's Earth Science Research and Environmental Predictions

NASA Technical Reports Server (NTRS)

Hilsenrath, E.

2004-01-01

NASA Earth Science program began in the 1960s with cloud imaging satellites used for weather observations. A fleet of satellites are now in orbit to investigate the Earth Science System to uncover the connections between land, Oceans and the atmosphere. Satellite systems using an array of active and passive remote sensors are used to search for answers on how is the Earth changing and what are the consequences for life on Earth? The answer to these questions can be used for applications to serve societal needs and contribute to decision support systems for weather, hazard, and air quality predictions and mitigation of adverse effects. Partnerships with operational agencies using NASA's observational capabilities are now being explored. The system of the future will require new technology, data assimilation systems which includes data and models that will be used for forecasts that respond to user needs.

Predicting short-term positive affect in individuals with social anxiety disorder: The role of selected personality traits and emotion regulation strategies.

PubMed

Weisman, Jaclyn S; Rodebaugh, Thomas L; Lim, Michelle H; Fernandez, Katya C

2015-08-01

Recently, research has provided support for a moderate, inverse relationship between social anxiety and dispositional positive affect. However, the dynamics of this relationship remain poorly understood. The present study evaluates whether certain personality traits and emotion regulation variables predict short-term positive affect for individuals with social anxiety disorder and healthy controls. Positive affect as measured by two self-report instruments was assessed before and after two tasks in which the participant conversed with either a friend or a romantic partner. Tests of models examining the hypothesized prospective predictors revealed that the paths did not differ significantly across diagnostic group and both groups showed the hypothesized patterns of endorsement for the emotion regulation variables. Further, a variable reflecting difficulty redirecting oneself when distressed prospectively predicted one measure of positive affect. Additional research is needed to explore further the role of emotion regulation strategies on positive emotions for individuals higher in social anxiety. Copyright © 2015 Elsevier Ltd. All rights reserved.

Predictors of short-term and long-term incontinence after robot-assisted radical prostatectomy.

PubMed

Shao, I-Hung; Chang, Ying-Hsu; Hou, Chun-Ming; Lin, Zheng-Feng; Wu, Chun-Te

2018-01-01

Purpose To determine retrospectively the prognostic factors for urinary incontinence following robot-assisted radical prostatectomy (RARP). Methods Altogether, 180 patients with localized prostate cancer underwent RARP (same surgeon). Preoperative physical status, disease characteristics, laboratory findings, and surgical technique were recorded and the patients checked 1, 6, 12, and 24 months after RARP regarding their contribution to predicting post-prostatectomy urinary incontinence (PPI). Results Overall, 114 (63.3%) patients had PPI 1 month after RARP and 19 patients (16.0%) at 24 months. Univariate analysis showed that age was a significant factor for predicting PPI at 1 month. PPI predictors at 24 months were age, body mass index, preoperative serum albumin level, previous transurethral resection of the prostate, total operative time, and bladder neck sparing. Multivariate analysis indicated that age and total operative time were significant predictors. Conclusion Older age and longer operative time were highly relevant to short- and long-term PPI occurrence after RARP.

Long-Term Durability Analysis of a 100,000+ Hr Stirling Power Convertor Heater Head

NASA Technical Reports Server (NTRS)

Bartolotta, Paul A.; Bowman, Randy R.; Krause, David L.; Halford, Gary R.

2000-01-01

DOE and NASA have identified Stirling Radioisotope Power Systems (SRPS) as the power supply for deep space exploration missions the Europa Orbiter and Solar Probe. As a part of this effort, NASA has initiated a long-term durability project for critical hot section components of the Stirling power convertor to qualify flight hardware. This project will develop a life prediction methodology that utilizes short-term (t < 20,000 hr) test data to verify long-term (t > 100,000 hr) design life. The project consists of generating a materials database for the specific heat of alloy, evaluation of critical hermetic sealed joints, life model characterization, and model verification. This paper will describe the qualification methodology being developed and provide a status for this effort.

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

PubMed

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.

A prediction of 3-D viscous flow and performance of the NASA Low-Speed Centrifugal Compressor

NASA Technical Reports Server (NTRS)

Moore, John; Moore, Joan G.

1990-01-01

A prediction of the three-dimensional turbulent flow in the NASA Low-Speed Centrifugal Compressor Impeller has been made. The calculation was made for the compressor design conditions with the specified uniform tip clearance gap. The predicted performance is significantly worse than that predicted in the NASA design study. This is explained by the high tip leakage flow in the present calculation and by the different model adopted for tip leakage flow mixing. The calculation gives an accumulation of high losses in the shroud/pressure-side quadrant near the exit of the impeller. It also predicts a region of meridional backflow near the shroud wall. Both of these flow features should be extensive enough in the NASA impeller to allow detailed flow measurements, leading to improved flow modeling. Recommendations are made for future flow studies in the NASA impeller.

A prediction of 3-D viscous flow and performance of the NASA low-speed centrifugal compressor

NASA Technical Reports Server (NTRS)

Moore, John; Moore, Joan G.

1989-01-01

A prediction of the 3-D turbulent flow in the NASA Low-Speed Centrifugal Compressor Impeller has been made. The calculation was made for the compressor design conditions with the specified uniform tip clearance gap. The predicted performance is significantly worse than that predicted in the NASA design study. This is explained by the high tip leakage flow in the present calculation and by the different model adopted for tip leakage flow mixing. The calculation gives an accumulation for high losses in the shroud/pressure-side quadrant near the exit of the impeller. It also predicts a region of meridional backflow near the shroud wall. Both of these flow features should be extensive enough in the NASA impeller to allow detailed flow measurements, leading to improved flow modelling. Recommendations are made for future flow studies in the NASA impeller.

An autoregressive integrated moving average model for short-term prediction of hepatitis C virus seropositivity among male volunteer blood donors in Karachi, Pakistan

PubMed Central

Akhtar, Saeed; Rozi, Shafquat

2009-01-01

AIM: To identify the stochastic autoregressive integrated moving average (ARIMA) model for short term forecasting of hepatitis C virus (HCV) seropositivity among volunteer blood donors in Karachi, Pakistan. METHODS: Ninety-six months (1998-2005) data on HCV seropositive cases (1000-1 × month-1) among male volunteer blood donors tested at four major blood banks in Karachi, Pakistan were subjected to ARIMA modeling. Subsequently, a fitted ARIMA model was used to forecast HCV seropositive donors for 91-96 mo to contrast with observed series of the same months. To assess the forecast accuracy, the mean absolute error rate (%) between the observed and predicted HCV seroprevalence was calculated. Finally, a fitted ARIMA model was used for short-term forecasts beyond the observed series. RESULTS: The goodness-of-fit test of the optimum ARIMA (2,1,7) model showed non-significant autocorrelations in the residuals of the model. The forecasts by ARIMA for 91-96 mo closely followed the pattern of observed series for the same months, with mean monthly absolute forecast errors (%) over 6 mo of 6.5%. The short-term forecasts beyond the observed series adequately captured the pattern in the data and showed increasing tendency of HCV seropositivity with a mean ± SD HCV seroprevalence (1000-1 × month-1) of 24.3 ± 1.4 over the forecast interval. CONCLUSION: To curtail HCV spread, public health authorities need to educate communities and health care providers about HCV transmission routes based on known HCV epidemiology in Pakistan and its neighboring countries. Future research may focus on factors associated with hyperendemic levels of HCV infection. PMID:19340903

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

PubMed

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.

How emotional pictures influence visuospatial binding in short-term memory in ageing and Alzheimer's disease?

PubMed

Borg, Céline; Leroy, Nicolas; Favre, Emilie; Laurent, Bernard; Thomas-Antérion, Catherine

2011-06-01

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 short-term memory in ageing and Alzheimer's disease (AD). Fourteen patients with mild AD, 14 healthy older participants (NC), and 14 younger adults (YA) performed two tasks. In the first task, involving visual short-term memory, participants were asked to remember a picture among four different pictures (negative or neutral) following a brief delay. The second task, a binding memory task, required the recognition by participants of a picture according to its spatial location. The attentional cost involved was higher than for the first task. The pattern of results showed that visual memory performance was better for negative stimuli than for neutral ones, irrespective of the group. In contrast, binding memory performance was essentially poorer for the location of negative pictures in the NC group, and for the location of both negative and neutral stimuli in the AD group, in comparison to the YA group. Taken together, these results show that emotion has beneficial effects on visual short-term memory in ageing and AD. In contrast, emotion does not improve their performances in the binding condition. Copyright © 2011 Elsevier Inc. All rights reserved.

Short and Long-Term Sunlight Radiation and Stroke Incidence

PubMed Central

McClure, Leslie A.; Judd, Suzanne E.; Howard, Virginia J.; Crosson, William L.; Al-Hamdan, Mohammad Z.; Wadley, Virginia G.; Peace, Fredrick; Kabagambe, Edmond K.

2012-01-01

OBJECTIVE Examine whether long and short-term sunlight radiation is related to stroke incidence. METHODS Fifteen-year residential histories merged with satellite, ground monitor, and model reanalysis data were used to determine sunlight radiation (insolation) and temperature exposure for a cohort of 16,606 stroke and coronary artery disease free black and white participants aged 45+ from the 48 contiguous United States. Fifteen, ten, five, two and one-year exposures were used to predict stroke incidence during follow-up in Cox proportional hazard models. Potential confounders and mediators were included during model-building. RESULTS Shorter exposure periods exhibited similar, but slightly stronger relationships than longer exposure periods. After adjustment for other covariates, the previous year’s monthly average insolation exposure below the median gave an HR=1.61 (95% CI: 1.15, 2.26) and the previous year’s highest compared to the second highest quartile of monthly average maximum temperature exposure gave an HR=1.92 (1.27, 2.92). INTERPRETATION These results indicate a relationship between lower levels of sunlight radiation and higher stroke incidence. The biological pathway of this relationship is not clear. Future research will show whether this finding stands, the pathway for this relationship, and if it is due to short or long-term exposures. PMID:23225379

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

PubMed

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

Recent Upgrades to NASA SPoRT Initialization Datasets for the Environmental Modeling System

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Lafontaine, Frank J.; Molthan, Andrew L.; Zavodsky, Bradley T.; Rozumalski, Robert A.

2012-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its NOAA/National Weather Service (NWS) partners that can initialize specific fields for local model runs within the NOAA/NWS Science and Training Resource Center Environmental Modeling System (EMS). The suite of SPoRT products for use in the EMS consists of a Sea Surface Temperature (SST) composite that includes a Lake Surface Temperature (LST) analysis over the Great Lakes, a Great Lakes sea-ice extent within the SST composite, a real-time Green Vegetation Fraction (GVF) composite, and NASA Land Information System (LIS) gridded output. This paper and companion poster describe each dataset and provide recent upgrades made to the SST, Great Lakes LST, GVF composites, and the real-time LIS runs.

Robust short-term memory without synaptic learning.

PubMed

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.

A COMPARISON OF WINTER SHORT-TERM AND ANNUAL AVERAGE RADON MEASUREMENTS IN BASEMENTS OF A RADON-PRONE REGION AND EVALUATION OF FURTHER RADON TESTING INDICATORS

PubMed Central

Barros, Nirmalla G.; Steck, Daniel J.; Field, R. William

2014-01-01

The primary objective of this study was to investigate the temporal variability between basement winter short-term (7 to 10 days) and basement annual radon measurements. Other objectives were to test the short-term measurement’s diagnostic performance at two reference levels and to evaluate its ability to predict annual average basement radon concentrations. Electret ion chamber (short-term) and alpha track (annual) radon measurements were obtained by trained personnel in Iowa residences. Overall, the geometric mean of the short-term radon concentrations (199 Bq m−3) was slightly greater than the geometric mean of the annual radon concentrations (181 Bq m−3). Short-term tests incorrectly predicted that the basement annual radon concentrations would be below 148 Bq m−3 12% of the time and 2% of the time at 74 Bq m−3. The short-term and annual radon concentrations were strongly correlated (r=0.87, p<0.0001). The foundation wall material of the basement was the only significant factor to have an impact on the absolute difference between the short-term and annual measurements. The findings from this study provide evidence of a substantially lower likelihood of obtaining a false negative result from a single short-term test in a region with high indoor radon potential when the reference level is lowered to 74 Bq m−3. PMID:24670901

Use of short-term toxicity data for prediction of long-term health effects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hartley, W.R.; Ohanian, E.V.

1988-01-01

Under the Safe Drinking Water Act Amendments of 1986, the US Environmental Protection Agency determines Maximum Contaminant Level Goals (MCLGs) and enforceable Maximum Contaminant Levels (MCLs) or provides lifetime health advisories (HAs) in the absence of regulatory standards. The critical value for calculation of the lifetime level is the reference dose (RfD). The RfD is an estimate of a lifetime dose which is likely to be without significant risk to human populations. The RfD is determined by dividing the no-observed-adverse-effect level (NOAEL) or the lowest-observed-adverse-effect level (LOAEL) by an uncertainty factor (UF). The NOAEL or LOAEL is determined from toxicologicalmore » or epidemiological studies. For many chemicals, human toxicological or epidemiological data are not available. Chronic mammalian studies are sometimes unavailable. Faced with the need for providing guidance for the increasing number of chemicals threatening our drinking water sources, this paper considers the possibility of providing provisional RfDs using data from toxicological studies of less than ninety days duration. The current UF approach is reviewed along with some proposed mathematical models for extrapolation of NOAELs from dose-response data. The current UF approach to developing the RfD is protective and conservative. More research is needed on the relationship of short- and long-term toxicity data to improve our current approach.« less

Improvement of short-term numerical wind predictions

NASA Astrophysics Data System (ADS)

Bedard, Joel

Geophysic Model Output Statistics (GMOS) are developed to optimize the use of NWP for complex sites. GMOS differs from other MOS that are widely used by meteorological centers in the following aspects: it takes into account the surrounding geophysical parameters such as surface roughness, terrain height, etc., along with wind direction; it can be directly applied without any training, although training will further improve the results. The GMOS was applied to improve the Environment Canada GEM-LAM 2.5km forecasts at North Cape (PEI, Canada): It improves the predictions RMSE by 25-30% for all time horizons and almost all meteorological conditions; the topographic signature of the forecast error due to insufficient grid refinement is eliminated and the NWP combined with GMOS outperform the persistence from a 2h horizon, instead of 4h without GMOS. Finally, GMOS was applied at another site (Bouctouche, NB, Canada): similar improvements were observed, thus showing its general applicability. Keywords: wind energy, wind power forecast, numerical weather prediction, complex sites, model output statistics

Effect of local cooling on short-term, intense exercise.

PubMed

Kwon, Young S; Robergs, Robert A; Schneider, Suzanne M

2013-07-01

The widespread belief that local cooling impairs short-term, strenuous exercise performance is controversial. Eighteen original investigations involving cooling before and intermittent cooling during short-term, intensive exercise are summarized in this review. Previous literature examining short-term intensive exercise and local cooling primarily has been limited to the effects on muscle performance immediately or within minutes following cold application. Most previous cooling studies used equal and longer than 10 minutes of pre-cooling, and found that cooling reduced strength, performance and endurance. Because short duration, high intensity exercise requires adequate warm-up to prepare for optimal performance, prolonged pre-cooling is not an effective method to prepare for this type of exercise. The literature related to the effect of acute local cooling immediately before short duration, high intensity isotonic exercise such as weight lifting is limited. However, local intermittent cooling during short-term, high intense exercise may provide possible beneficial effects; first, by pain reduction, caused by an "irritation effect" from hand thermal receptors which block pain sensation, or second, by a cooling effect, whereby stimulation of hand thermal receptors or a slight lowering of blood temperature might alter central fatigue.

NASA Acting Deputy Chief Technologist Briefed on Operation of Sonic Boom Prediction Algorithms

NASA Image and Video Library

2017-08-29

NASA Acting Deputy Chief Technologist Vicki Crips being briefed by Tim Cox, Controls Engineer at NASA’s Armstrong Flight Research Center at Edwards, California, on the operation of the sonic boom prediction algorithms being used in engineering simulation for the NASA Supersonic Quest program.

Portable positive protection : a guide for short duration and short term work zones.

DOT National Transportation Integrated Search

2016-06-01

Transportation agencies, contractors, researchers, and private vendors are actively looking for new methods and devices : to help make construction and maintenance work zones safer while maximizing mobility. Short-term and short-duration : work zones...

Predicting Long-term Temperature Increase for Time-Dependent SAR Levels with a Single Short-term Temperature Response

PubMed Central

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

2015-01-01

Purpose 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). Methods 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. Results 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. Conclusion With appropriate methods, it is possible to rapidly predict temperature increase throughout the body for actual MR examinations. (200/200 words) PMID:26096947

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

PubMed

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 versus long-term administration of single prophylactic antibiotic in elective gastric tumor surgery.

PubMed

Wang, Fang; Chen, Xin-Zu; Liu, Jie; Yang, Kun; Zhang, Bo; Chen, Zhi-Xin; Chen, Jia-Ping; Hu, Jian-Kun; Zhou, Zong-Guang; Mo, Xian-Min; Mo, Xian-Min

2012-09-01

To evaluate short-term versus long-term single prophylactic antibiotic for elective gastric tumor surgery. Patients in a single surgical team undergoing elective gastric tumor surgery were enrolled from November 2009 to December 2010. The included patients were aged from 18 to 70 years without conditions as severe comorbidity, preoperative infectious diseases, antibiotic administration 48 h before surgery, exploratory laparotomy only or combined colorectal resection, neoadjuvant chemotherapy, or steroid administration before surgery. The overall and infection-related postoperative complications and also economic outcomes were analyzed. The software SPSS 17.0 and TreeAge Pro 2007 were used for statistics. Patients (n=158 (45 vs. 113)) were enrolled in short-term and long-term groups. No death cases occurred. Overall postoperative complication rates were 8.9% and 8.0%, respectively (p=1.000). The rates of infection related complications were 8.9% and 4.4%, respectively (p=0.231). No surgical site infection (SSI) occurred in the short-term group, whereas SSI was 1.8% in the long-term group. Total hospitalization cost (THC) of short-term branch was 36,557RMB per patients and preferable against 39,523RMB of long-term branch. Incremental cost-effectiveness analysis showed there was a 10 times interval between the extra healthcare expenditure of benefit and harm. Short-term administration did not increase the risk of postoperative complications and was more cost-effective.

Summary and recommendations for the NASA/MIT workshop on short haul air transport

NASA Technical Reports Server (NTRS)

Simpson, R. W.

1971-01-01

The material is summarized that was covered by the MIT/NASA Waterville Valley workshop which dealt with the institutional, socio-economic, operational and technological problems associated with introducing new forms of short haul domestic air transportation. It was found that future air systems hold great potential in satisfying society's needs for a low noise, low landspace, high access, high speed, large network system for public travel over distances between 5 and 500 miles. It is concluded that quiet air systems are necessary for obtaining community approval, and is recommended that extremely high priority be assigned to the development of quiet aircraft for future short haul air systems.

Oxygenate Supply/Demand Balances in the Short-Term Integrated Forecasting Model (Short-Term Energy Outlook Supplement March 1998)

EIA Publications

1998-01-01

The blending of oxygenates, such as fuel ethanol and methyl tertiary butyl ether (MTBE), into motor gasoline has increased dramatically in the last few years because of the oxygenated and reformulated gasoline programs. Because of the significant role oxygenates now have in petroleum product markets, the Short-Term Integrated Forecasting System (STIFS) was revised to include supply and demand balances for fuel ethanol and MTBE. The STIFS model is used for producing forecasts in the Short-Term Energy Outlook. A review of the historical data sources and forecasting methodology for oxygenate production, imports, inventories, and demand is presented in this report.

Short-term load forecasting of power system

NASA Astrophysics Data System (ADS)

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.

A Global Perspective: NASA's Prediction of Worldwide Energy Resources (POWER) Project

NASA Technical Reports Server (NTRS)

Zhang, Taiping; Stackhouse, Paul W., Jr.; Chandler, William S.; Hoell, James M.; Westberg, David; Whitlock, Charles H.

2007-01-01

The Prediction of the Worldwide Energy Resources (POWER) Project, initiated under the NASA Science Mission Directorate Applied Science Energy Management Program, synthesizes and analyzes data on a global scale that are invaluable to the renewable energy industries, especially to the solar and wind energy sectors. The POWER project derives its data primarily from NASA's World Climate Research Programme (WCRP)/Global Energy and Water cycle Experiment (GEWEX) Surface Radiation Budget (SRB) project (Version 2.9) and the Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS) assimilation model (Version 4). The latest development of the NASA POWER Project and its plans for the future are presented in this paper.

Short- and long-term eating habit modification predict weight change in overweight, post-menopausal women: results from the WOMAN Study

PubMed Central

Gibbs, Bethany Barone; Kinzel, Laura S.; Gabriel, Kelley Pettee; Chang, Yue-fang; Kuller, Lewis H.

2012-01-01

Background Standard behavioral obesity treatment produces poor long-term results. Focusing on healthy eating behaviors, rather than caloric intake, may be an alternative strategy. Furthermore, important behaviors might differ for short- vs. long-term weight control. Objective To describe and compare associations between changes in eating behaviors and weight after 6 and 48 months Design Secondary analysis of data collected during a randomized weight loss intervention trial with 48-month follow-up Participants 465 overweight and obese postmenopausal women enrolled in the Women on the Move through Activity and Nutrition (WOMAN) Study Main outcome measures Changes in weight from baseline to 6 and 48 months. Statistical analyses performed Linear regression models examined the associations between 6- and 48-month changes in eating habits assessed by the Conner Diet Habit Survey and changes in weight. Analyses were conducted in the combined study population and stratified by randomization group. Results At 6 months in the combined population, weight loss was independently associated with decreased desserts (p<0.001), restaurant eating (p=0.042), sugar-sweetened beverages (p=0.009), and fried foods (p<0.001), and increased fish consumption (p=0.003). Results were similar in intervention participants; only reduced desserts and fried foods associated with weight loss in controls. At 48 months in the combined population, weight loss was again associated with decreased desserts (p=0.003) and sugar-sweetened beverages (p=0.011), but also decreased meats/cheeses (p=0.024) and increased fruits/vegetables (p<0.001). Decreased meats/cheeses predicted weight loss in intervention participants; desserts, sugar-sweetened beverages, and fruits/vegetables were independently associated in controls. Conclusions Changes in eating behaviors were associated with weight change, though important behaviors differed for short- and long-term weight change and by randomization group. Future

A short-term and long-term comparison of root coverage with an acellular dermal matrix and a subepithelial graft.

PubMed

Harris, Randall J

2004-05-01

Obtaining predictable and esthetic root coverage has become important. Unfortunately, there is only a limited amount of information available on the long-term results of root coverage procedures. The goal of this study was to evaluate the short-term and long-term root coverage results obtained with an acellular dermal matrix and a subepithelial graft. An a priori power analysis was done to determine that 25 was an adequate sample size for each group in this study. Twenty-five patients treated with either an acellular dermal matrix or a subepithelial graft for root coverage were included in this study. The short-term (mean 12.3 to 13.2 weeks) and long-term (mean 48.1 to 49.2 months) results were compared. Additionally, various factors were evaluated to determine whether they could affect the results. This study was a retrospective study of patients in a fee-for-service private periodontal practice. The patients were not randomly assigned to treatment groups. The mean root coverages for the short-term acellular dermal matrix (93.4%), short-term subepithelial graft (96.6%), and long-term subepithelial graft (97.0%) were statistically similar. All three were statistically greater than the long-term acellular dermal matrix mean root coverage (65.8%). Similar results were noted in the change in recession. There were smaller probing reductions and less of an increase in keratinized tissue with the acellular dermal matrix than the subepithelial graft. None of the factors evaluated resulted in the acellular dermal graft having a statistically significant better result than the subepithelial graft. However, in long-term cases where multiple defects were treated with an acellular dermal matrix, the mean root coverage (70.8%) was greater than the mean root coverage in long-term cases where a single defect was treated with an acellular dermal matrix (50.0%). The mean results with the subepithelial graft held up with time better than the mean results with an acellular dermal

Resting State Synchrony in Short-Term versus Long-Term Abstinent Alcoholics

PubMed Central

Camchong, Jazmin; Stenger, Victor Andrew; Fein, George

2012-01-01

BACKGROUND We previously reported that when compared to controls, long-term abstinent alcoholics (LTAA) have increased resting state synchrony (RSS) of the inhibitory control network and reduced synchrony of the appetitive drive network, and hypothesized that these levels of synchrony are adaptive, and support the behavioral changes required to maintain abstinence. In the current study, we investigate whether these RSS patterns can be identified in short-term abstinent alcoholics. METHODS Resting state functional magnetic resonance imaging data were collected from 27 short-term abstinent alcoholics (STAA), 23 LTAA and 23 non-substance abusing controls (NSAC). We examined baseline RSS using seed-based measures. RESULTS We found ordered RSS effects from NSAC to STAA and then to LTAA within both the appetitive drive and executive control networks: increasing RSS of the executive control network, and decreasing RSS of the reward processing network. Finally, we found significant correlations between strength of RSS in these networks and (a) cognitive flexibility and (b) current antisocial behavior. DISCUSSION Findings are consistent with an adaptive progression of RSS from short- to long-term abstinence so that, compared to normal controls, the synchrony (a) within the reward network progressively decreases and (b) within the executive control network progressively increases. PMID:23421812

Analysis Methods for Post Occupancy Evaluation of Energy-Use in High Performance Buildings Using Short-Term Monitoring

NASA Astrophysics Data System (ADS)

Singh, Vipul

2011-12-01

The green building movement has been an effective catalyst in reducing energy demands of buildings and a large number of 'green' certified buildings have been in operation for several years. Whether these buildings are actually performing as intended, and if not, identifying specific causes for this discrepancy falls into the general realm of post-occupancy evaluation (POE). POE involves evaluating building performance in terms of energy-use, indoor environmental quality, acoustics and water-use; the first aspect i.e. energy-use is addressed in this thesis. Normally, a full year or more of energy-use and weather data is required to determine the actual post-occupancy energy-use of buildings. In many cases, either measured building performance data is not available or the time and cost implications may not make it feasible to invest in monitoring the building for a whole year. Knowledge about the minimum amount of measured data needed to accurately capture the behavior of the building over the entire year can be immensely beneficial. This research identifies simple modeling techniques to determine best time of the year to begin in-situ monitoring of building energy-use, and the least amount of data required for generating acceptable long-term predictions. Four analysis procedures are studied. The short-term monitoring for long-term prediction (SMLP) approach and dry-bulb temperature analysis (DBTA) approach allow determining the best time and duration of the year for in-situ monitoring to be performed based only on the ambient temperature data of the location. Multivariate change-point (MCP) modeling uses simulated/monitored data to determine best monitoring period of the year. This is also used to validate the SMLP and DBTA approaches. The hybrid inverse modeling method-1 predicts energy-use by combining a short dataset of monitored internal loads with a year of utility-bills, and hybrid inverse method-2 predicts long term building performance using utility

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

PubMed

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.

Economic efficiency of short-term versus long-term water rights buyouts

USDA-ARS?s Scientific Manuscript database

Because of the decline of the Ogallala Aquifer, water districts, regional water managers, and state water officers are becoming increasingly interested in conservation policies. This study evaluates both short-term and long-term water rights buyout policies. This research develops dynamic production...

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

PubMed

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.

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

PubMed

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.

Impaired short-term memory for pitch in congenital amusia.

PubMed

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.

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

PubMed

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 < 0.01) and HC (median 0.80%, interquartile range 0.67-1.27%; P < 0.01). In acute-on-chronic hepatitis B liver failure group, nonsurvivors showed significantly higher GSTP1 methylation levels (P < 0.05) than survivors. GSTP1 methylation level was significantly correlated with total bilirubin (r = 0.29, P < 0.01), prothrombin time activity (r = -0.24, P = 0.01) and model for end-stage liver disease (MELD) score (r = 0.26, P = 0.01). When used to predict 1- or 2-month mortality of acute-on-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 < 0.01; AUC 0.83 vs. 0.70, P < 0.05 respectively]. Meanwhile, patients with GSTP1 methylation levels above the cut-off points showed significantly poorer survival than those below (P < 0.05). Aberrant GSTP1 promoter methylation exists in acute-on-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

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

NASA Astrophysics Data System (ADS)

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

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

PubMed

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.

PubMed

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.

Proposal for a New Predictive Model of Short-Term Mortality After Living Donor Liver Transplantation due to Acute Liver Failure.

PubMed

Chung, Hyun Sik; Lee, Yu Jung; Jo, Yun Sung

2017-02-21

BACKGROUND Acute liver failure (ALF) is known to be a rapidly progressive and fatal disease. Various models which could help to estimate the post-transplant outcome for ALF have been developed; however, none of them have been proved to be the definitive predictive model of accuracy. We suggest a new predictive model, and investigated which model has the highest predictive accuracy for the short-term outcome in patients who underwent living donor liver transplantation (LDLT) due to ALF. MATERIAL AND METHODS Data from a total 88 patients were collected retrospectively. King's College Hospital criteria (KCH), Child-Turcotte-Pugh (CTP) classification, and model for end-stage liver disease (MELD) score were calculated. Univariate analysis was performed, and then multivariate statistical adjustment for preoperative variables of ALF prognosis was performed. A new predictive model was developed, called the MELD conjugated serum phosphorus model (MELD-p). The individual diagnostic accuracy and cut-off value of models in predicting 3-month post-transplant mortality were evaluated using the area under the receiver operating characteristic curve (AUC). The difference in AUC between MELD-p and the other models was analyzed. The diagnostic improvement in MELD-p was assessed using the net reclassification improvement (NRI) and integrated discrimination improvement (IDI). RESULTS The MELD-p and MELD scores had high predictive accuracy (AUC >0.9). KCH and serum phosphorus had an acceptable predictive ability (AUC >0.7). The CTP classification failed to show discriminative accuracy in predicting 3-month post-transplant mortality. The difference in AUC between MELD-p and the other models had statistically significant associations with CTP and KCH. The cut-off value of MELD-p was 3.98 for predicting 3-month post-transplant mortality. The NRI was 9.9% and the IDI was 2.9%. CONCLUSIONS MELD-p score can predict 3-month post-transplant mortality better than other scoring systems after

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

PubMed

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

2012-01-01

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

Short-term variability in body weight predicts long-term weight gain.

PubMed

Lowe, Michael R; Feig, Emily H; Winter, Samantha R; Stice, Eric

2015-11-01

Body weight in lower animals and humans is highly stable despite a very large flux in energy intake and expenditure over time. Conversely, the existence of higher-than-average variability in weight may indicate a disruption in the mechanisms responsible for homeostatic weight regulation. In a sample chosen for weight-gain proneness, we evaluated whether weight variability over a 6-mo period predicted subsequent weight change from 6 to 24 mo. A total of 171 nonobese women were recruited to participate in this longitudinal study in which weight was measured 4 times over 24 mo. The initial 3 weights were used to calculate weight variability with the use of a root mean square error approach to assess fluctuations in weight independent of trajectory. Linear regression analysis was used to examine whether weight variability in the initial 6 mo predicted weight change 18 mo later. Greater weight variability significantly predicted amount of weight gained. This result was unchanged after control for baseline body mass index (BMI) and BMI change from baseline to 6 mo and for measures of disinhibition, restrained eating, and dieting. Elevated weight variability in young women may signal the degradation of body weight regulatory systems. In an obesogenic environment this may eventuate in accelerated weight gain, particularly in those with a genetic susceptibility toward overweight. Future research is needed to evaluate the reliability of weight variability as a predictor of future weight gain and the sources of its predictive effect. The trial on which this study is based is registered at clinicaltrials.gov as NCT00456131. © 2015 American Society for Nutrition.

Estimating long-term multivariate progression from short-term data.

PubMed

Donohue, Michael C; Jacqmin-Gadda, Hélène; Le Goff, Mélanie; Thomas, Ronald G; Raman, Rema; Gamst, Anthony C; Beckett, Laurel A; Jack, Clifford R; Weiner, Michael W; Dartigues, Jean-François; Aisen, Paul S

2014-10-01

Diseases that progress slowly are often studied by observing cohorts at different stages of disease for short periods of time. The Alzheimer's Disease Neuroimaging Initiative (ADNI) follows elders with various degrees of cognitive impairment, from normal to impaired. The study includes a rich panel of novel cognitive tests, biomarkers, and brain images collected every 6 months for as long as 6 years. The relative timing of the observations with respect to disease pathology is unknown. We propose a general semiparametric model and iterative estimation procedure to estimate simultaneously the pathological timing and long-term growth curves. The resulting estimates of long-term progression are fine-tuned using cognitive trajectories derived from the long-term "Personnes Agées Quid" study. We demonstrate with simulations that the method can recover long-term disease trends from short-term observations. The method also estimates temporal ordering of individuals with respect to disease pathology, providing subject-specific prognostic estimates of the time until onset of symptoms. When the method is applied to ADNI data, the estimated growth curves are in general agreement with prevailing theories of the Alzheimer's disease cascade. Other data sets with common outcome measures can be combined using the proposed algorithm. Software to fit the model and reproduce results with the statistical software R is available as the grace package. ADNI data can be downloaded from the Laboratory of NeuroImaging. Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

47 CFR 1.9035 - Short-term de facto transfer leasing arrangements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 1 2011-10-01 2011-10-01 false Short-term de facto transfer leasing... PROCEDURE Spectrum Leasing General Policies and Procedures § 1.9035 Short-term de facto transfer leasing...) and a spectrum lessee may enter into a short-term de facto transfer leasing arrangement in which the...

Predicting the short-term risk of diabetes in HIV-positive patients: the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study

PubMed Central

Petoumenos, Kathy; Worm, Signe W; Fontas, Eric; Weber, Rainer; De Wit, Stephane; Bruyand, Mathias; Reiss, Peter; El-Sadr, Wafaa; Monforte, Antonella D'Arminio; Friis-Møller, Nina; Lundgren, Jens D; Law, Matthew G

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 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-positive populations and to compare the existing models developed in the general population. Methods All patients recruited to the Data Collection on Adverse events of Anti-HIV Drugs (D:A:D) study with follow-up data, without prior DM, myocardial infarction or other CVD events and with a complete DM risk factor profile were included. Conventional risk factors identified in the general population as well as key HIV-related factors were assessed using Poisson-regression methods. Expected probabilities of DM events were also determined based on the Framingham Offspring Study DM equation. The D:A:D and Framingham equations were then assessed using an internal-external validation process; area under the receiver operating characteristic (AUROC) curve and predicted DM events were determined. Results Of 33,308 patients, 16,632 (50%) patients were included, with 376 cases of new onset DM during 89,469 person-years (PY). 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<200 cells/µL and lipodystrophy were predictive of new onset DM. The mean performance of the D:A:D and Framingham equations yielded AUROC of 0.894 (95% CI: 0.849, 0.940) and 0.877 (95% CI: 0.823, 0.932), respectively. The Framingham equation over-predicted DM events compared to D:A:D for lower glucose and lower

A Long-Term Predictive Validity Study: Can the CDI Short Form be Used to Predict Language and Early Literacy Skills Four Years Later?

ERIC Educational Resources Information Center

Can, Dilara Deniz; Ginsburg-Block, Marika; Golinkoff, Roberta Michnick; Hirsh-Pasek, Kathryn

2013-01-01

This longitudinal study examined the predictive validity of the MacArthur Communicative Developmental Inventories-Short Form (CDI-SF), a parent report questionnaire about children's language development (Fenson, Pethick, Renda, Cox, Dale & Reznick, 2000). Data were first gathered from parents on the CDI-SF vocabulary scores for seventy-six…

Retention interval affects visual short-term memory encoding.

PubMed

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

NASA Astrophysics Data System (ADS)

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.

ERIC Educational Resources Information Center

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…

Daily reports of intimate partner verbal aggression by self and partner: Short-term consequences and implications for measurement.

PubMed

Derrick, Jaye L; Testa, Maria; Leonard, Kenneth E

2014-10-01

Agreement within couples regarding the occurrence of aggression is surprisingly low. Survey research often collapses across partners' reports to create a pooled estimate of aggression in the relationship. This method ignores possible differences in partners' perceptions of the event, potentially weakening researchers' ability to detect consequences of aggression. The current study examines both partners' reports of verbal aggression to determine whether aggression reported by only one partner influences both partners' short-term outcomes. We used a 56-day daily diary to examine the effect of verbal aggression on short-term negative outcomes. We examined whether aggression reported by either partner is sufficient to predict consequences for both partners, or if an individual must report aggression to experience consequences. Victims' reports of receiving verbal aggression were a better predictor of next day victim consequences than perpetrators' reports. Perpetrators' reports of perpetrating verbal aggression were a better predictor of next day perpetrator consequences than victims' reports. Days when partners agreed that aggression had occurred generally predicted the worst outcomes. People's own reports of verbal aggression are the best predictor of short-term consequences. Pooling partner reports of aggression may make it more difficult to understand the consequences of intimate partner aggression.

A Revised Model of Short-Term Memory and Long-Term Learning of Verbal Sequences

ERIC Educational Resources Information Center

Burgess, Neil; Hitch, Graham J.

2006-01-01

The interaction between short- and long-term memory is studied within a model in which phonemic and (temporal) contextual information have separate influences on immediate verbal serial recall via connections with short- and long-term plasticity [Burgess, N., & Hitch, G.J. (1999). Memory for serial order: a network model of the phonological loop…

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

PubMed

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.

Language repetition and short-term memory: an integrative framework

PubMed Central

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. PMID:23874280

Short-term forecasting of electric loads using nonlinear autoregressive artificial neural networks with exogenous vector inputs

DOE PAGES

Buitrago, Jaime; Asfour, Shihab

2017-01-01

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.more » 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. Finally, the New England electrical load data are used to train and validate the forecast prediction.« less

Short-term forecasting of electric loads using nonlinear autoregressive artificial neural networks with exogenous vector inputs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buitrago, Jaime; Asfour, Shihab

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.more » 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. Finally, the New England electrical load data are used to train and validate the forecast prediction.« less

Interlaboratory evaluation of Hyalella azteca and Chironomus tentans short-term and long-term sediment toxicity tests

USGS Publications Warehouse

Norberg-King, T. J.; Sibley, P.K.; Burton, G.A.; Ingersoll, C.G.; Kemble, N.E.; Ireland, S.; Mount, D.R.; Rowland, C.D.

2006-01-01

Methods for assessing the long-term toxicity of sediments to Hyalella azteca and Chironomus tentans can significantly enhance the capacity to assess sublethal effects of contaminated sediments through multiple endpoints. Sublethal tests allow us to begin to understand the relationship between short-term and long-term effects for toxic sediments. We present an interlaboratory evaluation with long-term and 10-d tests using control and contaminated sediments in which we assess whether proposed and existing performance criteria (test acceptability criteria [TAC]) could be achieved. Laboratories became familiar with newly developed, long-term protocols by testing two control sediments in phase 1. In phase 2, the 10-d and long-term tests were examined with several sediments. Laboratories met the TACs, but results varied depending on the test organism, test duration, and endpoints. For the long-term tests in phase 1, 66 to 100% of the laboratories consistently met the TACs for survival, growth, or reproduction using H. azteca, and 70 to 100% of the laboratories met the TACs for survival and growth, emergence, reproduction, and hatchability using C. tentans. In phase 2, fewer laboratories participated in long-term tests: 71 to 88% of the laboratories met the TAC for H. azteca, whereas 50 to 67% met the TAC for C. tentans. In the 10-d tests with H. azteca, and C. tentans, 82 and 88% of the laboratories met the TAC for survival, respectively, and 80% met the TAC for C. tentans growth. For the 10-d and long-term tests, laboratories predicted similar toxicity. Overall, the interlaboratory evaluation showed good precision of the methods, appropriate endpoints were incorporated into the test protocols, and tests effectively predicted the toxicity of sediments.

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

PubMed

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.

Collision Avoidance Short Course: Conjunction Assessment Risk Analysis - NASA Robotic CARA. Part I: ; Theory

NASA Technical Reports Server (NTRS)

Hejduk, M. D.; Frigm, Ryan C.

2015-01-01

Satellite conjunction assessment is perhaps the fastest growing area in space situational awareness and protection with military, civil and commercial satellite owner-operators embracing more and more sophisticated processes to avoid the avoidable - namely collisions between high value space assets and orbital debris. NASA and Centre National d'Etudes Spatiales (CNES) have collaborated to offer an introductory short course on all the major aspects of the conjunctions assessment problem. This half-day course will cover satellite conjunction dynamics and theory. Joint Space Operations Center (JsPOC) conjunction data products, major risk assessment parameters and plots, conjunction remediation decision support, and present and future challenges. This briefing represents the NASA portion of the course.

Verbal short-term memory and vocabulary learning in polyglots.

PubMed

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.

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

PubMed

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.

Evaluation of NASA Data Products for RPO Applications

NASA Technical Reports Server (NTRS)

Frisbie, Troy; Knowlton, Kelly; Andrews, Jane

2005-01-01

This presentation summarizes preliminary investigations at SSC by NASA's ASD in Air Quality including decision support tools, partner plans, working groups, and committees. An overview of follow-on short-term and long-term objectives is also provided. A table of potential NASA sensors for use with air quality applications is included, along with specifications for MODIS 04 and 06 products. This presentation was originally given by Rich Piorot of the Vermont Department of Environmental Conservation - Air Quality as part of a round-table discussion during "Exploring Collaborative Opportunities in Air Quality Monitoring, Modelling and Communication Workshop" in Boulder, CO, on March 21-22, 2005; verbal consent for this presentation to be provided to Mr. Piorot was given by the NASA SSC ASD Air Quality Program Manager on March 14, 2005.

The GALA study: relationship between galectin-3 serum levels and short- and long-term outcomes of patients with acute heart failure.

PubMed

Miró, Òscar; González de la Presa, Bernardino; Herrero-Puente, Pablo; Fernández Bonifacio, Rosa; Möckel, Martin; Mueller, Christian; Casals, Gregori; Sandalinas, Silvia; Llorens, Pere; Martín-Sánchez, Francisco Javier; Jacob, Javier; Bedini, José Luis; Gil, Víctor

2017-12-01

We tested the hypothesis that early measurement of galectin-3 at the emergency department (ED) during an episode of acute heart failure (AHF) allows predicting short- and long-term outcomes. We performed an exploratory study including 115 patients consecutively diagnosed with AHF in a single ED. Clinical and analytical variables were recorded. The primary endpoint was 30-day all-cause mortality, and secondary endpoints were 30-day composite outcome (death, rehospitalization or ED reconsultation, whichever first) and 1-year mortality. Seven patients (6.1%) died within 30 days and 43 (37.4%) within 1 year. The 30-day composite endpoint was observed in 21.1% of patients. Galectin-3 was correlated with NT-proBNP and the glomerular filtration rate but not with age and s-cTnI. Measured at time of ED arrival, galectin-3 showed good discriminatory capacity for 30-day mortality (AUC ROC: 0.732; 95% CI 0.512-0.953; p = 0.041) but not for 1-year mortality (0.521; 0.408-0.633; p = 0.722). Patients with galectin-3 concentrations >42 μg/L had an OR = 7.67(95%CI = 1.57-37.53; p = 0.012) for 30-day mortality. Conversely, NT-proBNP only showed predictive capacity for 1-year mortality (0.642; 0.537-0.748; p = 0.014). Patients with NT-proBNP concentrations >5400 ng/L had an OR = 4.34 (95%CI = 1.93-9.77; p < 0.001) for 1-year mortality. These increased short- (galectin-3) and long-term (NT-proBNP) risks remained significant after adjustment for age or renal function. s-cTnI failed in both short- and long term death prediction. No biomarker predicted the short-term composite endpoint. These results suggest that galectin-3 could help to monitor the risk of short-term mortality in unselected patients with AHF attended in the ED.

NASA Gulf of Mexico Initiative Hypoxia Research

NASA Technical Reports Server (NTRS)

Armstrong, Curtis D.

2012-01-01

The Applied Science & Technology Project Office at Stennis Space Center (SSC) manages NASA's Gulf of Mexico Initiative (GOMI). Addressing short-term crises and long-term issues, GOMI participants seek to understand the environment using remote sensing, in-situ observations, laboratory analyses, field observations and computational models. New capabilities are transferred to end-users to help them make informed decisions. Some GOMI activities of interest to the hypoxia research community are highlighted.

A Real-Time MODIS Vegetation Composite for Land Surface Models and Short-Term Forecasting

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.; Jedlovec, Gary J.

2011-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center is producing real-time, 1- km resolution Normalized Difference Vegetation Index (NDVI) gridded composites over a Continental U.S. domain. These composites are updated daily based on swath data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the polar orbiting NASA Aqua and Terra satellites, with a product time lag of about one day. A simple time-weighting algorithm is applied to the NDVI swath data that queries the previous 20 days of data to ensure a continuous grid of data populated at all pixels. The daily composites exhibited good continuity both spatially and temporally during June and July 2010. The composites also nicely depicted high greenness anomalies that resulted from significant rainfall over southwestern Texas, Mexico, and New Mexico during July due to early-season tropical cyclone activity. The SPoRT Center is in the process of computing greenness vegetation fraction (GVF) composites from the MODIS NDVI data at the same spatial and temporal resolution for use in the NASA Land Information System (LIS). The new daily GVF dataset would replace the monthly climatological GVF database (based on Advanced Very High Resolution Radiometer [AVHRR] observations from 1992-93) currently available to the Noah land surface model (LSM) in both LIS and the public version of the Weather Research and Forecasting (WRF) model. The much higher spatial resolution (1 km versus 0.15 degree) and daily updates based on real-time satellite observations have the capability to greatly improve the simulation of the surface energy budget in the Noah LSM within LIS and WRF. Once code is developed in LIS to incorporate the daily updated GVFs, the SPoRT Center will conduct simulation sensitivity experiments to quantify the impacts and improvements realized by the MODIS real-time GVF data. This presentation will describe the methodology used to develop the 1-km MODIS NDVI composites and

Efficacy of simple short-term in vitro assays for predicting the potential of metal oxide nanoparticles to cause pulmonary inflammation.

PubMed

Lu, Senlin; Duffin, Rodger; Poland, Craig; Daly, Paul; Murphy, Fiona; Drost, Ellen; Macnee, William; Stone, Vicki; Donaldson, Ken

2009-02-01

There has been concern regarding risks from inhalation exposure to nanoparticles (NPs). The large number of particles requiring testing means that alternative approaches to animal testing are needed. We set out to determine whether short-term in vitro assays that assess intrinsic oxidative stress potential and membrane-damaging potency of a panel of metal oxide NPs can be used to predict their inflammogenic potency. For a panel of metal oxide NPs, we investigated intrinsic free radical generation, oxidative activity in an extracellular environment, cytotoxicity to lung epithelial cells, hemolysis, and inflammation potency in rat lungs. All exposures were carried out at equal surface area doses. Only nickel oxide (NiO) and alumina 2 caused significant lung inflammation when instilled into rat lungs at equal surface area, suggesting that these two had extra surface reactivity. We observed significant free radical generation with 4 of 13 metal oxides, only one of which was inflammogenic. Only 3 of 13 were significantly hemolytic, two of which were inflammogenic. Potency in generating free radicals in vitro did not predict inflammation, whereas alumina 2 had no free radical activity but was inflammogenic. The hemolysis assay was correct in predicting the proinflammatory potential of 12 of 13 of the particles examined. Using a battery of simple in vitro tests, it is possible to predict the inflammogenicity of metal oxide NPs, although some false-positive results are likely. More research using a larger panel is needed to confirm the efficacy and generality of this approach for metal oxide NPs.

Short-term and long-term attentional biases to frequently encountered target features.

PubMed

Sha, Li Z; Remington, Roger W; Jiang, Yuhong V

2017-07-01

It has long been known that frequently occurring targets are attended better than infrequent ones in visual search. But does this frequency-based attentional prioritization reflect momentary or durable changes in attention? Here we observed both short-term and long-term attentional biases for visual features as a function of different types of statistical associations between the targets, distractors, and features. Participants searched for a target, a line oriented horizontally or vertically among diagonal distractors, and reported its length. In one set of experiments we manipulated the target's color probability: Targets were more often in Color 1 than in Color 2. The distractors were in other colors. Participants found Color 1 targets more quickly than Color 2 targets, but this preference disappeared immediately when the target's color became random in the subsequent testing phase. In the other set of experiments, we manipulated the diagnostic values of the two colors: Color 1 was more often a target than a distractor; Color 2 was more often a distractor than a target. Participants found Color 1 targets more quickly than Color 2 targets. Importantly, and in contrast to the first set of experiments, the featural preference was sustained in the testing phase. These results suggest that short-term and long-term attentional biases are products of different statistical information. Finding a target momentarily activates its features, inducing short-term repetition priming. Long-term changes in attention, on the other hand, may rely on learning diagnostic features of the targets.

Overview of NASA Magnet and Linear Alternator Research Efforts

NASA Astrophysics Data System (ADS)

Geng, Steven M.; Niedra, Janis M.; Schwarze, Gene E.

2005-02-01

The Department of Energy, Lockheed Martin, Stirling Technology Company, and NASA Glenn Research Center are developing a high-efficiency, 110 watt Stirling Radioisotope Generator (SRG110) for NASA Space Science missions. NASA Glenn is conducting in-house research on rare earth permanent magnets and on linear alternators to assist in developing a free-piston Stirling convertor for the SRG110 and for developing advanced technology. The permanent magnet research efforts include magnet characterization, short-term magnet aging tests, and long-term magnet aging tests. Linear alternator research efforts have begun just recently at GRC with the characterization of a moving iron type linear alternator using GRC's alternator test rig. This paper reports on the progress and future plans of GRC's magnet and linear alternator research efforts.

Overview of NASA Magnet and Linear Alternator Research Efforts

NASA Technical Reports Server (NTRS)

Geng, Steven M.; Schwarze, Gene E.; Nieda, Janis M.

2005-01-01

The Department of Energy, Lockheed Martin, Stirling Technology Company, and NASA Glenn Research Center are developing a high-efficiency, 110 watt Stirling Radioisotope Generator (SRG110) for NASA Space Science missions. NASA Glenn is conducting in-house research on rare earth permanent magnets and on linear alternators to assist in developing a free-piston Stirling convertor for the SRG110 and for developing advanced technology. The permanent magnet research efforts include magnet characterization, short-term magnet aging tests, and long-term magnet aging tests. Linear alternator research efforts have begun just recently at GRC with the characterization of a moving iron type linear alternator using GRC's alternator test rig. This paper reports on the progress and future plans of GRC's magnet and linear alternator research efforts.

Utilization of NASA Lewis mobile terminals for the Hermes satellite

NASA Technical Reports Server (NTRS)

Edelman, E. A.; Fiala, J. L.; Rizzolla, L.

1977-01-01

The high power of the Hermes satellite enables two-way television and voice communication with small ground terminals. The Portable Earth Terminal (PET) and the Transportable Earth Terminal (TET) were developed and built by NASA-Lewis to provide communications capability to short-term users. The NASA-Lewis mobile terminals are described in terms of vehicles and onboard equipment, as well as operation aspects, including use in the field. The section on demonstrations divides the uses into categories of medicine, education, technology and government. Applications of special interest within each category are briefly described.

34 CFR 390.1 - What is the Rehabilitation Short-Term Training program?

Code of Federal Regulations, 2012 CFR

2012-07-01

... 34 Education 2 2012-07-01 2012-07-01 false What is the Rehabilitation Short-Term Training program...-TERM TRAINING General § 390.1 What is the Rehabilitation Short-Term Training program? This program is designed for the support of special seminars, institutes, workshops, and other short-term courses in...

34 CFR 390.1 - What is the Rehabilitation Short-Term Training program?

Code of Federal Regulations, 2014 CFR

2014-07-01

... 34 Education 2 2014-07-01 2013-07-01 true What is the Rehabilitation Short-Term Training program...-TERM TRAINING General § 390.1 What is the Rehabilitation Short-Term Training program? This program is designed for the support of special seminars, institutes, workshops, and other short-term courses in...

34 CFR 390.1 - What is the Rehabilitation Short-Term Training program?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 2 2010-07-01 2010-07-01 false What is the Rehabilitation Short-Term Training program...-TERM TRAINING General § 390.1 What is the Rehabilitation Short-Term Training program? This program is designed for the support of special seminars, institutes, workshops, and other short-term courses in...

34 CFR 390.1 - What is the Rehabilitation Short-Term Training program?

Code of Federal Regulations, 2011 CFR

2011-07-01

... 34 Education 2 2011-07-01 2010-07-01 true What is the Rehabilitation Short-Term Training program...-TERM TRAINING General § 390.1 What is the Rehabilitation Short-Term Training program? This program is designed for the support of special seminars, institutes, workshops, and other short-term courses in...

34 CFR 390.1 - What is the Rehabilitation Short-Term Training program?

Code of Federal Regulations, 2013 CFR

2013-07-01

... 34 Education 2 2013-07-01 2013-07-01 false What is the Rehabilitation Short-Term Training program...-TERM TRAINING General § 390.1 What is the Rehabilitation Short-Term Training program? This program is designed for the support of special seminars, institutes, workshops, and other short-term courses in...

NASA's In-Space Propulsion Technology Project's Products for Near-term Mission Applicability

NASA Astrophysics Data System (ADS)

Dankanich, John

2009-01-01

The In-Space Propulsion Technology (ISPT) project, funded by NASA's Science Mission Directorate (SMD), is continuing to invest in propulsion technologies that will enable or enhance NASA robotic science missions. The primary investments and products currently available for technology infusion include NASA's Evolutionary Xenon Thruster (NEXT) and the Advanced Materials Bipropellant Rocket (AMBR) engine. These products will reach TRL 6 in 2008 and are available for the current and all future mission opportunities. Development status, near-term mission benefits, applicability, and availability of in-space propulsion technologies in the areas of electric propulsion, advanced chemical thrusters, and aerocapture are presented.

Evaluation of regression and neural network models for solar forecasting over different short-term horizons

DOE PAGES

Inanlouganji, Alireza; Reddy, T. Agami; Katipamula, Srinivas

2018-04-13

Forecasting solar irradiation has acquired immense importance in view of the exponential increase in the number of solar photovoltaic (PV) system installations. In this article, analyses results involving statistical and machine-learning techniques to predict solar irradiation for different forecasting horizons are reported. Yearlong typical meteorological year 3 (TMY3) datasets from three cities in the United States with different climatic conditions have been used in this analysis. A simple forecast approach that assumes consecutive days to be identical serves as a baseline model to compare forecasting alternatives. To account for seasonal variability and to capture short-term fluctuations, different variants of themore » lagged moving average (LMX) model with cloud cover as the input variable are evaluated. Finally, the proposed LMX model is evaluated against an artificial neural network (ANN) model. How the one-hour and 24-hour models can be used in conjunction to predict different short-term rolling horizons is discussed, and this joint application is illustrated for a four-hour rolling horizon forecast scheme. Lastly, the effect of using predicted cloud cover values, instead of measured ones, on the accuracy of the models is assessed. Results show that LMX models do not degrade in forecast accuracy if models are trained with the forecast cloud cover data.« less

Evaluation of regression and neural network models for solar forecasting over different short-term horizons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Inanlouganji, Alireza; Reddy, T. Agami; Katipamula, Srinivas

Forecasting solar irradiation has acquired immense importance in view of the exponential increase in the number of solar photovoltaic (PV) system installations. In this article, analyses results involving statistical and machine-learning techniques to predict solar irradiation for different forecasting horizons are reported. Yearlong typical meteorological year 3 (TMY3) datasets from three cities in the United States with different climatic conditions have been used in this analysis. A simple forecast approach that assumes consecutive days to be identical serves as a baseline model to compare forecasting alternatives. To account for seasonal variability and to capture short-term fluctuations, different variants of themore » lagged moving average (LMX) model with cloud cover as the input variable are evaluated. Finally, the proposed LMX model is evaluated against an artificial neural network (ANN) model. How the one-hour and 24-hour models can be used in conjunction to predict different short-term rolling horizons is discussed, and this joint application is illustrated for a four-hour rolling horizon forecast scheme. Lastly, the effect of using predicted cloud cover values, instead of measured ones, on the accuracy of the models is assessed. Results show that LMX models do not degrade in forecast accuracy if models are trained with the forecast cloud cover data.« less

2-arachidonoylglycerol signaling impairs short-term fear extinction

PubMed Central

Hartley, N D; Gunduz-Cinar, O; Halladay, L; Bukalo, O; Holmes, A; Patel, S

2016-01-01

Impairments in fear extinction are thought to be central to the psychopathology of posttraumatic stress disorder, and endocannabinoid (eCB) signaling has been strongly implicated in extinction learning. Here we utilized the monoacylglycerol lipase inhibitor JZL184 to selectively augment brain 2-AG levels combined with an auditory cue fear-conditioning paradigm to test the hypothesis that 2-AG-mediated eCB signaling modulates short-term fear extinction learning in mice. We show that systemic JZL184 impairs short-term extinction learning in a CB1 receptor-dependent manner without affecting non-specific freezing behavior or the acquisition of conditioned fear. This effect was also observed in over-conditioned mice environmentally manipulated to re-acquire fear extinction. Cumulatively, the effects of JZL184 appear to be partly due to augmentation of 2-AG signaling in the basolateral nucleus of the amygdala (BLA), as direct microinfusion of JZL184 into the BLA produced similar results. Moreover, we elucidate a short ~3-day temporal window during which 2-AG augmentation impairs extinction behavior, suggesting a preferential role for 2-AG-mediated eCB signaling in the modulation of short-term behavioral sequelae to acute traumatic stress exposure. PMID:26926885

A Study of Short-Term Variations in Jupiter's Synchrotron Emission

NASA Technical Reports Server (NTRS)

Klein, M.J.; Gulkis, S.; Bolton, S. J.; Levin, S. M.

1999-01-01

Earth-based observations of the flux density and polarization of Jupiter's microwave emission provide useful data to test and constrain computational models of synchrotron radio emission from the inner regions of the Jovian magnetosphere. Stimulated by the sudden brightening of the synchrotron emission caused by the impacts of comet Shoemaker-Levy 9 in 1994, the observational techniques of the NASA-JPL Jupiter Patrol were modified to search for other short-term variations unrelated to the SL-9 event. The characteristics of the improved data base are described and the results of the search for variability on timescales of 5 to 100 days are reported. The first results of Jupiter observations from the Goldstone-Apple Valley Radio Telescope (GAVRT) project are reported and included in the data base. GAVRT is a new project in science education that engages middle- and high school students in science research. The paper also includes new observations of Jupiter's rotational beamed emission, commonly known as the "beaming curve", that describes the observed flux density as a function of System III longitude. The shape of the "beaming curve" is known to change with the parameter D(sub E), the declination of the earth relative to Jupiter's rotational equator. While the history of Jupiter's beaming curve exhibits remarkable stability and repeatability as a function of D(sub E), there may be evidence for short term departures from the nominal curves. Data supporting this tentative conclusion are presented. Preliminary results of a study comparing the observations and computer simulations of the synchrotron beaming curve will also be presented and discussed (see companion paper, "Modeling Jupiter's Synchrotron Emission", by Bolton et. al.). The research reported in this paper was performed by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

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

ERIC Educational Resources Information Center

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…

Auditory short-term memory activation during score reading.

PubMed

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.

Auditory Short-Term Memory Activation during Score Reading

PubMed Central

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. PMID:23326487

Predicting Short Term Runoff Efficiency Using Antecedent Soil Moisture Estimates From Ground Penetrating Radar Data

NASA Astrophysics Data System (ADS)

Hermance, J. F.; Bohidar, R. N.

2002-05-01

Hydrologists universally recognize the importance of antecedent soil moisture conditions for predicting the response of catchments to storm events. We describe a pilot study involving a series of repeat geophysical measurements over a 5 month period to determine the water content of the subsurface immediately before a sequence of precipitation events. We correlate the resultant streamflow "response" of the local catchment to each event with the antecedent soil moisture at our reference site using a metric commonly employed by hydrologists: the ratio Qef/W, referred to here as the "short term runoff efficiency", which is simply the time-integrated volume of event flow (Qef) at the catchment's outflow point normalized by the volume of total precipitation (W) over its area. To determine the volumetric water content (Cw) of soils, past studies suggest the effectiveness of pulsed radio frequency methods, such as time domain reflectometry (TDR), or ground-penetrating radar (GPR). To first order, for typical field conditions and procedures, the velocity of a radio pulse in the subsurface is inversely proportional to the square root of the bulk dielectric constant, which in turn is proportional to the soil's water content. For this study, the advantage of GPR over conventional TDR measurements is that the GPR procedure determines average velocities from two-way traveltimes to an interface at depth, resulting in estimates of average physical properties over much larger volumes of the subsurface than would TDR. Our hydrologic data are USGS daily averaged discharges from the Ten Mile River (watershed area = 138 km2; 53.2 mi2) in southern New England. Daily values of precipitation were provided by personnel from the Seekonk Water District Office (MA) adjacent to the field site. Our hydrograph separation was facilitated by the observation that the event flow seems to be adequately represented by a simple composite cascaded linear reservoir model. The GPR data involved a series

Short-term and working memory impairments in aphasia.

PubMed

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 Memory, Working Memory, and Executive Functioning in Preschoolers: Longitudinal Predictors of Mathematical Achievement at Age 7 Years

PubMed Central

Bull, Rebecca; Espy, Kimberly Andrews; Wiebe, Sandra A.

2009-01-01

This study examined whether measures of short-term memory, working memory, and executive functioning in preschool children predict later proficiency in academic achievement at 7 years of age (third year of primary school). Children were tested in preschool (M age = 4 years, 6 months) on a battery of cognitive measures, and mathematics and reading outcomes (from standardized, norm-referenced school-based assessments) were taken on entry to primary school, and at the end of the first and third year of primary school. Growth curve analyses examined predictors of math and reading achievement across the duration of the study and revealed that better digit span and executive function skills provided children with an immediate head start in math and reading that they maintained throughout the first three years of primary school. Visual-spatial short-term memory span was found to be a predictor specifically of math ability. Correlational and regression analyses revealed that visual short-term and working memory were found to specifically predict math achievement at each time point, while executive function skills predicted learning in general rather than learning in one specific domain. The implications of the findings are discussed in relation to further understanding the role of cognitive skills in different mathematical tasks, and in relation to the impact of limited cognitive skills in the classroom environment. PMID:18473197

Long-term irradiance observation and short-term flare prediction with LYRA on PROBA2

NASA Astrophysics Data System (ADS)

Dammasch, Ingolf; Dominique, Marie; West, Matthew; Katsiyannis, Thanassis; Ryan, Daniel; Wauters, Laurence

The solar radiometer LYRA on board the ESA micro-satellite PROBA2 has observed the Sun continuously since January 2010 in various spectral band passes, and has gained a considerable data base. Two of the LYRA channels cover the irradiance between soft X-ray and extreme ultraviolet. The variation of the sunspot number appears to show a strong similarity with the variation of these channels, when their long-range development is taken into account. The same holds for SXR levels observed by the GOES satellites. Due to LYRA's bandwidth and coverage of various active-region temperatures, its relatively smooth development may yield some information on the structure of the current solar cycle. On its websites, LYRA presents not only EUV and SXR time series in near real-time, but also information on flare parameters and long-term irradiance and sunspot levels. It will be demonstrated whether it is possible to aid space weather forecast with these statistical data, especially for the prediction of expected flare strength on a daily basis.

Upper surface blowing noise of the NASA-Ames quiet short-haul research aircraft

NASA Technical Reports Server (NTRS)

Bohn, A. J.; Shovlin, M. D.

1980-01-01

An experimental study of the propulsive-lift noise of the NASA-Ames quiet short-haul research aircraft (QSRA) is described. Comparisons are made of measured QSRA flyover noise and model propulsive-lift noise data available in references. Developmental tests of trailing-edge treatments were conducted using sawtooth-shaped and porous USB flap trailing-edge extensions. Small scale parametric tests were conducted to determine noise reduction/design relationships. Full-scale static tests were conducted with the QSRA preparatory to the selection of edge treatment designs for flight testing. QSRA flight and published model propulsive-lift noise data have similar characteristics. Noise reductions of 2 to 3 dB were achieved over a wide range of frequency and directivity angles in static tests of the QSRA. These noise reductions are expected to be achieved or surpassed in flight tests planned by NASA in 1980.

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

PubMed Central

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

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

PubMed

Astle, Duncan E; Nobre, Anna C; Scerif, Gaia

2012-01-01

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-year-olds, 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, be preceded ("precued"), or followed ("retrocued") 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 than in 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.

Cardioprotective Signature of Short-Term Caloric Restriction

PubMed Central

Isserlin, Ruth; Arab, Sara; Momen, Abdul; Cheng, Henry S.; Wu, Jun; Afroze, Talat; Li, Ren-Ke; Fish, Jason E.; Bader, Gary D.; Husain, Mansoor

2015-01-01

Objective To understand the molecular pathways underlying the cardiac preconditioning effect of short-term caloric restriction (CR). Background 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. Methods 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. Results 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. PMID:26098549

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

NASA Astrophysics Data System (ADS)

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.

A short-term ionospheric forecasting empirical regional model (IFERM) to predict the critical frequency of the F2 layer during moderate, disturbed, and very disturbed geomagnetic conditions over the European area

NASA Astrophysics Data System (ADS)

Pietrella, M.

2012-02-01

A short-term ionospheric forecasting empirical regional model (IFERM) has been developed to predict the state of the critical frequency of the F2 layer (foF2) under different geomagnetic conditions. IFERM is based on 13 short term ionospheric forecasting empirical local models (IFELM) developed to predict foF2 at 13 ionospheric observatories scattered around the European area. The forecasting procedures were developed by taking into account, hourly measurements of foF2, hourly quiet-time reference values of foF2 (foF2QT), and the hourly time-weighted accumulation series derived from the geomagnetic planetary index ap, (ap(τ)), for each observatory. Under the assumption that the ionospheric disturbance index ln(foF2/foF2QT) is correlated to the integrated geomagnetic disturbance index ap(τ), a set of statistically significant regression coefficients were established for each observatory, over 12 months, over 24 h, and under 3 different ranges of geomagnetic activity. This data was then used as input to compute short-term ionospheric forecasting of foF2 at the 13 local stations under consideration. The empirical storm-time ionospheric correction model (STORM) was used to predict foF2 in two different ways: scaling both the hourly median prediction provided by IRI (STORM_foF2MED,IRI model), and the foF2QT values (STORM_foF2QT model) from each local station. The comparison between the performance of STORM_foF2MED,IRI, STORM_foF2QT, IFELM, and the foF2QT values, was made on the basis of root mean square deviation (r.m.s.) for a large number of periods characterized by moderate, disturbed, and very disturbed geomagnetic activity. The results showed that the 13 IFELM perform much better than STORM_foF2,sub>MED,IRI and STORM_foF2QT especially in the eastern part of the European area during the summer months (May, June, July, and August) and equinoctial months (March, April, September, and October) under disturbed and very disturbed geomagnetic conditions, respectively

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

PubMed

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

NASA Astrophysics Data System (ADS)

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.

PubMed

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.

Of trophies and pillars: exploring the terror management functions of short-term and long-term relationship partners.

PubMed

Kosloff, Spee; Greenberg, Jeff; Sullivan, Daniel; Weise, David

2010-08-01

Prior terror management research shows that mortality salience (MS) motivates both self-esteem striving and worldview bolstering. The present research examined these processes in the context of dating preferences. It was hypothesized that in short-term romantic contexts, MS-induced self-esteem striving motivates interest in dating a physically attractive other, whereas in long-term romantic contexts, MS-induced motives for worldview validation heighten interest in dating a same-religion other. Study 1 showed that in a short-term dating context, MS increased preference for an attractive but religiously dissimilar person, whereas in a long-term dating context, MS increased preference for a religiously similar, less attractive person. Study 2 clarified that MS motivates preference for attractive short-term partners for their self-enhancing properties rather than their potential sexual availability. Study 3 supported the theorized processes, showing that under MS, self-esteem-relevant constructs became spontaneously accessible in short-term dating contexts, whereas worldview-relevant constructs became spontaneously accessible in long-term dating contexts.

Holding multiple items in short term memory: a neural mechanism.

PubMed

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

PubMed Central

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

Long-Term Post-CABG Survival: Performance of Clinical Risk Models Versus Actuarial Predictions.

PubMed

Carr, Brendan M; Romeiser, Jamie; Ruan, Joyce; Gupta, Sandeep; Seifert, Frank C; Zhu, Wei; Shroyer, A Laurie

2016-01-01

Clinical risk models are commonly used to predict short-term coronary artery bypass grafting (CABG) mortality but are less commonly used to predict long-term mortality. The added value of long-term mortality clinical risk models over traditional actuarial models has not been evaluated. To address this, the predictive performance of a long-term clinical risk model was compared with that of an actuarial model to identify the clinical variable(s) most responsible for any differences observed. Long-term mortality for 1028 CABG patients was estimated using the Hannan New York State clinical risk model and an actuarial model (based on age, gender, and race/ethnicity). Vital status was assessed using the Social Security Death Index. Observed/expected (O/E) ratios were calculated, and the models' predictive performances were compared using a nested c-index approach. Linear regression analyses identified the subgroup of risk factors driving the differences observed. Mortality rates were 3%, 9%, and 17% at one-, three-, and five years, respectively (median follow-up: five years). The clinical risk model provided more accurate predictions. Greater divergence between model estimates occurred with increasing long-term mortality risk, with baseline renal dysfunction identified as a particularly important driver of these differences. Long-term mortality clinical risk models provide enhanced predictive power compared to actuarial models. Using the Hannan risk model, a patient's long-term mortality risk can be accurately assessed and subgroups of higher-risk patients can be identified for enhanced follow-up care. More research appears warranted to refine long-term CABG clinical risk models. © 2015 The Authors. Journal of Cardiac Surgery Published by Wiley Periodicals, Inc.

ORAL TOXICITY OF 1,3-DICHLOROPROPANE: ACUTE, SHORT-TERM, AND LONG-TERM STUDIES IN RATS

EPA Science Inventory

The objective of this investigation was to characterize the acute and short- and long-term toxic potency of orally administered 1,2-dichloropropane (DCP). In the acute and short-term studies, male rats of 250-300 g were gavaged with 0, 100, 250, 500, or 1000 mg DCP/kg in corn oil...

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

PubMed

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.

Outcome Research on Short-Term Psychodynamic Psychotherapy: A Preliminary Review.

ERIC Educational Resources Information Center

White, Scott Allyn

This paper reviews the empirical research on short-term psychodynamic psychotherapy (STDP). It begins with a brief history of STDP, identifying current developers and researchers of STDP and listing commonalities among various short-term dynamic psychotherapies. In this review, research is grouped broadly into two categories: controlled…

Overview of developing desired conditions: Short-term actions, long-term objectives

Treesearch

J. D. Chew; K. O' Hara; J. G. Jones

2001-01-01

A number of modeling tools are required to go from short-term treatments to long-term objectives expressed as desired future conditions. Three models are used in an example that starts with determining desired stand level structure and ends with the implementation of treatments over time at a landscape scale. The Multi-Aged Stocking Assessment Model (MASAM) is used for...

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

PubMed

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.

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

PubMed Central

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 usingimages 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. PMID:26447470

Downscaling NASA Climatological Data to Produce Detailed Climate Zone Maps

NASA Technical Reports Server (NTRS)

Chandler, William S.; Hoell, James M.; Westberg, David J.; Whitlock, Charles H.; Zhang, Taiping; Stackhouse, P. W.

2011-01-01

The design of energy efficient sustainable buildings is heavily dependent on accurate long-term and near real-time local weather data. To varying degrees the current meteorological networks over the globe have been used to provide these data albeit often from sites far removed from the desired location. The national need is for access to weather and solar resource data accurate enough to use to develop preliminary building designs within a short proposal time limit, usually within 60 days. The NASA Prediction Of Worldwide Energy Resource (POWER) project was established by NASA to provide industry friendly access to globally distributed solar and meteorological data. As a result, the POWER web site (power.larc.nasa.gov) now provides global information on many renewable energy parameters and several buildings-related items but at a relatively coarse resolution. This paper describes a method of downscaling NASA atmospheric assimilation model results to higher resolution and maps those parameters to produce building climate zone maps using estimates of temperature and precipitation. The distribution of climate zones for North America with an emphasis on the Pacific Northwest for just one year shows very good correspondence to the currently defined distribution. The method has the potential to provide a consistent procedure for deriving climate zone information on a global basis that can be assessed for variability and updated more regularly.

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

PubMed

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

NASA Astrophysics Data System (ADS)

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

Development and validation of QMortality risk prediction algorithm to estimate short term risk of death and assess frailty: cohort study.

PubMed

Hippisley-Cox, Julia; Coupland, Carol

2017-09-20

Objectives  To derive and validate a risk prediction equation to estimate the short term risk of death, and to develop a classification method for frailty based on risk of death and risk of unplanned hospital admission. Design  Prospective open cohort study. Participants  Routinely collected data from 1436 general practices contributing data to QResearch in England between 2012 and 2016. 1079 practices were used to develop the scores and a separate set of 357 practices to validate the scores. 1.47 million patients aged 65-100 years were in the derivation cohort and 0.50 million patients in the validation cohort. Methods  Cox proportional hazards models in the derivation cohort were used to derive separate risk equations in men and women for evaluation of the risk of death at one year. Risk factors considered were age, sex, ethnicity, deprivation, smoking status, alcohol intake, body mass index, medical conditions, specific drugs, social factors, and results of recent investigations. Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for each age and ethnic group. The new mortality equation was used in conjunction with the existing QAdmissions equation (which predicts risk of unplanned hospital admission) to classify patients into frailty groups. Main outcome measure  The primary outcome was all cause mortality. Results  During follow-up 180 132 deaths were identified in the derivation cohort arising from 4.39 million person years of observation. The final model included terms for age, body mass index, Townsend score, ethnic group, smoking status, alcohol intake, unplanned hospital admissions in the past 12 months, atrial fibrillation, antipsychotics, cancer, asthma or chronic obstructive pulmonary disease, living in a care home, congestive heart failure, corticosteroids, cardiovascular disease, dementia, epilepsy, learning disability, leg ulcer, chronic liver disease or pancreatitis

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

NASA Astrophysics Data System (ADS)

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.

PubMed

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

NASA Astrophysics Data System (ADS)

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.

NASA Land Information System (LIS) Water Availability to Support Reclamation ET Estimation

NASA Technical Reports Server (NTRS)

Toll, David; Arsenault, Kristi; Pinheiro, Ana; Peters-Lidard, Christa; Houser, Paul; Kumar, Sujay; Engman, Ted; Nigro, Joe; Triggs, Jonathan

2005-01-01

The U.S. Bureau of Reclamation identified the remote sensing of evapotranspiration (ET) as an important water flux for study and designated a test site in the Lower Colorado River basin. A consortium of groups will work together with the goal to develop more accurate and cost effective techniques using the enhanced spatial and temporal coverage afforded by remote sensing. ET is a critical water loss flux where improved estimation should lead to better management of Reclamation responsibilities. There are several areas where NASA satellite and modeling data may be useful to meet Reclamation's objectives for improved ET estimation. In this paper we outline one possible contribution to use NASA's data integration capability of the Land Information System (LIS) to provide a merger of observational (in situ and satellite) with physical process models to provide estimates of ET and other water availability outputs (e.g., runoff, soil moisture) retrospectively, in near real-time, and also providing short-term predictions.

NREL/NASA Internal Short-Circuit Instigator in Lithium Ion Cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keyser, Matthew; Long, Dirk; Pesaran, Ahmad

Lithium-ion cells provide the highest specific energy (>280 Wh/kg) and energy density (>600 Wh/L) rechargeable battery building block to date with the longest life. Electrode/electrolyte thermal instability and flammability of the electrolyte of Li-ion cells make them prone to catastrophic thermal runaway under some rare internal short circuit conditions. Despite extensive QC/QA, standardized industry safety testing, and over 18 years of manufacturing experience, major recalls have taken place and incidents still occur. Many safety incidents that take place in the field originate due to an internal short that was not detectable or predictable at the point of manufacture. The Internalmore » Short-Circuit Instigator can be used to study types of separators, non-flammable electrolytes, electrolyte additives, fusible tabs, propagation studies, and gas generation within a cell.« less

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

NASA Astrophysics Data System (ADS)

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.

Determination of Tolerance to Internal Shorts and Its Screening in Lithium-ion Cells NASA - JSC Method

NASA Technical Reports Server (NTRS)

Jeevarajan, Judith

2009-01-01

This slide presentation reviews the method developed by the NASA Johnson Space Center (JSC) to determine tolerances to internal shorts and screening for problems in commercial off the shelf (COTS) Lithium-ion batteries. The test apparatus is shown and several examples of the usage and results of the test are discussed.

NASA Earth Science Research Results for Improved Regional Crop Yield Prediction

NASA Astrophysics Data System (ADS)

Mali, P.; O'Hara, C. G.; Shrestha, B.; Sinclair, T. R.; G de Goncalves, L. G.; Salado Navarro, L. R.

2007-12-01

National agencies such as USDA Foreign Agricultural Service (FAS), Production Estimation and Crop Assessment Division (PECAD) work specifically to analyze and generate timely crop yield estimates that help define national as well as global food policies. The USDA/FAS/PECAD utilizes a Decision Support System (DSS) called CADRE (Crop Condition and Data Retrieval Evaluation) mainly through an automated database management system that integrates various meteorological datasets, crop and soil models, and remote sensing data; providing significant contribution to the national and international crop production estimates. The "Sinclair" soybean growth model has been used inside CADRE DSS as one of the crop models. This project uses Sinclair model (a semi-mechanistic crop growth model) for its potential to be effectively used in a geo-processing environment with remote-sensing-based inputs. The main objective of this proposed work is to verify, validate and benchmark current and future NASA earth science research results for the benefit in the operational decision making process of the PECAD/CADRE DSS. For this purpose, the NASA South American Land Data Assimilation System (SALDAS) meteorological dataset is tested for its applicability as a surrogate meteorological input in the Sinclair model meteorological input requirements. Similarly, NASA sensor MODIS products is tested for its applicability in the improvement of the crop yield prediction through improving precision of planting date estimation, plant vigor and growth monitoring. The project also analyzes simulated Visible/Infrared Imager/Radiometer Suite (VIIRS, a future NASA sensor) vegetation product for its applicability in crop growth prediction to accelerate the process of transition of VIIRS research results for the operational use of USDA/FAS/PECAD DSS. The research results will help in providing improved decision making capacity to the USDA/FAS/PECAD DSS through improved vegetation growth monitoring from high

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

ERIC Educational Resources Information Center

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.…

Short-Term Volunteer Teachers in Rural China: Challenges and Needs

ERIC Educational Resources Information Center

Zhou, Huiquan; Shang, Xinyuan

2011-01-01

The brain-drain caused by imbalanced economic development has produced a lack of qualified teachers in rural China. Short-term volunteer teaching has emerged as a response. Despite the popularity of such programs, little systematic data have been gathered regarding their strengths and weaknesses. A short-term volunteer teaching program was…

Local short-term variability in solar irradiance

NASA Astrophysics Data System (ADS)

Lohmann, Gerald M.; Monahan, Adam H.; Heinemann, Detlev

2016-05-01

Characterizing spatiotemporal irradiance variability is important for the successful grid integration of increasing numbers of photovoltaic (PV) power systems. Using 1 Hz data recorded by as many as 99 pyranometers during the HD(CP)2 Observational Prototype Experiment (HOPE), we analyze field variability of clear-sky index k* (i.e., irradiance normalized to clear-sky conditions) and sub-minute k* increments (i.e., changes over specified intervals of time) for distances between tens of meters and about 10 km. By means of a simple classification scheme based on k* statistics, we identify overcast, clear, and mixed sky conditions, and demonstrate that the last of these is the most potentially problematic in terms of short-term PV power fluctuations. Under mixed conditions, the probability of relatively strong k* increments of ±0.5 is approximately twice as high compared to increment statistics computed without conditioning by sky type. Additionally, spatial autocorrelation structures of k* increment fields differ considerably between sky types. While the profiles for overcast and clear skies mostly resemble the predictions of a simple model published by , this is not the case for mixed conditions. As a proxy for the smoothing effects of distributed PV, we finally show that spatial averaging mitigates variability in k* less effectively than variability in k* increments, for a spatial sensor density of 2 km-2.

Pigeon visual short-term memory directly compared to primates.

PubMed

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 Effects of Midseason Coach Turnover on Team Performance in Soccer

ERIC Educational Resources Information Center

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…

Metropolitan French: Familiarization & Short-Term Training.