Measurement of historical cliff-top changes and estimation of future trends using GIS data between Bridlington and Hornsea - Holderness Coast (UK)

NASA Astrophysics Data System (ADS)

Castedo, Ricardo; de la Vega-Panizo, Rogelio; Fernández-Hernández, Marta; Paredes, Carlos

2015-02-01

A key requirement for effective coastal zone management is good knowledge of historical rates of change and the ability to predict future shoreline evolution, especially for rapidly eroding areas. Historical shoreline recession analysis was used for the prediction of future cliff shoreline positions along a section of 9 km between Bridlington and Hornsea, on the northern area of the Holderness Coast, UK. The analysis was based on historical maps and aerial photographs dating from 1852 to 2011 using the Digital Shoreline Analysis System (DSAS) 4.3, extension of ESRI's ArcInfo 10.×. The prediction of future shorelines was performed for the next 40 years using a variety of techniques, ranging from extrapolation from historical data, geometric approaches like the historical trend analysis, to a process-response numerical model that incorporates physically-based equations and geotechnical stability analysis. With climate change and sea-level rise implying that historical rates of change may not be a reliable guide for the future, enhanced visualization of the evolving coastline has the potential to improve awareness of these changing conditions. Following the IPCC, 2013 report, two sea-level rise rates, 2 mm/yr and 6 mm/yr, have been used to estimate future shoreline conditions. This study illustrated that good predictive models, once their limitations are estimated or at least defined, are available for use by managers, planners, engineers, scientists and the public to make better decisions regarding coastal management, development, and erosion-control strategies.

Temperament and Parenting during the First Year of Life Predict Future Child Conduct Problems

ERIC Educational Resources Information Center

Lahey, Benjamin B.; Van Hulle, Carol A.; Keenan, Kate; Rathouz, Paul J.; D'Onofrio, Brian M.; Rodgers, Joseph Lee; Waldman, Irwin D.

2008-01-01

Predictive associations between parenting and temperament during the first year of life and child conduct problems were assessed longitudinally in 1,863 offspring of a representative sample of women. Maternal ratings of infant fussiness, activity level, predictability, and positive affect each independently predicted maternal ratings of conduct…

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

NASA Technical Reports Server (NTRS)

Viken, Jeff; Dollyhigh, Samuel; Smith, Jeremy; Trani, Antonio; Baik, Hojong; Hinze, Nicholas; Ashiabor, Senanu

2006-01-01

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Predicting Health Resilience in Pediatric Type 1 Diabetes: A Test of the Resilience Model Framework.

PubMed

Rohan, Jennifer M; Huang, Bin; Pendley, Jennifer Shroff; Delamater, Alan; Dolan, Lawrence; Reeves, Grafton; Drotar, Dennis

2015-10-01

This research examined whether individual and family-level factors during the transition from late childhood to early adolescence protected individuals from an increased risk of poor glycemic control across time, which is a predictor of future diabetes-related complications (i.e., health resilience). This longitudinal, multisite study included 239 patients with type 1 diabetes and their caregivers. Glycemic control was based on hemoglobin A1c. Individual and family-level factors included: demographic variables, youth behavioral regulation, adherence (frequency of blood glucose monitoring), diabetes self-management, level of parental support for diabetes autonomy, level of youth mastery and responsibility for diabetes management, and diabetes-related family conflict. Longitudinal mixed-effects logistic regression indicated that testing blood glucose more frequently, better self-management, and less diabetes-related family conflict were indicators of health resilience. Multiple individual and family-level factors predicted risk for future health complications. Future research should develop interventions targeting specific individual and family-level factors to sustain glycemic control within recommended targets, which reduces the risk of developing future health complications during the transition to adolescence and adulthood. © The Author 2015. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Evaluation of Dynamic Coastal Response to Sea-level Rise Modifies Inundation Likelihood

NASA Technical Reports Server (NTRS)

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments, making assessments of SLR-induced hazards essential for informed decision making. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30x30m resolution predictions for more than 38,000 sq km of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Endothelial Progenitor Cell Levels Predict Future Physical Function: An Exploratory Analysis From the VA Enhanced Fitness Study.

PubMed

Povsic, Thomas J; Sloane, Richard; Pieper, Carl F; Pearson, Megan P; Peterson, Eric D; Cohen, Harvey J; Morey, Miriam C

2016-03-01

Levels of circulating progenitor cells (CPCs) are depleted with aging and chronic injury and are associated with level of physical functioning; however, little is known about the correlation of CPCs with longer-term measures of physical capabilities. We sought to determine the association of CPCs with future levels of physical function and with changes in physical function over time. CPCs were measured in 117 participants with impaired glucose tolerance in the Enhanced Fitness clinical trial based on the cell surface markers CD34 and CD133 and aldehyde dehydrogenase (ALDH) activity at baseline, 3 months, and 12 months. Physical function was assessed using usual and rapid gait speed, 6-minute walk distance, chair stand time, and SF-36 physical functioning score and reassessed at 3 and 12 months after clinical intervention. Higher baseline levels of CD133(+), CD34(+), CD133(+)CD34(+), and ALDH(br) were each highly predictive of faster gait speed and longer distance walked in 6 minutes at both 3 and 12 months. These associations remained robust after adjustment for age, body mass index, baseline covariates, and inflammation and were independent of interventions to improve physical fitness. Further, higher CPC levels predicted greater improvements in usual and rapid gait speed over 1 year. Baseline CPC levels are associated not only with baseline mobility but also with future physical function, including changes in gait speed. These findings suggest that CPC measurement may be useful as a marker of both current and future physiologic aging and functional decline. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The Future Revisited.

ERIC Educational Resources Information Center

Mason, Marilyn Gell

1996-01-01

Reviews earlier predictions about technological change in libraries, finds that providing equal access to information remains the library's mission, and forecasts the future. Topics include ownership versus access, electronic resources, information infrastructure, users, levels of service fees, circulation, librarians as "information…

Stress hormones predict hyperbolic time-discount rates six months later in adults.

PubMed

Takahashi, Taiki; Shinada, Mizuho; Inukai, Keigo; Tanida, Shigehito; Takahashi, Chisato; Mifune, Nobuhiro; Takagishi, Haruto; Horita, Yutaka; Hashimoto, Hirofumi; Yokota, Kunihiro; Kameda, Tatsuya; Yamagishi, Toshio

2010-01-01

Stress hormones have been associated with temporal discounting. Although time-discount rate is shown to be stable over a long term, no study to date examines whether individual differences in stress hormones could predict individuals' time-discount rates in the relatively distant future (e.g., six month later), which is of interest in neuroeconomics of stress-addiction association. We assessed 87 participants' salivary stress hormone (cortisol, cortisone, and alpha-amylase) levels and hyperbolic discounting of delayed rewards consisting of three magnitudes, at the time-interval of six months. For salivary steroid assays, we employed a liquid chromatography/ mass spectroscopy (LC/MS) method. The correlations between the stress hormone levels and time-discount rates were examined. We observed that salivary alpha-amylase (sAA) levels were negatively associated with time-discount rates in never-smokers. Notably, salivary levels of stress steroids (i.e., cortisol and cortisone) negatively and positively related to time-discount rates in men and women, respectively, in never-smokers. Ever-smokers' discount rates were not predicted from these stress hormone levels. Individual differences in stress hormone levels predict impulsivity in temporal discounting in the future. There are sex differences in the effect of stress steroids on temporal discounting; while there was no sex defference in the relationship between sAA and temporal discounting.

Tomorrow is Today: A Plan for Implementing the Study of the Future in the English Classroom.

ERIC Educational Resources Information Center

Thompson, David

This course, designed to help students explore serious thoughts about the future of society, is intended for an English literature class at the advanced secondary level. The course consists of nine interrelated modules that deal with the following topics: current predictions about the future, with special attention to the film "Future Shock";…

PREDICTING CLIMATE-INDUCED RANGE SHIFTS: MODEL DIFFERENCES AND MODEL RELIABILITY

EPA Science Inventory

Predicted changes in the global climate are likely to cause large shifts in the geographic ranges of many plant and animal species. To date, predictions of future range shifts have relied on a variety of modeling approaches with different levels of model accuracy. Using a common ...

Coupling centennial-scale shoreline change to sea-level rise and coastal morphology in the Gulf of Mexico using a Bayesian network

USGS Publications Warehouse

Plant, Nathaniel G.

2016-01-01

Predictions of coastal evolution driven by episodic and persistent processes associated with storms and relative sea-level rise (SLR) are required to test our understanding, evaluate our predictive capability, and to provide guidance for coastal management decisions. Previous work demonstrated that the spatial variability of long-term shoreline change can be predicted using observed SLR rates, tide range, wave height, coastal slope, and a characterization of the geomorphic setting. The shoreline is not suf- ficient to indicate which processes are important in causing shoreline change, such as overwash that depends on coastal dune elevations. Predicting dune height is intrinsically important to assess future storm vulnerability. Here, we enhance shoreline-change predictions by including dune height as a vari- able in a statistical modeling approach. Dune height can also be used as an input variable, but it does not improve the shoreline-change prediction skill. Dune-height input does help to reduce prediction uncer- tainty. That is, by including dune height, the prediction is more precise but not more accurate. Comparing hindcast evaluations, better predictive skill was found when predicting dune height (0.8) compared with shoreline change (0.6). The skill depends on the level of detail of the model and we identify an optimized model that has high skill and minimal overfitting. The predictive model can be implemented with a range of forecast scenarios, and we illustrate the impacts of a higher future sea-level. This scenario shows that the shoreline change becomes increasingly erosional and more uncertain. Predicted dune heights are lower and the dune height uncertainty decreases.

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

NASA Technical Reports Server (NTRS)

Viken, Jeff; Dollyhigh, Samuel; Smith, Jeremy; Trani, Antonio; Baik, Hojong; Hinze, Nicholas; Ashiabor, Senanu

2006-01-01

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Temperament and Parenting during the First Year of Life Predict Future Child Conduct Problems

PubMed Central

Lahey, Benjamin B.; Van Hulle, Carol A.; Keenan, Kate; Rathouz, Paul J.; D’Onofrio, Brian M.; Rodgers, Joseph Lee; Waldman, Irwin D.

2010-01-01

Predictive associations between parenting and temperament during the first year of life and child conduct problems were assessed longitudinally in 1,863 offspring of a representative sample of women. Maternal ratings of infant fussiness, activity level, predictability, and positive affect each independently predicted maternal ratings of conduct problems during ages 4–13 years. Furthermore, a significant interaction indicated that infants who were both low in fussiness and high in predictability were at very low risk for future conduct problems. Fussiness was a stronger predictor of conduct problems in boys whereas fearfulness was a stronger predictor in girls. Conduct problems also were robustly predicted by low levels of early mother-report cognitive stimulation. Interviewer-rated maternal responsiveness was a robust predictor of conduct problems, but only among infants low in fearfulness. Spanking during infancy predicted slightly more severe conduct problems, but the prediction was moderated by infant fussiness and positive affect. Thus, individual differences in risk for mother-rated conduct problems across childhood are already partly evident in maternal ratings of temperament during the first year of life and are predicted by early parenting and parenting-by-temperament interactions. PMID:18568397

Predicting Nitrate Transport under Future Climate Scenarios beneath the Nebraska Management Systems Evaluation Area (MSEA) site

NASA Astrophysics Data System (ADS)

Li, Y.; Akbariyeh, S.; Gomez Peña, C. A.; Bartlet-Hunt, S.

2017-12-01

Understanding the impacts of future climate change on soil hydrological processes and solute transport is crucial to develop appropriate strategies to minimize adverse impacts of agricultural activities on groundwater quality. The goal of this work is to evaluate the direct effects of climate change on the fate and transport of nitrate beneath a center-pivot irrigated corn field in Nebraska Management Systems Evaluation Area (MSEA) site. Future groundwater recharge rate and actual evapotranspiration rate were predicted based on an inverse modeling approach using climate data generated by Weather Research and Forecasting (WRF) model under the RCP 8.5 scenario, which was downscaled from global CCSM4 model to a resolution of 24 by 24 km2. A groundwater flow model was first calibrated based on historical groundwater table measurement and was then applied to predict future groundwater table in the period 2057-2060. Finally, predicted future groundwater recharge rate, actual evapotranspiration rate, and groundwater level, together with future precipitation data from WRF, were used in a three-dimensional (3D) model, which was validated based on rich historic data set collected from 1993-1996, to predict nitrate concentration in soil and groundwater from the year 2057 to 2060. Future groundwater recharge was found to be decreasing in the study area compared to average groundwater recharge data from the literature. Correspondingly, groundwater elevation was predicted to decrease (1 to 2 ft) over the five years of simulation. Predicted higher transpiration data from climate model resulted in lower infiltration of nitrate concentration in subsurface within the root zone.

Predicting Nitrate Transport under Future Climate Scenarios beneath the Nebraska Management Systems Evaluation Area (MSEA) site

NASA Astrophysics Data System (ADS)

Li, Y.; Akbariyeh, S.; Gomez Peña, C. A.; Bartlet-Hunt, S.

2016-12-01

Understanding the impacts of future climate change on soil hydrological processes and solute transport is crucial to develop appropriate strategies to minimize adverse impacts of agricultural activities on groundwater quality. The goal of this work is to evaluate the direct effects of climate change on the fate and transport of nitrate beneath a center-pivot irrigated corn field in Nebraska Management Systems Evaluation Area (MSEA) site. Future groundwater recharge rate and actual evapotranspiration rate were predicted based on an inverse modeling approach using climate data generated by Weather Research and Forecasting (WRF) model under the RCP 8.5 scenario, which was downscaled from global CCSM4 model to a resolution of 24 by 24 km2. A groundwater flow model was first calibrated based on historical groundwater table measurement and was then applied to predict future groundwater table in the period 2057-2060. Finally, predicted future groundwater recharge rate, actual evapotranspiration rate, and groundwater level, together with future precipitation data from WRF, were used in a three-dimensional (3D) model, which was validated based on rich historic data set collected from 1993-1996, to predict nitrate concentration in soil and groundwater from the year 2057 to 2060. Future groundwater recharge was found to be decreasing in the study area compared to average groundwater recharge data from the literature. Correspondingly, groundwater elevation was predicted to decrease (1 to 2 ft) over the five years of simulation. Predicted higher transpiration data from climate model resulted in lower infiltration of nitrate concentration in subsurface within the root zone.

Modular Engine Noise Component Prediction System (MCP) Technical Description and Assessment Document

NASA Technical Reports Server (NTRS)

Herkes, William H.; Reed, David H.

2005-01-01

This report describes an empirical prediction procedure for turbofan engine noise. The procedure generates predicted noise levels for several noise components, including inlet- and aft-radiated fan noise, and jet-mixing noise. This report discusses the noise source mechanisms, the development of the prediction procedures, and the assessment of the accuracy of these predictions. Finally, some recommendations for future work are presented.

Should coastal planners have concern over where land ice is melting?

PubMed Central

Larour, Eric; Ivins, Erik R.; Adhikari, Surendra

2017-01-01

There is a general consensus among Earth scientists that melting of land ice greatly contributes to sea-level rise (SLR) and that future warming will exacerbate the risks posed to human civilization. As land ice is lost to the oceans, both the Earth’s gravitational and rotational potentials are perturbed, resulting in strong spatial patterns in SLR, termed sea-level fingerprints. We lack robust forecasting models for future ice changes, which diminishes our ability to use these fingerprints to accurately predict local sea-level (LSL) changes. We exploit an advanced mathematical property of adjoint systems and determine the exact gradient of sea-level fingerprints with respect to local variations in the ice thickness of all of the world’s ice drainage systems. By exhaustively mapping these fingerprint gradients, we form a new diagnosis tool, henceforth referred to as gradient fingerprint mapping (GFM), that readily allows for improved assessments of future coastal inundation or emergence. We demonstrate that for Antarctica and Greenland, changes in the predictions of inundation at major port cities depend on the location of the drainage system. For example, in London, GFM shows LSL that is significantly affected by changes on the western part of the Greenland Ice Sheet (GrIS), whereas in New York, LSL change predictions are greatly sensitive to changes in the northeastern portions of the GrIS. We apply GFM to 293 major port cities to allow coastal planners to readily calculate LSL change as more reliable predictions of cryospheric mass changes become available. PMID:29152565

Physics-of-Failure Approach to Prognostics

NASA Technical Reports Server (NTRS)

Kulkarni, Chetan S.

2017-01-01

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in accurate prediction of the electrical components present in the system. In case of electric vehicles, computing remaining battery charge is safety-critical. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. In this presentation our approach to develop a system level health monitoring safety indicator for different electronic components is presented which runs estimation and prediction algorithms to determine state-of-charge and estimate remaining useful life of respective components. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making.

Davida Teller Award Lecture 2013: the importance of prediction and anticipation in the control of smooth pursuit eye movements.

PubMed

Kowler, Eileen; Aitkin, Cordelia D; Ross, Nicholas M; Santos, Elio M; Zhao, Min

2014-05-16

The ability of smooth pursuit eye movements to anticipate the future motion of targets has been known since the pioneering work of Dodge, Travis, and Fox (1930) and Westheimer (1954). This article reviews aspects of anticipatory smooth eye movements, focusing on the roles of the different internal or external cues that initiate anticipatory pursuit.We present new results showing that the anticipatory smooth eye movements evoked by different cues differ substantially, even when the cues are equivalent in the information conveyed about the direction of future target motion. Cues that convey an easily interpretable visualization of the motion path produce faster anticipatory smooth eye movements than the other cues tested, including symbols associated arbitrarily with the path, and the same target motion tested repeatedly over a block of trials. The differences among the cues may be understood within a common predictive framework in which the cues differ in the level of subjective certainty they provide about the future path. Pursuit may be driven by a combined signal in which immediate sensory motion, and the predictions about future motion generated by sets of cues, are weighted according to their respective levels of certainty. Anticipatory smooth eye movements, an overt indicator of expectations and predictions, may not be operating in isolation, but may be part of a global process in which the brain analyzes available cues, formulates predictions, and uses them to control perceptual, motor, and cognitive processes. © 2014 ARVO.

Inattention in primary school is not good for your future school achievement—A pattern classification study

PubMed Central

Bøe, Tormod; Lundervold, Arvid

2017-01-01

Inattention in childhood is associated with academic problems later in life. The contribution of specific aspects of inattentive behaviour is, however, less known. We investigated feature importance of primary school teachers’ reports on nine aspects of inattentive behaviour, gender and age in predicting future academic achievement. Primary school teachers of n = 2491 children (7–9 years) rated nine items reflecting different aspects of inattentive behaviour in 2002. A mean academic achievement score from the previous semester in high school (2012) was available for each youth from an official school register. All scores were at a categorical level. Feature importances were assessed by using multinominal logistic regression, classification and regression trees analysis, and a random forest algorithm. Finally, a comprehensive pattern classification procedure using k-fold cross-validation was implemented. Overall, inattention was rated as more severe in boys, who also obtained lower academic achievement scores in high school than girls. Problems related to sustained attention and distractibility were together with age and gender defined as the most important features to predict future achievement scores. Using these four features as input to a collection of classifiers employing k-fold cross-validation for prediction of academic achievement level, we obtained classification accuracy, precision and recall that were clearly better than chance levels. Primary school teachers’ reports of problems related to sustained attention and distractibility were identified as the two most important features of inattentive behaviour predicting academic achievement in high school. Identification and follow-up procedures of primary school children showing these characteristics should be prioritised to prevent future academic failure. PMID:29182663

Inattention in primary school is not good for your future school achievement-A pattern classification study.

PubMed

Lundervold, Astri J; Bøe, Tormod; Lundervold, Arvid

2017-01-01

Inattention in childhood is associated with academic problems later in life. The contribution of specific aspects of inattentive behaviour is, however, less known. We investigated feature importance of primary school teachers' reports on nine aspects of inattentive behaviour, gender and age in predicting future academic achievement. Primary school teachers of n = 2491 children (7-9 years) rated nine items reflecting different aspects of inattentive behaviour in 2002. A mean academic achievement score from the previous semester in high school (2012) was available for each youth from an official school register. All scores were at a categorical level. Feature importances were assessed by using multinominal logistic regression, classification and regression trees analysis, and a random forest algorithm. Finally, a comprehensive pattern classification procedure using k-fold cross-validation was implemented. Overall, inattention was rated as more severe in boys, who also obtained lower academic achievement scores in high school than girls. Problems related to sustained attention and distractibility were together with age and gender defined as the most important features to predict future achievement scores. Using these four features as input to a collection of classifiers employing k-fold cross-validation for prediction of academic achievement level, we obtained classification accuracy, precision and recall that were clearly better than chance levels. Primary school teachers' reports of problems related to sustained attention and distractibility were identified as the two most important features of inattentive behaviour predicting academic achievement in high school. Identification and follow-up procedures of primary school children showing these characteristics should be prioritised to prevent future academic failure.

Carotenoid-dependent coloration of male American kestrels predicts ability to reduce parasitic infections

NASA Astrophysics Data System (ADS)

Dawson, Russell D.; Bortolotti, Gary R.

2006-12-01

The signaling function of sexually selected traits, such as carotenoid-dependent avian plumage coloration, has received a great deal of recent attention especially with respect to parasitism and immunocompetence. We argue that parasite-mediated models of sexual selection may have an implicit temporal component that many researchers have ignored. For example, previous studies have demonstrated that carotenoid-dependent traits can signal past parasite exposure, current levels of parasitism, or the ability of individuals to manage parasitic infections in the future. We examined repeated measures of carotenoid-dependent skin color and blood parasitism in American kestrels ( Falco sparverius) to distinguish whether coloration might signal current parasitism or the potential to deal with infections in the future. We found no evidence that coloration was related to current levels of parasitism in either sex. However, coloration of males significantly predicted their response to parasitism; males with bright orange coloration during prelaying, when mate choice is occurring, were more likely than dull yellow males to reduce their levels of infection by the time incubation began. Coloration during prelaying may advertise a male’s health later in the breeding season. For kestrels, the ability to predict future health would be highly beneficial given the male’s role in providing food to his mate and offspring. Coloration of females was not a significant predictor of parasitism in the future, and we provide several possible explanations for this result.

Real-Time Safety Monitoring and Prediction for the National Airspace System

NASA Technical Reports Server (NTRS)

Roychoudhury, Indranil

2016-01-01

As new operational paradigms and additional aircraft are being introduced into the National Airspace System (NAS), maintaining safety in such a rapidly growing environment becomes more challenging. It is therefore desirable to have both an overview of the current safety of the airspace at different levels of granularity, as well an understanding of how the state of the safety will evolve into the future given the anticipated flight plans, weather forecasts, predicted health of assets in the airspace, and so on. To this end, we have developed a Real-Time Safety Monitoring (RTSM) that first, estimates the state of the NAS using the dynamic models. Then, given the state estimate and a probability distribution of future inputs to the NAS, the framework predicts the evolution of the NAS, i.e., the future state, and analyzes these future states to predict the occurrence of unsafe events. The entire probability distribution of airspace safety metrics is computed, not just point estimates, without significant assumptions regarding the distribution type and or parameters. We demonstrate our overall approach by predicting the occurrence of some unsafe events and show how these predictions evolve in time as flight operations progress.

Symbolic Processing Combined with Model-Based Reasoning

NASA Technical Reports Server (NTRS)

James, Mark

2009-01-01

A computer program for the detection of present and prediction of future discrete states of a complex, real-time engineering system utilizes a combination of symbolic processing and numerical model-based reasoning. One of the biggest weaknesses of a purely symbolic approach is that it enables prediction of only future discrete states while missing all unmodeled states or leading to incorrect identification of an unmodeled state as a modeled one. A purely numerical approach is based on a combination of statistical methods and mathematical models of the applicable physics and necessitates development of a complete model to the level of fidelity required for prediction. In addition, a purely numerical approach does not afford the ability to qualify its results without some form of symbolic processing. The present software implements numerical algorithms to detect unmodeled events and symbolic algorithms to predict expected behavior, correlate the expected behavior with the unmodeled events, and interpret the results in order to predict future discrete states. The approach embodied in this software differs from that of the BEAM methodology (aspects of which have been discussed in several prior NASA Tech Briefs articles), which provides for prediction of future measurements in the continuous-data domain.

Father Involvement and Young, Rural African American Men's Engagement in Substance Misuse and Multiple Sexual Partnerships.

PubMed

Barton, Allen W; Kogan, Steven M; Cho, Junhan; Brown, Geoffrey L

2015-12-01

This study was designed to examine the associations of biological father and social father involvement during childhood with African American young men's development and engagement in risk behaviors. With a sample of 505 young men living in the rural South of the United States, a dual mediation model was tested in which retrospective reports of involvement from biological fathers and social fathers were linked to young men's substance misuse and multiple sexual partnerships through men's relational schemas and future expectations. Results from structural equation modeling indicated that levels of involvement from biological fathers and social fathers predicted young men's relational schemas; only biological fathers' involvement predicted future expectations. In turn, future expectations predicted levels of substance misuse, and negative relational schemas predicted multiple sexual partnerships. Biological fathers' involvement evinced significant indirect associations with young men's substance misuse and multiple sexual partnerships through both schemas and expectations; social fathers' involvement exhibited an indirect association with multiple sexual partnerships through relational schemas. Findings highlight the unique influences of biological fathers and social fathers on multiple domains of African American young men's psychosocial development that subsequently render young men more or less likely to engage in risk behaviors.

Pathways between self-esteem and depression in couples.

PubMed

Johnson, Matthew D; Galambos, Nancy L; Finn, Christine; Neyer, Franz J; Horne, Rebecca M

2017-04-01

Guided by concepts from a relational developmental perspective, this study examined intra- and interpersonal associations between self-esteem and depressive symptoms in a sample of 1,407 couples surveyed annually across 6 years in the Panel Analysis of Intimate Relations and Family Dynamics (pairfam) study. Autoregressive cross-lagged model results demonstrated that self-esteem predicted future depressive symptoms for male partners at all times, replicating the vulnerability model for men (low self-esteem is a risk factor for future depression). Additionally, a cross-partner association emerged between symptoms of depression: Higher depressive symptoms in one partner were associated with higher levels of depression in the other partner one year later. Finally, supportive dyadic coping, the support that partners reported providing to one another in times of stress, was tested as a potential interpersonal mediator of pathways between self-esteem and depression. Female partners' higher initial levels of self-esteem predicted male partners' subsequent reports of increased supportive dyadic coping, which, in turn, predicted higher self-esteem and fewer symptoms of depression among female partners in the future. Male partners' initially higher symptoms of depression predicted less frequent supportive dyadic coping subsequently reported by female partners, which was associated with increased feelings of depression in the future. Couple relations represent an important contextual factor that may be implicated in the developmental pathways connecting self-esteem and symptoms of depression. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The effects of climate change on storm surges around the United Kingdom.

PubMed

Lowe, J A; Gregory, J M

2005-06-15

Coastal flooding is often caused by extreme events, such as storm surges. In this study, improved physical models have been used to simulate the climate system and storm surges, and to predict the effect of increased atmospheric concentrations of greenhouse gases on the surges. In agreement with previous studies, this work indicates that the changes in atmospheric storminess and the higher time-average sea-level predicted for the end of the twenty-first century will lead to changes in the height of water levels measured relative to the present day tide. However, the details of these projections differ somewhat from earlier assessments. Uncertainty in projections of future extreme water levels arise from uncertainty in the amount and timing of future greenhouse gas emissions, uncertainty in the physical models used to simulate the climate system and from the natural variability of the system. The total uncertainty has not yet been reliably quantified and achieving this should be a priority for future research.

Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood

USGS Publications Warehouse

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments1, 2, making assessments of SLR-induced hazards essential for informed decision making3. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30 × 30 m resolution predictions for more than 38,000 km2 of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Managing for No Net Loss of Ecological Services: An Approach for Quantifying Loss of Coastal Wetlands due to Sea Level Rise

NASA Astrophysics Data System (ADS)

Kassakian, Jennifer; Jones, Ann; Martinich, Jeremy; Hudgens, Daniel

2017-05-01

Sea level rise has the potential to substantially alter the extent and nature of coastal wetlands and the critical ecological services they provide. In making choices about how to respond to rising sea level, planners are challenged with weighing easily quantified risks (e.g., loss of property value due to inundation) against those that are more difficult to quantify (e.g., loss of primary production or carbon sequestration services provided by wetlands due to inundation). Our goal was to develop a cost-effective, appropriately-scaled, model-based approach that allows planners to predict, under various sea level rise and response scenarios, the economic cost of wetland loss—with the estimates proxied by the costs of future restoration required to maintain the existing level of wetland habitat services. Our approach applies the Sea Level Affecting Marshes Model to predict changes in wetland habitats over the next century, and then applies Habitat Equivalency Analysis to predict the cost of restoration projects required to maintain ecological services at their present, pre-sea level rise level. We demonstrate the application of this approach in the Delaware Bay estuary and in the Indian River Lagoon (Florida), and discuss how this approach can support future coastal decision-making.

Managing for No Net Loss of Ecological Services: An Approach for Quantifying Loss of Coastal Wetlands due to Sea Level Rise.

PubMed

Kassakian, Jennifer; Jones, Ann; Martinich, Jeremy; Hudgens, Daniel

2017-05-01

Sea level rise has the potential to substantially alter the extent and nature of coastal wetlands and the critical ecological services they provide. In making choices about how to respond to rising sea level, planners are challenged with weighing easily quantified risks (e.g., loss of property value due to inundation) against those that are more difficult to quantify (e.g., loss of primary production or carbon sequestration services provided by wetlands due to inundation). Our goal was to develop a cost-effective, appropriately-scaled, model-based approach that allows planners to predict, under various sea level rise and response scenarios, the economic cost of wetland loss-with the estimates proxied by the costs of future restoration required to maintain the existing level of wetland habitat services. Our approach applies the Sea Level Affecting Marshes Model to predict changes in wetland habitats over the next century, and then applies Habitat Equivalency Analysis to predict the cost of restoration projects required to maintain ecological services at their present, pre-sea level rise level. We demonstrate the application of this approach in the Delaware Bay estuary and in the Indian River Lagoon (Florida), and discuss how this approach can support future coastal decision-making.

An Examination of Exercise-Induced Feeling States and Their Association With Future Participation in Physical Activity Among Older Adults.

PubMed

Brunet, Jennifer; Guérin, Eva; Speranzini, Nicolas

2018-01-01

Although exercise-induced feeling states may play a role in driving future behavior, their role in relation to older adults' participation in physical activity (PA) has seldom been considered. The objectives of this study were to describe changes in older adults' feeling states during exercise, and examine if levels of and changes in feeling states predicted their future participation in PA. Self-reported data on feeling states were collected from 82 older adults immediately before, during, and after a moderate-intensity exercise session, and on participation in PA 1 month later. Data were analyzed using latent growth modeling. Feelings of revitalization, positive engagement, and tranquility decreased during exercise, whereas feelings of physical exhaustion increased. Feelings of revitalization immediately before the exercise session predicted future participation in PA; changes in feeling states did not. This study does not provide empirical evidence that older adults' exercise-induced feeling states predict their future participation in PA.

Two routes toward optimism: how agentic and communal themes in autobiographical memories guide optimism for the future.

PubMed

Austin, Adrienne; Costabile, Kristi

2017-11-01

Autobiographical memories are particularly adaptive because they function not only to preserve the past, but also to direct our future thoughts and behaviours. Two studies were conducted to examine how communal and agentic themes of positive autobiographical memories differentially predicted the route from autobiographical memories to optimism for the future. Across two studies, results revealed that the degree to which participants focused on communal themes in their autobiographical memories predicted their experience of nostalgia. In turn, the experience of nostalgia increased participants' levels of self-esteem and in turn, optimism for the future. By contrast, the degree to which participants focused on agentic themes in their memories predicted self-esteem and optimism, operating outside the experience of nostalgia. These effects remained even after controlling for self-focused attention. Together, these studies provide greater understanding of the interrelations among autobiographical memory, self-concept, and time, and demonstrate how agency and communion operate to influence perceptions of one's future when thinking about the past.

Information theory of adaptation in neurons, behavior, and mood.

PubMed

Sharpee, Tatyana O; Calhoun, Adam J; Chalasani, Sreekanth H

2014-04-01

The ability to make accurate predictions of future stimuli and consequences of one's actions are crucial for the survival and appropriate decision-making. These predictions are constantly being made at different levels of the nervous system. This is evidenced by adaptation to stimulus parameters in sensory coding, and in learning of an up-to-date model of the environment at the behavioral level. This review will discuss recent findings that actions of neurons and animals are selected based on detailed stimulus history in such a way as to maximize information for achieving the task at hand. Information maximization dictates not only how sensory coding should adapt to various statistical aspects of stimuli, but also that reward function should adapt to match the predictive information from past to future. Copyright © 2013 Elsevier Ltd. All rights reserved.

When relationships estimated in the past cannot be used to predict the future: using mechanistic models to predict landscape ecological dynamics in a changing world

Treesearch

Eric J. Gustafson

2013-01-01

Researchers and natural resource managers need predictions of how multiple global changes (e.g., climate change, rising levels of air pollutants, exotic invasions) will affect landscape composition and ecosystem function. Ecological predictive models used for this purpose are constructed using either a mechanistic (process-based) or a phenomenological (empirical)...

23 CFR 772.9 - Traffic noise prediction.

Code of Federal Regulations, 2014 CFR

2014-04-01

...) Average pavement type shall be used in the FHWA TNM for future noise level prediction unless a highway agency substantiates the use of a different pavement type for approval by the FHWA. (c) Noise contour... impact for the design year shall be used. ...

23 CFR 772.9 - Traffic noise prediction.

Code of Federal Regulations, 2012 CFR

2012-04-01

...) Average pavement type shall be used in the FHWA TNM for future noise level prediction unless a highway agency substantiates the use of a different pavement type for approval by the FHWA. (c) Noise contour... impact for the design year shall be used. ...

23 CFR 772.9 - Traffic noise prediction.

Code of Federal Regulations, 2013 CFR

2013-04-01

...) Average pavement type shall be used in the FHWA TNM for future noise level prediction unless a highway agency substantiates the use of a different pavement type for approval by the FHWA. (c) Noise contour... impact for the design year shall be used. ...

Prediction of future risk of insulin resistance and metabolic syndrome based on Korean boy's metabolite profiling.

PubMed

Lee, AeJin; Jang, Han Byul; Ra, Moonjin; Choi, Youngshim; Lee, Hye-Ja; Park, Ju Yeon; Kang, Jae Heon; Park, Kyung-Hee; Park, Sang Ick; Song, Jihyun

2015-01-01

Childhood obesity is strongly related to future insulin resistance and metabolic syndrome. Thus, identifying early biomarkers of obesity-related diseases based on metabolic profiling is useful to control future metabolic disorders. We compared metabolic profiles between obese and normal-weight children and investigated specific biomarkers of future insulin resistance and metabolic syndrome. In all, 186 plasma metabolites were analysed at baseline and after 2 years in 109 Korean boys (age 10.5±0.4 years) from the Korean Child Obesity Cohort Study using the AbsoluteIDQ™ p180 Kit. We observed that levels of 41 metabolites at baseline and 40 metabolites at follow-up were significantly altered in obese children (p<0.05). Obese children showed significantly higher levels of branched-chain amino acids (BCAAs) and several acylcarnitines and lower levels of acyl-alkyl phosphatidylcholines. Also, baseline BCAAs were significantly positively correlated with both homeostasis model assessment for insulin resistance (HOMA-IR) and continuous metabolic risk score at the 2-year follow-up. In logistic regression analyses with adjustments for degree of obesity at baseline, baseline BCAA concentration, greater than the median value, was identified as a predictor of future risk of insulin resistance and metabolic syndrome. High BCAA concentration could be "early" biomarkers for predicting future metabolic diseases. Copyright © 2014 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

Dimensionality of coping and its relation to depression.

PubMed

Rohde, P; Lewinsohn, P M; Tilson, M; Seeley, J R

1990-03-01

The dimensionality of coping, as measured by 65 items from 3 commonly used instruments, and the relation of coping and stress to concurrent and future depression were studied in a community sample of 742 older (greater than or equal to 50 years old) adults. Measures of coping, stress, and depression were obtained at 2 time points over a 2-year period. Depression was assessed by symptom checklist and by diagnostic interview. Three coping factors--Cognitive Self-Control, Ineffective Escapism, and Solace Seeking--that had adequate psychometric properties and accounted for 25% of the total item variance were identified. Ineffective Escapism was associated with current depression and had a direct and interactive effect on future depression, exacerbating the negative impact of stress rather than acting as a buffer. Although Cognitive Self-Control was unrelated to either concurrent or future depression, Solace Seeking significantly buffered the effect of stress in predicting a future diagnosis of depression. Stress and initial depression level predicted both measures of future depression. Gender (being female) predicted the future diagnosis of depression but not the increase of depressive symptoms.

Predictions of future ephemeral springtime waterbird stopover habitat availability under global change

USGS Publications Warehouse

Uden, Daniel R.; Allen, Craig R.; Bishop, Andrew A.; Grosse, Roger; Jorgensen, Christopher F.; LaGrange, Theodore G.; Stutheit, Randy G.; Vrtiska, Mark P.

2015-01-01

In the present period of rapid, worldwide change in climate and landuse (i.e., global change), successful biodiversity conservation warrants proactive management responses, especially for long-distance migratory species. However, the development and implementation of management strategies can be impeded by high levels of uncertainty and low levels of control over potentially impactful future events and their effects. Scenario planning and modeling are useful tools for expanding perspectives and informing decisions under these conditions. We coupled scenario planning and statistical modeling to explain and predict playa wetland inundation (i.e., presence/absence of water) and ponded area (i.e., extent of water) in the Rainwater Basin, an anthropogenically altered landscape that provides critical stopover habitat for migratory waterbirds. Inundation and ponded area models for total wetlands, those embedded in rowcrop fields, and those not embedded in rowcrop fields were trained and tested with wetland ponding data from 2004 and 2006–2009, and then used to make additional predictions under two alternative climate change scenarios for the year 2050, yielding a total of six predictive models and 18 prediction sets. Model performance ranged from moderate to good, with inundation models outperforming ponded area models, and models for non-rowcrop-embedded wetlands outperforming models for total wetlands and rowcrop-embedded wetlands. Model predictions indicate that if the temperature and precipitation changes assumed under our climate change scenarios occur, wetland stopover habitat availability in the Rainwater Basin could decrease in the future. The results of this and similar studies could be aggregated to increase knowledge about the potential spatial and temporal distributions of future stopover habitat along migration corridors, and to develop and prioritize multi-scale management actions aimed at mitigating the detrimental effects of global change on migratory waterbird populations.

Modelling obesity trends in Australia: unravelling the past and predicting the future.

PubMed

Hayes, A J; Lung, T W C; Bauman, A; Howard, K

2017-01-01

Modelling is increasingly being used to predict the epidemiology of obesity progression and its consequences. The aims of this study were: (a) to present and validate a model for prediction of obesity among Australian adults and (b) to use the model to project the prevalence of obesity and severe obesity by 2025. Individual level simulation combined with survey estimation techniques to model changing population body mass index (BMI) distribution over time. The model input population was derived from a nationally representative survey in 1995, representing over 12 million adults. Simulations were run for 30 years. The model was validated retrospectively and then used to predict obesity and severe obesity by 2025 among different aged cohorts and at a whole population level. The changing BMI distribution over time was well predicted by the model and projected prevalence of weight status groups agreed with population level data in 2008, 2012 and 2014.The model predicts more growth in obesity among younger than older adult cohorts. Projections at a whole population level, were that healthy weight will decline, overweight will remain steady, but obesity and severe obesity prevalence will continue to increase beyond 2016. Adult obesity prevalence was projected to increase from 19% in 1995 to 35% by 2025. Severe obesity (BMI>35), which was only around 5% in 1995, was projected to be 13% by 2025, two to three times the 1995 levels. The projected rise in obesity severe obesity will have more substantial cost and healthcare system implications than in previous decades. Having a robust epidemiological model is key to predicting these long-term costs and health outcomes into the future.

Predicting the size and elevation of future mountain forests: Scaling macroclimate to microclimate

NASA Astrophysics Data System (ADS)

Cory, S. T.; Smith, W. K.

2017-12-01

Global climate change is predicted to alter continental scale macroclimate and regional mesoclimate. Yet, it is at the microclimate scale that organisms interact with their physiochemical environments. Thus, to predict future changes in the biota such as biodiversity and distribution patterns, a quantitative coupling between macro-, meso-, and microclimatic parameters must be developed. We are evaluating the impact of climate change on the size and elevational distribution of conifer mountain forests by determining the microclimate necessary for new seedling survival at the elevational boundaries of the forest. This initial life stage, only a few centimeters away from the soil surface, appears to be the bottleneck to treeline migration and the expansion or contraction of a conifer mountain forest. For example, survival at the alpine treeline is extremely rare and appears to be limited to facilitated microsites with low sky exposure. Yet, abundant mesoclimate data from standard weather stations have rarely been scaled to the microclimate level. Our research is focusing on an empirical downscaling approach linking microclimate measurements at favorable seedling microsites to the meso- and macro-climate levels. Specifically, mesoclimate values of air temperature, relative humidity, incident sunlight, and wind speed from NOAA NCEI weather stations can be extrapolated to the microsite level that is physiologically relevant for seedling survival. Data will be presented showing a strong correlation between incident sunlight measured at 2-m and seedling microclimate, despite large differences from seedling/microsite temperatures. Our downscaling approach will ultimately enable predictions of microclimate from the much more abundant mesoclimate data available from a variety of sources. Thus, scaling from macro- to meso- to microclimate will be possible, enabling predictions of climate change models to be translated to the microsite level. This linkage between measurement scales will enable a more precise prediction of the effects of climate change on the future extent and elevational distribution of our mountain forests and an accompanying array of critical ecosystem services.

Metacognitive deficits predict future levels of negative symptoms in schizophrenia controlling for neurocognition, affect recognition, and self-expectation of goal attainment.

PubMed

Lysaker, Paul H; Kukla, Marina; Dubreucq, Julien; Gumley, Andrew; McLeod, Hamish; Vohs, Jenifer L; Buck, Kelly D; Minor, Kyle S; Luther, Lauren; Leonhardt, Bethany L; Belanger, Elizabeth A; Popolo, Raffaele; Dimaggio, Giancarlo

2015-10-01

The recalcitrance of negative symptoms in the face of pharmacologic treatment has spurred interest in understanding the psychological factors that contribute to their formation and persistence. Accordingly, this study investigated whether deficits in metacognition, or the ability to form integrated ideas about oneself, others, and the world, prospectively predicted levels of negative symptoms independent of deficits in neurocognition, affect recognition and defeatist beliefs. Participants were 53 adults with a schizophrenia spectrum disorder. Prior to entry into a rehabilitation program, all participants completed concurrent assessments of metacognition with the Metacognitive Assessment Scale-Abbreviated, negative symptoms with the Positive and Negative Syndrome Scale, neurocognition with the MATRICS battery, affect recognition with the Bell Lysaker Emotion Recognition Task, and one form of defeatist beliefs with the Recovery Assessment Scale. Negative symptoms were then reassessed one week, 9weeks, and 17weeks after entry into the program. A mixed effects regression model revealed that after controlling for baseline negative symptoms, a general index of neurocognition, defeatist beliefs and capacity for affect recognition, lower levels of metacognition predicted higher levels of negative symptoms across all subsequent time points. Poorer metacognition was able to predict later levels of elevated negative symptoms even after controlling for initial levels of negative symptoms. Results may suggest that metacognitive deficits are a risk factor for elevated levels of negative symptoms in the future. Clinical implications are also discussed. Published by Elsevier B.V.

Influence versus intent for predictive analytics in situation awareness

NASA Astrophysics Data System (ADS)

Cui, Biru; Yang, Shanchieh J.; Kadar, Ivan

2013-05-01

Predictive analytics in situation awareness requires an element to comprehend and anticipate potential adversary activities that might occur in the future. Most work in high level fusion or predictive analytics utilizes machine learning, pattern mining, Bayesian inference, and decision tree techniques to predict future actions or states. The emergence of social computing in broader contexts has drawn interests in bringing the hypotheses and techniques from social theory to algorithmic and computational settings for predictive analytics. This paper aims at answering the question on how influence and attitude (some interpreted such as intent) of adversarial actors can be formulated and computed algorithmically, as a higher level fusion process to provide predictions of future actions. The challenges in this interdisciplinary endeavor include drawing existing understanding of influence and attitude in both social science and computing fields, as well as the mathematical and computational formulation for the specific context of situation to be analyzed. The study of `influence' has resurfaced in recent years due to the emergence of social networks in the virtualized cyber world. Theoretical analysis and techniques developed in this area are discussed in this paper in the context of predictive analysis. Meanwhile, the notion of intent, or `attitude' using social theory terminologies, is a relatively uncharted area in the computing field. Note that a key objective of predictive analytics is to identify impending/planned attacks so their `impact' and `threat' can be prevented. In this spirit, indirect and direct observables are drawn and derived to infer the influence network and attitude to predict future threats. This work proposes an integrated framework that jointly assesses adversarial actors' influence network and their attitudes as a function of past actions and action outcomes. A preliminary set of algorithms are developed and tested using the Global Terrorism Database (GTD). Our results reveals the benefits to perform joint predictive analytics with both attitude and influence. At the same time, we discover significant challenges in deriving influence and attitude from indirect observables for diverse adversarial behavior. These observations warrant further investigation of optimal use of influence and attitude for predictive analytics, as well as the potential inclusion of other environmental or capability elements for the actors.

Regional analysis of drought and heat impacts on forests: current and future science directions.

PubMed

Law, Beverly E

2014-12-01

Accurate assessments of forest response to current and future climate and human actions are needed at regional scales. Predicting future impacts on forests will require improved analysis of species-level adaptation, resilience, and vulnerability to mortality. Land system models can be enhanced by creating trait-based groupings of species that better represent climate sensitivity, such as risk of hydraulic failure from drought. This emphasizes the need for more coordinated in situ and remote sensing observations to track changes in ecosystem function, and to improve model inputs, spatio-temporal diagnosis, and predictions of future conditions, including implications of actions to mitigate climate change. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

In a year, memory will benefit from learning, tomorrow it won't: distance and construal level effects on the basis of metamemory judgments.

PubMed

Halamish, Vered; Nussinson, Ravit; Ben-Ari, Liat

2013-09-01

Metamemory judgments may rely on 2 bases of information: subjective experience and abstract theories about memory. On the basis of construal level theory, we predicted that psychological distance and construal level (i.e., concrete vs. abstract thinking) would have a qualitative impact on the relative reliance on these 2 bases: When considering learning from proximity or under a low-construal mindset, learners would rely more heavily on their experience, whereas when considering learning from a distance or under a high-construal mindset, they would rely more heavily on their abstract theories. Consistent with this prediction, results of 2 experiments revealed that temporal distance (Experiment 1) and construal level (Experiment 2) affected the stability bias--the failure to predict the benefits of learning. When considering learning from proximity or using a low-construal mindset, participants relied less heavily on their theory regarding the benefits of learning and were therefore insensitive to future learning. However, when considering learning from temporal distance or using a high-construal mindset, participants relied more heavily on their theory and were therefore better able to predict the benefits of future learning, thus overcoming the stability bias. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Factors Predicting Post-High School Employment for Young Adults with Visual Impairments

ERIC Educational Resources Information Center

McDonnall, Michele Capella

2010-01-01

Although low levels of employment among transition-age youth with visual impairments (VI) have long been a concern, empirical research in this area is very limited. The purpose of this study was to identify factors that predict future employment for this population and to compare these factors to the factors that predict employment for the general…

Predicting climate-induced range shifts: model differences and model reliability.

Treesearch

Joshua J. Lawler; Denis White; Ronald P. Neilson; Andrew R. Blaustein

2006-01-01

Predicted changes in the global climate are likely to cause large shifts in the geographic ranges of many plant and animal species. To date, predictions of future range shifts have relied on a variety of modeling approaches with different levels of model accuracy. Using a common data set, we investigated the potential implications of alternative modeling approaches for...

Loneliness and Suicidal Risk in Young Adults: Does Believing in a Changeable Future Help Minimize Suicidal Risk Among the Lonely?

PubMed

Chang, Edward C; Wan, Liangqiu; Li, Pengzi; Guo, Yuncheng; He, Jiaying; Gu, Yu; Wang, Yingjie; Li, Xiaoqing; Zhang, Zhan; Sun, Yingrui; Batterbee, Casey N-H; Chang, Olivia D; Lucas, Abigael G; Hirsch, Jameson K

2017-07-04

This study examined loneliness and future orientation as predictors of suicidal risk, namely, depressive symptoms and suicide ideation, in a sample of 228 college students (54 males and 174 females). Results of regression analyses indicated that loneliness was a significant predictor of both indices of suicidal risk. The inclusion of future orientation was found to significantly augment the prediction model of both depressive symptoms and suicide ideation, even after accounting for loneliness. Noteworthy, beyond loneliness and future orientation, the Loneliness × Future Orientation interaction term was found to further augment both prediction models of suicidal risk. Consistent with the notion that future orientation is an important buffer of suicidal risk, among lonely students, those with high future orientation, compared to low future orientation, were found to report significantly lower levels of depressive symptoms and suicide ideation. Some implications of the present findings for studying both risk and protective factors associated with suicidal risk in young adults are discussed.

Likelihood of achieving air quality targets under model uncertainties.

PubMed

Digar, Antara; Cohan, Daniel S; Cox, Dennis D; Kim, Byeong-Uk; Boylan, James W

2011-01-01

Regulatory attainment demonstrations in the United States typically apply a bright-line test to predict whether a control strategy is sufficient to attain an air quality standard. Photochemical models are the best tools available to project future pollutant levels and are a critical part of regulatory attainment demonstrations. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed. This paper introduces a computationally efficient methodology for estimating the likelihood that an emission control strategy will achieve an air quality objective in light of uncertainties in photochemical model input parameters (e.g., uncertain emission and reaction rates, deposition velocities, and boundary conditions). The method incorporates Monte Carlo simulations of a reduced form model representing pollutant-precursor response under parametric uncertainty to probabilistically predict the improvement in air quality due to emission control. The method is applied to recent 8-h ozone attainment modeling for Atlanta, Georgia, to assess the likelihood that additional controls would achieve fixed (well-defined) or flexible (due to meteorological variability and uncertain emission trends) targets of air pollution reduction. The results show that in certain instances ranking of the predicted effectiveness of control strategies may differ between probabilistic and deterministic analyses.

Using a Bayesian network to predict barrier island geomorphologic characteristics

USGS Publications Warehouse

Gutierrez, Ben; Plant, Nathaniel G.; Thieler, E. Robert; Turecek, Aaron

2015-01-01

Quantifying geomorphic variability of coastal environments is important for understanding and describing the vulnerability of coastal topography, infrastructure, and ecosystems to future storms and sea level rise. Here we use a Bayesian network (BN) to test the importance of multiple interactions between barrier island geomorphic variables. This approach models complex interactions and handles uncertainty, which is intrinsic to future sea level rise, storminess, or anthropogenic processes (e.g., beach nourishment and other forms of coastal management). The BN was developed and tested at Assateague Island, Maryland/Virginia, USA, a barrier island with sufficient geomorphic and temporal variability to evaluate our approach. We tested the ability to predict dune height, beach width, and beach height variables using inputs that included longer-term, larger-scale, or external variables (historical shoreline change rates, distances to inlets, barrier width, mean barrier elevation, and anthropogenic modification). Data sets from three different years spanning nearly a decade sampled substantial temporal variability and serve as a proxy for analysis of future conditions. We show that distinct geomorphic conditions are associated with different long-term shoreline change rates and that the most skillful predictions of dune height, beach width, and beach height depend on including multiple input variables simultaneously. The predictive relationships are robust to variations in the amount of input data and to variations in model complexity. The resulting model can be used to evaluate scenarios related to coastal management plans and/or future scenarios where shoreline change rates may differ from those observed historically.

Stock price prediction using geometric Brownian motion

NASA Astrophysics Data System (ADS)

Farida Agustini, W.; Restu Affianti, Ika; Putri, Endah RM

2018-03-01

Geometric Brownian motion is a mathematical model for predicting the future price of stock. The phase that done before stock price prediction is determine stock expected price formulation and determine the confidence level of 95%. On stock price prediction using geometric Brownian Motion model, the algorithm starts from calculating the value of return, followed by estimating value of volatility and drift, obtain the stock price forecast, calculating the forecast MAPE, calculating the stock expected price and calculating the confidence level of 95%. Based on the research, the output analysis shows that geometric Brownian motion model is the prediction technique with high rate of accuracy. It is proven with forecast MAPE value ≤ 20%.

Perceived Marginalization and the Prediction of Romantic Relationship Stability

ERIC Educational Resources Information Center

Lehmiller, Justin J.; Agnew, Christopher R.

2007-01-01

The present research examined how perceived marginalization of one's romantic relationship is associated with level of future commitment to and stability of that involvement. Results from a 7-month longitudinal study of romantically involved individuals (N = 215) revealed that perceived social network marginalization at Time 1 predicted breakup…

A Longitudinal Examination of Parenting Behaviors and Perceived Discrimination Predicting Latino Adolescents' Ethnic Identity

ERIC Educational Resources Information Center

Umana-Taylor, Adriana J.; Guimond, Amy B.

2010-01-01

Characteristics of the familial and societal context were examined as predictors of Latino adolescents' (N = 323; 49.5% female) ethnic identity. Consistent with previous work, familial ethnic socialization significantly predicted future levels of ethnic identity exploration, resolution, and affirmation for both male adolescents and female…

Using Conversation Topics for Predicting Therapy Outcomes in Schizophrenia

PubMed Central

Howes, Christine; Purver, Matthew; McCabe, Rose

2013-01-01

Previous research shows that aspects of doctor-patient communication in therapy can predict patient symptoms, satisfaction and future adherence to treatment (a significant problem with conditions such as schizophrenia). However, automatic prediction has so far shown success only when based on low-level lexical features, and it is unclear how well these can generalize to new data, or whether their effectiveness is due to their capturing aspects of style, structure or content. Here, we examine the use of topic as a higher-level measure of content, more likely to generalize and to have more explanatory power. Investigations show that while topics predict some important factors such as patient satisfaction and ratings of therapy quality, they lack the full predictive power of lower-level features. For some factors, unsupervised methods produce models comparable to manual annotation. PMID:23943658

The Science-Policy Link: Stakeholder Reactions to the Uncertainties of Future Sea Level Rise

NASA Astrophysics Data System (ADS)

Plag, H.; Bye, B.

2011-12-01

Policy makers and stakeholders in the coastal zone are equally challenged by the risk of an anticipated rise of coastal Local Sea Level (LSL) as a consequence of future global warming. Many low-lying and often densely populated coastal areas are under risk of increased inundation. More than 40% of the global population is living in or near the coastal zone and this fraction is steadily increasing. A rise in LSL will increase the vulnerability of coastal infrastructure and population dramatically, with potentially devastating consequences for the global economy, society, and environment. Policy makers are faced with a trade-off between imposing today the often very high costs of coastal protection and adaptation upon national economies and leaving the costs of potential major disasters to future generations. They are in need of actionable information that provides guidance for the development of coastal zones resilient to future sea level changes. Part of this actionable information comes from risk and vulnerability assessments, which require information on future LSL changes as input. In most cases, a deterministic approach has been applied based on predictions of the plausible range of future LSL trajectories as input. However, there is little consensus in the scientific community on how these trajectories should be determined, and what the boundaries of the plausible range are. Over the last few years, many publications in Science, Nature and other peer-reviewed scientific journals have revealed a broad range of possible futures and significant epistemic uncertainties and gaps concerning LSL changes. Based on the somewhat diffuse science input, policy and decision makers have made rather different choices for mitigation and adaptation in cases such as Venice, The Netherlands, New York City, and the San Francisco Bay area. Replacing the deterministic, prediction-based approach with a statistical one that fully accounts for the uncertainties and epistemic gaps would provide a different kind of science input to policy makers and stakeholders. Like in many other insurance problems (for example, earthquakes), where deterministic predictions are not possible and decisions have to be made on the basis of statistics and probabilities, the statistical approach to coastal resilience would require stakeholders to make decisions on the basis of probabilities instead of predictions. The science input for informed decisions on adaptation would consist of general probabilities of decadal to century scale sea level changes derived from paleo records, including the probabilities for large and rapid rises. Similar to other problems where the appearance of a hazard is associated with a high risk (like a fire in a house), this approach would also require a monitoring and warning system (a "smoke detector") capable of detecting any onset of a rapid sea level rise.

Predicting Vessel Trajectories from Ais Data Using R

DTIC Science & Technology

2017-06-01

future position at the expectation level set by the user, therefore producing a valid methodology for both estimating the future vessel location and... methodology for both estimating the future vessel location and for assessing anomalous vessel behavior. vi THIS PAGE INTENTIONALLY LEFT BLANK vii... methodology , that brings them one step closer to attaining these goals. A key idea in the current literature is that the series of vessel locations

Fear of Terrorism in New York After the September 11 Terrorist Attacks: Implications for Emergency Mental Health and Preparedness

PubMed Central

Boscarino, Joseph A.; Figley, Charles R.; Adams, Richard E.

2009-01-01

To examine the public’s response to future terrorist attacks, we surveyed 1,001 New Yorkers in the community one year after the September 11 attacks. Overall, New Yorkers were very concerned about future terrorist attacks and also concerned about attacks involving biological or nuclear weapons. In addition, while most New Yorkers reported that if a biological or nuclear attack occurred they would evaluate available information before evacuating, a significant number reported they would immediately evacuate, regardless of police or public health communications to the contrary. The level of public concern was significantly higher on all measures among New York City and Long Island residents (downstate) compared to the rest of the state. A model predicting higher fear of terrorism indicated that downstate residents, women, those 45 to 64 years old, African Americans and Hispanics, those with less education/income, and those more likely to flee, were more fearful of future attacks. In addition, making disaster preparations and carefully evaluating emergency information also predicted a higher level of fear as well. A second model predicting who would flee suggested that those more likely to evaluate available information were less likely to immediately evacuate, while those with a higher fear of future attacks were more likely to flee the area. Given these findings and the possibility of future attacks, mental health professionals need to be more involved in preparedness efforts, especially related to the psychological impact of attacks involving weapons of mass destruction. PMID:14730761

Fear of terrorism in New York after the September 11 terrorist attacks: implications for emergency mental health and preparedness.

PubMed

Boscarino, Joseph A; Figley, Charles R; Adams, Richard E

2003-01-01

To examine the public's response to future terrorist attacks, we surveyed 1,001 New Yorkers in the community one year after the September 11 attacks. Overall, New Yorkers were very concerned about future terrorist attacks and also concerned about attacks involving biological or nuclear weapons. In addition, while most New Yorkers reported that if a biological or nuclear attack occurred they would evaluate available information before evacuating, a significant number reported they would immediately evacuate, regardless of police or public health communications to the contrary. The level of public concern was significantly higher on all measures among New York City and Long Island residents (downstate) compared to the rest of the state. A model predicting higher fear of terrorism indicated that downstate residents, women, those 45 to 64 years old, African Americans and Hispanics, those with less education/income, and those more likely to flee, were more fearful of future attacks. In addition, making disaster preparations and carefully evaluating emergency information also predicted a higher level of fear as well. A second model predicting who would flee suggested that those more likely to evaluate available information were less likely to immediately evacuate, while those with a higher fear of future attacks were more likely to flee the area. Given these findings and the possibility of future attacks, mental health professionals need to be more involved in preparedness efforts, especially related to the psychological impact of attacks involving weapons of mass destruction.

How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability.

PubMed

Fitzpatrick, Matthew C; Blois, Jessica L; Williams, John W; Nieto-Lugilde, Diego; Maguire, Kaitlin C; Lorenz, David J

2018-03-23

Future climates are projected to be highly novel relative to recent climates. Climate novelty challenges models that correlate ecological patterns to climate variables and then use these relationships to forecast ecological responses to future climate change. Here, we quantify the magnitude and ecological significance of future climate novelty by comparing it to novel climates over the past 21,000 years in North America. We then use relationships between model performance and climate novelty derived from the fossil pollen record from eastern North America to estimate the expected decrease in predictive skill of ecological forecasting models as future climate novelty increases. We show that, in the high emissions scenario (RCP 8.5) and by late 21st century, future climate novelty is similar to or higher than peak levels of climate novelty over the last 21,000 years. The accuracy of ecological forecasting models is projected to decline steadily over the coming decades in response to increasing climate novelty, although models that incorporate co-occurrences among species may retain somewhat higher predictive skill. In addition to quantifying future climate novelty in the context of late Quaternary climate change, this work underscores the challenges of making reliable forecasts to an increasingly novel future, while highlighting the need to assess potential avenues for improvement, such as increased reliance on geological analogs for future novel climates and improving existing models by pooling data through time and incorporating assemblage-level information. © 2018 John Wiley & Sons Ltd.

Usefulness of Circulating Decoy Receptor 3 in Predicting Coronary Artery Disease Severity and Future Major Adverse Cardiovascular Events in Patients With Multivessel Coronary Artery Disease.

PubMed

Chang, Ting-Yung; Hsu, Chien-Yi; Huang, Po-Hsun; Chiang, Chia-Hung; Leu, Hsin-Bang; Huang, Chin-Chou; Chen, Jaw-Wen; Lin, Shing-Jong

2015-10-01

Decoy receptor 3 (DcR3), a member of the tumor necrosis factor receptor superfamily, is an antiapoptotic soluble receptor considered to play an important role in immune modulation and has pro-inflammatory functions. This study was designed to test whether circulating DcR3 levels are associated with coronary artery disease (CAD) severity and predict future major adverse cardiovascular events (MACEs) in patients with CAD. Circulating DcR3 levels and the Syntax score (SXscore) were determined in patients with multivessel CAD. The primary end point was the MACE within 12 months. In total, 152 consecutive patients with angiographically confirmed multivessel CAD who had received percutaneous coronary intervention were enrolled and were divided into 3 groups according to CAD lesion severity. Group 1 was defined as low SXscore (≤13), group 2 as intermediate SXscore (>13 and ≤22), and group 3 as high SXscore (>22). DcR3 levels were significantly higher in the high SXscore group than the other 2 groups (13,602 ± 7,256 vs 8,025 ± 7,789 vs 4,637 ± 4,403 pg/ml, p <0.001). By multivariate analysis, circulating DcR3 levels were identified as an independent predictor for high SXscore (adjusted odds ratio 1.15, 95% confidence interval 1.09 to 1.21; p <0.001). The Kaplan-Meier analysis showed that increased circulating DcR3 levels are associated with enhanced 1-year MACE in patients with multivessel CAD (log-rank p <0.001). In conclusion, increased circulating DcR3 levels are associated with CAD severity and predict future MACE in patients with multivessel CAD. Copyright © 2015 Elsevier Inc. All rights reserved.

Rising sea levels will reduce extreme temperature variations in tide-dominated reef habitats.

PubMed

Lowe, Ryan Joseph; Pivan, Xavier; Falter, James; Symonds, Graham; Gruber, Renee

2016-08-01

Temperatures within shallow reefs often differ substantially from those in the surrounding ocean; therefore, predicting future patterns of thermal stresses and bleaching at the scale of reefs depends on accurately predicting reef heat budgets. We present a new framework for quantifying how tidal and solar heating cycles interact with reef morphology to control diurnal temperature extremes within shallow, tidally forced reefs. Using data from northwestern Australia, we construct a heat budget model to investigate how frequency differences between the dominant lunar semidiurnal tide and diurnal solar cycle drive ~15-day modulations in diurnal temperature extremes. The model is extended to show how reefs with tidal amplitudes comparable to their depth, relative to mean sea level, tend to experience the largest temperature extremes globally. As a consequence, we reveal how even a modest sea level rise can substantially reduce temperature extremes within tide-dominated reefs, thereby partially offsetting the local effects of future ocean warming.

Digital shoreline analysis system-based change detection along the highly eroding Krishna-Godavari delta front

NASA Astrophysics Data System (ADS)

Kallepalli, Akhil; Kakani, Nageswara Rao; James, David B.; Richardson, Mark A.

2017-07-01

Coastal regions are highly vulnerable to rising sea levels due to global warming. Previous Intergovernmental Panel on Climate Change (2013) predictions of 26 to 82 cm global sea level rise are now considered conservative. Subsequent investigations predict much higher levels which would displace 10% of the world's population living less than 10 m above sea level. Remote sensing and GIS technologies form the mainstay of models on coastal retreat and inundation to future sea-level rise. This study estimates the varying trends along the Krishna-Godavari (K-G) delta region. The rate of shoreline shift along the 330-km long K-G delta coast was estimated using satellite images between 1977 and 2008. With reference to a selected baseline from along an inland position, end point rate and net shoreline movement were calculated using a GIS-based digital shoreline analysis system. The results indicated a net loss of about 42.1 km2 area during this 31-year period, which is in agreement with previous literature. Considering the nature of landforms and EPR, the future hazard line (or coastline) is predicted for the area; the predication indicates a net erosion of about 57.6 km2 along the K-G delta coast by 2050 AD.

Prognostics and Health Monitoring: Application to Electric Vehicles

NASA Technical Reports Server (NTRS)

Kulkarni, Chetan S.

2017-01-01

As more and more autonomous electric vehicles emerge in our daily operation progressively, a very critical challenge lies in accurate prediction of remaining useful life of the systemssubsystems, specifically the electrical powertrain. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle.Our research approach is to develop a system level health monitoring safety indicator either to the pilotautopilot for the electric vehicles which runs estimation and prediction algorithms to estimate remaining useful life of the vehicle e.g. determine state-of-charge in batteries. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making.

Prediction and Perception of Psychosocial Environment by Entering College Freshmen.

ERIC Educational Resources Information Center

Perl, Harold I.

Many adjustment problems may stem from the difference between initial expectations and later, experienced perceptions. To test this theory in relation to the social climate of university living units, and to assess initial perceptions and predictions of the future in relation to level of social exploration as a coping style, 92 entering freshmen…

Family Ethnic Socialization and Ethnic Identity: A Family-Driven, Youth-Driven, or Reciprocal Process?

PubMed Central

Umaña-Taylor, Adriana J.; Zeiders, Katharine H.; Updegraff, Kimberly A.

2013-01-01

The current study examined the longitudinal associations between family ethnic socialization and youths’ ethnic identity among a sample of Mexican-origin youth (N = 178, Mage = 18.17, SD = .46). Findings from multiple-group cross lagged panel models over a two year period indicated that for U.S.-born youth with immigrant parents, the process appeared to be family-driven: Youths’ perceptions of family ethnic socialization in late adolescence were associated with significantly greater ethnic identity exploration and resolution in emerging adulthood, while youths’ ethnic identity during late adolescence did not significantly predict youths’ future perceptions of family ethnic socialization. Conversely, for U.S.-born youth with U.S. born parents, youths’ ethnic identity significantly predicted their future perceptions of family ethnic socialization but perceptions of family ethnic socialization did not predict future levels of youths’ ethnic identity, suggesting a youth-driven process. Findings were consistent for males and females. PMID:23421841

Blood glucose level prediction based on support vector regression using mobile platforms.

PubMed

Reymann, Maximilian P; Dorschky, Eva; Groh, Benjamin H; Martindale, Christine; Blank, Peter; Eskofier, Bjoern M

2016-08-01

The correct treatment of diabetes is vital to a patient's health: Staying within defined blood glucose levels prevents dangerous short- and long-term effects on the body. Mobile devices informing patients about their future blood glucose levels could enable them to take counter-measures to prevent hypo or hyper periods. Previous work addressed this challenge by predicting the blood glucose levels using regression models. However, these approaches required a physiological model, representing the human body's response to insulin and glucose intake, or are not directly applicable to mobile platforms (smart phones, tablets). In this paper, we propose an algorithm for mobile platforms to predict blood glucose levels without the need for a physiological model. Using an online software simulator program, we trained a Support Vector Regression (SVR) model and exported the parameter settings to our mobile platform. The prediction accuracy of our mobile platform was evaluated with pre-recorded data of a type 1 diabetes patient. The blood glucose level was predicted with an error of 19 % compared to the true value. Considering the permitted error of commercially used devices of 15 %, our algorithm is the basis for further development of mobile prediction algorithms.

Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

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

Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef

Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modesmore » and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this article, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.« less

Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

DOE PAGES

Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; ...

2016-10-04

Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modesmore » and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this article, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.« less

Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

NASA Astrophysics Data System (ADS)

Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; Hu, Aixue; Hamlington, Benjamin; Kenigson, Jessica; Palanisamy, Hindumathi; Thompson, Philip

2017-01-01

Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth's climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modes and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this paper, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.

Modeling the effects of dispersal on predicted contemporary and future fisher (Martes pennanti) distribution in the U.S

Treesearch

Lucretia Olson; M. Schwartz

2013-01-01

Many species at high trophic levels are predicted to be impacted by shifts in habitat associated with climate change. While temperate coniferous forests are predicted to be one of the least affected ecosystems, the impact of shifting habitat on terrestrial carnivores that live within these ecosystems may depend on the dispersal rates of the species and the patchiness...

Using genetic algorithms to optimise current and future health planning--the example of ambulance locations.

PubMed

Sasaki, Satoshi; Comber, Alexis J; Suzuki, Hiroshi; Brunsdon, Chris

2010-01-28

Ambulance response time is a crucial factor in patient survival. The number of emergency cases (EMS cases) requiring an ambulance is increasing due to changes in population demographics. This is decreasing ambulance response times to the emergency scene. This paper predicts EMS cases for 5-year intervals from 2020, to 2050 by correlating current EMS cases with demographic factors at the level of the census area and predicted population changes. It then applies a modified grouping genetic algorithm to compare current and future optimal locations and numbers of ambulances. Sets of potential locations were evaluated in terms of the (current and predicted) EMS case distances to those locations. Future EMS demands were predicted to increase by 2030 using the model (R2 = 0.71). The optimal locations of ambulances based on future EMS cases were compared with current locations and with optimal locations modelled on current EMS case data. Optimising the location of ambulance stations locations reduced the average response times by 57 seconds. Current and predicted future EMS demand at modelled locations were calculated and compared. The reallocation of ambulances to optimal locations improved response times and could contribute to higher survival rates from life-threatening medical events. Modelling EMS case 'demand' over census areas allows the data to be correlated to population characteristics and optimal 'supply' locations to be identified. Comparing current and future optimal scenarios allows more nuanced planning decisions to be made. This is a generic methodology that could be used to provide evidence in support of public health planning and decision making.

Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes.

PubMed

Brown, Jason L; Weber, Jennifer J; Alvarado-Serrano, Diego F; Hickerson, Michael J; Franks, Steven J; Carnaval, Ana C

2016-01-01

Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning. © 2016 Botanical Society of America.

Impulsive versus premeditated aggression in the prediction of violent criminal recidivism.

PubMed

Swogger, Marc T; Walsh, Zach; Christie, Michael; Priddy, Brittany M; Conner, Kenneth R

2015-01-01

Past aggression is a potent predictor of future aggression and informs the prediction of violent criminal recidivism. However, aggression is a heterogeneous construct and different types of aggression may confer different levels of risk for future violence. In this prospective study of 91 adults in a pretrial diversion program, we examined (a) premeditated versus impulsive aggression in the prediction of violent recidivism during a one-year follow-up period, and (b) whether either type of aggression would have incremental validity in the prediction of violent recidivism after taking into account frequency of past general aggression. Findings indicate that premeditated, but not impulsive, aggression predicts violent recidivism. Moreover, premeditated aggression remained a predictor of recidivism even with general aggression frequency in the model. Results provide preliminary evidence that the assessment of premeditated aggression provides relevant information for the management of violent offenders. © 2014 Wiley Periodicals, Inc.

Impulsive versus Premeditated Aggression in the Prediction of Violent Criminal Recidivism

PubMed Central

Swogger, Marc T.; Walsh, Zach; Christie, Michael; Priddy, Brittany M.; Conner, Kenneth R.

2015-01-01

Past aggression is a potent predictor of future aggression and informs the prediction of violent criminal recidivism. However, aggression is a heterogeneous construct and different types of aggression may confer different levels of risk for future violence. In this prospective study of 91 adults in a pretrial diversion program, we examined a) premeditated versus impulsive aggression in the prediction of violent recidivism during a one-year follow-up period, and b) whether either type of aggression would have incremental validity in the prediction of violent recidivism after taking into account frequency of past general aggression. Findings indicate that premeditated, but not impulsive, aggression predicts violent recidivism. Moreover, premeditated aggression remained a predictor of recidivism even with general aggression frequency in the model. Results provide preliminary evidence that the assessment of premeditated aggression provides relevant information for the management of violent offenders. PMID:25043811

Predictability of state-level flood damage in the conterminous United States: the role of hazard, exposure and vulnerability

DOE PAGES

Zhou, Qianqian; Leng, Guoyong; Feng, Leyang

2017-07-13

Understanding historical changes in flood damage and the underlying mechanisms is critical for predicting future changes for better adaptations. In this study, a detailed assessment of flood damage for 1950–1999 is conducted at the state level in the conterminous United States (CONUS). Geospatial datasets on possible influencing factors are then developed by synthesizing natural hazards, population, wealth, cropland and urban area to explore the relations with flood damage. A considerable increase in flood damage in CONUS is recorded for the study period which is well correlated with hazards. Comparably, runoff indexed hazards simulated by the Variable Infiltration Capacity (VIC) modelmore » can explain a larger portion of flood damage variations than precipitation in 84% of the states. Cropland is identified as an important factor contributing to increased flood damage in central US while urbanland exhibits positive and negative relations with total flood damage and damage per unit wealth in 20 and 16 states, respectively. Altogether, flood damage in 34 out of 48 investigated states can be predicted at the 90% confidence level. In extreme cases, ~76% of flood damage variations can be explained in some states, highlighting the potential of future flood damage prediction based on climate change and socioeconomic scenarios.« less

Predictability of state-level flood damage in the conterminous United States: the role of hazard, exposure and vulnerability

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

Zhou, Qianqian; Leng, Guoyong; Feng, Leyang

Understanding historical changes in flood damage and the underlying mechanisms is critical for predicting future changes for better adaptations. In this study, a detailed assessment of flood damage for 1950–1999 is conducted at the state level in the conterminous United States (CONUS). Geospatial datasets on possible influencing factors are then developed by synthesizing natural hazards, population, wealth, cropland and urban area to explore the relations with flood damage. A considerable increase in flood damage in CONUS is recorded for the study period which is well correlated with hazards. Comparably, runoff indexed hazards simulated by the Variable Infiltration Capacity (VIC) modelmore » can explain a larger portion of flood damage variations than precipitation in 84% of the states. Cropland is identified as an important factor contributing to increased flood damage in central US while urbanland exhibits positive and negative relations with total flood damage and damage per unit wealth in 20 and 16 states, respectively. Altogether, flood damage in 34 out of 48 investigated states can be predicted at the 90% confidence level. In extreme cases, ~76% of flood damage variations can be explained in some states, highlighting the potential of future flood damage prediction based on climate change and socioeconomic scenarios.« less

The Usefulness of Assessing and Identifying Workers' Temperaments and Their Effects on Occupational Stress in the Workplace.

PubMed

Deguchi, Yasuhiko; Iwasaki, Shinichi; Konishi, Akihito; Ishimoto, Hideyuki; Ogawa, Koichiro; Fukuda, Yuichi; Nitta, Tomoko; Inoue, Koki

2016-01-01

The relationship between temperaments and mental disorders has been reported in previous studies, but there has been little attention to temperaments in the occupational safety and health research. The aim of this study was to clarify the effects of temperaments on occupational stress among local government employees. The subjects were 145 Japanese daytime workers in local government. Temperaments were assessed by the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego-Auto questionnaire (TEMPS-A). Occupational stress was assessed using the Generic Job Stress Questionnaire (GJSQ). Hierarchical multiple linear regression analysis was used. Hyperthymic temperament predicted a higher level of job control, and a lower level of role ambiguity and job future ambiguity. Irritable temperament predicted a lower level of social support from supervisors and a higher level of role conflict, variance in workload and intragroup conflict. Anxious temperament predicted a lower level of social support from coworkers and a higher level of job future ambiguity. The sample size was small. Only Japanese local government employees were surveyed. Hyperthymic temperament played a protective role, and irritable, anxious temperament played a vulnerable role against one's own occupational stress and recognizing the roles they play in work life would lead to self-insight. Additionally, recognition of the temperaments and temperament-related stressors by one's supervisors or coworkers would facilitate provision of social support.

The Usefulness of Assessing and Identifying Workers’ Temperaments and Their Effects on Occupational Stress in the Workplace

PubMed Central

Konishi, Akihito; Ishimoto, Hideyuki; Ogawa, Koichiro; Fukuda, Yuichi; Nitta, Tomoko; Inoue, Koki

2016-01-01

The relationship between temperaments and mental disorders has been reported in previous studies, but there has been little attention to temperaments in the occupational safety and health research. The aim of this study was to clarify the effects of temperaments on occupational stress among local government employees. The subjects were 145 Japanese daytime workers in local government. Temperaments were assessed by the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego-Auto questionnaire (TEMPS-A). Occupational stress was assessed using the Generic Job Stress Questionnaire (GJSQ). Hierarchical multiple linear regression analysis was used. Hyperthymic temperament predicted a higher level of job control, and a lower level of role ambiguity and job future ambiguity. Irritable temperament predicted a lower level of social support from supervisors and a higher level of role conflict, variance in workload and intragroup conflict. Anxious temperament predicted a lower level of social support from coworkers and a higher level of job future ambiguity. The sample size was small. Only Japanese local government employees were surveyed. Hyperthymic temperament played a protective role, and irritable, anxious temperament played a vulnerable role against one’s own occupational stress and recognizing the roles they play in work life would lead to self-insight. Additionally, recognition of the temperaments and temperament-related stressors by one’s supervisors or coworkers would facilitate provision of social support. PMID:27227771

Predictive value of high-sensitivity troponin-I for future adverse cardiovascular outcome in stable patients with type 2 diabetes mellitus

PubMed Central

2014-01-01

Introduction High-sensitivity cardiac troponin I(hs-TnI) and T levels(hs-TnT) are sensitive biomarkers of cardiomyocyte turnover or necrosis. Prior studies of the predictive role of hs-TnT in type 2 diabetes mellitus(T2DM) patients have yielded conflicting results. This study aimed to determine whether hs-TnI, which is detectable in a higher proportion of normal subjects than hsTnT, is associated with a major adverse cardiovascular event(MACE) in T2DM patients. Methods and results We compared hs-TnI level in stored serum samples from 276 consecutive patients (mean age 65 ± 10 years; 57% male) with T2DM with that of 115 age-and sex-matched controls. All T2DM patients were prospectively followed up for at least 4 years for incidence of MACE including heart failure(HF), myocardial infarction(MI) and cardiovascular mortality. At baseline, 274(99%) patients with T2DM had detectable hs-TnI, and 57(21%) had elevated hs-TnI (male: 8.5 ng/L, female: 7.6 ng/L, above the 99th percentile in healthy controls). A total of 43 MACE occurred: HF(n = 18), MI(n = 11) and cardiovascular mortality(n = 14). Kaplan-Meier analysis showed that an elevated hs-TnI was associated with MACE, HF, MI and cardiovascular mortality. Although multivariate analysis revealed that an elevated hs-TnI independently predicted MACE, it had limited sensitivity(62.7%) and positive predictive value(38.5%). Contrary to this, a normal hs-TnI level had an excellent negative predictive value(92.2%) for future MACE in patients with T2DM. Conclusion The present study demonstrates that elevated hs-TnI in patients with T2DM is associated with increased MACE, HF, MI and cardiovascular mortality. Importantly, a normal hs-TnI level has an excellent negative predictive value for future adverse cardiovascular events during long-term follow-up. PMID:24661773

The shaping of genetic variation in edge-of-range populations under past and future climate change

PubMed Central

Razgour, Orly; Juste, Javier; Ibáñez, Carlos; Kiefer, Andreas; Rebelo, Hugo; Puechmaille, Sébastien J; Arlettaz, Raphael; Burke, Terry; Dawson, Deborah A; Beaumont, Mark; Jones, Gareth; Wiens, John

2013-01-01

With rates of climate change exceeding the rate at which many species are able to shift their range or adapt, it is important to understand how future changes are likely to affect biodiversity at all levels of organisation. Understanding past responses and extent of niche conservatism in climatic tolerance can help predict future consequences. We use an integrated approach to determine the genetic consequences of past and future climate changes on a bat species, Plecotus austriacus. Glacial refugia predicted by palaeo-modelling match those identified from analyses of extant genetic diversity and model-based inference of demographic history. Former refugial populations currently contain disproportionately high genetic diversity, but niche conservatism, shifts in suitable areas and barriers to migration mean that these hotspots of genetic diversity are under threat from future climate change. Evidence of population decline despite recent northward migration highlights the need to conserve leading-edge populations for spearheading future range shifts. PMID:23890483

The contribution to future flood risk in the Severn Estuary from extreme sea level rise due to ice sheet mass loss

NASA Astrophysics Data System (ADS)

Quinn, N.; Bates, P. D.; Siddall, M.

2013-12-01

The rate at which sea levels will rise in the coming century is of great interest to decision makers tasked with developing mitigation policies to cope with the risk of coastal inundation. Accurate estimates of future sea levels are vital in the provision of effective policy. Recent reports from UK Climate Impacts Programme (UKCIP) suggest that mean sea levels in the UK may rise by as much as 80 cm by 2100; however, a great deal of uncertainty surrounds model predictions, particularly the contribution from ice sheets responding to climatic warming. For this reason, the application of semi-empirical modelling approaches for sea level rise predictions has increased of late, the results from which suggest that the rate of sea level rise may be greater than previously thought, exceeding 1 m by 2100. Furthermore, studies in the Red Sea indicate that rapid sea level rise beyond 1m per century has occurred in the past. In light of such research, the latest UKCIP assessment has included a H++ scenario for sea level rise in the UK of up to 1.9 m which is defined as improbable but, crucially, physically plausible. The significance of such low-probability sea level rise scenarios upon the estimation of future flood risk is assessed using the Somerset levels (UK) as a case study. A simple asymmetric probability distribution is constructed to include sea level rise scenarios of up to 1.9 m by 2100 which are added to a current 1:200 year event water level to force a two-dimensional hydrodynamic model of coastal inundation. From the resulting ensemble predictions an estimation of risk by 2100 is established. The results indicate that although the likelihood of extreme sea level rise due to rapid ice sheet mass loss is low, the resulting hazard can be large, resulting in a significant (27%) increase to the projected annual risk. Furthermore, current defence construction guidelines for the coming century in the UK are expected to account for 95% of the sea level rise distribution presented in this research, while the larger, low probability scenarios beyond this level are estimated to contribute a residual annual risk of approximately £0.45 million. These findings clearly demonstrate that uncertainty in future sea level rise is a vital component of coastal flood risk, and therefore, needs to be accounted for by decision makers when considering mitigation policies related to coastal flooding.

Relationships Between Future Orientation, Impulsive Sensation Seeking, and Risk Behavior Among Adjudicated Adolescents

PubMed Central

Robbins, Reuben N.; Bryan, Angela

2005-01-01

Because of high levels of risk behavior, adjudicated adolescents are at high risk for negative health outcomes such as nicotine and drug addiction and sexually transmitted diseases. The goal of this article is to examine relationships between future orientation and impulsive-sensation-seeking personality constructs to risk behaviors among 300 adjudicated adolescents. Significant relationships between impulsive sensation seeking and future orientation were found for several risk behaviors. Individuals with more positive future orientation were less likely to use marijuana, hard drugs, alcohol during sex, had fewer alcohol problems, had lower levels of alcohol frequency and quantity of use, and perceived greater risks associated with such behaviors. Higher impulsivity reliably predicted alcohol problems, alcohol use, condom use, and cigarette smoking. PMID:16429605

Do changes in climate and land use pose a risk to the future water availability of Mediterranean Lakes?

NASA Astrophysics Data System (ADS)

Bucak, T.; Trolle, D.; Andersen, H. E.; Thodsen, H.; Erdoğan, Ş.; Levi, E. E.; Filiz, N.; Jeppesen, E.; Beklioğlu, M.

2016-12-01

Inter- and intra-annual water level fluctuations and change in water flow regime are intrinsic characteristics of Mediterranean lakes. However, considering the climate change projections for the water-limited Mediterranean region where potential evapotranspiration exceeds precipitation and with increased air temperatures and decreased precipitation, more dramatic water level declines in lakes and severe water scarcity problems are expected to occur in the future. Our study lake, Lake Beyşehir, the largest freshwater lake in the Mediterranean basin, is - like other Mediterranean lakes - under pressure due to water abstraction for irrigated crop farming and climatic changes, and integrated water level management is therefore required. We used an integrated modeling approach to predict the future lake water level of Lake Beyşehir in response to the future changes in both climate and, potentially, land use by linking the catchment model Soil and Water Assessment Tool (SWAT) with a Support Vector Machine Regression model (ɛ-SVR). We found that climate change projections caused enhanced potential evapotranspiration and reduced total runoff, whereas the effects of various land use scenarios within the catchment were comparatively minor. In all climate scenarios applied in the ɛ-SVR model, changes in hydrological processes caused a water level reduction, predicting that the lake may dry out already in the 2040s with the current outflow regulation considering the most pessimistic scenario. Based on model runs with optimum outflow management, a 9-60% reduction in outflow withdrawal is needed to prevent the lake from drying out by the end of this century. Our results indicate that shallow Mediterranean lakes may face a severe risk of drying out and loss of ecosystem value in near future if the current intense water abstraction is maintained. Therefore, we conclude that outflow management in water-limited regions in a warmer and drier future and sustainable use of water sources are vitally important to sustain lake ecosystems and their ecosystem services.

Boosted food web productivity through ocean acidification collapses under warming.

PubMed

Goldenberg, Silvan U; Nagelkerken, Ivan; Ferreira, Camilo M; Ullah, Hadayet; Connell, Sean D

2017-10-01

Future climate is forecast to drive bottom-up (resource driven) and top-down (consumer driven) change to food web dynamics and community structure. Yet, our predictive understanding of these changes is hampered by an over-reliance on simplified laboratory systems centred on single trophic levels. Using a large mesocosm experiment, we reveal how future ocean acidification and warming modify trophic linkages across a three-level food web: that is, primary (algae), secondary (herbivorous invertebrates) and tertiary (predatory fish) producers. Both elevated CO 2 and elevated temperature boosted primary production. Under elevated CO 2 , the enhanced bottom-up forcing propagated through all trophic levels. Elevated temperature, however, negated the benefits of elevated CO 2 by stalling secondary production. This imbalance caused secondary producer populations to decline as elevated temperature drove predators to consume their prey more rapidly in the face of higher metabolic demand. Our findings demonstrate how anthropogenic CO 2 can function as a resource that boosts productivity throughout food webs, and how warming can reverse this effect by acting as a stressor to trophic interactions. Understanding the shifting balance between the propagation of resource enrichment and its consumption across trophic levels provides a predictive understanding of future dynamics of stability and collapse in food webs and fisheries production. © 2017 John Wiley & Sons Ltd.

Predict the Medicare Functional Classification Level (K-level) using the Amputee Mobility Predictor in people with unilateral transfemoral and transtibial amputation: A pilot study.

PubMed

Dillon, Michael P; Major, Matthew J; Kaluf, Brian; Balasanov, Yuri; Fatone, Stefania

2018-04-01

While Amputee Mobility Predictor scores differ between Medicare Functional Classification Levels (K-level), this does not demonstrate that the Amputee Mobility Predictor can accurately predict K-level. To determine how accurately K-level could be predicted using the Amputee Mobility Predictor in combination with patient characteristics for persons with transtibial and transfemoral amputation. Prediction. A cumulative odds ordinal logistic regression was built to determine the effect that the Amputee Mobility Predictor, in combination with patient characteristics, had on the odds of being assigned to a particular K-level in 198 people with transtibial or transfemoral amputation. For people assigned to the K2 or K3 level by their clinician, the Amputee Mobility Predictor predicted the clinician-assigned K-level more than 80% of the time. For people assigned to the K1 or K4 level by their clinician, the prediction of clinician-assigned K-level was less accurate. The odds of being in a higher K-level improved with younger age and transfemoral amputation. Ordinal logistic regression can be used to predict the odds of being assigned to a particular K-level using the Amputee Mobility Predictor and patient characteristics. This pilot study highlighted critical method design issues, such as potential predictor variables and sample size requirements for future prospective research. Clinical relevance This pilot study demonstrated that the odds of being assigned a particular K-level could be predicted using the Amputee Mobility Predictor score and patient characteristics. While the model seemed sufficiently accurate to predict clinician assignment to the K2 or K3 level, further work is needed in larger and more representative samples, particularly for people with low (K1) and high (K4) levels of mobility, to be confident in the model's predictive value prior to use in clinical practice.

The language of future-thought: an fMRI study of embodiment and tense processing.

PubMed

Gilead, Michael; Liberman, Nira; Maril, Anat

2013-01-15

The ability to comprehend and represent the temporal properties of an occurrence is a crucial aspect of human language and cognition. Despite advances in neurolinguistic research into semantic processing, surprisingly little is known regarding the mechanisms which support the comprehension of temporal semantics. We used fMRI to investigate neural activity associated with processing of concrete and abstract sentences across the three temporal categories: past, present, and future. Theories of embodied cognition predict that concreteness-related activity would be evident in sensory and motor areas regardless of tense. Contrastingly, relying upon construal level theory we hypothesized that: (1) the neural markers associated with concrete language processing would appear for past and present tense sentences, but not for future sentences; (2) future tense sentences would activate intention-processing areas. Consistent with our first prediction, the results showed that activation in the parahippocampal gyrus differentiated between concrete and abstract sentences for past and present tense sentences, but not for future sentences. Not consistent with our second prediction, future tense sentences did not activate most of the regions that are implicated in the processing of intentions, but only activated the vmPFC. We discuss the implications of the current results to theories of embodied cognition and tense semantics. Copyright © 2012 Elsevier Inc. All rights reserved.

From discrimination to internalized mental illness stigma: The mediating roles of anticipated discrimination and anticipated stigma.

PubMed

Quinn, Diane M; Williams, Michelle K; Weisz, Bradley M

2015-06-01

Internalizing mental illness stigma is related to poorer well-being, but less is known about the factors that predict levels of internalized stigma. This study explored how experiences of discrimination relate to greater anticipation of discrimination and devaluation in the future and how anticipation of stigma in turn predicts greater stigma internalization. Participants were 105 adults with mental illness who self-reported their experiences of discrimination based on their mental illness, their anticipation of discrimination and social devaluation from others in the future, and their level of internalized stigma. Participants were approached in several locations and completed surveys on laptop computers. Correlational analyses indicated that more experiences of discrimination due to one's mental illness were related to increased anticipated discrimination in the future, increased anticipated social stigma from others, and greater internalized stigma. Multiple serial mediator analyses showed that the effect of experiences of discrimination on internalized stigma was fully mediated by increased anticipated discrimination and anticipated stigma. Experiences of discrimination over one's lifetime may influence not only how much future discrimination people with mental illness are concerned with but also how much they internalize negative feelings about the self. Mental health professionals may need to address concerns with future discrimination and devaluation in order to decrease internalized stigma. (c) 2015 APA, all rights reserved).

Model Projections of Future Fluvial Sediment Delivery to Major Deltas Under Environmental Change

NASA Astrophysics Data System (ADS)

Darby, S. E.; Dunn, F.; Nicholls, R. J.; Cohen, S.; Zarfl, C.

2017-12-01

Deltas are important hot spots for climate change impacts on which over half a billion people live worldwide. Most of the world's deltas are sinking as a result of natural and anthropogenic subsidence and due to eustatic sea level rise. The ability to predict rates of delta aggradation is therefore critical to assessments of the extent to which sedimentation can potentially offset sea level rise, but our ability to make such predictions is severely hindered by a lack of insight into future trends of the fluvial sediment load supplied to their deltas by feeder watersheds. To address this gap we investigate fluvial sediment fluxes under future environmental change for a selection (47) of the world's major river deltas. Specifically, we employed the numerical model WBMsed to project future variations in mean annual fluvial sediment loads under a range of environmental change scenarios that account for changes in climate, socio-economics and dam construction. Our projections indicate a clear decrease (by 34 to 41% on average, depending on the specific scenario) in future fluvial sediment supply to most of the 47 deltas. These reductions in sediment delivery are driven primarily by anthropogenic disturbances, with reservoir construction being the most influential factor globally. Our results indicate the importance of developing new management strategies for reservoir construction and operation.

Propeller aircraft interior noise model utilization study and validation

NASA Technical Reports Server (NTRS)

Pope, L. D.

1984-01-01

Utilization and validation of a computer program designed for aircraft interior noise prediction is considered. The program, entitled PAIN (an acronym for Propeller Aircraft Interior Noise), permits (in theory) predictions of sound levels inside propeller driven aircraft arising from sidewall transmission. The objective of the work reported was to determine the practicality of making predictions for various airplanes and the extent of the program's capabilities. The ultimate purpose was to discern the quality of predictions for tonal levels inside an aircraft occurring at the propeller blade passage frequency and its harmonics. The effort involved three tasks: (1) program validation through comparisons of predictions with scale-model test results; (2) development of utilization schemes for large (full scale) fuselages; and (3) validation through comparisons of predictions with measurements taken in flight tests on a turboprop aircraft. Findings should enable future users of the program to efficiently undertake and correctly interpret predictions.

Assessment of the climate change impacts on fecal coliform contamination in a tidal estuarine system.

PubMed

Liu, Wen-Cheng; Chan, Wen-Ting

2015-12-01

Climate change is one of the key factors affecting the future microbiological water quality in rivers and tidal estuaries. A coupled 3D hydrodynamic and fecal coliform transport model was developed and applied to the Danshuei River estuarine system for predicting the influences of climate change on microbiological water quality. The hydrodynamic and fecal coliform model was validated using observational salinity and fecal coliform distributions. According to the analyses of the statistical error, predictions of the salinity and the fecal coliform concentration from the model simulation quantitatively agreed with the observed data. The validated model was then applied to predict the fecal coliform contamination as a result of climate change, including the change of freshwater discharge and the sea level rise. We found that the reduction of freshwater discharge under climate change scenarios resulted in an increase in the fecal coliform concentration. The sea level rise would decrease fecal coliform distributions because both the water level and the water volume increased. A reduction in freshwater discharge has a negative impact on the fecal coliform concentration, whereas a rising sea level has a positive influence on the fecal coliform contamination. An appropriate strategy for the effective microbiological management in tidal estuaries is required to reveal the persistent trends of climate in the future.

Predicting consumer behavior with Web search.

PubMed

Goel, Sharad; Hofman, Jake M; Lahaie, Sébastien; Pennock, David M; Watts, Duncan J

2010-10-12

Recent work has demonstrated that Web search volume can "predict the present," meaning that it can be used to accurately track outcomes such as unemployment levels, auto and home sales, and disease prevalence in near real time. Here we show that what consumers are searching for online can also predict their collective future behavior days or even weeks in advance. Specifically we use search query volume to forecast the opening weekend box-office revenue for feature films, first-month sales of video games, and the rank of songs on the Billboard Hot 100 chart, finding in all cases that search counts are highly predictive of future outcomes. We also find that search counts generally boost the performance of baseline models fit on other publicly available data, where the boost varies from modest to dramatic, depending on the application in question. Finally, we reexamine previous work on tracking flu trends and show that, perhaps surprisingly, the utility of search data relative to a simple autoregressive model is modest. We conclude that in the absence of other data sources, or where small improvements in predictive performance are material, search queries provide a useful guide to the near future.

Predicting consumer behavior with Web search

PubMed Central

Goel, Sharad; Hofman, Jake M.; Lahaie, Sébastien; Pennock, David M.; Watts, Duncan J.

2010-01-01

Recent work has demonstrated that Web search volume can “predict the present,” meaning that it can be used to accurately track outcomes such as unemployment levels, auto and home sales, and disease prevalence in near real time. Here we show that what consumers are searching for online can also predict their collective future behavior days or even weeks in advance. Specifically we use search query volume to forecast the opening weekend box-office revenue for feature films, first-month sales of video games, and the rank of songs on the Billboard Hot 100 chart, finding in all cases that search counts are highly predictive of future outcomes. We also find that search counts generally boost the performance of baseline models fit on other publicly available data, where the boost varies from modest to dramatic, depending on the application in question. Finally, we reexamine previous work on tracking flu trends and show that, perhaps surprisingly, the utility of search data relative to a simple autoregressive model is modest. We conclude that in the absence of other data sources, or where small improvements in predictive performance are material, search queries provide a useful guide to the near future. PMID:20876140

EVALUATING THE PREDICTIVE VALIDITY OF SUICIDAL INTENT AND MEDICAL LETHALITY IN YOUTH

PubMed Central

Sapyta, Jeffrey; Goldston, David B.; Erkanli, Alaattin; Daniel, Stephanie S.; Heilbron, Nicole; Mayfield, Andrew; Treadway, S. Lyn

2012-01-01

Objectives To examine whether suicidal intent and medical lethality of past suicide attempts are predictive of future attempts, the association between intent and lethality, and the consistency of these characteristics across repeated attempts among youth. Method Suicide attempts in a 15-year prospective study of 180 formerly psychiatrically hospitalized adolescents (Mage at hospitalization = 14.83; 51% female; 80% Caucasian) were characterized using the Subjective Intent Rating Scale and Lethality of Attempt Rating Scale. Anderson-Gill recurrent events survival models and generalized estimating equations were used to assess predictive validity. Generalized linear models were used to examine stability of characteristics across attempts. Results Neither intent nor lethality from the most recent attempt predicted future attempts. The highest level of intent and most severe lethality of attempts during the follow-up predicted subsequent attempts, but the degree to which highest intent and most severe lethality contributed to prediction after considering methods of suicide attempts, past number of attempts, or psychiatric diagnoses was mixed. Across successive attempts, there was little consistency in reported characteristics. Intent and lethality were related to each other only for attempts occurring in early adulthood. Conclusions Highest intent and lethality were better predictors of future attempts than intent and lethality of the most recent attempt. However, these characteristics should only be considered as predictors within the context of other factors. For youth, clinicians should not infer true intent from the lethality of attempts, nor assume that characteristics of future suicide attempts will be similar to previous attempts. PMID:22250854

Behavior-Based Budget Management Using Predictive Analytics

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

Troy Hiltbrand

Historically, the mechanisms to perform forecasting have primarily used two common factors as a basis for future predictions: time and money. While time and money are very important aspects of determining future budgetary spend patterns, organizations represent a complex system of unique individuals with a myriad of associated behaviors and all of these behaviors have bearing on how budget is utilized. When looking to forecasted budgets, it becomes a guessing game about how budget managers will behave under a given set of conditions. This becomes relatively messy when human nature is introduced, as different managers will react very differently undermore » similar circumstances. While one manager becomes ultra conservative during periods of financial austerity, another might be un-phased and continue to spend as they have in the past. Both might revert into a state of budgetary protectionism masking what is truly happening at a budget holder level, in order to keep as much budget and influence as possible while at the same time sacrificing the greater good of the organization. To more accurately predict future outcomes, the models should consider both time and money and other behavioral patterns that have been observed across the organization. The field of predictive analytics is poised to provide the tools and methodologies needed for organizations to do just this: capture and leverage behaviors of the past to predict the future.« less

Age, gender and deterrability: Are younger male drivers more likely to discount the future?

PubMed

Freeman, James; Kaye, Sherrie-Anne; Truelove, Verity; Davey, Jeremy

2017-07-01

Utilizing the Classical Deterrence theory and Stafford and Warr's (1993) reconceptualized model of deterrence, the current study examined whether age, gender, and discounting the future tendencies influence perceptions of being apprehended for speeding offences. Licensed motorists (N=700; 57% female) in Queensland (Australia) were recruited to complete a self-report questionnaire that measured perceptual deterrence, speeding related behaviors and discounting the future tendencies. Data were analyzed utilizing descriptive, bivariate and multivariate regressions. Significant (albeit weak) positive correlations were found between age and perceptions of apprehension certainty. Males were significantly more likely to report higher incidences of speeding (including while avoiding detection) compared to females. In contrast, females were more likely to perceive high levels of apprehension certainty and consider impending penalties to be more severe. At a multivariate level, discounting the future tendencies (in addition to being male, reporting lower levels of perceptual severity and swiftness, and more instances of punishment avoidance) were predictive of lower perceptual certainty levels. This study is one of the first to reveal that being male and having a tendency to discount the consequences of the future may directly influence drivers' perceptual deterrence levels. Copyright © 2017 Elsevier Ltd. All rights reserved.

Coping Skills Help Explain How Future-Oriented Adolescents Accrue Greater Well-Being Over Time.

PubMed

Chua, Li Wen; Milfont, Taciano L; Jose, Paul E

2015-11-01

Adolescents who endorse greater levels of future orientation report greater well-being over time, but we do not know the mechanism by which this happens. The present longitudinal study examined whether both adaptive as well as maladaptive coping strategies might explain how future orientation leads to ill-being and well-being over time in young New Zealanders. A sample of 1,774 preadolescents and early adolescents (51.9 % female) aged 10-15 years at Time 1 completed a self-report survey three times with 1 year intervals in between. Longitudinal mediation path models were constructed to determine whether and how maladaptive and adaptive coping strategies at Time 2 functioned as mediators between future orientation at Time 1 and ill-being and well-being at Time 3. Results showed that future orientation predicted lower maladaptive coping, which in turn predicted lower substance use and self-harming behavior. All three well-being outcomes (i.e., happiness with weight, vitality, and sleep) were consistently predicted by future orientation, and all three pathways were mediated by both lower maladaptive and higher adaptive coping strategies (with the exception of happiness with weight, which was mediated only by lower maladaptive coping). The results suggest that several pathways by which future orientation leads to greater well-being occurs through an increased use of adaptive coping, a decreased use of maladaptive coping, or both.

Short-term acoustic forecasting via artificial neural networks for neonatal intensive care units.

PubMed

Young, Jason; Macke, Christopher J; Tsoukalas, Lefteri H

2012-11-01

Noise levels in hospitals, especially neonatal intensive care units (NICUs), have become of great concern for hospital designers. This paper details an artificial neural network (ANN) approach to forecasting the sound loads in NICUs. The ANN is used to learn the relationship between past, present, and future noise levels. By training the ANN with data specific to the location and device used to measure the sound, the ANN is able to produce reasonable predictions of noise levels in the NICU. Best case results show average absolute errors of 5.06 ± 4.04% when used to predict the noise levels one hour ahead, which correspond to 2.53 dBA ± 2.02 dBA. The ANN has the tendency to overpredict during periods of stability and underpredict during large transients. This forecasting algorithm could be of use in any application where prediction and prevention of harmful noise levels are of the utmost concern.

Predicting the impact of tsunami in California under rising sea level

NASA Astrophysics Data System (ADS)

Dura, T.; Garner, A. J.; Weiss, R.; Kopp, R. E.; Horton, B.

2017-12-01

The flood hazard for the California coast depends not only on the magnitude, location, and rupture length of Alaska-Aleutian subduction zone earthquakes and their resultant tsunamis, but also on rising sea levels, which combine with tsunamis to produce overall flood levels. The magnitude of future sea-level rise remains uncertain even on the decadal scale, with future sea-level projections becoming even more uncertain at timeframes of a century or more. Earthquake statistics indicate that timeframes of ten thousand to one hundred thousand years are needed to capture rare, very large earthquakes. Because of the different timescales between reliable sea-level projections and earthquake distributions, simply combining the different probabilities in the context of a tsunami hazard assessment may be flawed. Here, we considered 15 earthquakes between Mw 8 to Mw 9.4 bound by -171oW and -140oW of the Alaska-Aleutian subduction zone. We employed 24 realizations at each magnitude with random epicenter locations and different fault length-to-width ratios, and simulated the tsunami evolution from these 360 earthquakes at each decade from the years 2000 to 2200. These simulations were then carried out for different sea-level-rise projections to analyze the future flood hazard for California. Looking at the flood levels at tide gauges, we found that the flood level simulated at, for example, the year 2100 (including respective sea-level change) is different from the flood level calculated by adding the flood for the year 2000 to the sea-level change prediction for the year 2100. This is consistent for all sea-level rise scenarios, and this difference in flood levels range between 5% and 12% for the larger half of the given magnitude interval. Focusing on flood levels at the tide gauge in the Port of Los Angeles, the most probable flood level (including all earthquake magnitudes) in the year 2000 was 5 cm. Depending on the sea-level predictions, in the year 2050 the most probable flood levels could rise to 20 to 30 cm, but increase significantly from 2100 to 2200 to between 0.5 m and 2.5 m. Aside from the significant increase in flood level, it should be noted that the range over which potential most probable flood levels can vary is significant and defines a tremendous challenge for long-term planning of hazard mitigating measures.

Tryptophan Predicts the Risk for Future Type 2 Diabetes

PubMed Central

Chen, Tianlu; Zheng, Xiaojiao; Ma, Xiaojing; Bao, Yuqian; Ni, Yan; Hu, Cheng; Rajani, Cynthia; Huang, Fengjie; Zhao, Aihua; Jia, Weiping; Jia, Wei

2016-01-01

Recently, 5 amino acids were identified and verified as important metabolites highly associated with type 2 diabetes (T2D) development. This report aims to assess the association of tryptophan with the development of T2D and to evaluate its performance with existing amino acid markers. A total of 213 participants selected from a ten-year longitudinal Shanghai Diabetes Study (SHDS) were examined in two ways: 1) 51 subjects who developed diabetes and 162 individuals who remained metabolically healthy in 10 years; 2) the same 51 future diabetes and 23 strictly matched ones selected from the 162 healthy individuals. Baseline fasting serum tryptophan concentrations were quantitatively measured using ultra-performance liquid chromatography triple quadruple mass spectrometry. First, serum tryptophan level was found significantly higher in future T2D and was positively and independently associated with diabetes onset risk. Patients with higher tryptophan level tended to present higher degree of insulin resistance and secretion, triglyceride and blood pressure. Second, the prediction potential of tryptophan is non-inferior to the 5 existing amino acids. The predictive performance of the combined score improved after taking tryptophan into account. Our findings unveiled the potential of tryptophan as a new marker associated with diabetes risk in Chinese populations. The addition of tryptophan provided complementary value to the existing amino acid predictors. PMID:27598004

Increased Fidelity in Prediction Methods For Landing Gear Noise

NASA Technical Reports Server (NTRS)

Lopes, Leonard V.; Brentner, Kenneth S.; Morris, Philip J.; Lockard, David P.

2006-01-01

An aeroacoustic prediction scheme has been developed for landing gear noise. The method is designed to handle the complex landing gear geometry of current and future aircraft. The gear is represented by a collection of subassemblies and simple components that are modeled using acoustic elements. These acoustic elements are generic, but generate noise representative of the physical components on a landing gear. The method sums the noise radiation from each component of the undercarriage in isolation accounting for interference with adjacent components through an estimate of the local upstream and downstream flows and turbulence intensities. The acoustic calculations are made in the code LGMAP, which computes the sound pressure levels at various observer locations. The method can calculate the noise from the undercarriage in isolation or installed on an aircraft for both main and nose landing gear. Comparisons with wind tunnel and flight data are used to initially calibrate the method, then it may be used to predict the noise of any landing gear. In this paper, noise predictions are compared with wind tunnel data for model landing gears of various scales and levels of fidelity, as well as with flight data on fullscale undercarriages. The present agreement between the calculations and measurements suggests the method has promise for future application in the prediction of airframe noise.

How are compassion fatigue, burnout, and compassion satisfaction affected by quality of working life? Findings from a survey of mental health staff in Italy.

PubMed

Cetrano, Gaia; Tedeschi, Federico; Rabbi, Laura; Gosetti, Giorgio; Lora, Antonio; Lamonaca, Dario; Manthorpe, Jill; Amaddeo, Francesco

2017-11-21

Quality of working life includes elements such as autonomy, trust, ergonomics, participation, job complexity, and work-life balance. The overarching aim of this study was to investigate if and how quality of working life affects Compassion Fatigue, Burnout, and Compassion Satisfaction among mental health practitioners. Staff working in three Italian Mental Health Departments completed the Professional Quality of Life Scale, measuring Compassion Fatigue, Burnout, and Compassion Satisfaction, and the Quality of Working Life Questionnaire. The latter was used to collect socio-demographics, occupational characteristics and 13 indicators of quality of working life. Multiple regressions controlling for other variables were undertaken to predict Compassion Fatigue, Burnout, and Compassion Satisfaction. Four hundred questionnaires were completed. In bivariate analyses, experiencing more ergonomic problems, perceiving risks for the future, a higher impact of work on life, and lower levels of trust and of perceived quality of meetings were associated with poorer outcomes. Multivariate analysis showed that (a) ergonomic problems and impact of work on life predicted higher levels of both Compassion Fatigue and Burnout; (b) impact of life on work was associated with Compassion Fatigue and lower levels of trust and perceiving more risks for the future with Burnout only; (c) perceived quality of meetings, need of training, and perceiving no risks for the future predicted higher levels of Compassion Satisfaction. In order to provide adequate mental health services, service providers need to give their employees adequate ergonomic conditions, giving special attention to time pressures. Building trustful relationships with management and within the teams is also crucial. Training and meetings are other important targets for potential improvement. Additionally, insecurity about the future should be addressed as it can affect both Burnout and Compassion Satisfaction. Finally, strategies to reduce possible work-life conflicts need to be considered.

Anxious or Depressed and Still Happy?

PubMed Central

Spinhoven, Philip; Elzinga, Bernet M.; Giltay, Erik; Penninx, Brenda W. J. H.

2015-01-01

This study aimed to examine cross-sectionally to what extent persons with higher symptom levels or a current or past emotional disorder report to be less happy than controls and to assess prospectively whether time-lagged measurements of extraversion and neuroticism predict future happiness independent of time-lagged measurements of emotional disorders or symptom severity. A sample of 2142 adults aged 18–65, consisting of healthy controls and persons with current or past emotional disorder according to DSM-IV criteria completed self-ratings for happiness and emotional well-being and symptom severity. Lagged measurements of personality, symptom severity and presence of anxiety and depressive disorder at T0 (year 0), T2 (year 2) and T4 (year 4) were used to predict happiness and emotional well-being at T6 (year 6) controlling for demographics. In particular persons with more depressive symptoms, major depressive disorder, social anxiety disorder and comorbid emotional disorders reported lower levels of happiness and emotional well-being. Depression symptom severity and to a lesser extent depressive disorder predicted future happiness and emotional well-being at T6. Extraversion and to a lesser extent neuroticism also consistently forecasted future happiness and emotional well-being independent of concurrent lagged measurements of emotional disorders and symptoms. A study limitation is that we only measured happiness and emotional well-being at T6 and our measures were confined to hedonistic well-being and did not include psychological and social well-being. In sum, consistent with the two continua model of emotional well-being and mental illness, a ‘happy’ personality characterized by high extraversion and to a lesser extent low neuroticism forecasts future happiness and emotional well-being independent of concurrently measured emotional disorders or symptom severity levels. Boosting positive emotionality may be an important treatment goal for persons personally inclined to lower levels of happiness. PMID:26461261

A Bayesian network to predict coastal vulnerability to sea level rise

USGS Publications Warehouse

Gutierrez, B.T.; Plant, N.G.; Thieler, E.R.

2011-01-01

Sea level rise during the 21st century will have a wide range of effects on coastal environments, human development, and infrastructure in coastal areas. The broad range of complex factors influencing coastal systems contributes to large uncertainties in predicting long-term sea level rise impacts. Here we explore and demonstrate the capabilities of a Bayesian network (BN) to predict long-term shoreline change associated with sea level rise and make quantitative assessments of prediction uncertainty. A BN is used to define relationships between driving forces, geologic constraints, and coastal response for the U.S. Atlantic coast that include observations of local rates of relative sea level rise, wave height, tide range, geomorphic classification, coastal slope, and shoreline change rate. The BN is used to make probabilistic predictions of shoreline retreat in response to different future sea level rise rates. Results demonstrate that the probability of shoreline retreat increases with higher rates of sea level rise. Where more specific information is included, the probability of shoreline change increases in a number of cases, indicating more confident predictions. A hindcast evaluation of the BN indicates that the network correctly predicts 71% of the cases. Evaluation of the results using Brier skill and log likelihood ratio scores indicates that the network provides shoreline change predictions that are better than the prior probability. Shoreline change outcomes indicating stability (-1 1 m/yr) was not well predicted. We find that BNs can assimilate important factors contributing to coastal change in response to sea level rise and can make quantitative, probabilistic predictions that can be applied to coastal management decisions. Copyright ?? 2011 by the American Geophysical Union.

Why are coast redwood and giant sequoia not where they are not?

Treesearch

W.J. Libby

2017-01-01

Models predicting future climates and other kinds of information are being developed to anticipate where these two species may fail, where they may continue to thrive, and where they may colonize, given changes in climate and other elements of the environment. Important elements of such predictions, among others, are: photoperiod; site qualities; changes in levels and...

Recent Results on "Approximations to Optimal Alarm Systems for Anomaly Detection"

NASA Technical Reports Server (NTRS)

Martin, Rodney Alexander

2009-01-01

An optimal alarm system and its approximations may use Kalman filtering for univariate linear dynamic systems driven by Gaussian noise to provide a layer of predictive capability. Predicted Kalman filter future process values and a fixed critical threshold can be used to construct a candidate level-crossing event over a predetermined prediction window. An optimal alarm system can be designed to elicit the fewest false alarms for a fixed detection probability in this particular scenario.

Water level management of lakes connected to regulated rivers: An integrated modeling and analytical methodology

NASA Astrophysics Data System (ADS)

Hu, Tengfei; Mao, Jingqiao; Pan, Shunqi; Dai, Lingquan; Zhang, Peipei; Xu, Diandian; Dai, Huichao

2018-07-01

Reservoir operations significantly alter the hydrological regime of the downstream river and river-connected lake, which has far-reaching impacts on the lake ecosystem. To facilitate the management of lakes connected to regulated rivers, the following information must be provided: (1) the response of lake water levels to reservoir operation schedules in the near future and (2) the importance of different rivers in terms of affecting the water levels in different lake regions of interest. We develop an integrated modeling and analytical methodology for the water level management of such lakes. The data-driven method is used to model the lake level as it has the potential of producing quick and accurate predictions. A new genetic algorithm-based synchronized search is proposed to optimize input variable time lags and data-driven model parameters simultaneously. The methodology also involves the orthogonal design and range analysis for extracting the influence of an individual river from that of all the rivers. The integrated methodology is applied to the second largest freshwater lake in China, the Dongting Lake. The results show that: (1) the antecedent lake levels are of crucial importance for the current lake level prediction; (2) the selected river discharge time lags reflect the spatial heterogeneity of the rivers' impacts on lake level changes; (3) the predicted lake levels are in very good agreement with the observed data (RMSE ≤ 0.091 m; R2 ≥ 0.9986). This study demonstrates the practical potential of the integrated methodology, which can provide both the lake level responses to future dam releases and the relative contributions of different rivers to lake level changes.

Rising sea levels will reduce extreme temperature variations in tide-dominated reef habitats

PubMed Central

Lowe, Ryan Joseph; Pivan, Xavier; Falter, James; Symonds, Graham; Gruber, Renee

2016-01-01

Temperatures within shallow reefs often differ substantially from those in the surrounding ocean; therefore, predicting future patterns of thermal stresses and bleaching at the scale of reefs depends on accurately predicting reef heat budgets. We present a new framework for quantifying how tidal and solar heating cycles interact with reef morphology to control diurnal temperature extremes within shallow, tidally forced reefs. Using data from northwestern Australia, we construct a heat budget model to investigate how frequency differences between the dominant lunar semidiurnal tide and diurnal solar cycle drive ~15-day modulations in diurnal temperature extremes. The model is extended to show how reefs with tidal amplitudes comparable to their depth, relative to mean sea level, tend to experience the largest temperature extremes globally. As a consequence, we reveal how even a modest sea level rise can substantially reduce temperature extremes within tide-dominated reefs, thereby partially offsetting the local effects of future ocean warming. PMID:27540589

Having Fun on Facebook?: Mothers' Enjoyment as a Moderator of Mental Health and Facebook Use.

PubMed

Kaufmann, Renee; Buckner, Marjorie M; Ledbetter, Andrew M

2017-08-01

This study reports results of a study that examined the extent to which contextual factors (i.e., income level and number of children) might predict a mother's mental health quality, which, in turn, may predict level of engagement with Facebook. Results supported this model, finding that mothers with more children and lower income possess lower mental health quality, and lower mental health quality predicted more frequent Facebook use. However, this pattern was qualified by a mother's level of enjoyment of Facebook, such that mental health quality did not significantly predict Facebook intensity when enjoyment of Facebook was low. This research extends practitioners' knowledge of mothers' mental health quality by identifying a behavior that may indicate lower mental health quality and enhance abilities to recognize mothers who may need support or treatment. Future directions for this research are included.

Development of a Geographic Information System (GIS) tool for the preliminary assessment of the effects of predicted sea level and tidal change on transportation infrastructure.

DOT National Transportation Integrated Search

2013-09-01

In this project, researchers from the University of Florida developed a sketch planning tool that can be used to conduct statewide and regional assessments of transportation facilities potentially vulnerable to sea level change trends. Possible futur...

Does Educational Level Matter in Adopting Online Education? A Malaysian Perspective

ERIC Educational Resources Information Center

Haghshenas, Hanif; Chatroudi, Ehsan Aminaei; Njeje, Fredy Anthony

2012-01-01

Having applied Unified Theory of Acceptance and Use of Technology (UTAUT) to predict intention and future usage behavior, the moderating effect of educational level was added to the model in moderating the relationship between variables. Also, despite past studies, Effort Expectancy had a higher beta than Performance Expectancy, while Social…

Fifth International Symposium on Liquid Space Propulsion

NASA Technical Reports Server (NTRS)

Garcia, R. (Compiler)

2005-01-01

Contents include the fiollowing: Theme: Life-life Combustion Devices Technology. Technical Sessions: International Perspectives. System Level Effects. Component Level Processes. Material Considerations. Design Environments -- Predictions. Injector Design Technology. Design Environments -- Measurements. Panel Discussion: Views on future research and development needs and Symposium observations. Aquarium Welcome and Southern Belle Riverboat Recognition Banquet evening events.

Childhood drinking and depressive symptom level predict harmful personality change

PubMed Central

Riley, Elizabeth N.; Smith, Gregory T.

2016-01-01

Personality traits in children predict numerous life outcomes. Although traits are generally stable, if there is personality change in youth, it could affect subsequent behavior in important ways. We found that the trait of urgency, the tendency to act impulsively when highly emotional, increases for some youth in early adolescence. This increase can be predicted from the behavior of young children: alcohol consumption and depressive symptom level in elementary school children (5th grade) predicted increases in urgency 18 months later. Urgency, in turn, predicted increases in a wide range of maladaptive behaviors another 30 months later, at the end of the first year of high school. The mechanism by which early drinking behavior and depressive symptoms predict personality is not yet clear and merits future research; notably, the findings are consistent with mechanisms proposed by personality change theory and urgency theory. PMID:28392979

Resource Management in Constrained Dynamic Situations

NASA Astrophysics Data System (ADS)

Seok, Jinwoo

Resource management is considered in this dissertation for systems with limited resources, possibly combined with other system constraints, in unpredictably dynamic environments. Resources may represent fuel, power, capabilities, energy, and so on. Resource management is important for many practical systems; usually, resources are limited, and their use must be optimized. Furthermore, systems are often constrained, and constraints must be satisfied for safe operation. Simplistic resource management can result in poor use of resources and failure of the system. Furthermore, many real-world situations involve dynamic environments. Many traditional problems are formulated based on the assumptions of given probabilities or perfect knowledge of future events. However, in many cases, the future is completely unknown, and information on or probabilities about future events are not available. In other words, we operate in unpredictably dynamic situations. Thus, a method is needed to handle dynamic situations without knowledge of the future, but few formal methods have been developed to address them. Thus, the goal is to design resource management methods for constrained systems, with limited resources, in unpredictably dynamic environments. To this end, resource management is organized hierarchically into two levels: 1) planning, and 2) control. In the planning level, the set of tasks to be performed is scheduled based on limited resources to maximize resource usage in unpredictably dynamic environments. In the control level, the system controller is designed to follow the schedule by considering all the system constraints for safe and efficient operation. Consequently, this dissertation is mainly divided into two parts: 1) planning level design, based on finite state machines, and 2) control level methods, based on model predictive control. We define a recomposable restricted finite state machine to handle limited resource situations and unpredictably dynamic environments for the planning level. To obtain a policy, dynamic programing is applied, and to obtain a solution, limited breadth-first search is applied to the recomposable restricted finite state machine. A multi-function phased array radar resource management problem and an unmanned aerial vehicle patrolling problem are treated using recomposable restricted finite state machines. Then, we use model predictive control for the control level, because it allows constraint handling and setpoint tracking for the schedule. An aircraft power system management problem is treated that aims to develop an integrated control system for an aircraft gas turbine engine and electrical power system using rate-based model predictive control. Our results indicate that at the planning level, limited breadth-first search for recomposable restricted finite state machines generates good scheduling solutions in limited resource situations and unpredictably dynamic environments. The importance of cooperation in the planning level is also verified. At the control level, a rate-based model predictive controller allows good schedule tracking and safe operations. The importance of considering the system constraints and interactions between the subsystems is indicated. For the best resource management in constrained dynamic situations, the planning level and the control level need to be considered together.

Anticipated affective consequences of physical activity adoption and maintenance.

PubMed

Dunton, Genevieve Fridlund; Vaughan, Elaine

2008-11-01

The expected emotional consequences of future actions are thought to play an important role in health behavior change. This research examined whether anticipated affective consequences of success and failure vary across stages of physical activity change and differentially predict physical activity adoption as compared to maintenance. Using a prospective design over a 3-month period, a community sample of 329 healthy, middle-aged adults were assessed at 2 time points. Anticipated positive and negative emotions, stage of behavior change (precontemplation [PC], contemplation [C], preparation [P], action [A], maintenance [M]), and level of physical activity. At baseline, anticipated positive emotions were greater in C versus PC, whereas anticipated negative emotions were greater in M versus A and in M versus P. Higher anticipated positive but not negative emotions predicted physical activity adoption and maintenance after 3 months. Although the expected affective consequences of future success and failure differentiated among individuals in the early and later stages of physical activity change, respectively; only the anticipated affective consequences of success predicted future behavior.

Quantifying an aquifer nitrate budget and future nitrate discharge using field data from streambeds and well nests

NASA Astrophysics Data System (ADS)

Gilmore, Troy E.; Genereux, David P.; Solomon, D. Kip; Farrell, Kathleen M.; Mitasova, Helena

2016-11-01

Novel groundwater sampling (age, flux, and nitrate) carried out beneath a streambed and in wells was used to estimate (1) the current rate of change of nitrate storage, dSNO3/dt, in a contaminated unconfined aquifer, and (2) future [NO3-]FWM (the flow-weighted mean nitrate concentration in groundwater discharge) and fNO3 (the nitrate flux from aquifer to stream). Estimates of dSNO3/dt suggested that at the time of sampling (2013) the nitrate storage in the aquifer was decreasing at an annual rate (mean = -9 mmol/m2yr) equal to about one-tenth the rate of nitrate input by recharge. This is consistent with data showing a slow decrease in the [NO3-] of groundwater recharge in recent years. Regarding future [NO3-]FWM and fNO3, predictions based on well data show an immediate decrease that becomes more rapid after ˜5 years before leveling out in the early 2040s. Predictions based on streambed data generally show an increase in future [NO3-]FWM and fNO3 until the late 2020s, followed by a decrease before leveling out in the 2040s. Differences show the potential value of using information directly from the groundwater—surface water interface to quantify the future impact of groundwater nitrate on surface water quality. The choice of denitrification kinetics was similarly important; compared to zero-order kinetics, a first-order rate law levels out estimates of future [NO3-]FWM and fNO3 (lower peak, higher minimum) as legacy nitrate is flushed from the aquifer. Major fundamental questions about nonpoint-source aquifer contamination can be answered without a complex numerical model or long-term monitoring program.

Ground penetrating radar (GPR) for pavement evaluation.

DOT National Transportation Integrated Search

2012-12-01

In the near future the Arkansas State Highway and Transportation Department Pavement Management System (PMS) will utilize a : Falling Weight Deflectometer (FWD) to collect network level pavement structural data to aid in predicting performance of pav...

Future-oriented tweets predict lower county-level HIV prevalence in the United States.

PubMed

Ireland, Molly E; Schwartz, H Andrew; Chen, Qijia; Ungar, Lyle H; Albarracín, Dolores

2015-12-01

Future orientation promotes health and well-being at the individual level. Computerized text analysis of a dataset encompassing billions of words used across the United States on Twitter tested whether community-level rates of future-oriented messages correlated with lower human immunodeficiency virus (HIV) rates and moderated the association between behavioral risk indicators and HIV. Over 150 million tweets mapped to U.S. counties were analyzed using 2 methods of text analysis. First, county-level HIV rates (cases per 100,000) were regressed on aggregate usage of future-oriented language (e.g., will, gonna). A second data-driven method regressed HIV rates on individual words and phrases. Results showed that counties with higher rates of future tense on Twitter had fewer HIV cases, independent of strong structural predictors of HIV such as population density. Future-oriented messages also appeared to buffer health risk: Sexually transmitted infection rates and references to risky behavior on Twitter were associated with higher HIV prevalence in all counties except those with high rates of future orientation. Data-driven analyses likewise showed that words and phrases referencing the future (e.g., tomorrow, would be) correlated with lower HIV prevalence. Integrating big data approaches to text analysis and epidemiology with psychological theory may provide an inexpensive, real-time method of anticipating outbreaks of HIV and etiologically similar diseases. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Future-Oriented Tweets Predict Lower County-Level HIV Prevalence in the United States

PubMed Central

Ireland, Molly E.; Schwartz, Hansen A.; Chen, Qijia; Ungar, Lyle; Albarracín, Dolores

2016-01-01

Objective Future orientation promotes health and well-being at the individual level. Computerized text analysis of a dataset encompassing billions of words used across the United States on Twitter tested whether community-level rates of future-oriented messages correlated with lower HIV rates and moderated the association between behavioral risk indicators and HIV. Method Over 150 million Tweets mapped to US counties were analyzed using two methods of text analysis. First, county-level HIV rates (cases per 100,000) were regressed on aggregate usage of future-oriented language (e.g., will, gonna). A second data-driven method regressed HIV rates on individual words and phrases. Results Results showed that counties with higher rates of future tense on Twitter had fewer HIV cases, independent of strong structural predictors of HIV such as population density. Future-oriented messages also appeared to buffer health risk: Sexually transmitted infection rates and references to risky behavior on Twitter were associated with higher HIV prevalence in all counties except those with high rates of future orientation. Data-driven analyses likewise showed that words and phrases referencing the future (e.g., tomorrow, would be) correlated with lower HIV prevalence. Conclusion Integrating big data approaches to text analysis and epidemiology with psychological theory may provide an inexpensive, real-time method of anticipating outbreaks of HIV and etiologically similar diseases. PMID:26651466

Consumer factors predicting level of treatment response to illness management and recovery.

PubMed

White, Dominique A; McGuire, Alan B; Luther, Lauren; Anderson, Adrienne I; Phalen, Peter; McGrew, John H

2017-12-01

This study aims to identify consumer-level predictors of level of treatment response to illness management and recovery (IMR) to target the appropriate consumers and aid psychiatric rehabilitation settings in developing intervention adaptations. Secondary analyses from a multisite study of IMR were conducted. Self-report data from consumer participants of the parent study (n = 236) were analyzed for the current study. Consumers completed prepost surveys assessing illness management, coping, goal-related hope, social support, medication adherence, and working alliance. Correlations and multiple regression analyses were run to identify self-report variables that predicted level of treatment response to IMR. Analyses revealed that goal-related hope significantly predicted level of improved illness self-management, F(1, 164) = 10.93, p < .001, R2 = .248, R2 change = .05. Additionally, we found that higher levels of maladaptive coping at baseline were predictive of higher levels of adaptive coping at follow-up, F(2, 180) = 5.29, p < .02, R2 = .38, R2 change = .02. Evidence did not support additional predictors. Previously, consumer-level predictors of level of treatment response have not been explored for IMR. Although 2 significant predictors were identified, study findings suggest more work is needed. Future research is needed to identify additional consumer-level factors predictive of IMR treatment response in order to identify who would benefit most from this treatment program. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Predicting introductory programming performance: A multi-institutional multivariate study

NASA Astrophysics Data System (ADS)

Bergin, Susan; Reilly, Ronan

2006-12-01

A model for predicting student performance on introductory programming modules is presented. The model uses attributes identified in a study carried out at four third-level institutions in the Republic of Ireland. Four instruments were used to collect the data and over 25 attributes were examined. A data reduction technique was applied and a logistic regression model using 10-fold stratified cross validation was developed. The model used three attributes: Leaving Certificate Mathematics result (final mathematics examination at second level), number of hours playing computer games while taking the module and programming self-esteem. Prediction success was significant with 80% of students correctly classified. The model also works well on a per-institution level. A discussion on the implications of the model is provided and future work is outlined.

Predictors of smoking lapse in a human laboratory paradigm.

PubMed

Roche, Daniel J O; Bujarski, Spencer; Moallem, Nathasha R; Guzman, Iris; Shapiro, Jenessa R; Ray, Lara A

2014-07-01

During a smoking quit attempt, a single smoking lapse is highly predictive of future relapse. While several risk factors for a smoking lapse have been identified during clinical trials, a laboratory model of lapse was until recently unavailable and, therefore, it is unclear whether these characteristics also convey risk for lapse in a laboratory environment. The primary study goal was to examine whether real-world risk factors of lapse are also predictive of smoking behavior in a laboratory model of smoking lapse. After overnight abstinence, 77 smokers completed the McKee smoking lapse task, in which they were presented with the choice of smoking or delaying in exchange for monetary reinforcement. Primary outcome measures were the latency to initiate smoking behavior and the number of cigarettes smoked during the lapse. Several baseline measures of smoking behavior, mood, and individual traits were examined as predictive factors. Craving to relieve the discomfort of withdrawal, withdrawal severity, and tension level were negatively predictive of latency to smoke. In contrast, average number of cigarettes smoked per day, withdrawal severity, level of nicotine dependence, craving for the positive effects of smoking, and craving to relieve the discomfort of withdrawal were positively predictive of number of cigarettes smoked. The results suggest that real-world risk factors for smoking lapse are also predictive of smoking behavior in a laboratory model of lapse. Future studies using the McKee lapse task should account for between subject differences in the unique factors that independently predict each outcome measure.

Player's success prediction in rugby union: From youth performance to senior level placing.

PubMed

Fontana, Federico Y; Colosio, Alessandro L; Da Lozzo, Giorgio; Pogliaghi, Silvia

2017-04-01

The study questioned if and to what extent specific anthropometric and functional characteristics measured in youth draft camps, can accurately predict subsequent career progression in rugby union. Original research. Anthropometric and functional characteristics of 531 male players (U16) were retrospectively analysed in relation to senior level team representation at age 21-24. Players were classified as International (Int: National team and international clubs) or National (Nat: 1st, 2nd and other divisions and dropout). Multivariate analysis of variance (one-way MANOVA) tested differences between Int and Nat, along a combination of anthropometric (body mass, height, body fat, fat-free mass) and functional variables (SJ, CMJ, t 15m , t 30m , VO 2max ). A discriminant function (DF) was determined to predict group assignment based on the linear combination of variables that best discriminate groups. Correct level assignment was expressed as % hit rate. A combination of anthropometric and functional characteristics reflects future level assignment (Int vs. Nat). Players' success can be accurately predicted (hit rate=81% and 77% for Int and Nat respectively) by a DF that combines anthropometric and functional variables as measured at ∼15 years of age, percent body fat and speed being the most influential predictors of group stratification. Within a group of 15 year-olds with exceptional physical characteristics, future players' success can be predicted using a linear combination of anthropometric and functional variables, among which a lower percent body fat and higher speed over a 15m sprint provide the most important predictors of the highest career success. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

The Representation of Prediction Error in Auditory Cortex

PubMed Central

Rubin, Jonathan; Ulanovsky, Nachum; Tishby, Naftali

2016-01-01

To survive, organisms must extract information from the past that is relevant for their future. How this process is expressed at the neural level remains unclear. We address this problem by developing a novel approach from first principles. We show here how to generate low-complexity representations of the past that produce optimal predictions of future events. We then illustrate this framework by studying the coding of ‘oddball’ sequences in auditory cortex. We find that for many neurons in primary auditory cortex, trial-by-trial fluctuations of neuronal responses correlate with the theoretical prediction error calculated from the short-term past of the stimulation sequence, under constraints on the complexity of the representation of this past sequence. In some neurons, the effect of prediction error accounted for more than 50% of response variability. Reliable predictions often depended on a representation of the sequence of the last ten or more stimuli, although the representation kept only few details of that sequence. PMID:27490251

The Blackwater NWR inundation model. Rising sea level on a low-lying coast: land use planning for wetlands

USGS Publications Warehouse

Larsen, Curt; Clark, Inga; Guntenspergen, Glenn; Cahoon, Don; Caruso, Vincent; Hupp, Cliff; Yanosky, Tom

2004-01-01

The Blackwater National Wildlife Refuge (BNWR), on the Eastern Shore of Chesapeake Bay (figure 1), occupies an area less than 1 meter above sea level. The Refuge has been featured prominently in studies of the impact of sea level rise on coastal wetlands. Most notably, the refuge has been sited by the Intergovernmental Panel on Climate Change (IPCC) as a key example of 'wetland loss' attributable to rising sea level due to global temperature increase. Comparative studies of aerial photos taken since 1938 show an expanding area of open water in the central area of the refuge. The expanding area of open water can be shown to parallel the record of sea level rise over the past 60 years. The U.S. Fish and Wildlife Service (FWS) manages the refuge to support migratory waterfowl and to preserve endangered upland species. High marsh vegetation is critical to FWS waterfowl management strategies. A broad area once occupied by high marsh has decreased with rising sea level. The FWS needs a planning tool to help predict current and future areas of high marsh available for waterfowl. 'Wetland loss' is a relative term. It is dependant on the boundaries chosen for measurement. Wetland vegetation, zoned by elevation and salinity (figure 3), respond to rising sea level. Wetlands migrate inland and upslope and may vary in areas depending on the adjacent land slopes. Refuge managers need a geospatial tool that allows them to predict future areas that will be converted to high and intertidal marsh. Shifts in location and area of coverage must be anticipated. Viability of a current marsh area is also important. When will sea level rise make short-term management strategies to maintain an area impractical? The USGS has developed an inundation model for the BNWR centered on the refuge and surrounding areas. Such models are simple in concept, but they require a detailed topographic map upon which to superimpose future sea level positions. The new system of LIDAR mapping of land and shallow water surfaces has solved this problem. Our team has developed a detailed LIDAR map of the BNWR area at a 30 centimeter (ca. 1 ft) contour interval (figure 2). The new map allows us to identify the present marsh vegetation zones and to predict the location and area of future zones on a decade-by- decade basis over the next century at increments of sea level rise on the order of 3 cm/decade (ca. 1 inch). We have developed two scenarios for the model. The first is a steady-state model that uses the historic rate of sea level rise of 3.1 mm/yr to predict marsh areas. The second is a 'global warming' scenario utilizing a conservative IPCC model with an exponentially-increasing rate of sea level rise. Under either scenario, the BNWR is progressively inundated with an expanding core of open water. Although their positions change in the future, the areas of intertidal marsh as well as those of the critical high marsh remain fairly constant until the year 2050. Beyond that time, the low-lying land surface is overtopped by rising sea level and the area is dominated by open water. Our model suggests that wetland habitat in the Blackwater area might be maintained and sustained through a combination of public and private preservation efforts through easements in combination with judicious Federal land acquisition into the predicted areas of suitable marsh formation - but for only the next 50 years. Beyond that time much of this area will become open water.

Predictors of future anabolic androgenic steroid use.

PubMed

Wichstrøm, Lars

2006-09-01

To prospectively study the stability of anabolic androgenic steroid (AAS) use and predictors of AAS use, and to investigate whether AAS use alters the risk of later emotional and behavioral problems. Survey of a national sample of Norwegian high school students (age 15-19) in 1994 followed up in 1999 (N = 2924). Measures of frequent alcohol intoxication (50+ times per 12 months), cannabis use (12 months), hard drug use (12 months), being offered cannabis, eating problems, conduct problems, sexual debut before age 15, BMI, involvement in power sports, perceived physical appearance, and satisfaction with body parts were obtained. Life-time prevalence of AAS use were 1.9 and 0.8% in the follow-up period. Multivariate logistic regression revealed that future AAS use was predicted by young age, male gender, previous AAS use, involvement in power sports, and frequent alcohol intoxication. AAS use did not predict future emotional or behavioral problems other than reducing the risk of future frequent alcohol intoxication. Frequent alcohol intoxication and involvement in power sports appear to predict future AAS use. At the population level there was little stability in individual AAS use from adolescence to early adulthood. No detrimental effects of AAS use could be detected in this study, but low statistical power limits this conclusion.

Contrasting outcomes of species- and community-level analyses of the temporal consistency of functional composition.

PubMed

Katabuchi, Masatoshi; Wright, S Joseph; Swenson, Nathan G; Feeley, Kenneth J; Condit, Richard; Hubbell, Stephen P; Davies, Stuart J

2017-09-01

Multiple anthropogenic drivers affect every natural community, and there is broad interest in using functional traits to understand and predict the consequences for future biodiversity. There is, however, no consensus regarding the choice of analytical methods. We contrast species- and community-level analyses of change in the functional composition for four traits related to drought tolerance using three decades of repeat censuses of trees in the 50-ha Forest Dynamics Plot on Barro Colorado Island, Panama. Community trait distributions shifted significantly through time, which may indicate a shift toward more drought tolerant species. However, at the species level, changes in abundance were unrelated to trait values. To reconcile these seemingly contrasting results, we evaluated species-specific contributions to the directional shifts observed at the community level. Abundance changes of just one to six of 312 species were responsible for the community-level shifts observed for each trait. Our results demonstrate that directional changes in community-level functional composition can result from idiosyncratic change in a few species rather than widespread community-wide changes associated with functional traits. Future analyses of directional change in natural communities should combine community-, species-, and possibly individual-level analyses to uncover relationships with function that can improve understanding and enable prediction. © 2017 by the Ecological Society of America.

Dengue prediction by the web: Tweets are a useful tool for estimating and forecasting Dengue at country and city level.

PubMed

Marques-Toledo, Cecilia de Almeida; Degener, Carolin Marlen; Vinhal, Livia; Coelho, Giovanini; Meira, Wagner; Codeço, Claudia Torres; Teixeira, Mauro Martins

2017-07-01

Infectious diseases are a leading threat to public health. Accurate and timely monitoring of disease risk and progress can reduce their impact. Mentioning a disease in social networks is correlated with physician visits by patients, and can be used to estimate disease activity. Dengue is the fastest growing mosquito-borne viral disease, with an estimated annual incidence of 390 million infections, of which 96 million manifest clinically. Dengue burden is likely to increase in the future owing to trends toward increased urbanization, scarce water supplies and, possibly, environmental change. The epidemiological dynamic of Dengue is complex and difficult to predict, partly due to costly and slow surveillance systems. In this study, we aimed to quantitatively assess the usefulness of data acquired by Twitter for the early detection and monitoring of Dengue epidemics, both at country and city level at a weekly basis. Here, we evaluated and demonstrated the potential of tweets modeling for Dengue estimation and forecast, in comparison with other available web-based data, Google Trends and Wikipedia access logs. Also, we studied the factors that might influence the goodness-of-fit of the model. We built a simple model based on tweets that was able to 'nowcast', i.e. estimate disease numbers in the same week, but also 'forecast' disease in future weeks. At the country level, tweets are strongly associated with Dengue cases, and can estimate present and future Dengue cases until 8 weeks in advance. At city level, tweets are also useful for estimating Dengue activity. Our model can be applied successfully to small and less developed cities, suggesting a robust construction, even though it may be influenced by the incidence of the disease, the activity of Twitter locally, and social factors, including human development index and internet access. Tweets association with Dengue cases is valuable to assist traditional Dengue surveillance at real-time and low-cost. Tweets are able to successfully nowcast, i.e. estimate Dengue in the present week, but also forecast, i.e. predict Dengue at until 8 weeks in the future, both at country and city level with high estimation capacity.

Predicting future spatial distribution of SOC across entire France

NASA Astrophysics Data System (ADS)

Meersmans, Jeroen; Van Rompaey, Anton; Quine, Tim; Martin, Manuel; Pagé, Christian; Arrouays, Dominique

2013-04-01

Soil organic carbon (SOC) is widely recognized as a key factor controlling soil quality and as a crucial and active component of the global C-cycle. Hence, there exists a growing interest in monitoring and modeling the spatial and temporal behavior of this pool. So far, a large attempt has been made to map SOC at national scales for current and/or past situations. Despite some coarse predictions, detailed spatial SOC predictions for the future are still lacking. In this study we aim to predict future spatial evolution of SOC driven by climate and land use change for France up to the year 2100. Therefore, we combined 1) an existing model, predicting SOC as a function of soil type, climate, land use and management (Meersmans et al 2012), with 2) eight different IPCC spatial explicit climate change predictions (conducted by CERFACS) and 3) Land use change scenario predictions. We created business-as-usual land use change scenarios by extrapolating observed trends and calibrating logistic regression models, incorporating a large set of physical and socio-economic factors, at the regional level in combination with a multi-objective land allocation (MOLA) procedure. The resultant detailed projections of future SOC evolution across all regions of France, allow us to identify regions that are most likely to be characterized by a significant gain or loss of SOC and the degree to which land use decisions/outcomes control the scale of loss and gain. Therefore, this methodology and resulting maps can be considered as powerful tools to aid decision making concerning appropriate soil management, in order to enlarge SOC storage possibilities and reduce soil related CO2 fluxes.

From Discrimination to Internalized Mental Illness Stigma: The Mediating Roles of Anticipated Discrimination and Anticipated Stigma

PubMed Central

Quinn, Diane M.; Williams, Michelle K.; Weisz, Bradley M.

2015-01-01

Objective Internalizing mental illness stigma is related to poorer well-being, but less is known about the factors that predict levels of internalized stigma. This study explored how experiences of discrimination relate to greater anticipation of discrimination and devaluation in the future, and how anticipation of stigma, in turn predicts greater stigma internalization. Method Participants were 105 adults with mental illness who self-reported their experiences of discrimination based on their mental illness, their anticipation of discrimination and social devaluation from others in the future, and their level of internalized stigma. Participants were approached in several locations and completed surveys on laptop computers. Results Correlational analyses indicated that more experiences of discrimination due to one’s mental illness were related to increased anticipated discrimination in the future, increased anticipated social stigma from others, and greater internalized stigma. Multiple serial mediator analyses showed that the effect of experiences of discrimination on internalized stigma was fully mediated by increased anticipated discrimination and anticipated stigma. Conclusion and Implications for Practice Experiences of discrimination over the lifetime may influence not only how much future discrimination people with mental illness are concerned with but also how much they internalize negative feelings about the self. Mental health professionals may need to address concerns with future discrimination and devaluation in order to decrease internalized stigma. PMID:25844910

Impact of climate change on mercury concentrations and deposition in the eastern United States.

PubMed

Megaritis, Athanasios G; Murphy, Benjamin N; Racherla, Pavan N; Adams, Peter J; Pandis, Spyros N

2014-07-15

The global-regional climate-air pollution modeling system (GRE-CAPS) was applied over the eastern United States to study the impact of climate change on the concentration and deposition of atmospheric mercury. Summer and winter periods (300 days for each) were simulated, and the present-day model predictions (2000s) were compared to the future ones (2050s) assuming constant emissions. Climate change affects Hg(2+) concentrations in both periods. On average, atmospheric Hg(2+) levels are predicted to increase in the future by 3% in summer and 5% in winter respectively due to enhanced oxidation of Hg(0) under higher temperatures. The predicted concentration change of Hg(2+) was found to vary significantly in space due to regional-scale changes in precipitation, ranging from -30% to 30% during summer and -20% to 40% during winter. Particulate mercury, Hg(p) has a similar spatial response to climate change as Hg(2+), while Hg(0) levels are not predicted to change significantly. In both periods, the response of mercury deposition to climate change varies spatially with an average predicted increase of 6% during summer and 4% during winter. During summer, deposition increases are predicted mostly in the western parts of the domain while mercury deposition is predicted to decrease in the Northeast and also in many areas in the Midwest and Southeast. During winter mercury deposition is predicted to change from -30% to 50% mainly due to the changes in rainfall and the corresponding changes in wet deposition. Copyright © 2014 Elsevier B.V. All rights reserved.

Acoustics Research of Propulsion Systems

NASA Technical Reports Server (NTRS)

Gao, Ximing; Houston, Janice D.

2014-01-01

The liftoff phase induces some of the highest acoustic loading over a broad frequency for a launch vehicle. These external acoustic environments are used in the prediction of the internal vibration responses of the vehicle and components. Thus, predicting these liftoff acoustic environments is critical to the design requirements of any launch vehicle but there are challenges. Present liftoff vehicle acoustic environment prediction methods utilize stationary data from previously conducted hold-down tests; i.e. static firings conducted in the 1960's, to generate 1/3 octave band Sound Pressure Level (SPL) spectra. These data sets are used to predict the liftoff acoustic environments for launch vehicles. To facilitate the accuracy and quality of acoustic loading, predictions at liftoff for future launch vehicles such as the Space Launch System (SLS), non-stationary flight data from the Ares I-X were processed in PC-Signal in two forms which included a simulated hold-down phase and the entire launch phase. In conjunction, the Prediction of Acoustic Vehicle Environments (PAVE) program was developed in MATLAB to allow for efficient predictions of sound pressure levels (SPLs) as a function of station number along the vehicle using semiempirical methods. This consisted, initially, of generating the Dimensionless Spectrum Function (DSF) and Dimensionless Source Location (DSL) curves from the Ares I-X flight data. These are then used in the MATLAB program to generate the 1/3 octave band SPL spectra. Concluding results show major differences in SPLs between the hold-down test data and the processed Ares IX flight data making the Ares I-X flight data more practical for future vehicle acoustic environment predictions.

Prospective Coding by Spiking Neurons

PubMed Central

Brea, Johanni; Gaál, Alexisz Tamás; Senn, Walter

2016-01-01

Animals learn to make predictions, such as associating the sound of a bell with upcoming feeding or predicting a movement that a motor command is eliciting. How predictions are realized on the neuronal level and what plasticity rule underlies their learning is not well understood. Here we propose a biologically plausible synaptic plasticity rule to learn predictions on a single neuron level on a timescale of seconds. The learning rule allows a spiking two-compartment neuron to match its current firing rate to its own expected future discounted firing rate. For instance, if an originally neutral event is repeatedly followed by an event that elevates the firing rate of a neuron, the originally neutral event will eventually also elevate the neuron’s firing rate. The plasticity rule is a form of spike timing dependent plasticity in which a presynaptic spike followed by a postsynaptic spike leads to potentiation. Even if the plasticity window has a width of 20 milliseconds, associations on the time scale of seconds can be learned. We illustrate prospective coding with three examples: learning to predict a time varying input, learning to predict the next stimulus in a delayed paired-associate task and learning with a recurrent network to reproduce a temporally compressed version of a sequence. We discuss the potential role of the learning mechanism in classical trace conditioning. In the special case that the signal to be predicted encodes reward, the neuron learns to predict the discounted future reward and learning is closely related to the temporal difference learning algorithm TD(λ). PMID:27341100

Do We Need Better Climate Predictions to Adapt to a Changing Climate? (Invited)

NASA Astrophysics Data System (ADS)

Dessai, S.; Hulme, M.; Lempert, R.; Pielke, R., Jr.

2009-12-01

Based on a series of international scientific assessments, climate change has been presented to society as a major problem that needs urgently to be tackled. The science that underpins these assessments has been pre-dominantly from the realm of the natural sciences and central to this framing have been ‘projections’ of future climate change (and its impacts on environment and society) under various greenhouse gas emissions scenarios and using a variety of climate model predictions with embedded assumptions. Central to much of the discussion surrounding adaptation to climate change is the claim - explicit or implicit - that decision makers need accurate and increasingly precise assessments of future impacts of climate change in order to adapt successfully. If true, this claim places a high premium on accurate and precise climate predictions at a range of geographical and temporal scales; such predictions therefore become indispensable, and indeed a prerequisite for, effective adaptation decision-making. But is effective adaptation tied to the ability of the scientific enterprise to predict future climate with accuracy and precision? If so, this may impose a serious and intractable limit on adaptation. This paper proceeds in three sections. It first gathers evidence of claims that climate prediction is necessary for adaptation decision-making. This evidence is drawn from peer-reviewed literature and from published science funding strategies and government policy in a number of different countries. The second part discusses the challenges of climate prediction and why science will consistently be unable to provide accurate and precise predictions of future climate relevant for adaptation (usually at the local/regional level). Section three discusses whether these limits to future foresight represent a limit to adaptation, arguing that effective adaptation need not be limited by a general inability to predict future climate. Given the deep uncertainties involved in climate prediction (and even more so in the prediction of climate impacts) and given that climate is usually only one factor in decisions aimed at climate adaptation, we conclude that the ‘predict and provide’ approach to science in support of climate change adaptation is largely flawed. We consider other important areas of public policy fraught with uncertainty - e.g. earthquake risk, national security, public health - where such a ‘predict and provide’ approach is not attempted. Instead of relying on an approach which has climate prediction (and consequent risk assessment) at its heart - which because of the associated epistemological limits to prediction will consequently act as an apparent limit to adaptation - we need to view adaptation differently, in a manner that opens up options for decision making under uncertainty. We suggest an approach which examines the robustness of adaptation strategies/policies/activities to the myriad of uncertainties that face us in the future, only one of which is the state of climate.

The Predictive Validity of the ABFM's In-Training Examination.

PubMed

O'Neill, Thomas R; Li, Zijia; Peabody, Michael R; Lybarger, Melanie; Royal, Kenneth; Puffer, James C

2015-05-01

Our objective was to examine the predictive validity of the American Board of Family Medicine's (ABFM) In-Training Examination (ITE) with regard to predicting outcomes on the ABFM certification examination. This study used a repeated measures design across three levels of medical training (PGY1--PGY2, PGY2--PGY3, and PGY3--initial certification) with three different cohorts (2010--2011, 2011--2012, and 2012--2013) to examine: (1) how well the residents' ITE scores correlated with their test scores in the following year, (2) what the typical score increase was across training years, and (3) what was the sensitivity, specificity, positive predictive value, and negative predictive value of the PGY3 scores with regard to predicting future results on the MC-FP Examination. ITE scores generally correlate at about .7 with the following year's ITE or with the following year's certification examination. The mean growth from PGY1 to PGY2 was 52 points, from PGY2 to PGY3 was 34 points, and from PGY3 to initial certification was 27 points. The sensitivity, specificity, positive predictive value, and negative predictive value were .91, .47, .96, and .27, respectively. The ITE is a useful predictor of future ITE and initial certification examination performance.

Future states: the axioms underlying prospective, future-oriented, health planning instruments.

PubMed

Koch, T

2001-02-01

Proscriptive planning exercises are critical to and generally accepted as integral to health planning at varying scales. These require specific instruments designed to predict future actions on the basis of present knowledge. At the macro-level of health economics, for example, a number of future-oriented Quality of Life Instruments (QL) are commonly employed. At the level of individual decision making, on the other hand, Advance Directives (AD's) are advanced as a means by which healthy individuals can assure their wishes will be carried out if at some future point they are incapacitated. As proscriptive tools, both instrument classes appear to share an axiomatic set whose individual parts have not been rigorously considered. This paper attempts to first identify and then consider a set of five axioms underlying future oriented health planning instruments. These axioms are then critiqued using data from a pre-test survey designed specifically to address their assumptions. Results appear to challenge the validity of the axioms underlying the proscriptive planning instruments.

Corticosterone mediated costs of reproduction link current to future breeding.

PubMed

Crossin, Glenn T; Phillips, Richard A; Lattin, Christine R; Romero, L Michael; Williams, Tony D

2013-11-01

Life-history theory predicts that costs are associated with reproduction. One possible mediator of costs involves the secretion of glucocorticoid hormones, which in birds can be measured in feathers grown during the breeding period. Glucocorticoids mediate physiological responses to unpredictable environmental or other stressors, but they can also function as metabolic regulators during more predictable events such as reproduction. Here we show that corticosterone ("Cort") in feathers grown during the breeding season reflects reproductive effort in two Antarctic seabird species (giant petrels, Macronectes spp.). In females of both species, but not males, feather Cort ("fCort") was nearly 1.5-fold higher in successful than failed breeders (those that lost their eggs/chicks), suggesting a cost of successful reproduction, i.e., high fCort levels in females reflect the elevated plasma Cort levels required to support high metabolic demands of chick-rearing. Successful breeding also led to delayed moult prior to winter migration. The fCort levels and pre-migration moult score that we measured at the end of current breeding were predictive of subsequent reproductive effort in the following year. Birds with high fCort and a delayed initiation of moult were much more likely to defer breeding in the following year. Cort levels and the timing of moult thus provide a potential mechanism for the tradeoff between current and future reproduction. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

A dark past, a restrained present, and an apocalyptic future: time perspective, personality, and life satisfaction among anorexia nervosa patients.

PubMed

Garcia, Danilo; Granjard, Alexandre; Lundblad, Suzanna; Archer, Trevor

2017-01-01

Despite reporting low levels of well-being, anorexia nervosa patients express temperament traits (e.g., extraversion and persistence) necessary for high levels of life satisfaction. Nevertheless, among individuals without eating disorders, a balanced organization of the flow of time, influences life satisfaction beyond temperamental dispositions. A balanced time perspective is defined as: high past positive, low past negative, high present hedonistic, low present fatalistic, and high future. We investigated differences in time perspective dimensions, personality traits, and life satisfaction between anorexia nervosa patients and matched controls. We also investigated if the personality traits and the outlook on time associated to positive levels of life satisfaction among controls also predicted anorexia patients' life satisfaction. Additionally, we investigated if time perspective dimensions predicted life satisfaction beyond personality traits among both patients and controls. A total of 88 anorexia nervosa patients from a clinic in the West of Sweden and 111 gender-age matched controls from a university in the West of Sweden participated in the Study. All participants responded to the Zimbardo Time Perspective Inventory, the Ten Item Personality Inventory, and the Temporal Satisfaction with Life Scale. A t -test showed that patients scored higher in the past negative, the present fatalistic, and the future dimensions, lower in the past positive and the present hedonistic dimensions, higher in conscientiousness, extraversion, and agreeableness, and lower in life satisfaction. Regression analyses showed that life satisfaction was predicted by openness to experience and emotional stability for controls and by emotional stability among patients. When time dimensions were entered in the regression, emotional stability and the past negative and past positive time dimensions predicted life satisfaction among controls, but only the past positive and present hedonistic time dimensions predicted life satisfaction among patients. Anorexia patients were less satisfied with life despite being more conscientious, social, and agreeable than controls. Moreover, compared to controls, patients had an unbalanced time perspective: a dark view of the past (i.e., high past negative), a restrained present (i.e., low present hedonistic) and an apocalyptic view of the future (i.e., high present fatalistic). It is plausible to suggest that, therapeutic interventions should focus on empowering patients to cultivate a sentimental and positive view of the past (i.e., high past positive) and the desire to experience pleasure without concern for future consequences (i.e., high present hedonistic) so that they can make self-directed and flexible choices for their own well-being. Such interventions might have effects on life satisfaction beyond the patients' temperamental disposition.

Statistical modelling predicts almost complete loss of major periglacial processes in Northern Europe by 2100.

PubMed

Aalto, Juha; Harrison, Stephan; Luoto, Miska

2017-09-11

The periglacial realm is a major part of the cryosphere, covering a quarter of Earth's land surface. Cryogenic land surface processes (LSPs) control landscape development, ecosystem functioning and climate through biogeochemical feedbacks, but their response to contemporary climate change is unclear. Here, by statistically modelling the current and future distributions of four major LSPs unique to periglacial regions at fine scale, we show fundamental changes in the periglacial climate realm are inevitable with future climate change. Even with the most optimistic CO 2 emissions scenario (Representative Concentration Pathway (RCP) 2.6) we predict a 72% reduction in the current periglacial climate realm by 2050 in our climatically sensitive northern Europe study area. These impacts are projected to be especially severe in high-latitude continental interiors. We further predict that by the end of the twenty-first century active periglacial LSPs will exist only at high elevations. These results forecast a future tipping point in the operation of cold-region LSP, and predict fundamental landscape-level modifications in ground conditions and related atmospheric feedbacks.Cryogenic land surface processes characterise the periglacial realm and control landscape development and ecosystem functioning. Here, via statistical modelling, the authors predict a 72% reduction of the periglacial realm in Northern Europe by 2050, and almost complete disappearance by 2100.

Measurement Error Correction Formula for Cluster-Level Group Differences in Cluster Randomized and Observational Studies

ERIC Educational Resources Information Center

Cho, Sun-Joo; Preacher, Kristopher J.

2016-01-01

Multilevel modeling (MLM) is frequently used to detect cluster-level group differences in cluster randomized trial and observational studies. Group differences on the outcomes (posttest scores) are detected by controlling for the covariate (pretest scores) as a proxy variable for unobserved factors that predict future attributes. The pretest and…

Predictors of Adolescent Outcomes among 4–6 Year Old Children with Attention-Deficit/Hyperactivity Disorder

PubMed Central

Lahey, Benjamin B.; Lee, Steve S.; Sibley, Margaret H.; Applegate, Brooks; Molina, Brooke S. G.; Pelham, William E.

2015-01-01

Children who met DSM-IV criteria for attention-deficit/hyperactivity disorder (ADHD) with functional impairment in at least one setting at 4–6 years of age were followed prospectively through age 18 years. On average, the 125 children (107 boys) with ADHD at baseline improved over time, but still continued to exhibit more symptoms, functional impairment, and risky behavior through adolescence than demographically matched healthy comparison children. These findings support the predictive validity of the diagnosis of ADHD at younger ages by demonstrating that the symptoms and impairment are enduring. Nonetheless, there were marked variations in developmental outcomes. Among children with ADHD, higher numbers of inattention and hyperactivity-impulsivity symptoms and higher number of concurrent symptoms (oppositional, conduct disorder, anxiety, and depression) measured at baseline each predicted higher future levels of the same dimension of symptoms. In addition, higher baseline levels of inattention, oppositional, conduct disorder, and anxiety symptoms predicted greater future functional impairment. Among children with ADHD, girls and children from families with lower family incomes had relatively poorer outcomes. Although outcomes varied along a continuum, approximately 10% of the children with ADHD at 4–6 years could be classified as functioning in the normative range on multiple measures during 15–18 years. Although this finding awaits replication, lower levels of hyperactivity-impulsivity symptoms at 4–6 years predicted more normative functioning during adolescence. These findings suggest that ADHD identified in early childhood predicts an increased likelihood of functional impairment through adolescence for most, but not all, children. PMID:26854503

Human Adaptive Behavior in Common Pool Resource Systems

PubMed Central

Brandt, Gunnar; Merico, Agostino; Vollan, Björn; Schlüter, Achim

2012-01-01

Overexploitation of common-pool resources, resulting from uncooperative harvest behavior, is a major problem in many social-ecological systems. Feedbacks between user behavior and resource productivity induce non-linear dynamics in the harvest and the resource stock that complicate the understanding and the prediction of the co-evolutionary system. With an adaptive model constrained by data from a behavioral economic experiment, we show that users’ expectations of future pay-offs vary as a result of the previous harvest experience, the time-horizon, and the ability to communicate. In our model, harvest behavior is a trait that adjusts to continuously changing potential returns according to a trade-off between the users’ current harvest and the discounted future productivity of the resource. Given a maximum discount factor, which quantifies the users’ perception of future pay-offs, the temporal dynamics of harvest behavior and ecological resource can be predicted. Our results reveal a non-linear relation between the previous harvest and current discount rates, which is most sensitive around a reference harvest level. While higher than expected returns resulting from cooperative harvesting in the past increase the importance of future resource productivity and foster sustainability, harvests below the reference level lead to a downward spiral of increasing overexploitation and disappointing returns. PMID:23285180

Oil prices and long-run risk

NASA Astrophysics Data System (ADS)

Ready, Robert Clayton

I show that relative levels of aggregate consumption and personal oil consumption provide an excellent proxy for oil prices, and that high oil prices predict low future aggregate consumption growth. Motivated by these facts, I add an oil consumption good to the long-run risk model of Bansal and Yaron [2004] to study the asset pricing implications of observed changes in the dynamic interaction of consumption and oil prices. Empirically I observe that, compared to the first half of my 1987--2010 sample, oil consumption growth in the last 10 years is unresponsive to levels of oil prices, creating an decrease in the mean-reversion of oil prices, and an increase in the persistence of oil price shocks. The model implies that the change in the dynamics of oil consumption generates increased systematic risk from oil price shocks due to their increased persistence. However, persistent oil prices also act as a counterweight for shocks to expected consumption growth, with high expected growth creating high expectations of future oil prices which in turn slow down growth. The combined effect is to reduce overall consumption risk and lower the equity premium. The model also predicts that these changes affect the riskiness of of oil futures contracts, and combine to create a hump shaped term structure of oil futures, consistent with recent data.

No food for thought: moderating effects of delay discounting and future time perspective on the relation between income and food insecurity.

PubMed

Epstein, Leonard H; Jankowiak, Noelle; Lin, Henry; Paluch, Rocco; Koffarnus, Mikhail N; Bickel, Warren K

2014-09-01

Low income is related to food insecurity, and research has suggested that a scarcity of resources associated with low income can shift attention to the present, thereby discounting the future. We tested whether attending to the present and discounting the future may moderate the influence of income on food insecurity. Delay discounting and measures of future time perspective (Zimbardo Time Perspective Inventory, Consideration of Future Consequences Scale, time period of financial planning, and subjective probability of living to age 75 y) were studied as moderators of the relation between income and food insecurity in a diverse sample of 975 adults, 31.8% of whom experienced some degree of food insecurity. Income, financial planning, subjective probability of living to age 75 y, and delay discounting predicted food insecurity as well as individuals who were high in food insecurity. Three-way interactions showed that delay discounting interacted with financial planning and income to predict food insecurity (P = 0.003). At lower levels of income, food insecurity was lowest for subjects who had good financial planning skills and did not discount the future, whereas having good financial skills and discounting the future had minimal influence on food insecurity. The same 3-way interaction was observed when high food insecurity was predicted (P = 0.008). Because of the role of scarce resources on narrowing attention and reducing prospective thinking, research should address whether modifying future orientation may reduce food insecurity even in the face of diminishing financial resources. © 2014 American Society for Nutrition.

Body mass index influences infliximab post-infusion levels and correlates with prospective loss of response to the drug in a cohort of inflammatory bowel disease patients under maintenance therapy with Infliximab.

PubMed

Scaldaferri, Franco; D'Ambrosio, Daria; Holleran, Grainne; Poscia, Andrea; Petito, Valentina; Lopetuso, Loris; Graziani, Cristina; Laterza, Lucrezia; Pistone, Maria Teresa; Pecere, Silvia; Currò, Diego; Gaetani, Eleonora; Armuzzi, Alessandro; Papa, Alfredo; Cammarota, Giovanni; Gasbarrini, Antonio

2017-01-01

Infliximab is an effective treatment for inflammatory bowel disease (IBD). Studies differ regarding the influence of body mass index (BMI) on the response to infliximab, with the majority of studies indicating that increased BMI may be associated with a poorer response to Infliximab. However, the pharmacokinetic mechanisms causing this have not yet been reported. Examine the correlation between BMI/immunosuppressant use with clinical response, trough and post-infusion levels of infliximab, tumour necrosis factor-α(TNF-α) and anti-drug antibodies(ATI), and determine if these factors can predict future response. We collected serum from 24 patients receiving Infliximab before and 30 minutes following infusion. Clinical parameters were collected retrospectively and prospectively. ELISA measurements of infliximab, TNF-α and ATI were performed. We confirmed that patients with higher infliximab trough levels have a better response rate and that patients with an elevated BMI display a higher rate of loss of response (20%). Patients with a higher BMI had elevated post-infusion levels of infliximab. Additionally, the ratio of IFX/TNF-α trough levels correlated with clinical response to the following infusion. This study confirms that an elevated BMI is associated with a poorer response to infliximab. For the first time, we describe that a higher BMI correlates with higher post-infusion levels, however this does not correlate with a higher rate of response to the drug, suggesting that circulating drug levels do not correlate with tissue levels. Furthermore, in our small cohort of patients, we identified a possible predictive marker of future response to treatment which may be used to guide dose escalation and predict non-response to infliximab.

King Tides and Climate Change

EPA Pesticide Factsheets

The highest predicted high tide of the year at a coastal location can bring unusually high water levels and can cause flooding. Learn about these tides including what they are, when they occur, and what they can mean for the future.

CSF biomarkers of Alzheimer disease

PubMed Central

Fagan, Anne M.; Grant, Elizabeth A.; Holtzman, David M.; Morris, John C.

2013-01-01

Objectives: To test whether CSF Alzheimer disease biomarkers (β-amyloid 42 [Aβ42], tau, phosphorylated tau at threonine 181 [ptau181], tau/Aβ42, and ptau181/Aβ42) predict future decline in noncognitive outcomes among individuals cognitively normal at baseline. Methods: Longitudinal data from participants (N = 430) who donated CSF within 1 year of a clinical assessment indicating normal cognition and were aged 50 years or older were analyzed. Mixed linear models were used to test whether baseline biomarker values predicted future decline in function (instrumental activities of daily living), weight, behavior, and mood. Clinical Dementia Rating Sum of Boxes and Mini-Mental State Examination scores were also examined. Results: Abnormal levels of each biomarker were related to greater impairment with time in behavior (p < 0.035) and mood (p < 0.012) symptoms, and more difficulties with independent activities of daily living (p < 0.012). However, biomarker levels were unrelated to weight change with time (p > 0.115). As expected, abnormal biomarker values also predicted more rapidly changing Mini-Mental State Examination (p < 0.041) and Clinical Dementia Rating Sum of Boxes (p < 0.001) scores compared with normal values. Conclusions: CSF biomarkers among cognitively normal individuals are associated with future decline in some, but not all, noncognitive Alzheimer disease symptoms studied. Additional work is needed to determine the extent to which these findings generalize to other samples. PMID:24212387

CSF biomarkers of Alzheimer disease: "noncognitive" outcomes.

PubMed

Roe, Catherine M; Fagan, Anne M; Grant, Elizabeth A; Holtzman, David M; Morris, John C

2013-12-03

To test whether CSF Alzheimer disease biomarkers (β-amyloid 42 [Aβ42], tau, phosphorylated tau at threonine 181 [ptau181], tau/Aβ42, and ptau181/Aβ42) predict future decline in noncognitive outcomes among individuals cognitively normal at baseline. Longitudinal data from participants (N = 430) who donated CSF within 1 year of a clinical assessment indicating normal cognition and were aged 50 years or older were analyzed. Mixed linear models were used to test whether baseline biomarker values predicted future decline in function (instrumental activities of daily living), weight, behavior, and mood. Clinical Dementia Rating Sum of Boxes and Mini-Mental State Examination scores were also examined. Abnormal levels of each biomarker were related to greater impairment with time in behavior (p < 0.035) and mood (p < 0.012) symptoms, and more difficulties with independent activities of daily living (p < 0.012). However, biomarker levels were unrelated to weight change with time (p > 0.115). As expected, abnormal biomarker values also predicted more rapidly changing Mini-Mental State Examination (p < 0.041) and Clinical Dementia Rating Sum of Boxes (p < 0.001) scores compared with normal values. CSF biomarkers among cognitively normal individuals are associated with future decline in some, but not all, noncognitive Alzheimer disease symptoms studied. Additional work is needed to determine the extent to which these findings generalize to other samples.

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

S. Bays; W. Skerjanc; M. Pope

A comparative analysis and comparison of results obtained between 2-D lattice calculations and 3-D full core nodal calculations, in the frame of MOX fuel design, was conducted. This study revealed a set of advantages and disadvantages, with respect to each method, which can be used to guide the level of accuracy desired for future fuel and fuel cycle calculations. For the purpose of isotopic generation for fuel cycle analyses, the approach of using a 2-D lattice code (i.e., fuel assembly in infinite lattice) gave reasonable predictions of uranium and plutonium isotope concentrations at the predicted 3-D core simulation batch averagemore » discharge burnup. However, it was found that the 2-D lattice calculation can under-predict the power of pins located along a shared edge between MOX and UO2 by as much as 20%. In this analysis, this error did not occur in the peak pin. However, this was a coincidence and does not rule out the possibility that the peak pin could occur in a lattice position with high calculation uncertainty in future un-optimized studies. Another important consideration in realistic fuel design is the prediction of the peak axial burnup and neutron fluence. The use of 3-D core simulation gave peak burnup conditions, at the pellet level, to be approximately 1.4 times greater than what can be predicted using back-of-the-envelope assumptions of average specific power and irradiation time.« less

VTE Risk assessment - a prognostic Model: BATER Cohort Study of young women.

PubMed

Heinemann, Lothar Aj; Dominh, Thai; Assmann, Anita; Schramm, Wolfgang; Schürmann, Rolf; Hilpert, Jan; Spannagl, Michael

2005-04-18

BACKGROUND: Community-based cohort studies are not available that evaluated the predictive power of both clinical and genetic risk factors for venous thromboembolism (VTE). There is, however, clinical need to forecast the likelihood of future occurrence of VTE, at least qualitatively, to support decisions about intensity of diagnostic or preventive measures. MATERIALS AND METHODS: A 10-year observation period of the Bavarian Thromboembolic Risk (BATER) study, a cohort study of 4337 women (18-55 years), was used to develop a predictive model of VTE based on clinical and genetic variables at baseline (1993). The objective was to prepare a probabilistic scheme that discriminates women with virtually no VTE risk from those at higher levels of absolute VTE risk in the foreseeable future. A multivariate analysis determined which variables at baseline were the best predictors of a future VTE event, provided a ranking according to the predictive power, and permitted to design a simple graphic scheme to assess the individual VTE risk using five predictor variables. RESULTS: Thirty-four new confirmed VTEs occurred during the observation period of over 32,000 women-years (WYs). A model was developed mainly based on clinical information (personal history of previous VTE and family history of VTE, age, BMI) and one composite genetic risk markers (combining Factor V Leiden and Prothrombin G20210A Mutation). Four levels of increasing VTE risk were arbitrarily defined to map the prevalence in the study population: No/low risk of VTE (61.3%), moderate risk (21.1%), high risk (6.0%), very high risk of future VTE (0.9%). In 10.6% of the population the risk assessment was not possible due to lacking VTE cases. The average incidence rates for VTE in these four levels were: 4.1, 12.3, 47.2, and 170.5 per 104 WYs for no, moderate, high, and very high risk, respectively. CONCLUSION: Our prognostic tool - containing clinical information (and if available also genetic data) - seems to be worthwhile testing in medical practice in order to confirm or refute the positive findings of this study. Our cohort study will be continued to include more VTE cases and to increase predictive value of the model.

Predicting school sense of community: students' perceptions at two Catholic universities.

PubMed

Bottom, Todd L; Ferrari, Joseph R; Matteo, Elizabeth; Todd, Nathan R

2013-01-01

Understanding the factors that predict sense of community (SOC) among college students has important implications for higher education policy and practice. The present study determined whether perceptions of inclusion and religious pluralism across 2,199 university students' (1,442 women, 757 men; M age = 23.42, SD =7.84) at two Catholic universities predicted levels of school sense of community (SSOC). As expected, results indicated that perceptions of both inclusion and religious pluralism significantly predicted SSOC. However, mixed results were found regarding the interaction of university setting with inclusion and religious pluralism. Limitations and future directions for research are discussed.

The Roles of Family and Teacher Support in Moderating and Mediating Externalized and Internalized Outcomes of Exposure to Community Violence Among Arab and Jewish Adolescents in Israel.

PubMed

Haj-Yahia, Muhammad M; Leshem, Becky; Guterman, Neil B

2018-02-01

The study examined family and teacher support as factors that can protect adolescents from internalized and externalized problems after exposure to community violence (ECV). Self-administered questionnaires were filled out by a sample of 1,832 Arab and Jewish Israeli high school students. The Arab adolescents reported significantly higher levels of community violence victimization, internalized problems, externalized problems, family support, and teacher support than the Jewish adolescents. The girls reported higher levels of internalized problems, and the boys reported higher levels of externalized problems. ECV predicted high levels of internalized and externalized problems, family support predicted low levels of internalized and externalized problems, and teacher support had no predictive role. Path analysis confirmed the significance of the relationships between ECV effects, support variables, and gender. The limitations of the study and implications of the findings for future research and for the development of family care and family intervention programs are discussed.

A Bayesian network to predict vulnerability to sea-level rise: data report

USGS Publications Warehouse

Gutierrez, Benjamin T.; Plant, Nathaniel G.; Thieler, E. Robert

2011-01-01

During the 21st century, sea-level rise is projected to have a wide range of effects on coastal environments, development, and infrastructure. Consequently, there has been an increased focus on developing modeling or other analytical approaches to evaluate potential impacts to inform coastal management. This report provides the data that were used to develop and evaluate the performance of a Bayesian network designed to predict long-term shoreline change due to sea-level rise. The data include local rates of relative sea-level rise, wave height, tide range, geomorphic classification, coastal slope, and shoreline-change rate compiled as part of the U.S. Geological Survey Coastal Vulnerability Index for the U.S. Atlantic coast. In this project, the Bayesian network is used to define relationships among driving forces, geologic constraints, and coastal responses. Using this information, the Bayesian network is used to make probabilistic predictions of shoreline change in response to different future sea-level-rise scenarios.

Trend in Obesity Prevalence in European Adult Cohort Populations during Follow-up since 1996 and Their Predictions to 2015

PubMed Central

von Ruesten, Anne; Steffen, Annika; Floegel, Anna; van der A, Daphne L.; Masala, Giovanna; Tjønneland, Anne; Halkjaer, Jytte; Palli, Domenico; Wareham, Nicholas J.; Loos, Ruth J. F.; Sørensen, Thorkild I. A.; Boeing, Heiner

2011-01-01

Objective To investigate trends in obesity prevalence in recent years and to predict the obesity prevalence in 2015 in European populations. Methods Data of 97 942 participants from seven cohorts involved in the European Prospective Investigation into Cancer and Nutrition (EPIC) study participating in the Diogenes project (named as “Diogenes cohort” in the following) with weight measurements at baseline and follow-up were used to predict future obesity prevalence with logistic linear and non-linear (leveling off) regression models. In addition, linear and leveling off models were fitted to the EPIC-Potsdam dataset with five weight measures during the observation period to find out which of these two models might provide the more realistic prediction. Results During a mean follow-up period of 6 years, the obesity prevalence in the Diogenes cohort increased from 13% to 17%. The linear prediction model predicted an overall obesity prevalence of about 30% in 2015, whereas the leveling off model predicted a prevalence of about 20%. In the EPIC-Potsdam cohort, the shape of obesity trend favors a leveling off model among men (R2 = 0.98), and a linear model among women (R2 = 0.99). Conclusion Our data show an increase in obesity prevalence since the 1990ies, and predictions by 2015 suggests a sizeable further increase in European populations. However, the estimates from the leveling off model were considerably lower. PMID:22102897

Climate change impact on soil erosion in the Mandakini River Basin, North India

NASA Astrophysics Data System (ADS)

Khare, Deepak; Mondal, Arun; Kundu, Sananda; Mishra, Prabhash Kumar

2017-09-01

Correct estimation of soil loss at catchment level helps the land and water resources planners to identify priority areas for soil conservation measures. Soil erosion is one of the major hazards affected by the climate change, particularly the increasing intensity of rainfall resulted in increasing erosion, apart from other factors like landuse change. Changes in climate have an adverse effect with increasing rainfall. It has caused increasing concern for modeling the future rainfall and projecting future soil erosion. In the present study, future rainfall has been generated with the downscaling of GCM (Global Circulation Model) data of Mandakini river basin, a hilly catchment in the state of Uttarakhand, India, to obtain future impact on soil erosion within the basin. The USLE is an erosion prediction model designed to predict the long-term average annual soil loss from specific field slopes in specified landuse and management systems (i.e., crops, rangeland, and recreational areas) using remote sensing and GIS technologies. Future soil erosion has shown increasing trend due to increasing rainfall which has been generated from the statistical-based downscaling method.

Individual and community risk factors and sexually transmitted diseases among arrested youths: a two level analysis.

PubMed

Dembo, Richard; Belenko, Steven; Childs, Kristina; Wareham, Jennifer; Schmeidler, James

2009-08-01

High rates of infection for chlamydia and gonorrhea have been noted among youths involved in the juvenile justice system. Although both individual and community-level factors have been found to be associated with sexually transmitted disease (STD) risk, their relative importance has not been tested in this population. A two-level logistic regression analysis was completed to assess the influence of individual-level and community-level predictors on STD test results among arrested youths processed at a centralized intake facility. Results from weighted two level logistic regression analyses (n = 1,368) indicated individual-level factors of gender (being female), age, race (being African American), and criminal history predicted the youths' positive STD status. For the community-level predictors, concentrated disadvantage significantly and positively predicted the youths' STD status. Implications of these findings for future research and public health policy are discussed.

Water Level Prediction of Lake Cascade Mahakam Using Adaptive Neural Network Backpropagation (ANNBP)

NASA Astrophysics Data System (ADS)

Mislan; Gaffar, A. F. O.; Haviluddin; Puspitasari, N.

2018-04-01

A natural hazard information and flood events are indispensable as a form of prevention and improvement. One of the causes is flooding in the areas around the lake. Therefore, forecasting the surface of Lake water level to anticipate flooding is required. The purpose of this paper is implemented computational intelligence method namely Adaptive Neural Network Backpropagation (ANNBP) to forecasting the Lake Cascade Mahakam. Based on experiment, performance of ANNBP indicated that Lake water level prediction have been accurate by using mean square error (MSE) and mean absolute percentage error (MAPE). In other words, computational intelligence method can produce good accuracy. A hybrid and optimization of computational intelligence are focus in the future work.

Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis.

PubMed

Agarwal, Vibhu; Zhang, Liangliang; Zhu, Josh; Fang, Shiyuan; Cheng, Tim; Hong, Chloe; Shah, Nigam H

2016-09-21

By recent estimates, the steady rise in health care costs has deprived more than 45 million Americans of health care services and has encouraged health care providers to better understand the key drivers of health care utilization from a population health management perspective. Prior studies suggest the feasibility of mining population-level patterns of health care resource utilization from observational analysis of Internet search logs; however, the utility of the endeavor to the various stakeholders in a health ecosystem remains unclear. The aim was to carry out a closed-loop evaluation of the utility of health care use predictions using the conversion rates of advertisements that were displayed to the predicted future utilizers as a surrogate. The statistical models to predict the probability of user's future visit to a medical facility were built using effective predictors of health care resource utilization, extracted from a deidentified dataset of geotagged mobile Internet search logs representing searches made by users of the Baidu search engine between March 2015 and May 2015. We inferred presence within the geofence of a medical facility from location and duration information from users' search logs and putatively assigned medical facility visit labels to qualifying search logs. We constructed a matrix of general, semantic, and location-based features from search logs of users that had 42 or more search days preceding a medical facility visit as well as from search logs of users that had no medical visits and trained statistical learners for predicting future medical visits. We then carried out a closed-loop evaluation of the utility of health care use predictions using the show conversion rates of advertisements displayed to the predicted future utilizers. In the context of behaviorally targeted advertising, wherein health care providers are interested in minimizing their cost per conversion, the association between show conversion rate and predicted utilization score, served as a surrogate measure of the model's utility. We obtained the highest area under the curve (0.796) in medical visit prediction with our random forests model and daywise features. Ablating feature categories one at a time showed that the model performance worsened the most when location features were dropped. An online evaluation in which advertisements were served to users who had a high predicted probability of a future medical visit showed a 3.96% increase in the show conversion rate. Results from our experiments done in a research setting suggest that it is possible to accurately predict future patient visits from geotagged mobile search logs. Results from the offline and online experiments on the utility of health utilization predictions suggest that such prediction can have utility for health care providers.

Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis

PubMed Central

Zhang, Liangliang; Zhu, Josh; Fang, Shiyuan; Cheng, Tim; Hong, Chloe; Shah, Nigam H

2016-01-01

Background By recent estimates, the steady rise in health care costs has deprived more than 45 million Americans of health care services and has encouraged health care providers to better understand the key drivers of health care utilization from a population health management perspective. Prior studies suggest the feasibility of mining population-level patterns of health care resource utilization from observational analysis of Internet search logs; however, the utility of the endeavor to the various stakeholders in a health ecosystem remains unclear. Objective The aim was to carry out a closed-loop evaluation of the utility of health care use predictions using the conversion rates of advertisements that were displayed to the predicted future utilizers as a surrogate. The statistical models to predict the probability of user’s future visit to a medical facility were built using effective predictors of health care resource utilization, extracted from a deidentified dataset of geotagged mobile Internet search logs representing searches made by users of the Baidu search engine between March 2015 and May 2015. Methods We inferred presence within the geofence of a medical facility from location and duration information from users’ search logs and putatively assigned medical facility visit labels to qualifying search logs. We constructed a matrix of general, semantic, and location-based features from search logs of users that had 42 or more search days preceding a medical facility visit as well as from search logs of users that had no medical visits and trained statistical learners for predicting future medical visits. We then carried out a closed-loop evaluation of the utility of health care use predictions using the show conversion rates of advertisements displayed to the predicted future utilizers. In the context of behaviorally targeted advertising, wherein health care providers are interested in minimizing their cost per conversion, the association between show conversion rate and predicted utilization score, served as a surrogate measure of the model’s utility. Results We obtained the highest area under the curve (0.796) in medical visit prediction with our random forests model and daywise features. Ablating feature categories one at a time showed that the model performance worsened the most when location features were dropped. An online evaluation in which advertisements were served to users who had a high predicted probability of a future medical visit showed a 3.96% increase in the show conversion rate. Conclusions Results from our experiments done in a research setting suggest that it is possible to accurately predict future patient visits from geotagged mobile search logs. Results from the offline and online experiments on the utility of health utilization predictions suggest that such prediction can have utility for health care providers. PMID:27655225

The role of science self-efficacy, science career efficacy, science career interest, and intentions to enroll in nonrequired science courses in the future selection of science-related careers for high school students

NASA Astrophysics Data System (ADS)

Ballard, Sherri Patrice

1998-12-01

Underrepresentation of non-Asian minority groups and women in science and math related professions has been an area of concern for many years. The purpose of this study was to examine the role of career selection variables for African-American and European-American students on future aspirations of pursuing a science-related career. Other examined variables included gender, academic track and socioeconomic status. A survey was completed by 368 high school students in rural settings in the Southeastern portion of the United States. Gender, race, tracking, and socioeconomic differences in career selection variables and future aspirations of pursuing a science-related career were explored using a 2 x 2 x 2 x 2 MANOVA. Multiple regression was used to examine the predictiveness of career selection variables relative to future career aspirations of pursuing a science-related career. Results indicated that African-Americans reported higher total science career interest, and higher science career efficacy. European-American students reported higher levels of science self-efficacy relative to making a B or better in science courses and solving science-related problems. Also, European-Americans reported higher levels of interest in science-related tasks, a subscale on the science career interest variable. When the effect of gender was examined across the total sample, no differences were found. However, when gender was examined by race, European-American females reported higher levels of science career interest than European-American males. Students from high academic tracking groups reported greater efficacy for completing science-related technical skills. Science career interest was predictive of future career selection for this sample.

Anticipating Their Future: Adolescent Values for the Future Predict Adult Behaviors

PubMed Central

Finlay, Andrea; Wray-Lake, Laura; Warren, Michael; Maggs, Jennifer L.

2014-01-01

Adolescent future values – beliefs about what will matter to them in the future – may shape their adult behavior. Utilizing a national longitudinal British sample, this study examined whether adolescent future values in six domains (i.e., family responsibility, full-time job, personal responsibility, autonomy, civic responsibility, and hedonistic privilege) predicted adult social roles, civic behaviors, and alcohol use. Future values positively predicted behaviors within the same domain; fewer cross-domain associations were evident. Civic responsibility positively predicted adult civic behaviors, but negatively predicted having children. Hedonistic privilege positively predicted adult alcohol use and negatively predicted civic behaviors. Results suggest that attention should be paid to how adolescents are thinking about their futures due to the associated links with long-term social and health behaviors. PMID:26279595

Modelling the influence of predicted future climate change on the risk of wind damage within New Zealand's planted forests.

PubMed

Moore, John R; Watt, Michael S

2015-08-01

Wind is the major abiotic disturbance in New Zealand's planted forests, but little is known about how the risk of wind damage may be affected by future climate change. We linked a mechanistic wind damage model (ForestGALES) to an empirical growth model for radiata pine (Pinus radiata D. Don) and a process-based growth model (cenw) to predict the risk of wind damage under different future emissions scenarios and assumptions about the future wind climate. The cenw model was used to estimate site productivity for constant CO2 concentration at 1990 values and for assumed increases in CO2 concentration from current values to those expected during 2040 and 2090 under the B1 (low), A1B (mid-range) and A2 (high) emission scenarios. Stand development was modelled for different levels of site productivity, contrasting silvicultural regimes and sites across New Zealand. The risk of wind damage was predicted for each regime and emission scenario combination using the ForestGALES model. The sensitivity to changes in the intensity of the future wind climate was also examined. Results showed that increased tree growth rates under the different emissions scenarios had the greatest impact on the risk of wind damage. The increase in risk was greatest for stands growing at high stand density under the A2 emissions scenario with increased CO2 concentration. The increased productivity under this scenario resulted in increased tree height, without a corresponding increase in diameter, leading to more slender trees that were predicted to be at greater risk from wind damage. The risk of wind damage was further increased by the modest increases in the extreme wind climate that are predicted to occur. These results have implications for the development of silvicultural regimes that are resilient to climate change and also indicate that future productivity gains may be offset by greater losses from disturbances. © 2015 John Wiley & Sons Ltd.

Predicting Noninsulin Antidiabetic Drug Adherence Using a Theoretical Framework Based on the Theory of Planned Behavior in Adults With Type 2 Diabetes

PubMed Central

Zomahoun, Hervé Tchala Vignon; Moisan, Jocelyne; Lauzier, Sophie; Guillaumie, Laurence; Grégoire, Jean-Pierre; Guénette, Line

2016-01-01

Abstract Understanding the process behind noninsulin antidiabetic drug (NIAD) nonadherence is necessary for designing effective interventions to resolve this problem. This study aimed to explore the ability of the theory of planned behavior (TPB), which is known as a good predictor of behaviors, to predict the future NIAD adherence in adults with type 2 diabetes. We conducted a prospective study of adults with type 2 diabetes. They completed a questionnaire on TPB variables and external variables. Linear regression was used to explore the TPB's ability to predict future NIAD adherence, which was prospectively measured as the proportion of days covered by at least 1 NIAD using pharmacy claims data. The interaction between past NIAD adherence and intention was tested. The sample included 340 people. There was an interaction between past NIAD adherence and intention to adhere to the NIAD (P = 0.032). Intention did not predict future NIAD adherence in the past adherers and nonadherers groups, but its association measure was high among past nonadherers (β = 5.686, 95% confidence interval [CI] −10.174, 21.546). In contrast, intention was mainly predicted by perceived behavioral control both in the past adherers (β = 0.900, 95% CI 0.796, 1.004) and nonadherers groups (β = 0.760, 95% CI 0.555, 0.966). The present study suggests that TPB is a good tool to predict intention to adhere and future NIAD adherence. However, there was a gap between intention to adhere and actual adherence to the NIAD, which is partly explained by the past adherence level in adults with type 2 diabetes. PMID:27082543

Domains of Social Support That Predict Bereavement Distress Following Homicide Loss.

PubMed

Bottomley, Jamison S; Burke, Laurie A; Neimeyer, Robert A

2017-05-01

Psychological adaptation following homicide loss can prove more challenging for grievers than other types of losses. Although social support can be beneficial in bereavement, research is mixed in terms of identifying whether it serves as a buffer to distress following traumatic loss. In particular, studies have not parsed out specific domains of social support that best predict positive bereavement outcomes. Recruiting a sample of 47 African Americans bereaved by homicide, we examined six types of social support along with the griever's perceived need for or satisfaction with each and analyzed them in relation to depression, anxiety, complicated grief, and posttraumatic stress disorder outcomes. Results of multivariate analyses revealed that the griever's level of satisfaction with physical assistance at the initial assessment best predicted lower levels of depression, anxiety, and posttraumatic stress disorder levels 6 months later, while less need for physical assistance predicted lower complicated grief at follow-up. Clinical implications and suggestions for future research are discussed.

Relationships between racial-ethnic identity, self-esteem and in-group attitudes among First Nation children.

PubMed

Corenblum, Barry

2014-03-01

Positive in-group distinctiveness has been associated with self-esteem increases among adolescents and adults. To examine whether in-group biases are associated with self-esteem enhancement among minority group children, Native Canadian children (N = 414, 209 female) age 6-11 completed each year for 5 years, measures assessing their level of concrete operational thought, racial-ethnic identity, racial-ethnic centrality, implicit and explicit self-esteem, and implicit and explicit in-group attitudes. According to cognitive developmental theory, increases in the level of concrete operational thought will predict increases in racial-ethnic identity, and increases in identity should, in turn, predict more favorable in-group attitudes. Social identity theory predicts that more favorable in-group attitudes should predict increases in self-esteem. Multi-level structural equation modelling revealed support for these hypotheses. Cognitively mature children who identify closely with their group enhanced their level of self-esteem by positively differentiating between group members on dimensions that favor their group. Limitations of the present study and suggestions for future studies are also presented.

Effect of Pumping on Groundwater Levels: A Case Study

NASA Astrophysics Data System (ADS)

Sindhu, G.; Vijayachandran, Lekshmi

2018-03-01

Groundwater is a major source for drinking and domestic purposes. Nowadays, extensive pumping has become a major issue of concern since pumping has led to rapid decline in the groundwater table, thus imposing landward gradient, leading to saline water intrusion especially in coastal areas. Groundwater pumping has seen its utmost effect on coastal aquifer systems, where the sea-ward gradient gets disturbed due to anthropogenic influences. Hence, a groundwater flow modelling of an aquifer system is essential for understanding the various hydro-geologic conditions, which can be used to study the responses of the aquifer system with regard to various pumping scenarios. Besides, a model helps to predict the water levels for the future period with respect to changing environment. In this study, a finite element groundwater flow model of a coastal aquifer system at Aakulam, Trivandrum district is developed, calibrated and simulated using the software Finite Element subsurface Flow system (FEFLOW 6.2).This simulated model is then used to predict the groundwater levels for a future 5 year period during pre monsoon and post monsoon season.

Effect of Pumping on Groundwater Levels: A Case Study

NASA Astrophysics Data System (ADS)

Sindhu, G.; Vijayachandran, Lekshmi

2018-06-01

Groundwater is a major source for drinking and domestic purposes. Nowadays, extensive pumping has become a major issue of concern since pumping has led to rapid decline in the groundwater table, thus imposing landward gradient, leading to saline water intrusion especially in coastal areas. Groundwater pumping has seen its utmost effect on coastal aquifer systems, where the sea-ward gradient gets disturbed due to anthropogenic influences. Hence, a groundwater flow modelling of an aquifer system is essential for understanding the various hydro-geologic conditions, which can be used to study the responses of the aquifer system with regard to various pumping scenarios. Besides, a model helps to predict the water levels for the future period with respect to changing environment. In this study, a finite element groundwater flow model of a coastal aquifer system at Aakulam, Trivandrum district is developed, calibrated and simulated using the software Finite Element subsurface Flow system (FEFLOW 6.2).This simulated model is then used to predict the groundwater levels for a future 5 year period during pre monsoon and post monsoon season.

TANDI: threat assessment of network data and information

NASA Astrophysics Data System (ADS)

Holsopple, Jared; Yang, Shanchieh Jay; Sudit, Moises

2006-04-01

Current practice for combating cyber attacks typically use Intrusion Detection Sensors (IDSs) to passively detect and block multi-stage attacks. This work leverages Level-2 fusion that correlates IDS alerts belonging to the same attacker, and proposes a threat assessment algorithm to predict potential future attacker actions. The algorithm, TANDI, reduces the problem complexity by separating the models of the attacker's capability and opportunity, and fuse the two to determine the attacker's intent. Unlike traditional Bayesian-based approaches, which require assigning a large number of edge probabilities, the proposed Level-3 fusion procedure uses only 4 parameters. TANDI has been implemented and tested with randomly created attack sequences. The results demonstrate that TANDI predicts future attack actions accurately as long as the attack is not part of a coordinated attack and contains no insider threats. In the presence of abnormal attack events, TANDI will alarm the network analyst for further analysis. The attempt to evaluate a threat assessment algorithm via simulation is the first in the literature, and shall open up a new avenue in the area of high level fusion.

ATLAS trigger operations: Upgrades to ``Xmon'' rate prediction system

NASA Astrophysics Data System (ADS)

Myers, Ava; Aukerman, Andrew; Hong, Tae Min; Atlas Collaboration

2017-01-01

We present ``Xmon,'' a tool to monitor trigger rates in the Control Room of the ATLAS Experiment. We discuss Xmon's recent (1) updates, (2) upgrades, and (3) operations. (1) Xmon was updated to modify the tool written for the three-level trigger architecture in Run-1 (2009-2012) to adapt to the new two-level system for Run-2 (2015-current). The tool takes as input the beam luminosity to make a rate prediction, which is compared with incoming rates to detect anomalies that occur both globally throughout a run and locally within a run. Global offsets are more commonly caught by the predictions based upon past runs, where offline processing allows for function adjustments and fit quality through outlier rejection. (2) Xmon was upgraded to detect local offsets using on-the-fly predictions, which uses a sliding window of in-run rates to make predictions. (3) Xmon operations examples are given. Future work involves further automation of the steps to provide the predictive functions and for alerting shifters.

Longevity of the Human Spaceflight Program

NASA Astrophysics Data System (ADS)

Gott, J. Richard

2007-02-01

The longevity of the human spaceflight program is important to our survival prospects. On May 27, 1993 I proposed a method for estimating future longevity, based on past observed longevity using the Copernican Principle: if your observation point is not special the 95% confidence level prediction of future longevity is between (1/39)th and 39 times the past longevity. The prediction for the future longevity of the human spaceflight program (then 32 years old) was greater than 10 months but less than 1248 years. We have already passed the lower limit. This Copernican formula has been tested a number of times, correctly predicting, among other things, future longevities of Broadway plays and musicals, and the Conservative Government in the United Kingdom. Recently, a study of future longevities of the 313 world leaders in power on May 27, 1993 has been completed. Assuming none still in office serve past age 100, the success rate of the 95% Copernican Formula is currently 94.55% with only one case (out of 313) left to be decided. The human spaceflight program has not been around long and so there is the danger its future will not be long enough to allow us to colonize off the earth. Policy implications are discussed. A smart plan would be to try to establish a self-supporting colony on Mars in the next 45 years. This should not require sending any more tons of material into space in the next 45 years than we have in the last 45 years.

Neogeomorphology, prediction, and the anthropic landscape

NASA Astrophysics Data System (ADS)

Haff, P. K.

The surface of the earth is undergoing profound change due to human impact. By some measures the level of human impact is comparable to the effects of major classical geomorphic processes such as fluvial sediment transport. This change is occurring rapidly, has no geologic precedent, and may represent an irreversible transition to a new and novel landscape with which we have no experience. For these reasons prediction of future landscape evolution will be of increasing importance. The combination of physical and social forces that drive modern landscape change represents the Anthropic Force. Neogeomorphology is the study of the Anthropic Force and its present and likely future effects on the landscape. Unique properties associated with the Anthropic Force include consciousness, intention and design. These properties support the occurrence of nonclassical geomorphic phenomena, such as landscape planning, engineering, and management. The occurrence of short time-scale phenomena induced by anthropic landscape change, the direct effects of this change on society, and the ability to anticipate and intentionally influence the future trajectory of the global landscape underscore the importance of prediction in a neogeomorphic world.

A general approach for predicting the behavior of the Supreme Court of the United States

PubMed Central

Bommarito, Michael J.; Blackman, Josh

2017-01-01

Building on developments in machine learning and prior work in the science of judicial prediction, we construct a model designed to predict the behavior of the Supreme Court of the United States in a generalized, out-of-sample context. To do so, we develop a time-evolving random forest classifier that leverages unique feature engineering to predict more than 240,000 justice votes and 28,000 cases outcomes over nearly two centuries (1816-2015). Using only data available prior to decision, our model outperforms null (baseline) models at both the justice and case level under both parametric and non-parametric tests. Over nearly two centuries, we achieve 70.2% accuracy at the case outcome level and 71.9% at the justice vote level. More recently, over the past century, we outperform an in-sample optimized null model by nearly 5%. Our performance is consistent with, and improves on the general level of prediction demonstrated by prior work; however, our model is distinctive because it can be applied out-of-sample to the entire past and future of the Court, not a single term. Our results represent an important advance for the science of quantitative legal prediction and portend a range of other potential applications. PMID:28403140

The Linear Predictability of Sea Level: A Benchmark

NASA Astrophysics Data System (ADS)

Sonnewald, M.; Wunsch, C.; Heimbach, P.

2016-12-01

A benchmark of linear predictive skill of global sea level is presented, complimenting more complicated model studies of future predictive skill. Sea level is of great socioeconomic interest, as most of the worlds population live by the sea. Currently, the spread in model projections suggests poor predictive skill outside the seasonal cycle. We use 20 years of data from the ECCOv4 state estimate (1992-2012), assessing the variance attributable to the seasons and the linear predictability potential of the deseasoned component of sea level. The Northern Hemisphere has large regions where the seasons make up >90% of the variance, particularly in the western boundary current regions and zonal bands along the equator. The deaseasoned sea level is more dominant in the Southern Hemisphere, particularly in the Southern Ocean. We treat the deseasoned sea level as a weakly stationary random process, whose predictability is given by the covariance structure. Fitting an ARMA(n,m) model, we choose the order using the Akaike and Bayesian Information Criteria (AIC and BIC). The AIC is more appropriate, with generally higher orders chosen and offering slightly more predictive accuracy. Monthly detrended data shows skill generally of the order of a few months, with isolated regions of twelve months or more. With the trend, the predictive skill increases, particularly in the South Pacific. We assess the annually averaged data, although our time-series is too short to assess the variability. There is some predictive skill, which is enhanced if the trend is not removed. A major caveat of our approach is that we test and train our model on the same dataset due to the short duration of available data.

Landscape genomic prediction for restoration of a Eucalyptus foundation species under climate change.

PubMed

Supple, Megan Ann; Bragg, Jason G; Broadhurst, Linda M; Nicotra, Adrienne B; Byrne, Margaret; Andrew, Rose L; Widdup, Abigail; Aitken, Nicola C; Borevitz, Justin O

2018-04-24

As species face rapid environmental change, we can build resilient populations through restoration projects that incorporate predicted future climates into seed sourcing decisions. Eucalyptus melliodora is a foundation species of a critically endangered community in Australia that is a target for restoration. We examined genomic and phenotypic variation to make empirical based recommendations for seed sourcing. We examined isolation by distance and isolation by environment, determining high levels of gene flow extending for 500 km and correlations with climate and soil variables. Growth experiments revealed extensive phenotypic variation both within and among sampling sites, but no site-specific differentiation in phenotypic plasticity. Model predictions suggest that seed can be sourced broadly across the landscape, providing ample diversity for adaptation to environmental change. Application of our landscape genomic model to E. melliodora restoration projects can identify genomic variation suitable for predicted future climates, thereby increasing the long term probability of successful restoration. © 2018, Supple et al.

Long-Range Solar Activity Predictions: A Reprieve from Cycle #24's Activity

NASA Technical Reports Server (NTRS)

Richon, K.; Schatten, K.

2003-01-01

We discuss the field of long-range solar activity predictions and provide an outlook into future solar activity. Orbital predictions for satellites in Low Earth Orbit (LEO) depend strongly on exospheric densities. Solar activity forecasting is important in this regard, as the solar ultra-violet (UV) and extreme ultraviolet (EUV) radiations inflate the upper atmospheric layers of the Earth, forming the exosphere in which satellites orbit. Rather than concentrate on statistical, or numerical methods, we utilize a class of techniques (precursor methods) which is founded in physical theory. The geomagnetic precursor method was originally developed by the Russian geophysicist, Ohl, using geomagnetic observations to predict future solar activity. It was later extended to solar observations, and placed within the context of physical theory, namely the workings of the Sun s Babcock dynamo. We later expanded the prediction methods with a SOlar Dynamo Amplitude (SODA) index. The SODA index is a measure of the buried solar magnetic flux, using toroidal and poloidal field components. It allows one to predict future solar activity during any phase of the solar cycle, whereas previously, one was restricted to making predictions only at solar minimum. We are encouraged that solar cycle #23's behavior fell closely along our predicted curve, peaking near 192, comparable to the Schatten, Myers and Sofia (1996) forecast of 182+/-30. Cycle #23 extends from 1996 through approximately 2006 or 2007, with cycle #24 starting thereafter. We discuss the current forecast of solar cycle #24, (2006-2016), with a predicted smoothed F10.7 radio flux of 142+/-28 (1-sigma errors). This, we believe, represents a reprieve, in terms of reduced fuel costs, etc., for new satellites to be launched or old satellites (requiring reboosting) which have been placed in LEO. By monitoring the Sun s most deeply rooted magnetic fields; long-range solar activity can be predicted. Although a degree of uncertainty in the long-range predictions remains, requiring future monitoring, we do not expect the next cycle's + 2-sigma value will rise significantly above solar cycle #23's activity level.

Predictive data modeling of human type II diabetes related statistics

NASA Astrophysics Data System (ADS)

Jaenisch, Kristina L.; Jaenisch, Holger M.; Handley, James W.; Albritton, Nathaniel G.

2009-04-01

During the course of routine Type II treatment of one of the authors, it was decided to derive predictive analytical Data Models of the daily sampled vital statistics: namely weight, blood pressure, and blood sugar, to determine if the covariance among the observed variables could yield a descriptive equation based model, or better still, a predictive analytical model that could forecast the expected future trend of the variables and possibly eliminate the number of finger stickings required to montior blood sugar levels. The personal history and analysis with resulting models are presented.

Theory of Mind: A Neural Prediction Problem

PubMed Central

Koster-Hale, Jorie; Saxe, Rebecca

2014-01-01

Predictive coding posits that neural systems make forward-looking predictions about incoming information. Neural signals contain information not about the currently perceived stimulus, but about the difference between the observed and the predicted stimulus. We propose to extend the predictive coding framework from high-level sensory processing to the more abstract domain of theory of mind; that is, to inferences about others’ goals, thoughts, and personalities. We review evidence that, across brain regions, neural responses to depictions of human behavior, from biological motion to trait descriptions, exhibit a key signature of predictive coding: reduced activity to predictable stimuli. We discuss how future experiments could distinguish predictive coding from alternative explanations of this response profile. This framework may provide an important new window on the neural computations underlying theory of mind. PMID:24012000

Predicting Future Commitment to Care for Frail Parents Among Employed Caregivers.

PubMed

Lechner, Viola M

1992-06-01

A study of 133 full time employees with parent care responsibilities investigated various factors that could reduce this group's future caregiving commitment to aging parents. Study factors included: caregiver attributes, level of caregiving involvement, job stress, tensions between the caregiver and the dependent parent, caregiver's level of physical and mental strain, and limited support from family and friends. The relationship between the caregiver and the parent was the best predictor of sustained commitment to caregiving. One aspect of the employees' work experience made a small, but important contribution to respondents' future care plans. Those employees who frequently adjusted their work schedule and routine to accommodate parent care demands were less likely to sustain their caregiving commitment. Reasons for these findings are explored and implications for social policy and clinical practice are discussed.

Image Feature Types and Their Predictions of Aesthetic Preference and Naturalness

PubMed Central

Ibarra, Frank F.; Kardan, Omid; Hunter, MaryCarol R.; Kotabe, Hiroki P.; Meyer, Francisco A. C.; Berman, Marc G.

2017-01-01

Previous research has investigated ways to quantify visual information of a scene in terms of a visual processing hierarchy, i.e., making sense of visual environment by segmentation and integration of elementary sensory input. Guided by this research, studies have developed categories for low-level visual features (e.g., edges, colors), high-level visual features (scene-level entities that convey semantic information such as objects), and how models of those features predict aesthetic preference and naturalness. For example, in Kardan et al. (2015a), 52 participants provided aesthetic preference and naturalness ratings, which are used in the current study, for 307 images of mixed natural and urban content. Kardan et al. (2015a) then developed a model using low-level features to predict aesthetic preference and naturalness and could do so with high accuracy. What has yet to be explored is the ability of higher-level visual features (e.g., horizon line position relative to viewer, geometry of building distribution relative to visual access) to predict aesthetic preference and naturalness of scenes, and whether higher-level features mediate some of the association between the low-level features and aesthetic preference or naturalness. In this study we investigated these relationships and found that low- and high- level features explain 68.4% of the variance in aesthetic preference ratings and 88.7% of the variance in naturalness ratings. Additionally, several high-level features mediated the relationship between the low-level visual features and aaesthetic preference. In a multiple mediation analysis, the high-level feature mediators accounted for over 50% of the variance in predicting aesthetic preference. These results show that high-level visual features play a prominent role predicting aesthetic preference, but do not completely eliminate the predictive power of the low-level visual features. These strong predictors provide powerful insights for future research relating to landscape and urban design with the aim of maximizing subjective well-being, which could lead to improved health outcomes on a larger scale. PMID:28503158

Contextual influences on participation in community organizing: a multilevel longitudinal study.

PubMed

Christens, Brian D; Speer, Paul W

2011-06-01

This article reports results from a study of contextual influences on participation among people involved in congregation-based community organizing. Data are drawn from 11,538 individual participants in 115 congregations taking part in one of five local organizing initiatives in different cities over a five-year period. Analyses used 3-level longitudinal models with binary indicators of participation/non-participation in group meetings each successive year as the criterion. Time-varying predictors at level-1 included prior participation in group meetings as a control, the types of group meetings that participants attended, the number of face-to-face meetings held between each participant and organizing staff of the local organizing initiatives, and a measure of the involvement of participants' affiliation networks. At level-2, demographic information was collected for a subset of participants (N = 461) and was included in a separate model. Neighborhood compositional characteristics were examined at level-3, including median income, economic heterogeneity, and residential stability. Study results found that characteristics of organizational settings (i.e., types of group meetings attended and frequency of face-to-face contact) predicted future participation in group meetings but that individual and neighborhood-level demographic characteristics were generally not predictive of future participation in community organizing activities.

The Geology of the Florida Keys.

ERIC Educational Resources Information Center

Shinn, Eugene A.

1988-01-01

Describes some of the ancient geologic history of the Florida Keys from Key Largo to Key West including the effects of glaciers, sea level rise, reef distribution, spurs and grooves, backstepping and ecological zonation, growth rates and erosion. Predicts future changes in this area. (CW)

IMPROVE AND APPLY CHEMICAL MECHANISMS FOR DEVELOPING OZONE CONTROL STRATEGIES

EPA Science Inventory

Air quality models that realistically describe the formation of ozone, air toxics, and other pollutants are needed by EPA and state agencies to predict current and future concentrations of these pollutants and develop ways to decrease their concentrations below harmful levels. ...

A multi-level strategy for anticipating future glacier lake formation and associated hazard potentials

NASA Astrophysics Data System (ADS)

Frey, H.; Haeberli, W.; Linsbauer, A.; Huggel, C.; Paul, F.

2010-02-01

In the course of glacier retreat, new glacier lakes can develop. As such lakes can be a source of natural hazards, strategies for predicting future glacier lake formation are important for an early planning of safety measures. In this article, a multi-level strategy for the identification of overdeepened parts of the glacier beds and, hence, sites with potential future lake formation, is presented. At the first two of the four levels of this strategy, glacier bed overdeepenings are estimated qualitatively and over large regions based on a digital elevation model (DEM) and digital glacier outlines. On level 3, more detailed and laborious models are applied for modeling the glacier bed topography over smaller regions; and on level 4, special situations must be investigated in-situ with detailed measurements such as geophysical soundings. The approaches of the strategy are validated using historical data from Trift Glacier, where a lake formed over the past decade. Scenarios of future glacier lakes are shown for the two test regions Aletsch and Bernina in the Swiss Alps. In the Bernina region, potential future lake outbursts are modeled, using a GIS-based hydrological flow routing model. As shown by a corresponding test, the ASTER GDEM and the SRTM DEM are both suitable to be used within the proposed strategy. Application of this strategy in other mountain regions of the world is therefore possible as well.

No food for thought: moderating effects of delay discounting and future time perspective on the relation between income and food insecurity1234

PubMed Central

Epstein, Leonard H; Jankowiak, Noelle; Lin, Henry; Paluch, Rocco; Koffarnus, Mikhail N; Bickel, Warren K

2014-01-01

Background: Low income is related to food insecurity, and research has suggested that a scarcity of resources associated with low income can shift attention to the present, thereby discounting the future. Objective: We tested whether attending to the present and discounting the future may moderate the influence of income on food insecurity. Design: Delay discounting and measures of future time perspective (Zimbardo Time Perspective Inventory, Consideration of Future Consequences Scale, time period of financial planning, and subjective probability of living to age 75 y) were studied as moderators of the relation between income and food insecurity in a diverse sample of 975 adults, 31.8% of whom experienced some degree of food insecurity. Results: Income, financial planning, subjective probability of living to age 75 y, and delay discounting predicted food insecurity as well as individuals who were high in food insecurity. Three-way interactions showed that delay discounting interacted with financial planning and income to predict food insecurity (P = 0.003). At lower levels of income, food insecurity was lowest for subjects who had good financial planning skills and did not discount the future, whereas having good financial skills and discounting the future had minimal influence on food insecurity. The same 3-way interaction was observed when high food insecurity was predicted (P = 0.008). Conclusion: Because of the role of scarce resources on narrowing attention and reducing prospective thinking, research should address whether modifying future orientation may reduce food insecurity even in the face of diminishing financial resources. This trial was registered at clinicaltrials.gov as NCT02099812. PMID:25008855

Latitudinal variation in carbon storage can help predict changes in swamps affected by global warming

USGS Publications Warehouse

Middleton, Beth A.; McKee, Karen

2004-01-01

Plants may offer our best hope of removing greenhouse gases (gases that contribute to global warming) emitted to the atmosphere from the burning of fossil fuels. At the same time, global warming could change environments so that natural plant communities will either need to shift into cooler climate zones, or become extirpated (Prasad and Iverson, 1999; Crumpacker and others, 2001; Davis and Shaw, 2001). It is impossible to know the future, but studies combining field observation of production and modeling can help us make predictions about what may happen to these wetland communities in the future. Widespread wetland types such as baldcypress (Taxodium distichum) swamps in the southeastern portion of the United States could be especially good at carbon sequestration (amount of CO2 stored by forests) from the atmosphere. They have high levels of production and sometimes store undecomposed dead plant material in wet conditions with low oxygen, thus keeping gases stored that would otherwise be released into the atmosphere (fig. 1). To study the ability of baldcypress swamps to store carbon, our project has taken two approaches. The first analysis looked at published data to develop an idea (hypothesis) of how production levels change across a temperature gradient in the baldcypress region (published data study). The second study tested this idea by comparing production levels across a latitudinal range by using swamps in similar field conditions (ongoing carbon storage study). These studies will help us make predictions about the future ability of baldcypress swamps to store carbon in soil and plant biomass, as well as the ability of these forests to shift northward with global warming.

A crucial step toward realism: responses to climate change from an evolving metacommunity perspective.

PubMed

Urban, Mark C; De Meester, Luc; Vellend, Mark; Stoks, Robby; Vanoverbeke, Joost

2012-02-01

We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The 'evolving metacommunity' framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats.

A crucial step toward realism: responses to climate change from an evolving metacommunity perspective

PubMed Central

Urban, Mark C; De Meester, Luc; Vellend, Mark; Stoks, Robby; Vanoverbeke, Joost

2012-01-01

We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The ‘evolving metacommunity’ framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats. PMID:25568038

Anticipated debt and financial stress in medical students.

PubMed

Morra, Dante J; Regehr, Glenn; Ginsburg, Shiphra

2008-01-01

While medical student debt is increasing, the effect of debt on student well-being and performance remains unclear. As a part of a larger study examining medical student views of their future profession, data were collected to examine the role that current and anticipated debt has in predicting stress among medical students. A survey was administered to medical students in all four years at the University of Toronto. Of the 804 potential respondents across the four years of training, 549 surveys had sufficient data for inclusion in this analysis, for a response rate of 68%. Through multiple regression analysis, we evaluated the correlation between current and anticipated debt and financial stress. Although perceived financial stress correlates with both current and anticipated debt levels, anticipated debt was able to account for an additional 11.5% of variance in reported stress when compared to current debt levels alone. This study demonstrates a relationship between perceived financial stress and debt levels, and suggests that anticipated debt levels might be a more robust metric to capture financial burden, as it standardizes for year of training and captures future financial liabilities (future tuition and other future expenses).

Land use planning and wildfire: development policies influence future probability of housing loss

USGS Publications Warehouse

Syphard, Alexandra D.; Massada, Avi Bar; Butsic, Van; Keeley, Jon E.

2013-01-01

Increasing numbers of homes are being destroyed by wildfire in the wildland-urban interface. With projections of climate change and housing growth potentially exacerbating the threat of wildfire to homes and property, effective fire-risk reduction alternatives are needed as part of a comprehensive fire management plan. Land use planning represents a shift in traditional thinking from trying to eliminate wildfires, or even increasing resilience to them, toward avoiding exposure to them through the informed placement of new residential structures. For land use planning to be effective, it needs to be based on solid understanding of where and how to locate and arrange new homes. We simulated three scenarios of future residential development and projected landscape-level wildfire risk to residential structures in a rapidly urbanizing, fire-prone region in southern California. We based all future development on an econometric subdivision model, but we varied the emphasis of subdivision decision-making based on three broad and common growth types: infill, expansion, and leapfrog. Simulation results showed that decision-making based on these growth types, when applied locally for subdivision of individual parcels, produced substantial landscape-level differences in pattern, location, and extent of development. These differences in development, in turn, affected the area and proportion of structures at risk from burning in wildfires. Scenarios with lower housing density and larger numbers of small, isolated clusters of development, i.e., resulting from leapfrog development, were generally predicted to have the highest predicted fire risk to the largest proportion of structures in the study area, and infill development was predicted to have the lowest risk. These results suggest that land use planning should be considered an important component to fire risk management and that consistently applied policies based on residential pattern may provide substantial benefits for future risk reduction.

Major challenges for correlational ecological niche model projections to future climate conditions.

PubMed

Peterson, A Townsend; Cobos, Marlon E; Jiménez-García, Daniel

2018-06-20

Species-level forecasts of distributional potential and likely distributional shifts, in the face of changing climates, have become popular in the literature in the past 20 years. Many refinements have been made to the methodology over the years, and the result has been an approach that considers multiple sources of variation in geographic predictions, and how that variation translates into both specific predictions and uncertainty in those predictions. Although numerous previous reviews and overviews of this field have pointed out a series of assumptions and caveats associated with the methodology, three aspects of the methodology have important impacts but have not been treated previously in detail. Here, we assess those three aspects: (1) effects of niche truncation on model transfers to future climate conditions, (2) effects of model selection procedures on future-climate transfers of ecological niche models, and (3) relative contributions of several factors (replicate samples of point data, general circulation models, representative concentration pathways, and alternative model parameterizations) to overall variance in model outcomes. Overall, the view is one of caution: although resulting predictions are fascinating and attractive, this paradigm has pitfalls that may bias and limit confidence in niche model outputs as regards the implications of climate change for species' geographic distributions. © 2018 New York Academy of Sciences.

Modelling benthic macrofauna and seagrass distribution patterns in a North Sea tidal basin in response to 2050 climatic and environmental scenarios

NASA Astrophysics Data System (ADS)

Singer, Anja; Millat, Gerald; Staneva, Joanna; Kröncke, Ingrid

2017-03-01

Small-scale spatial distribution patterns of seven macrofauna species, seagrass beds and mixed mussel/oyster reefs were modelled for the Jade Bay (North Sea, Germany) in response to climatic and environmental scenarios (representing 2050). For the species distribution models four presence-absence modelling methods were merged within the ensemble forecasting platform 'biomod2'. The present spatial distribution (representing 2009) was modelled by statistically related species presences, true species absences and six high-resolution environmental grids. The future spatial distribution was then predicted in response to expected climate change-induced ongoing (1) sea-level rise and (2) water temperature increase. Between 2009 and 2050, the present and future prediction maps revealed a significant range gain for two macrofauna species (Macoma balthica, Tubificoides benedii), whereas the species' range sizes of five macrofauna species remained relatively stable across space and time. The predicted probability of occurrence (PO) of two macrofauna species (Cerastoderma edule, Scoloplos armiger) decreased significantly under the potential future habitat conditions. In addition, a clear seagrass bed extension (Zostera noltii) on the lower intertidal flats (mixed sediments) and a decrease in the PO of mixed Mytilus edulis/Crassostrea gigas reefs was predicted for 2050. Until the mid-21st century, our future climatic and environmental scenario revealed significant changes in the range sizes (gains-losses) and/or the PO (increases-decreases) for seven of the 10 modelled species at the study site.

Electrical-analog analysis of ground-water depletion in central Arizona

USGS Publications Warehouse

Anderson, T.W.

1968-01-01

The Salt River Valley and the lower Santa Cruz River basin are the two largest agricultural areas in Arizona. The extensive use of ground water for irrigation has resulted in the need for a thorough appraisal of the present and future ground-water resources. The ground-water reservoir provides 80 percent (3.2 million acre-feet) of the total annual water supply. The amount of water pumped greatly exceeds the rate at which the ground-water supply is being replenished and has resulted in water-level declines of as much as 20 feet per year in some places. The depletion problem is of economic importance because ground water will become more expensive as pumping lifts increase and well yields decrease. The use of electrical-analog modeling techniques has made it possible to predict future ground-water levels under conditions of continued withdrawal in excess of the rate of replenishment. The electrical system is a representation of the hydrologic system: resistors and capacitors represent transmissibility and storage coefficients. The analogy between the two systems is accepted when the data obtained from the model closely match the field data in this instance, measured water-level change since 1923. The prediction of future water-table conditions is accomplished by a simple extension of the pumping trends to determine the resultant effect on the regional water levels. The results of this study indicate the probable depths to water in central Arizona in 1974 and 1984 if the aquifer characteristics are accurately modeled and if withdrawal of ground water continues at the same rate and under the tame areal distribution as existed between 1958 and 1964. The greatest depths to water in 1984 will be more than 700 feet near Stanfield and more than 650 feet in Deer Valley and northeast of Gilbert. South of Eloy and northwest of Litchfield Park, a static water level of more than 550 feet is predicted. The total water-level decline in the 20-year period 1964-84 at the deepest points of the major cones of depression will range from 150 to 300 feet, and the average decline in the entire central Arizona area will be about 100 feet.

A dark past, a restrained present, and an apocalyptic future: time perspective, personality, and life satisfaction among anorexia nervosa patients

PubMed Central

Granjard, Alexandre; Lundblad, Suzanna; Archer, Trevor

2017-01-01

Background Despite reporting low levels of well-being, anorexia nervosa patients express temperament traits (e.g., extraversion and persistence) necessary for high levels of life satisfaction. Nevertheless, among individuals without eating disorders, a balanced organization of the flow of time, influences life satisfaction beyond temperamental dispositions. A balanced time perspective is defined as: high past positive, low past negative, high present hedonistic, low present fatalistic, and high future. We investigated differences in time perspective dimensions, personality traits, and life satisfaction between anorexia nervosa patients and matched controls. We also investigated if the personality traits and the outlook on time associated to positive levels of life satisfaction among controls also predicted anorexia patients’ life satisfaction. Additionally, we investigated if time perspective dimensions predicted life satisfaction beyond personality traits among both patients and controls. Method A total of 88 anorexia nervosa patients from a clinic in the West of Sweden and 111 gender-age matched controls from a university in the West of Sweden participated in the Study. All participants responded to the Zimbardo Time Perspective Inventory, the Ten Item Personality Inventory, and the Temporal Satisfaction with Life Scale. Results A t-test showed that patients scored higher in the past negative, the present fatalistic, and the future dimensions, lower in the past positive and the present hedonistic dimensions, higher in conscientiousness, extraversion, and agreeableness, and lower in life satisfaction. Regression analyses showed that life satisfaction was predicted by openness to experience and emotional stability for controls and by emotional stability among patients. When time dimensions were entered in the regression, emotional stability and the past negative and past positive time dimensions predicted life satisfaction among controls, but only the past positive and present hedonistic time dimensions predicted life satisfaction among patients. Conclusion Anorexia patients were less satisfied with life despite being more conscientious, social, and agreeable than controls. Moreover, compared to controls, patients had an unbalanced time perspective: a dark view of the past (i.e., high past negative), a restrained present (i.e., low present hedonistic) and an apocalyptic view of the future (i.e., high present fatalistic). It is plausible to suggest that, therapeutic interventions should focus on empowering patients to cultivate a sentimental and positive view of the past (i.e., high past positive) and the desire to experience pleasure without concern for future consequences (i.e., high present hedonistic) so that they can make self-directed and flexible choices for their own well-being. Such interventions might have effects on life satisfaction beyond the patients’ temperamental disposition. PMID:28929023

Auditory Verbal Hallucinations in Schizophrenia From a Levels of Explanation Perspective.

PubMed

Hugdahl, Kenneth; Sommer, Iris E

2018-02-15

In the present article, we present a "Levels of Explanation" (LoE) approach to auditory verbal hallucinations (AVHs) in schizophrenia. Mental phenomena can be understood at different levels of explanation, including cultural, clinical, cognitive, brain imaging, cellular, and molecular levels. Current research on AVHs is characterized by accumulation of data at all levels, but with little or no interaction of findings between levels. A second advantage with a Levels of Explanation approach is that it fosters interdisciplinarity and collaboration across traditional borders, facilitating a real breakthrough in future research. We exemplify a Levels of Explanation approach with data from 3 levels where findings at 1 level provide predictions for another level. More specifically, we show how functional neuroimaging data at the brain level correspond with behavioral data at the cognitive level, and how data at these 2 levels correspond with recent findings of changes in neurotransmitter function at the cellular level. We further discuss implications for new therapeutic interventions, and the article is ended by suggestion how future research could incorporate genetic influences on AVHs at the molecular level of explanation by providing examples for animal work.

A core competency-based objective structured clinical examination (OSCE) can predict future resident performance.

PubMed

Wallenstein, Joshua; Heron, Sheryl; Santen, Sally; Shayne, Philip; Ander, Douglas

2010-10-01

This study evaluated the ability of an objective structured clinical examination (OSCE) administered in the first month of residency to predict future resident performance in the Accreditation Council for Graduate Medical Education (ACGME) core competencies. Eighteen Postgraduate Year 1 (PGY-1) residents completed a five-station OSCE in the first month of postgraduate training. Performance was graded in each of the ACGME core competencies. At the end of 18 months of training, faculty evaluations of resident performance in the emergency department (ED) were used to calculate a cumulative clinical evaluation score for each core competency. The correlations between OSCE scores and clinical evaluation scores at 18 months were assessed on an overall level and in each core competency. There was a statistically significant correlation between overall OSCE scores and overall clinical evaluation scores (R = 0.48, p < 0.05) and in the individual competencies of patient care (R = 0.49, p < 0.05), medical knowledge (R = 0.59, p < 0.05), and practice-based learning (R = 0.49, p < 0.05). No correlation was noted in the systems-based practice, interpersonal and communication skills, or professionalism competencies. An early-residency OSCE has the ability to predict future postgraduate performance on a global level and in specific core competencies. Used appropriately, such information can be a valuable tool for program directors in monitoring residents' progress and providing more tailored guidance. © 2010 by the Society for Academic Emergency Medicine.

Status of Cycle 23 Forecasts

NASA Technical Reports Server (NTRS)

Hathaway, D. H.

2000-01-01

A number of techniques for predicting solar activity on a solar cycle time scale are identified, described, and tested with historical data. Some techniques, e.g,, regression and curve-fitting, work well as solar activity approaches maximum and provide a month- by-month description of future activity, while others, e.g., geomagnetic precursors, work well near solar minimum but provide an estimate only of the amplitude of the cycle. A synthesis of different techniques is shown to provide a more accurate and useful forecast of solar cycle activity levels. A combination of two uncorrelated geomagnetic precursor techniques provides the most accurate prediction for the amplitude of a solar activity cycle at a time well before activity minimum. This precursor method gave a smoothed sunspot number maximum of 154+21 for cycle 23. A mathematical function dependent upon the time of cycle initiation and the cycle amplitude then describes the level of solar activity for the complete cycle. As the time of cycle maximum approaches a better estimate of the cycle activity is obtained by including the fit between recent activity levels and this function. This Combined Solar Cycle Activity Forecast now gives a smoothed sunspot maximum of 140+20 for cycle 23. The success of the geomagnetic precursors in predicting future solar activity suggests that solar magnetic phenomena at latitudes above the sunspot activity belts are linked to solar activity, which occurs many years later in the lower latitudes.

Dengue prediction by the web: Tweets are a useful tool for estimating and forecasting Dengue at country and city level

PubMed Central

Degener, Carolin Marlen; Vinhal, Livia; Coelho, Giovanini; Meira, Wagner; Codeço, Claudia Torres; Teixeira, Mauro Martins

2017-01-01

Background Infectious diseases are a leading threat to public health. Accurate and timely monitoring of disease risk and progress can reduce their impact. Mentioning a disease in social networks is correlated with physician visits by patients, and can be used to estimate disease activity. Dengue is the fastest growing mosquito-borne viral disease, with an estimated annual incidence of 390 million infections, of which 96 million manifest clinically. Dengue burden is likely to increase in the future owing to trends toward increased urbanization, scarce water supplies and, possibly, environmental change. The epidemiological dynamic of Dengue is complex and difficult to predict, partly due to costly and slow surveillance systems. Methodology / Principal findings In this study, we aimed to quantitatively assess the usefulness of data acquired by Twitter for the early detection and monitoring of Dengue epidemics, both at country and city level at a weekly basis. Here, we evaluated and demonstrated the potential of tweets modeling for Dengue estimation and forecast, in comparison with other available web-based data, Google Trends and Wikipedia access logs. Also, we studied the factors that might influence the goodness-of-fit of the model. We built a simple model based on tweets that was able to ‘nowcast’, i.e. estimate disease numbers in the same week, but also ‘forecast’ disease in future weeks. At the country level, tweets are strongly associated with Dengue cases, and can estimate present and future Dengue cases until 8 weeks in advance. At city level, tweets are also useful for estimating Dengue activity. Our model can be applied successfully to small and less developed cities, suggesting a robust construction, even though it may be influenced by the incidence of the disease, the activity of Twitter locally, and social factors, including human development index and internet access. Conclusions Tweets association with Dengue cases is valuable to assist traditional Dengue surveillance at real-time and low-cost. Tweets are able to successfully nowcast, i.e. estimate Dengue in the present week, but also forecast, i.e. predict Dengue at until 8 weeks in the future, both at country and city level with high estimation capacity. PMID:28719659

Advanced Regional and Decadal Predictions of Coastal Inundation for the U.S. Atlantic and Gulf Coasts (Invited)

NASA Astrophysics Data System (ADS)

Horton, B.; Corbett, D. R.; Donnelly, J. P.; Kemp, A.; Lin, N.; Lindeman, K.; Mann, M. E.; Peltier, W. R.; Rahmstorf, S.

2013-12-01

Future inundation of the U.S. Atlantic and Gulf coasts will depend upon sea-level rise and the intensity and frequency of tropical cyclones, each of which will be affected by climate change. Through ongoing, collaborative research we are employing new interdisciplinary approaches to bring about a step change in the reliability of predictions of such inundation. The rate of sea level rise along the U.S. Atlantic and Gulf coasts increased throughout the 20th century. Whilst there is widespread agreement that it continue to accelerate during the 21st century, great uncertainty surrounds its magnitude and geographic variability. Key uncertainties include the role of continental ice sheets, mountain glaciers, and ocean density changes. Insufficient understanding of these complex physical processes precludes accurate prediction of sea-level rise. New approaches using semi-empirical models that relate instrumental records of climate and sea-level rise have projected up to 2 m of sea-level rise by AD 2100. But the time span of instrumental sea-level records is insufficient to adequately constrain the climate:sea-level relationship. We produced new, high-resolution proxy sea-level reconstructions to provide crucial additional constraints to such semi-empirical models. Our dataset spans the alternation between the 'Medieval Climate Anomaly' and 'Little Ice Age'. Before the models can provide appropriate data for coastal management and planning, they must be complemented with regional estimates of sea-level rise. Therefore, the proxy sea-level data has been collected from four study areas (Connecticut, New Jersey, North Carolina and Florida) to accommodate the required extent of regional variability. In the case of inundation arising from tropical cyclones, the historical and observational records are insufficient for predicting their nature and recurrence, because they are such extreme and rare events. Moreover, future storm surges will be superimposed on background sea-level rise. To overcome these problems, we coupled regional sea-level rise projections with hurricane simulations and storm surge models to map coastal inundation for the current climate and the best and worst case climate scenarios of the IPCC AR4. With agency, NGO, and business partners, we have integrated these findings into coastal policy initiatives, including the first ever adoption of sea level Adaptation Action Areas in a Florida city land use plan.

Nursing self-efficacy of an integrated clinical and administrative information system.

PubMed

Dillon, Thomas W; Lending, Diane; Crews, Thaddeus R; Blankenship, Ray

2003-01-01

Self-efficacy is a user's confidence that he or she has the ability to use an information system. A survey gathered demographics, self-assessed computer skills, attitude and self-efficacy before installation of an integrated clinical and administrative information system. Results showed that higher levels of nursing education, home computer use, and average levels of self-assessed e-mail, Internet search, word processing, and general computer expertise predicted self-efficacy of the system. In addition, previous use of home and office electronics equipment, such as an answering machine, predicted self-efficacy. Implications for training and future adoption of clinical information systems are presented.

Predictive local receptive fields based respiratory motion tracking for motion-adaptive radiotherapy.

PubMed

Yubo Wang; Tatinati, Sivanagaraja; Liyu Huang; Kim Jeong Hong; Shafiq, Ghufran; Veluvolu, Kalyana C; Khong, Andy W H

2017-07-01

Extracranial robotic radiotherapy employs external markers and a correlation model to trace the tumor motion caused by the respiration. The real-time tracking of tumor motion however requires a prediction model to compensate the latencies induced by the software (image data acquisition and processing) and hardware (mechanical and kinematic) limitations of the treatment system. A new prediction algorithm based on local receptive fields extreme learning machines (pLRF-ELM) is proposed for respiratory motion prediction. All the existing respiratory motion prediction methods model the non-stationary respiratory motion traces directly to predict the future values. Unlike these existing methods, the pLRF-ELM performs prediction by modeling the higher-level features obtained by mapping the raw respiratory motion into the random feature space of ELM instead of directly modeling the raw respiratory motion. The developed method is evaluated using the dataset acquired from 31 patients for two horizons in-line with the latencies of treatment systems like CyberKnife. Results showed that pLRF-ELM is superior to that of existing prediction methods. Results further highlight that the abstracted higher-level features are suitable to approximate the nonlinear and non-stationary characteristics of respiratory motion for accurate prediction.

Predictive Monitoring for Improved Management of Glucose Levels

PubMed Central

Reifman, Jaques; Rajaraman, Srinivasan; Gribok, Andrei; Ward, W. Kenneth

2007-01-01

Background Recent developments and expected near-future improvements in continuous glucose monitoring (CGM) devices provide opportunities to couple them with mathematical forecasting models to produce predictive monitoring systems for early, proactive glycemia management of diabetes mellitus patients before glucose levels drift to undesirable levels. This article assesses the feasibility of data-driven models to serve as the forecasting engine of predictive monitoring systems. Methods We investigated the capabilities of data-driven autoregressive (AR) models to (1) capture the correlations in glucose time-series data, (2) make accurate predictions as a function of prediction horizon, and (3) be made portable from individual to individual without any need for model tuning. The investigation is performed by employing CGM data from nine type 1 diabetic subjects collected over a continuous 5-day period. Results With CGM data serving as the gold standard, AR model-based predictions of glucose levels assessed over nine subjects with Clarke error grid analysis indicated that, for a 30-minute prediction horizon, individually tuned models yield 97.6 to 100.0% of data in the clinically acceptable zones A and B, whereas cross-subject, portable models yield 95.8 to 99.7% of data in zones A and B. Conclusions This study shows that, for a 30-minute prediction horizon, data-driven AR models provide sufficiently-accurate and clinically-acceptable estimates of glucose levels for timely, proactive therapy and should be considered as the modeling engine for predictive monitoring of patients with type 1 diabetes mellitus. It also suggests that AR models can be made portable from individual to individual with minor performance penalties, while greatly reducing the burden associated with model tuning and data collection for model development. PMID:19885110

Predictive accuracy of a ground-water model--Lessons from a postaudit

USGS Publications Warehouse

Konikow, Leonard F.

1986-01-01

Hydrogeologic studies commonly include the development, calibration, and application of a deterministic simulation model. To help assess the value of using such models to make predictions, a postaudit was conducted on a previously studied area in the Salt River and lower Santa Cruz River basins in central Arizona. A deterministic, distributed-parameter model of the ground-water system in these alluvial basins was calibrated by Anderson (1968) using about 40 years of data (1923–64). The calibrated model was then used to predict future water-level changes during the next 10 years (1965–74). Examination of actual water-level changes in 77 wells from 1965–74 indicates a poor correlation between observed and predicted water-level changes. The differences have a mean of 73 ft that is, predicted declines consistently exceeded those observed and a standard deviation of 47 ft. The bias in the predicted water-level change can be accounted for by the large error in the assumed total pumpage during the prediction period. However, the spatial distribution of errors in predicted water-level change does not correlate with the spatial distribution of errors in pumpage. Consequently, the lack of precision probably is not related only to errors in assumed pumpage, but may indicate the presence of other sources of error in the model, such as the two-dimensional representation of a three-dimensional problem or the lack of consideration of land-subsidence processes. This type of postaudit is a valuable method of verifying a model, and an evaluation of predictive errors can provide an increased understanding of the system and aid in assessing the value of undertaking development of a revised model.

Future sea-level rise in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Galassi, Gaia; Spada, Giorgio

2014-05-01

Secular sea level variations in the Mediterranean Sea are the result of a number of processes characterized by distinct time scales and spatial patterns. Here we predict the future sea level variations in the Mediterranean Sea to year 2050 combining the contributions from terrestrial ice melt (TIM), glacial isostatic adjustment (GIA), and the ocean response (OR) that includes the thermal expansion and the ocean circulation contributions. The three contributions are characterized by comparable magnitudes but distinctly different sea-level fingerprints across the Mediterranean basin. The TIM component of future sea-level rise is taken from Spada et al. (2013) and it is mainly driven by the melt of small glaciers and ice caps and by the dynamic ice loss from Antarctica. The sea-level fingerprint associated with GIA is studied using two distinct models available from the literature: ICE-5G(VM2) (Peltier, 2004) and the ice model progressively developed at the Research School of Earth Sciences (RSES) of the National Australian University (KL05) (see Fleming and Lambeck, 2004 and references therein). Both the GIA and the TIM sea-level predictions have been obtained with the aid of the SELEN program (Spada and Stocchi, 2007). The spatially-averaged OR component, which includes thermosteric and halosteric sea-level variations, recently obtained using a regional coupled ocean-atmosphere model (Carillo et al., 2012), vary between 2 and 7 cm according to scenarios adopted (EA1B and EA1B2, see Meehl at al., 2007). Since the sea-level variations associated with TIM mainly result from the gravitational interactions between the cryosphere components, the oceans and the solid Earth, and long-wavelength rotational variations, they are characterized by a very smooth global pattern and by a marked zonal symmetry reflecting the dipole geometry of the ice sources. Since the Mediterranean Sea is located in the intermediate far-field of major ice sources, TIM sea-level changes have sub-eustatic values (i.e. they do not exceed the global average) and show little (but still significant) variations across the basin associated with the subsidence driven by the meltwater load. For year 2050, TIM calculations predict a sea-level rise of ~10 and ~30 cm for the mid range and the high end scenarios, respectively. Mainly because of the distinct mantle viscosity profiles adopted in ICE-5G(VM2) and KL05, the GIA patterns differ significantly and, in contrast with the TIM fingerprint, are both characterized by strong variations across the Mediterranean Sea, showing maximum values in the bulk of the basin. For the OR component, a significant geographical variation is observed across the Mediterranean sub-basins, corresponding to different Atlantic boundary conditionsAccording to this study, the total future sea-level rise for year 2050 will reach maximum values for the extreme scenario (hig-hend prediction for TIM, KL05 for GIA and EA1B2 for OR) of ˜ 27 cm in average with peak of ˜ 30 cm in the central sub-basins. Our results show that when these three components of future sea-level rise are simultaneously considered, the spatial variability is enhanced because of the neatly distinct geometry of the three fingerprints. References: Carillo, A., Sannino, G., Artale, V., Ruti, P., Calmanti, S., DellAquila, A., 2012, Clim. Dyn. 39 (9-10), 2167-2184; Fleming, K. and Lambeck, K., 2004, Quat. Sci. Rev. 23 (9-10), 1053-1077; Meehl, G.A., and 11 others, 2007, in Climate Change 2007: The Physical Science Basis, Cambridge University Press; Peltier W.R., 2004, Annu. Rev. Earth Pl. Sc., 32, 111-149; Spada, G. and Stocchi, P., 2007, Comput. and Geosci., 33(4), 538-562; Spada G., Bamber J. L., Hurkmans R. T. W. L., 2013, Geophys. Res. Lett., 1-5, 40.

Validation of Afterbody Aeroheating Predictions for Planetary Probes: Status and Future Work

NASA Technical Reports Server (NTRS)

Wright, Michael J.; Brown, James L.; Sinha, Krishnendu; Candler, Graham V.; Milos, Frank S.; Prabhu, DInesh K.

2005-01-01

A review of the relevant flight conditions and physical models for planetary probe afterbody aeroheating calculations is given. Readily available sources of afterbody flight data and published attempts to computationally simulate those flights are summarized. A current status of the application of turbulence models to afterbody flows is presented. Finally, recommendations for additional analysis and testing that would reduce our uncertainties in our ability to accurately predict base heating levels are given.

Testing Relations of Crystallized and Fluid Intelligence and the Incremental Predictive Validity of Conscientiousness and Its Facets on Career Success in a Small Sample of German and Swiss Workers.

PubMed

Hagmann-von Arx, Priska; Gygi, Jasmin T; Weidmann, Rebekka; Grob, Alexander

2016-01-01

This study examined the relation of fluid and crystallized intelligence with extrinsic (occupational skill level, income) and intrinsic (job satisfaction) career success as well as the incremental predictive validity of conscientiousness and its facets. Participants (N = 121) completed the Reynolds Intellectual Assessment Scales (RIAS), the Revised NEO Personality Inventory (NEO-PI-R), and reported their occupational skill level, income, and job satisfaction. Results revealed that crystallized intelligence was positively related to occupational skill level, but not to income. The association of crystallized intelligence and job satisfaction was negative and stronger for the lowest occupational skill level, whereas it was non-significant for higher levels. Fluid intelligence showed no association with career success. Beyond intelligence, conscientiousness and its facet self-discipline were associated with income, whereas conscientiousness and its facets competence and achievement striving were associated with job satisfaction. The results are discussed in terms of their implications for the assessment process as well as for future research to adequately predict career success.

Testing Relations of Crystallized and Fluid Intelligence and the Incremental Predictive Validity of Conscientiousness and Its Facets on Career Success in a Small Sample of German and Swiss Workers

PubMed Central

Hagmann-von Arx, Priska; Gygi, Jasmin T.; Weidmann, Rebekka; Grob, Alexander

2016-01-01

This study examined the relation of fluid and crystallized intelligence with extrinsic (occupational skill level, income) and intrinsic (job satisfaction) career success as well as the incremental predictive validity of conscientiousness and its facets. Participants (N = 121) completed the Reynolds Intellectual Assessment Scales (RIAS), the Revised NEO Personality Inventory (NEO-PI-R), and reported their occupational skill level, income, and job satisfaction. Results revealed that crystallized intelligence was positively related to occupational skill level, but not to income. The association of crystallized intelligence and job satisfaction was negative and stronger for the lowest occupational skill level, whereas it was non-significant for higher levels. Fluid intelligence showed no association with career success. Beyond intelligence, conscientiousness and its facet self-discipline were associated with income, whereas conscientiousness and its facets competence and achievement striving were associated with job satisfaction. The results are discussed in terms of their implications for the assessment process as well as for future research to adequately predict career success. PMID:27148112

Association of testosterone levels and future suicide attempts in females with bipolar disorder

PubMed Central

Sher, Leo; Grunebaum, Michael F.; Sullivan, Gregory M.; Burke, Ainsley K.; Cooper, Thomas B.; Mann, J. John; Oquendo, Maria A.

2015-01-01

Background Considerable evidence suggests that testosterone may play a role in the pathophysiology of mood disorders in females. This is the first prospective study to examine whether blood testosterone levels predict suicide attempts in females with bipolar disorder. Methods Females with a DSM-IV diagnosis of a bipolar disorder in a depressive or mixed episode with at least one past suicide attempt were enrolled. Demographic and clinical parameters were assessed and recorded. Plasma testosterone was assayed using a double antibody radioimmunoassay procedure. Patients were followed up prospectively for up to 2.5 years. Results At baseline, testosterone levels positively correlated with the number of previous major depressive episodes and suicide attempts. Cox proportional hazards regression analysis found that higher baseline testosterone levels predicted suicide attempts during the follow-up period. Limitations A limitation of the study is that the sample size is modest. Another limitation is that we did not have a bipolar nonattempter or healthy volunteer control group for comparison. Conclusion Testosterone levels may predict suicidal behavior in women with bipolar disorder. PMID:25012416

Trajectories of sleep disturbance and daytime sleepiness in women before and after surgery for breast cancer.

PubMed

Van Onselen, Christina; Paul, Steven M; Lee, Kathryn; Dunn, Laura; Aouizerat, Bradley E; West, Claudia; Dodd, Marylin; Cooper, Bruce; Miaskowski, Christine

2013-02-01

Sleep disturbance is a problem for oncology patients. To evaluate how sleep disturbance and daytime sleepiness (DS) changed from before to six months following surgery and whether certain characteristics predicted initial levels and/or the trajectories of these parameters. Patients (n=396) were enrolled prior to surgery and completed monthly assessments for six months following surgery. The General Sleep Disturbance Scale was used to assess sleep disturbance and DS. Using hierarchical linear modeling, demographic, clinical, symptom, and psychosocial adjustment characteristics were evaluated as predictors of initial levels and trajectories of sleep disturbance and DS. All seven General Sleep Disturbance Scale scores were above the cutoff for clinically meaningful levels of sleep disturbance. Lower performance status; higher comorbidity, attentional fatigue, and physical fatigue; and more severe hot flashes predicted higher preoperative levels of sleep disturbance. Higher levels of education predicted higher sleep disturbance scores over time. Higher levels of depressive symptoms predicted higher preoperative levels of sleep disturbance, which declined over time. Lower performance status; higher body mass index; higher fear of future diagnostic tests; not having had sentinel lymph node biopsy; having had an axillary lymph node dissection; and higher depression, physical fatigue, and attentional fatigue predicted higher DS prior to surgery. Higher levels of education, not working for pay, and not having undergone neo-adjuvant chemotherapy predicted higher DS scores over time. Sleep disturbance is a persistent problem for patients with breast cancer. The effects of interventions that can address modifiable risk factors need to be evaluated. Copyright © 2013 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

Exploring Resource Sharing between Secondary School Teachers of Agriculture and Science Departments Nationally.

ERIC Educational Resources Information Center

Dormody, Thomas J.

1992-01-01

A survey of 372 secondary agriculture teachers received 274 responses showing a majority of agriculture and science departments share resources, although at low levels. Many more predicted future sharing. Equipment and supplies were most often shared, instructional services least often. (SK)

The Sky Is the Limit.

ERIC Educational Resources Information Center

Learning, 1994

1994-01-01

Pullout pages provide suggestions for teaching elementary students at all levels about the wonders of human ingenuity. The suggestions help students see that great ideas come from the need to solve real-life problems and that one great idea leads to another, so current inventions help predict future inventions. (SM)

Solar Activity Heading for a Maunder Minimum?

NASA Astrophysics Data System (ADS)

Schatten, K. H.; Tobiska, W. K.

2003-05-01

Long-range (few years to decades) solar activity prediction techniques vary greatly in their methods. They range from examining planetary orbits, to spectral analyses (e.g. Fourier, wavelet and spectral analyses), to artificial intelligence methods, to simply using general statistical techniques. Rather than concentrate on statistical/mathematical/numerical methods, we discuss a class of methods which appears to have a "physical basis." Not only does it have a physical basis, but this basis is rooted in both "basic" physics (dynamo theory), but also solar physics (Babcock dynamo theory). The class we discuss is referred to as "precursor methods," originally developed by Ohl, Brown and Williams and others, using geomagnetic observations. My colleagues and I have developed some understanding for how these methods work and have expanded the prediction methods using "solar dynamo precursor" methods, notably a "SODA" index (SOlar Dynamo Amplitude). These methods are now based upon an understanding of the Sun's dynamo processes- to explain a connection between how the Sun's fields are generated and how the Sun broadcasts its future activity levels to Earth. This has led to better monitoring of the Sun's dynamo fields and is leading to more accurate prediction techniques. Related to the Sun's polar and toroidal magnetic fields, we explain how these methods work, past predictions, the current cycle, and predictions of future of solar activity levels for the next few solar cycles. The surprising result of these long-range predictions is a rapid decline in solar activity, starting with cycle #24. If this trend continues, we may see the Sun heading towards a "Maunder" type of solar activity minimum - an extensive period of reduced levels of solar activity. For the solar physicists, who enjoy studying solar activity, we hope this isn't so, but for NASA, which must place and maintain satellites in low earth orbit (LEO), it may help with reboost problems. Space debris, and other aspects of objects in LEO will also be affected. This research is supported by the NSF and NASA.

Bridging a divide: architecture for a joint hospital-primary care data warehouse.

PubMed

An, Jeff; Keshavjee, Karim; Mirza, Kashif; Vassanji, Karim; Greiver, Michelle

2015-01-01

Healthcare costs are driven by a surprisingly small number of patients. Predicting who is likely to require care in the near future could help reduce costs by pre-empting use of expensive health care resources such as emergency departments and hospitals. We describe the design of an architecture for a joint hospital-primary care data warehouse (JDW) that can monitor the effectiveness of in-hospital interventions in reducing readmissions and predict which patients are most likely to be admitted to hospital in the near future. The design identifies the key governance elements, the architectural principles, the business case, the privacy architecture, future work flows, the IT infrastructure, the data analytics and the high level implementation plan for realization of the JDW. This architecture fills a gap in bridging data from two separate hospital and primary care organizations, not a single managed care entity with multiple locations. The JDW architecture design was well received by the stakeholders engaged and by senior leadership at the hospital and the primary care organization. Future plans include creating a demonstration system and conducting a pilot study.

Predicting county-level cancer incidence rates and counts in the United States

PubMed Central

Yu, Binbing

2018-01-01

Many countries, including the United States, publish predicted numbers of cancer incidence and death in current and future years for the whole country. These predictions provide important information on the cancer burden for cancer control planners, policymakers and the general public. Based on evidence from several empirical studies, the joinpoint (segmented-line linear regression) model has been adopted by the American Cancer Society to estimate the number of new cancer cases in the United States and in individual states since 2007. Recently, cancer incidence in smaller geographic regions such as counties and FIPS code regions is of increasing interest by local policymakers. The natural extension is to directly apply the joinpoint model to county-level cancer incidence data. The direct application has several drawbacks and its performance has not been evaluated. To address the concerns, we developed a spatial random-effects joinpoint model for county-level cancer incidence data. The proposed model was used to predict both cancer incidence rates and counts at the county level. The standard joinpoint model and the proposed method were compared through a validation study. The proposed method out-performed the standard joinpoint model for almost all cancer sites, especially for moderate or rare cancer sites and for counties with small population sizes. As an application, we predicted county-level prostate cancer incidence rates and counts for the year 2011 in Connecticut. PMID:23670947

Scaling Techniques for Combustion Device Random Vibration Predictions

NASA Technical Reports Server (NTRS)

Kenny, R. J.; Ferebee, R. C.; Duvall, L. D.

2016-01-01

This work presents compares scaling techniques that can be used for prediction of combustion device component random vibration levels with excitation due to the internal combustion dynamics. Acceleration and unsteady dynamic pressure data from multiple component test programs are compared and normalized per the two scaling approaches reviewed. Two scaling technique are reviewed and compared against the collected component test data. The first technique is an existing approach developed by Barrett, and the second technique is an updated approach new to this work. Results from utilizing both techniques are presented and recommendations about future component random vibration prediction approaches are given.

A comparison between the observed and predicted Fe II spectrum in different plasmas

NASA Astrophysics Data System (ADS)

Johansson, S.

This paper gives a survey of the spectral distribution of emission lines of Fe II, predicted from a single atomic model. The observed differences between the recorded and the predicted spectrum are discussed in terms of deficiencies of the model and interactions within the emitting plasma. A number of illustrative examples of unexpected features with applications to astrophysics are given. Selective population, due to charge transfer and resonant photo excitation, is elucidated. The future need of more laboratory data for Fe II as regards energy levels and line classification is also discussed.

Serum Levels of Progranulin Do Not Reflect Cerebrospinal Fluid Levels in Neurodegenerative Disease.

PubMed

Wilke, Carlo; Gillardon, Frank; Deuschle, Christian; Dubois, Evelyn; Hobert, Markus A; Müller vom Hagen, Jennifer; Krüger, Stefanie; Biskup, Saskia; Blauwendraat, Cornelis; Hruscha, Michael; Kaeser, Stephan A; Heutink, Peter; Maetzler, Walter; Synofzik, Matthis

2016-01-01

Altered progranulin levels play a major role in neurodegenerative diseases, like Alzheimer's dementia (AD), frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS), even in the absence of GRN mutations. Increasing progranulin levels could hereby provide a novel treatment strategy. However, knowledge on progranulin regulation in neurodegenerative diseases remains limited. We here demonstrate that cerebrospinal fluid progranulin levels do not correlate with its serum levels in AD, FTD and ALS, indicating a differential regulation of its central and peripheral levels in neurodegeneration. Blood progranulin levels thus do not reliably predict central nervous progranulin levels and their response to future progranulin-increasing therapeutics.

ISMIP6: Ice Sheet Model Intercomparison Project for CMIP6

NASA Technical Reports Server (NTRS)

Nowicki, S.

2015-01-01

ISMIP6 (Ice Sheet Model Intercomparison Project for CMIP6) targets the Cryosphere in a Changing Climate and the Future Sea Level Grand Challenges of the WCRP (World Climate Research Program). Primary goal is to provide future sea level contribution from the Greenland and Antarctic ice sheets, along with associated uncertainty. Secondary goal is to investigate feedback due to dynamic ice sheet models. Experiment design uses and augment the existing CMIP6 (Coupled Model Intercomparison Project Phase 6) DECK (Diagnosis, Evaluation, and Characterization of Klima) experiments. Additonal MIP (Model Intercomparison Project)- specific experiments will be designed for ISM (Ice Sheet Model). Effort builds on the Ice2sea, SeaRISE (Sea-level Response to Ice Sheet Evolution) and COMBINE (Comprehensive Modelling of the Earth System for Better Climate Prediction and Projection) efforts.

Current & future vulnerability of sarasota county Florida to hurricane storm surge & sea level rise

USGS Publications Warehouse

Frazier, T.; Wood, N.; Yarnal, B.

2008-01-01

Coastal communities in portions of the United States are vulnerable to storm-surge inundation from hurricanes and this vulnerability will likely increase, given predicted rises in sea level from climate change and growing coastal development. In this paper, we provide an overview of research to determine current and future societal vulnerability to hurricane storm-surge inundation and to help public officials and planners integrate these scenarios into their long-range land use plans. Our case study is Sarasota County, Florida, where planners face the challenge of balancing increasing population growth and development with the desire to lower vulnerability to storm surge. Initial results indicate that a large proportion of Sarasota County's residential and employee populations are in areas prone to storm-surge inundation from a Category 5 hurricane. This hazard zone increases when accounting for potential sea-level-rise scenarios, thereby putting additional populations at risk. Subsequent project phases involve the development of future land use and vulnerability scenarios in collaboration with local officials. Copyright ASCE 2008.

A Study on the Relationship between Self Directed Learning and Achievement in Information Technology of Students at Secondary Level

ERIC Educational Resources Information Center

Jaleel, Sajna; O. M., Anuroofa

2017-01-01

Education at any level has normally been based on some image of the future; that was not impossible in a world that was changing slowly. Today, educators are preparing learners for a world we cannot even predict, and self-directed learning has become an essential foundation for 21st century learners. In recent years teachers are giving importance…

Induced Insecurity: Understanding the Potential Pitfalls in Developing Theater Campaign Plans

DTIC Science & Technology

2015-06-11

effective partnerships that meet outlined in higher- level strategic guidance . 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. UMITATION OF... effective partnerships that meet the desired end states outlined in higher-level strategic guidance. DEDICATION To the millions of men and women who...and draw conclusions, it does not always prove to be an effective means of predicting the outcome of current or future events. In addition, the

Near-future carbon dioxide levels alter fish behaviour by interfering with neurotransmitter function

NASA Astrophysics Data System (ADS)

Nilsson, Göran E.; Dixson, Danielle L.; Domenici, Paolo; McCormick, Mark I.; Sørensen, Christina; Watson, Sue-Ann; Munday, Philip L.

2012-03-01

Predicted future CO2 levels have been found to alter sensory responses and behaviour of marine fishes. Changes include increased boldness and activity, loss of behavioural lateralization, altered auditory preferences and impaired olfactory function. Impaired olfactory function makes larval fish attracted to odours they normally avoid, including ones from predators and unfavourable habitats. These behavioural alterations have significant effects on mortality that may have far-reaching implications for population replenishment, community structure and ecosystem function. However, the underlying mechanism linking high CO2 to these diverse responses has been unknown. Here we show that abnormal olfactory preferences and loss of behavioural lateralization exhibited by two species of larval coral reef fish exposed to high CO2 can be rapidly and effectively reversed by treatment with an antagonist of the GABA-A receptor. GABA-A is a major neurotransmitter receptor in the vertebrate brain. Thus, our results indicate that high CO2 interferes with neurotransmitter function, a hitherto unrecognized threat to marine populations and ecosystems. Given the ubiquity and conserved function of GABA-A receptors, we predict that rising CO2 levels could cause sensory and behavioural impairment in a wide range of marine species, especially those that tightly control their acid-base balance through regulatory changes in HCO3- and Cl- levels.

Evaluating coastal landscape response to sea-level rise in the northeastern United States: approach and methods

USGS Publications Warehouse

Lentz, Erika E.; Stippa, Sawyer R.; Thieler, E. Robert; Plant, Nathaniel G.; Gesch, Dean B.; Horton, Radley M.

2014-02-13

The U.S. Geological Survey is examining effects of future sea-level rise on the coastal landscape from Maine to Virginia by producing spatially explicit, probabilistic predictions using sea-level projections, vertical land movement rates (due to isostacy), elevation data, and land-cover data. Sea-level-rise scenarios used as model inputs are generated by using multiple sources of information, including Coupled Model Intercomparison Project Phase 5 models following representative concentration pathways 4.5 and 8.5 in the Intergovernmental Panel on Climate Change Fifth Assessment Report. A Bayesian network is used to develop a predictive coastal response model that integrates the sea-level, elevation, and land-cover data with assigned probabilities that account for interactions with coastal geomorphology as well as the corresponding ecological and societal systems it supports. The effects of sea-level rise are presented as (1) level of landscape submergence and (2) coastal response type characterized as either static (that is, inundation) or dynamic (that is, landform or landscape change). Results are produced at a spatial scale of 30 meters for four decades (the 2020s, 2030s, 2050s, and 2080s). The probabilistic predictions can be applied to landscape management decisions based on sea-level-rise effects as well as on assessments of the prediction uncertainty and need for improved data or fundamental understanding. This report describes the methods used to produce predictions, including information on input datasets; the modeling approach; model outputs; data-quality-control procedures; and information on how to access the data and metadata online.

Evaluating Coastal Landscape Response to Sea-Level Rise in the Northeastern United States - Approach and Methods

NASA Technical Reports Server (NTRS)

Lentz, Erika E.; Stippa, Sawyer R.; Thieler, E. Robert; Plant, Nathaniel G.; Gesch, Dean B.; Horton, Radley M.

2015-01-01

The U.S. Geological Survey is examining effects of future sea-level rise on the coastal landscape from Maine to Virginia by producing spatially explicit, probabilistic predictions using sea-level projections, vertical land movement rates (due to isostacy), elevation data, and land-cover data. Sea-level-rise scenarios used as model inputs are generated by using multiple sources of information, including Coupled Model Intercomparison Project Phase 5 models following representative concentration pathways 4.5 and 8.5 in the Intergovernmental Panel on Climate Change Fifth Assessment Report. A Bayesian network is used to develop a predictive coastal response model that integrates the sea-level, elevation, and land-cover data with assigned probabilities that account for interactions with coastal geomorphology as well as the corresponding ecological and societal systems it supports. The effects of sea-level rise are presented as (1) level of landscape submergence and (2) coastal response type characterized as either static (that is, inundation) or dynamic (that is, landform or landscape change). Results are produced at a spatial scale of 30 meters for four decades (the 2020s, 2030s, 2050s, and 2080s). The probabilistic predictions can be applied to landscape management decisions based on sea-level-rise effects as well as on assessments of the prediction uncertainty and need for improved data or fundamental understanding. This report describes the methods used to produce predictions, including information on input datasets; the modeling approach; model outputs; data-quality-control procedures; and information on how to access the data and metadata online.

The predicted influence of climate change on lesser prairie-chicken reproductive parameters

USGS Publications Warehouse

Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, D.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Nina events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

The predicted influence of climate change on lesser prairie-chicken reproductive parameters.

PubMed

Grisham, Blake A; Boal, Clint W; Haukos, David A; Davis, Dawn M; Boydston, Kathy K; Dixon, Charles; Heck, Willard R

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

Predicting the effect of disability on employment status and income.

PubMed

Randolph, Diane Smith

2004-01-01

Research shows that participation in employment contributes to life satisfaction for persons with disabilities [18]. Title I of the Americans with Disabilities Act (ADA) sought to prohibit discrimination against persons with disabilities in the workplace, however, the ADA's effectiveness remains controversial. This research utilizes data from the disability supplement of the 2000 Behavioral Risk Factor Surveillance System to examine the impact of disability status on predicting employment status and income. Confounding variables such as gender, age, educational level, race and marital/parental status are examined regarding their influence on results. Results from analysis utilizing zero-order correlation, linear and logistic regression analysis techniques revealed that disability status has a significant predictive effect on inability to work. Furthermore, results continue to show that despite legislation, the higher the level of disability, the lower the employment status (those employed for wages) and income. Finally, disability status, coupled with being female or decreased educational level, consistently shows significance in predicting lower employment status and income than men or non-minorities with disabilities. Future research opportunities and policy implications are discussed with regard to the results presented.

Climatically-mediated landcover change: impacts on Brazilian territory.

PubMed

Zanin, Marina; Tessarolo, Geiziane; Machado, Nathália; Albernaz, Ana Luisa M

2017-01-01

In the face of climate change threats, governments are drawing attention to policies for mitigating its effects on biodiversity. However, the lack of distribution data makes predictions at species level a difficult task, mainly in regions of higher biodiversity. To overcome this problem, we use native landcover as a surrogate biodiversity, because it can represent specialized habitat for species, and investigate the effects of future climate change on Brazilian biomes. We characterize the climatic niches of native landcover and use ecological niche modeling to predict the potential distribution under current and future climate scenarios. Our results highlight expansion of the distribution of open vegetation and the contraction of closed forests. Drier Brazilian biomes, like Caatinga and Cerrado, are predicted to expand their distributions, being the most resistant to climate change impacts. However, these would also be affected by losses of their closed forest enclaves and their habitat-specific or endemic species. Replacement by open vegetation and overall reductions are a considerable risk for closed forest, threatening Amazon and Atlantic forest biomes. Here, we evidence the impacts of climate change on Brazilian biomes, and draw attention to the necessity for management and attenuation plans to guarantee the future of Brazilian biodiversity.

Unravelling the structure of species extinction risk for predictive conservation science.

PubMed

Lee, Tien Ming; Jetz, Walter

2011-05-07

Extinction risk varies across species and space owing to the combined and interactive effects of ecology/life history and geography. For predictive conservation science to be effective, large datasets and integrative models that quantify the relative importance of potential factors and separate rapidly changing from relatively static threat drivers are urgently required. Here, we integrate and map in space the relative and joint effects of key correlates of The International Union for Conservation of Nature-assessed extinction risk for 8700 living birds. Extinction risk varies significantly with species' broad-scale environmental niche, geographical range size, and life-history and ecological traits such as body size, developmental mode, primary diet and foraging height. Even at this broad scale, simple quantifications of past human encroachment across species' ranges emerge as key in predicting extinction risk, supporting the use of land-cover change projections for estimating future threat in an integrative setting. A final joint model explains much of the interspecific variation in extinction risk and provides a remarkably strong prediction of its observed global geography. Our approach unravels the species-level structure underlying geographical gradients in extinction risk and offers a means of disentangling static from changing components of current and future threat. This reconciliation of intrinsic and extrinsic, and of past and future extinction risk factors may offer a critical step towards a more continuous, forward-looking assessment of species' threat status based on geographically explicit environmental change projections, potentially advancing global predictive conservation science.

Understanding reproducibility of human IVF traits to predict next IVF cycle outcome.

PubMed

Wu, Bin; Shi, Juanzi; Zhao, Wanqiu; Lu, Suzhen; Silva, Marta; Gelety, Timothy J

2014-10-01

Evaluating the failed IVF cycle often provides useful prognostic information. Before undergoing another attempt, patients experiencing an unsuccessful IVF cycle frequently request information about the probability of future success. Here, we introduced the concept of reproducibility and formulae to predict the next IVF cycle outcome. The experimental design was based on the retrospective review of IVF cycle data from 2006 to 2013 in two different IVF centers and statistical analysis. The reproducibility coefficients (r) of IVF traits including number of oocytes retrieved, oocyte maturity, fertilization, embryo quality and pregnancy were estimated using the interclass correlation coefficient between the repeated IVF cycle measurements for the same patient by variance component analysis. The formulae were designed to predict next IVF cycle outcome. The number of oocytes retrieved from patients and their fertilization rate had the highest reproducibility coefficients (r = 0.81 ~ 0.84), which indicated a very close correlation between the first retrieval cycle and subsequent IVF cycles. Oocyte maturity and number of top quality embryos had middle level reproducibility (r = 0.38 ~ 0.76) and pregnancy rate had a relative lower reproducibility (r = 0.23 ~ 0.27). Based on these parameters, the next outcome for these IVF traits might be accurately predicted by the designed formulae. The introduction of the concept of reproducibility to our human IVF program allows us to predict future IVF cycle outcomes. The traits of oocyte numbers retrieved, oocyte maturity, fertilization, and top quality embryos had higher or middle reproducibility, which provides a basis for accurate prediction of future IVF outcomes. Based on this prediction, physicians may counsel their patients or change patient's stimulation plans, and laboratory embryologists may improve their IVF techniques accordingly.

Radicals and Reservoirs in the GMI Chemistry and Transport Model: Comparison to Measurements

NASA Technical Reports Server (NTRS)

Douglas, Anne R.; Stolarski, Richard S.; Strahan, Susan E.; Connell, Peter S.

2004-01-01

The most important use of atmospheric chemistry and transport models is to predict the future composition of the atmosphere. The amounts of gases like chlorofluorcarbons, methyl bromide, nitrous oxide and methane are changing and the stratospheric ozone layer will change because these gases are changing. Methyl bromide, nitrous oxide and methane all have natural sources, and also change because of human activity. Chlorofluorcarbons are man-made gases; these are known to decrease stratospheric ozone and future production is banned. They are long-lived gases, and many decades will pass before they are insignificant in the atmosphere. The models are used to predict changes in ozone and other gases; this is a straightforward application. The models must be also tested using observations for the present day atmosphere. This is a challenging task, because the model contains more than 50 species and more than 150 chemical reactions. Data from satellites, ground stations, aircraft and balloons are used to evaluate the model. Different models that are used in international assessments produce different results; in the most recent assessment some predict that ozone will return to 1980 levels by 2025 and others predict that this will not happen until 2050. Since all the parts of the models are conceptually the same, there must be differences in implementation that produce these differences, This work takes a single model, two different sets of winds and temperatures, and repeats the same prediction for the future. Here we compare the results for these two simulations with many observations. The purpose is to identify differences in the model results for the present atmosphere that will lead to different predictions. This sort of controlled comparison will reduce uncertainty in the predictions for stratospheric ozone.

Uric Acid Levels Can Predict Metabolic Syndrome and Hypertension in Adolescents: A 10-Year Longitudinal Study.

PubMed

Sun, Hai-Lun; Pei, Dee; Lue, Ko-Huang; Chen, Yen-Lin

2015-01-01

The relationships between uric acid and chronic disease risk factors such as metabolic syndrome, type 2 diabetes mellitus, and hypertension have been studied in adults. However, whether these relationships exist in adolescents is unknown. We randomly selected 8,005 subjects who were between 10 to 15 years old at baseline. Measurements of uric acid were used to predict the future occurrence of metabolic syndrome, hypertension, and type 2 diabetes. In total, 5,748 adolescents were enrolled and followed for a median of 7.2 years. Using cutoff points of uric acid for males and females (7.3 and 6.2 mg/dl, respectively), a high level of uric acid was either the second or third best predictor for hypertension in both genders (hazard ratio: 2.920 for males, 5.222 for females; p<0.05). However, uric acid levels failed to predict type 2 diabetes mellitus, and only predicted metabolic syndrome in males (hazard ratio: 1.658; p<0.05). The same results were found in multivariate adjusted analysis. In conclusion, a high level of uric acid indicated a higher likelihood of developing hypertension in both genders and metabolic syndrome in males after 10 years of follow-up. However, uric acid levels did not affect the occurrence of type 2 diabetes in both genders.

A big data analysis of the relationship between future thinking and decision-making.

PubMed

Thorstad, Robert; Wolff, Phillip

2018-02-20

We use big data methods to investigate how decision-making might depend on future sightedness (that is, on how far into the future people's thoughts about the future extend). In study 1, we establish a link between future thinking and decision-making at the population level in showing that US states with citizens having relatively far future sightedness, as reflected in their tweets, take fewer risks than citizens in states having relatively near future sightedness. In study 2, we analyze people's tweets to confirm a connection between future sightedness and decision-making at the individual level in showing that people with long future sightedness are more likely to choose larger future rewards over smaller immediate rewards. In study 3, we show that risk taking decreases with increases in future sightedness as reflected in people's tweets. The ability of future sightedness to predict decisions suggests that future sightedness is a relatively stable cognitive characteristic. This implication was supported in an analysis of tweets by over 38,000 people that showed that future sightedness has both state and trait characteristics (study 4). In study 5, we provide evidence for a potential mechanism by which future sightedness can affect decisions in showing that far future sightedness can make the future seem more connected to the present, as reflected in how people refer to the present, past, and future in their tweets over the course of several minutes. Our studies show how big data methods can be applied to naturalistic data to reveal underlying psychological properties and processes.

Serum Amino Acid Profiles in Childhood Predict Triglyceride Level in Adulthood: A 7-Year Longitudinal Study in Girls.

PubMed

Wiklund, Petri; Zhang, Xiaobo; Tan, Xiao; Keinänen-Kiukaanniemi, Sirkka; Alen, Markku; Cheng, Sulin

2016-05-01

Branched-chain and aromatic amino acids are associated with high risk of developing dyslipidemia and type II diabetes in adults. This study aimed to examine whether serum amino acid profiles associate with triglyceride concentrations during pubertal growth and predict hypertriglyceridemia in early adulthood. This was a 7.5-year longitudinal study. The study was conducted at the Health Science Laboratory, University of Jyväskylä. A total of 396 nondiabetic Finnish girls aged 11.2 ± 0.8 years at the baseline participated in the study. Body composition was assessed by dual-energy x-ray absorptiometry; serum concentrations of glucose, insulin, and triglyceride by enzymatic photometric methods; and amino acids by nuclear magnetic resonance spectroscopy. Serum leucine and isoleucine correlated significantly with future triglyceride, independent of baseline triglyceride level (P < .05 for all). In early adulthood (at the age of 18 years), these amino acids were significantly associated with hypertriglyceridemia, whereas fat mass and homeostasis model assessment of insulin resistance were not. Leucine was the strongest determinant discriminating subjects with hypertriglyceridemia from those with normal triglyceride level (area under the curve, 0.822; 95% confidence interval, 0.740-0.903; P = .000001). Serum leucine and isoleucine were associated with future serum triglyceride levels in girls during pubertal growth and predicted hypertriglyceridemia in early adulthood. Therefore, these amino acid indices may serve as biomarkers to identify individuals at high risk for developing hypertriglyceridemia and cardiovascular disease later in life. Further studies are needed to elucidate the role these amino acids play in the lipid metabolism.

Simulating Silvicultural Treatments Using FIA Data

Treesearch

Christopher W. Woodall; Carl E. Fiedler

2005-01-01

Potential uses of the Forest Inventory and Analysis Database (FIADB) extend far beyond descriptions and summaries of current forest resources. Silvicultural treatments, although typically conducted at the stand level, may be simulated using the FIADB for predicting future forest conditions and resources at broader scales. In this study, silvicultural prescription...

Predicting the Probability of Stand Disturbance

Treesearch

Gregory A. Reams; Joseph M. McCollum

1999-01-01

Forest managers are often interested in identifying and scheduling future stand treatment opportunities. One of the greatest management opportunities is presented following major stand level disturbances that result from natural or anthropogenic forces. Remeasurement data from the Forest Inventory and Analysis (FIA) permanent plot system are used to fit a set of...

Parents' Role in Adolescents' Educational Expectations

ERIC Educational Resources Information Center

Rimkute, Laura; Hirvonen, Riikka; Tolvanen, Asko; Aunola, Kaisa; Nurmi, Jari-Erik

2012-01-01

The present study examined the extent to which mothers' and fathers' expectations for their offspring's future education, their level of education, and adolescents' academic achievement predict adolescents' educational expectations. To investigate this, 230 adolescents were examined twice while they were in comprehensive school (in the 7th and 9th…

Climate control of terrestrial carbon exchange across biomes and continents

Treesearch

Chuixiang Yi; Daniel Ricciuto; Runze Li; John Wolbeck; Xiyan Xu; Mats Nilsson; John Frank; William J. Massman

2010-01-01

Understanding the relationships between climate and carbon exchange by terrestrial ecosystems is critical to predict future levels of atmospheric carbon dioxide because of the potential accelerating effects of positive climate-carbon cycle feedbacks. However, directly observed relationships between climate and terrestrial CO2 exchange with the atmosphere across biomes...

Comparison of Two Analysis Approaches for Measuring Externalized Mental Models

ERIC Educational Resources Information Center

Al-Diban, Sabine; Ifenthaler, Dirk

2011-01-01

Mental models are basic cognitive constructs that are central for understanding phenomena of the world and predicting future events. Our comparison of two analysis approaches, SMD and QFCA, for measuring externalized mental models reveals different levels of abstraction and different perspectives. The advantages of the SMD include possibilities…

76 FR 4092 - Fisheries of the South Atlantic and Gulf of Mexico; South Atlantic Fishery Management Council...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-24

... reports, and discuss methodologies for predicting future catch levels for use in amendment analyses. The...: February 15, 2011: 9 a.m.-5 p.m. and February 16, 2011: 9 a.m.-1 p.m. The SSC's Social and Economics Panel...

A Report by the Air Pollution Committee

ERIC Educational Resources Information Center

Kirkpatrick, Lane

1972-01-01

Description of a Symposium on Air Resource Protection and the Environment,'' held at the 1972 Environmental Health Conference and Exposition. Reports included a mathematical model for predicting future levels of air pollution, evaluation and identification of transportation controls, and a panel discussion of points raised by the speakers. (LK)

Death anxiety as a predictor of future time orientation among individuals with spinal cord injuries.

PubMed

Martz, E; Livneh, H

2003-09-16

The purpose of this study was to examine the relationship between death anxiety and future time orientation among individuals who sustained spinal cord injuries (SCI). Participants were 317 individuals with SCI, of whom 57.4% were US veterans. Data were obtained by means of mailed questionnaires and included responses to the Death Anxiety Scale (DAS), the Future Time Orientation (FTOS) measure, as well as information on participants' personal and disability-related characteristics. A hierarchical multiple regression analysis was conducted to examine the influence of a set of demographic variables, followed by a set of disability-related variables, and finally two factorially-derived measures of death anxiety (denial of death and distressed awareness of death) on future time orientation. Two disability-related variables (pain level and existence of pressure ulcers) and one of the two death anxiety measures (distressed awareness of death) significantly predicted future time orientation. A post-hoc analysis, adding depression as a predictor, was also significant, indicating that an increased level of depression uniquely contributed to a truncated future time orientation. Distressed anxiety and depression may be important factors affecting goals and plans of people with SCI. Future research should attempt to clarify the intricate relationships among negative affectivity, future time orientation, and psychosocial adaptation to SCI.

Potential for shoreline changes due to sea-level rise along the U.S. mid-Atlantic region

USGS Publications Warehouse

Gutierrez, Benjamin T.; Williams, S. Jeffress; Thieler, E. Robert

2007-01-01

Sea-level rise over the next century is expected to contribute significantly to physical changes along open-ocean shorelines. Predicting the form and magnitude of coastal changes is important for understanding the impacts to humans and the environment. Presently, the ability to predict coastal changes is limited by the scientific understanding of the many variables and processes involved in coastal change, and the lack of consensus regarding the validity of existing conceptual, analytical, or numerical models. In order to assess potential future coastal changes in the mid-Atlantic U.S. for the U.S. Climate Change Science Program (CCSP), a workshop was convened by the U.S. Geological Survey. Assessments of future coastal change were made by a committee of coastal scientists with extensive professional experience in the mid-Atlantic region. Thirteen scientists convened for a two-day meeting to exchange information and develop a consensus opinion on potential future coastal changes for the mid-Atlantic coast in response to sea-level rise. Using criteria defined in past work, the mid-Atlantic coast was divided into four geomorphic compartments: spits, headlands, wave-dominated barriers, and mixed-energy barriers. A range of potential coastal responses was identified for each compartment based on four sea-level rise scenarios. The four scenarios were based on the assumptions that: a) the long-term sea-level rise rate observed over the 20th century would persist over the 21st century, b) the 20th century rate would increase by 2 mm/yr, c) the 20th century rate would increase by 7 mm/yr, or d) sea-level would rise by 2 m over the next few hundred years. Potential responses to these sea-level rise scenarios depend on the landforms that occur within a region and include increased likelihood for erosion and shoreline retreat for all coastal types, increased likelihood for erosion, overwash and inlet breaching for barrier islands, as well as the possibility of a threshold state (e.g., dramatic change in barrier evolution, such as segmentation or disintegration) for some barrier island systems. The likelihood of the potential coastal responses is expressed using standard terminology employed in climate change assessments (e.g., as used by the Intergovernmental Panel on Climate Change and CCSP). This assessment was based on the coastal geomorphology in its present condition and does not consider any coastal protection that might be undertaken in the future. The committee recognized that a variety of erosion mitigation measures have been implemented along developed portions of the coast and these are very likely to be applied in the future. It was also acknowledged that economics, political will, and other factors can drive decisions to implement these measures, and that such decisions cannot be predicted with confidence. The results of this assessment are depicted graphically on maps of the study area.

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.

High Pressure Regenerative Turbine Engine: 21st Century Propulsion

NASA Technical Reports Server (NTRS)

Lear, W. E.; Laganelli, A. L.; Senick, Paul (Technical Monitor)

2001-01-01

A novel semi-closed cycle gas turbine engine was demonstrated and was found to meet the program goals. The proof-of-principle test of the High Pressure Regenerative Turbine Engine produced data that agreed well with models, enabling more confidence in designing future prototypes based on this concept. Emission levels were significantly reduced as predicted as a natural attribute of this power cycle. Engine testing over a portion of the operating range allowed verification of predicted power increases compared to the baseline.

Predicting Effects of Water Regime Changes on Waterbirds: Insights from Staging Swans

PubMed Central

Nolet, Bart A.; Gyimesi, Abel; van Krimpen, Roderick R. D.; de Boer, Willem F.; Stillman, Richard A.

2016-01-01

Predicting the environmental impact of a proposed development is notoriously difficult, especially when future conditions fall outside the current range of conditions. Individual-based approaches have been developed and applied to predict the impact of environmental changes on wintering and staging coastal bird populations. How many birds make use of staging sites is mostly determined by food availability and accessibility, which in the case of many waterbirds in turn is affected by water level. Many water systems are regulated and water levels are maintained at target levels, set by management authorities. We used an individual-based modelling framework (MORPH) to analyse how different target water levels affect the number of migratory Bewick’s swans Cygnus columbianus bewickii staging at a shallow freshwater lake (Lauwersmeer, the Netherlands) in autumn. As an emerging property of the model, we found strong non-linear responses of swan usage to changes in water level, with a sudden drop in peak numbers as well as bird-days with a 0.20 m rise above the current target water level. Such strong non-linear responses are probably common and should be taken into account in environmental impact assessments. PMID:26862895

Predicting Effects of Water Regime Changes on Waterbirds: Insights from Staging Swans.

PubMed

Nolet, Bart A; Gyimesi, Abel; van Krimpen, Roderick R D; de Boer, Willem F; Stillman, Richard A

2016-01-01

Predicting the environmental impact of a proposed development is notoriously difficult, especially when future conditions fall outside the current range of conditions. Individual-based approaches have been developed and applied to predict the impact of environmental changes on wintering and staging coastal bird populations. How many birds make use of staging sites is mostly determined by food availability and accessibility, which in the case of many waterbirds in turn is affected by water level. Many water systems are regulated and water levels are maintained at target levels, set by management authorities. We used an individual-based modelling framework (MORPH) to analyse how different target water levels affect the number of migratory Bewick's swans Cygnus columbianus bewickii staging at a shallow freshwater lake (Lauwersmeer, the Netherlands) in autumn. As an emerging property of the model, we found strong non-linear responses of swan usage to changes in water level, with a sudden drop in peak numbers as well as bird-days with a 0.20 m rise above the current target water level. Such strong non-linear responses are probably common and should be taken into account in environmental impact assessments.

Insensitivity of evapotranspiration to seasonal rainfall distribution directs climate change impacts at water yield

NASA Astrophysics Data System (ADS)

Montaldo, N.; Oren, R.

2017-12-01

Over the past century, climate change is affecting precipitation regimes across the world. In the Mediterranean regions there is a persistent trend of precipitation and runoff decreases, generating a desertification process. Given the past winter precipitation shifts, the impacts on evapotranspiration (ET) need to be carefully evaluated, and the compelling question is what will be the impact of future climate change scenarios (predicting changes of precipitation and vapor pressure deficit, VPD) on evapotranspiration and water yield? Looking for the key elements of the climate change that are impacting annual ET, we investigate main climate conditions (e.g. precipitation and VPD) and basin physiographic properties contributing to annual ET. We propose a simplified model for annual ET predictions that accounts for the strong meteo seasonality typical of Mediterranean climates, using the steady state assumption of the basin water balance at mean annual scale. We investigate the Sardinia case study because the position of the island of Sardinia in the center of the western Mediterranean Sea basin and its low urbanization and human activity make Sardinia a perfect reference laboratory for Mediterranean hydrologic studies. Sardinian runoff decreased drastically over the 1975-2010 period, with mean yearly runoff reduced by more than 40% compared to the previous 1922-1974 period, and most yearly runoff in the Sardinian basins (70% on average) is produced by winter precipitation due to the seasonality typical of the Mediterranean climate regime. The use of our proposed model allows to predict future ET and water yield using future climate scenarios. We use the future climate scenarios predicted by Global climate models (GCM) in the Fifth Assessment report of the Intergovernmental Panel on Climate Change (IPCC), and we select most reliable models testing the past GCM predictions with historical data. Contrasting shifts of precipitation (both positive and negative) are predicted in the future scenarios by GCMs but these changes will produce significant changes (level of significance > 90%) only in runoff and not in ET. Surprisingly, we show that ET is insensitive to intra-annual rainfall distribution changes, and is insensitive to VPD scenario changes.

Transactional Relations Between Marital Functioning and Depressive Symptoms

PubMed Central

Kouros, Chrystyna D.; Cummings, E. Mark

2012-01-01

The present study investigated dynamic, longitudinal associations between depressive symptoms and marital processes. Two hundred ninety-six couples reported on marital satisfaction, marital conflict, and depressive symptoms yearly for three years. Observational measures of marital conflict were also collected. Results suggested that different domains of marital functioning related to husbands’ versus wives’ symptoms. For husbands, transactional relations between marital satisfaction and depressive symptoms were identified: high levels of depressive symptoms predicted subsequent decreases in marital satisfaction, and decreased marital satisfaction predicted subsequent elevations in symptoms over time. For wives, high levels of marital conflict predicted subsequent elevations in symptoms over time. Cross-partner results indicated that husbands’ depressive symptoms were also related to subsequent declines in wives’ marital satisfaction. Results are discussed with regard to theoretical perspectives on the marital functioning-depression link and directions for future research are outlined. PMID:21219284

Future probabilities of coastal floods in Finland

NASA Astrophysics Data System (ADS)

Pellikka, Havu; Leijala, Ulpu; Johansson, Milla M.; Leinonen, Katri; Kahma, Kimmo K.

2018-04-01

Coastal planning requires detailed knowledge of future flooding risks, and effective planning must consider both short-term sea level variations and the long-term trend. We calculate distributions that combine short- and long-term effects to provide estimates of flood probabilities in 2050 and 2100 on the Finnish coast in the Baltic Sea. Our distributions of short-term sea level variations are based on 46 years (1971-2016) of observations from the 13 Finnish tide gauges. The long-term scenarios of mean sea level combine postglacial land uplift, regionally adjusted scenarios of global sea level rise, and the effect of changes in the wind climate. The results predict that flooding risks will clearly increase by 2100 in the Gulf of Finland and the Bothnian Sea, while only a small increase or no change compared to present-day conditions is expected in the Bothnian Bay, where the land uplift is stronger.

Silent Expectations: Dynamic Causal Modeling of Cortical Prediction and Attention to Sounds That Weren't.

PubMed

Chennu, Srivas; Noreika, Valdas; Gueorguiev, David; Shtyrov, Yury; Bekinschtein, Tristan A; Henson, Richard

2016-08-10

There is increasing evidence that human perception is realized by a hierarchy of neural processes in which predictions sent backward from higher levels result in prediction errors that are fed forward from lower levels, to update the current model of the environment. Moreover, the precision of prediction errors is thought to be modulated by attention. Much of this evidence comes from paradigms in which a stimulus differs from that predicted by the recent history of other stimuli (generating a so-called "mismatch response"). There is less evidence from situations where a prediction is not fulfilled by any sensory input (an "omission" response). This situation arguably provides a more direct measure of "top-down" predictions in the absence of confounding "bottom-up" input. We applied Dynamic Causal Modeling of evoked electromagnetic responses recorded by EEG and MEG to an auditory paradigm in which we factorially crossed the presence versus absence of "bottom-up" stimuli with the presence versus absence of "top-down" attention. Model comparison revealed that both mismatch and omission responses were mediated by increased forward and backward connections, differing primarily in the driving input. In both responses, modeling results suggested that the presence of attention selectively modulated backward "prediction" connections. Our results provide new model-driven evidence of the pure top-down prediction signal posited in theories of hierarchical perception, and highlight the role of attentional precision in strengthening this prediction. Human auditory perception is thought to be realized by a network of neurons that maintain a model of and predict future stimuli. Much of the evidence for this comes from experiments where a stimulus unexpectedly differs from previous ones, which generates a well-known "mismatch response." But what happens when a stimulus is unexpectedly omitted altogether? By measuring the brain's electromagnetic activity, we show that it also generates an "omission response" that is contingent on the presence of attention. We model these responses computationally, revealing that mismatch and omission responses only differ in the location of inputs into the same underlying neuronal network. In both cases, we show that attention selectively strengthens the brain's prediction of the future. Copyright © 2016 Chennu et al.

Adolescents' thoughts about parents' jobs and their importance for adolescents' future orientation.

PubMed

Neblett, Nicole Gardner; Cortina, Kai Schnabel

2006-10-01

The current study examined the relation between adolescents' perceptions of their parents' jobs and their future orientation, and tested the role of parental support. Four hundred and fifteen ninth through twelfth graders were surveyed about their parents' job rewards, self-direction, and stressors, as well as their expectations for employment and education prospects. Results indicate that perceptions of parents' rewards, self-direction, and stress predict how positively or negatively adolescents perceive the future to be. Results also suggest that higher levels of parental support may weaken the association between perceptions and future orientation when adolescents perceive their parents experience unfavorable conditions at work. These results suggest that adolescents' perceptions of parents' jobs have implications for their preparation for adulthood.

Advanced Regional and Decadal Predictions of Coastal Inundation for the U.S. Atlantic and Gulf Coasts

NASA Astrophysics Data System (ADS)

Horton, B. P.; Donnelly, J. P.; Corbett, D. R.; Kemp, A.; Lindeman, K.; Mann, M. E.; Peltier, W. R.; Rahmstorf, S.

2012-12-01

Future inundation of the US Atlantic and Gulf coasts will depend upon both sea-level rise and the intensity and frequency of tropical cyclones, each of which will be affected by climate change. In this proposal, we will employ new interdisciplinary approaches to bring about a step change in the reliability of predictions of such inundation. The rate of sea-level rise along the US Atlantic and Gulf coasts has increased throughout the 20th century. Whilst there is widespread agreement that it continue to accelerate during the 21st century, great uncertainty surrounds its magnitude and geographic distribution. Key uncertainties include the role of continental ice sheets, mountain glaciers and ocean density changes. Insufficient understanding of these complex physical processes precludes accurate prediction of sea-level rise. New approaches using semi-empirical models that relate instrumental records of climate and sea-level rise have projected up to 2 m of sea-level rise by AD 2100. But the time span of instrumental sea-level records is insufficient to adequately constrain the climate:sea-level relationship. Here, we produce new high resolution proxy data of sea-level and temperature to provide crucial additional constraints to such semi-empirical models. Our dataset will span the alternation between the "Medieval Climate Anomaly" and "Little Ice Age". Before the models can provide appropriate data for coastal management and planning, they must be complemented with regional estimates of sea-level rise. Therefore, the proxy sea-level data has been collected from six study areas (Massachusetts, New Jersey, North Carolina, Georgia and Atlantic and Gulf coasts of Florida) to accommodate the required extent of regional variability. In the case of inundation arising from tropical cyclones, the historical and observational records are insufficient for predicting their nature and recurrence, because they are such extreme and rare events. Moreover, in the future, the resultant storm surges will be superimposed on background sea-level rise. To overcome these problems, we couple regional sea-level rise projections with hurricane simulations and storm surge models to map coastal inundation for the current climate and the best and worst case climate scenarios of the IPCC AR4. The products of this proposal will raise the bar for the scientific prediction of region-specific inundation probabilities in terms of coordinated semi-empirical proxy data, hindcast- and forecast-driven sea-level modeling and tropical cyclone forecasting. To optimize transfer of this often complex information for effective adaptive decision-making by managers and planners, we will systematically review >800 adaptation reports and consult early and often with primary endusers to identify their exact needs. We will produce high penetration print and web products for diverse audiences, specific to each region.

Predicting running away in girls who are victims of commercial sexual exploitation.

PubMed

Hershberger, Alexandra R; Sanders, Jasmyn; Chick, Crisanna; Jessup, Megan; Hanlin, Hugh; Cyders, Melissa A

2018-05-01

Youth that are victims of commercial sexual exploitation of children (CSEC) have a host of clinical problems and often run away from home, residential care, and treatment, which complicates and limits treatment effectiveness. No research to date has attempted to predict running away in CSEC victims. The present study aimed to 1) characterize a clinically referred sample of girls who were victims of CSEC and compare them to other high-risk girls (i.e., girls who also have a history of trauma and running away, but deny CSEC); and 2) examine the utility of using the Youth Level of Service/Case Management Inventory (YLS/CMI) to predict future running away. Data were collected from de-identified charts of 80 girls (mean age = 15.38, SD = 1.3, 37.9% White, 52.5% CSEC victims) who were referred for psychological assessment by the Department of Child Services. Girls in the CSEC group were more likely to have experienced sexual abuse (χ 2  = 6.85, p = .009), an STI (χ 2  = 6.45, p = .01), a post-traumatic stress disorder diagnosis (χ 2  = 11.84, p = .001), and a substance use disorder diagnosis (χ 2  = 11.32, p = .001) than high-risk girls. Moderated regression results indicated that YLS/CMI scores significantly predicted future running away among the CSEC group (β = 0.23, SE = .06, p = .02), but not the high-risk group (β = -.008, SE = .11, p =.90). The YLS/CMI shows initial promise for predicting future running away in girls who are CSEC victims. Predicting running away can help identify those at risk for and prevent running away and improve treatment outcomes. We hope current findings stimulate future work in this area. Copyright © 2018 Elsevier Ltd. All rights reserved.

Bidirectional Prospective Associations Between Cardiac Autonomic Activity and Inflammatory Markers.

PubMed

Hu, Mandy Xian; Lamers, Femke; Neijts, Melanie; Willemsen, Gonneke; de Geus, Eco J C; Penninx, Brenda W J H

2018-06-01

Autonomic nervous system (ANS) imbalance has been cross-sectionally associated with inflammatory processes. Longitudinal studies are needed to shed light on the nature of this relationship. We examined cross-sectional and bidirectional prospective associations between cardiac autonomic measures and inflammatory markers. Analyses were conducted with baseline (n = 2823), 2-year (n = 2099), and 6-year (n = 1774) data from the Netherlands Study of Depression and Anxiety. To compare the pattern of results, prospective analyses with ANS (during sleep, leisure time, and work) and inflammation were conducted in two data sets from the Netherlands Twin Register measured for 4.9 years (n = 356) and 5.4 years (n = 472). Autonomic nervous system measures were heart rate (HR) and respiratory sinus arrhythmia (RSA). Inflammatory markers were C-reactive protein (CRP) and interleukin (IL)-6. The Netherlands Study of Depression and Anxiety results showed that higher HR and lower RSA were cross-sectionally significantly associated with higher inflammatory levels. Higher HR predicted higher levels of CRP (B = .065, p < .001) and IL-6 (B = .036, p = .014) at follow-up. Higher CRP levels predicted lower RSA (B = -.024, p = .048) at follow-up. The Netherlands Twin Register results confirmed that higher HR was associated with higher CRP and IL-6 levels 4.9 years later. Higher IL-6 levels predicted higher HR and lower RSA at follow-up. Autonomic imbalance is associated with higher levels of inflammation. Independent data from two studies converge in evidence that higher HR predicts subsequent higher levels of CRP and IL-6. Inflammatory markers may also predict future ANS activity, but evidence for this was less consistent.

Generalized trust predicts young children's willingness to delay gratification.

PubMed

Ma, Fengling; Chen, Biyun; Xu, Fen; Lee, Kang; Heyman, Gail D

2018-05-01

Young children's willingness to delay gratification by forgoing an immediate reward to obtain a more desirable one in the future predicts a wide range of positive social, cognitive, and health outcomes. Standard accounts of this phenomenon have focused on individual differences in cognitive control skills that allow children to engage in goal-oriented behavior, but recent findings suggest that person-specific trust is also important, with children showing a stronger tendency to delay gratification if they have reason to trust the individual who is promising the future reward. The current research builds on those findings by examining generalized trust, which refers to the extent to which others are generally viewed as trustworthy. A total of 150 3- to 5-year-olds in China were tested. Participants were given the opportunity to obtain one sticker immediately, or wait for 15 min for two stickers. Results showed that participants with high levels of generalized trust waited longer even after controlling for age and level of executive function. These results suggest that trust plays a role in delaying gratification even when children have no information about the individual who is promising the future reward. More broadly, the findings build on recent evidence that there is more to delay of gratification than cognitive capacity, and they suggest that there are individual differences in whether children consider sacrificing for a future outcome to be worth the risk. Copyright © 2017 Elsevier Inc. All rights reserved.

DNA methylation of loci within ABCG1 and PHOSPHO1 in blood DNA is associated with future type 2 diabetes risk.

PubMed

Dayeh, Tasnim; Tuomi, Tiinamaija; Almgren, Peter; Perfilyev, Alexander; Jansson, Per-Anders; de Mello, Vanessa D; Pihlajamäki, Jussi; Vaag, Allan; Groop, Leif; Nilsson, Emma; Ling, Charlotte

2016-07-02

Identification of subjects with a high risk of developing type 2 diabetes (T2D) is fundamental for prevention of the disease. Consequently, it is essential to search for new biomarkers that can improve the prediction of T2D. The aim of this study was to examine whether 5 DNA methylation loci in blood DNA (ABCG1, PHOSPHO1, SOCS3, SREBF1, and TXNIP), recently reported to be associated with T2D, might predict future T2D in subjects from the Botnia prospective study. We also tested if these CpG sites exhibit altered DNA methylation in human pancreatic islets, liver, adipose tissue, and skeletal muscle from diabetic vs. non-diabetic subjects. DNA methylation at the ABCG1 locus cg06500161 in blood DNA was associated with an increased risk for future T2D (OR = 1.09, 95% CI = 1.02-1.16, P-value = 0.007, Q-value = 0.018), while DNA methylation at the PHOSPHO1 locus cg02650017 in blood DNA was associated with a decreased risk for future T2D (OR = 0.85, 95% CI = 0.75-0.95, P-value = 0.006, Q-value = 0.018) after adjustment for age, gender, fasting glucose, and family relation. Furthermore, the level of DNA methylation at the ABCG1 locus cg06500161 in blood DNA correlated positively with BMI, HbA1c, fasting insulin, and triglyceride levels, and was increased in adipose tissue and blood from the diabetic twin among monozygotic twin pairs discordant for T2D. DNA methylation at the PHOSPHO1 locus cg02650017 in blood correlated positively with HDL levels, and was decreased in skeletal muscle from diabetic vs. non-diabetic monozygotic twins. DNA methylation of cg18181703 (SOCS3), cg11024682 (SREBF1), and cg19693031 (TXNIP) was not associated with future T2D risk in subjects from the Botnia prospective study.

Does Childhood Attention-Deficit/Hyperactivity Disorder (ADHD) Predict Levels of Depressive Symptoms during Emerging Adulthood?

PubMed Central

Meinzer, Michael C.; Pettit, Jeremy W.; Waxmonsky, James G.; Gnagy, Elizabeth; Molina, Brooke S.G.; Pelham, William E.

2015-01-01

Little is known about the development and course of depressive symptoms through emerging adulthood among individuals with a childhood history of attention-deficit/hyperactivity disorder (ADHD). The aim of this study was to examine if a history of ADHD in childhood significantly predicted depressive symptoms during emerging adulthood (i.e., ages 18–25 years), including the initial level of depressive symptoms, continued levels of depressive symptoms at each age year, and the rate of change in depressive symptoms over time. 394 participants (205 with ADHD and 189 without ADHD; 348 males and 46 females) drawn from the Pittsburgh ADHD Longitudinal Study (PALS) completed annual self-ratings of depressive symptoms between the ages of 18 and 25 years. Childhood history of ADHD significantly predicted a higher initial level of depressive symptoms at age 18, and higher levels of depressive symptoms at every age year during emerging adulthood. ADHD did not significantly predict the rate of change in depressive symptoms from age 18 to age 25. Childhood history of ADHD remained a significant predictor of initial level of depressive symptoms at age 18 after controlling for comorbid psychiatric diagnoses, but not after controlling for concurrent ADHD symptoms and psychosocial impairment. Participants with childhood histories of ADHD experienced significantly higher levels of depressive symptoms than non-ADHD comparison participants by age 18 and continued to experience higher, although not increasing, levels of depressive symptoms through emerging adulthood. Clinical implications and directions for future research are discussed. PMID:26272531

Skilful prediction of Sahel summer rainfall on inter-annual and multi-year timescales

PubMed Central

Sheen, K. L.; Smith, D. M.; Dunstone, N. J.; Eade, R.; Rowell, D. P.; Vellinga, M.

2017-01-01

Summer rainfall in the Sahel region of Africa exhibits one of the largest signals of climatic variability and with a population reliant on agricultural productivity, the Sahel is particularly vulnerable to major droughts such as occurred in the 1970s and 1980s. Rainfall levels have subsequently recovered, but future projections remain uncertain. Here we show that Sahel rainfall is skilfully predicted on inter-annual and multi-year (that is, >5 years) timescales and use these predictions to better understand the driving mechanisms. Moisture budget analysis indicates that on multi-year timescales, a warmer north Atlantic and Mediterranean enhance Sahel rainfall through increased meridional convergence of low-level, externally sourced moisture. In contrast, year-to-year rainfall levels are largely determined by the recycling rate of local moisture, regulated by planetary circulation patterns associated with the El Niño-Southern Oscillation. Our findings aid improved understanding and forecasting of Sahel drought, paramount for successful adaptation strategies in a changing climate. PMID:28541288

The (un)reliability of item-level semantic priming effects.

PubMed

Heyman, Tom; Bruninx, Anke; Hutchison, Keith A; Storms, Gert

2018-04-05

Many researchers have tried to predict semantic priming effects using a myriad of variables (e.g., prime-target associative strength or co-occurrence frequency). The idea is that relatedness varies across prime-target pairs, which should be reflected in the size of the priming effect (e.g., cat should prime dog more than animal does). However, it is only insightful to predict item-level priming effects if they can be measured reliably. Thus, in the present study we examined the split-half and test-retest reliabilities of item-level priming effects under conditions that should discourage the use of strategies. The resulting priming effects proved extremely unreliable, and reanalyses of three published priming datasets revealed similar cases of low reliability. These results imply that previous attempts to predict semantic priming were unlikely to be successful. However, one study with an unusually large sample size yielded more favorable reliability estimates, suggesting that big data, in terms of items and participants, should be the future for semantic priming research.

Oil & War: Revisiting M. King Hubbert's predictions.

NASA Astrophysics Data System (ADS)

Nur, A. M.

2003-12-01

Oil is, unlike almost any other natural resource on earth, not only finite but also irreversibly consumed. At the same time worldwide data shows that at least at present and for the foreseeable future oil consumption rate is directly proportional to the national standard of living. In 1956 and again in 1962, M. King Hubbert predicted, using a simple model based on the logistic equation, that oil production in the lower 48 United States will follow a bell shaped curve with a production peak around the year 1971 and a production level of ~ 3 billion barrels per year, followed by a rapid decline. While his model approach was ridiculed at the time production data to date reveals a remarkable agreement with this prediction: US oil production did peak in 1971 at a level of 3.2.10 barrels a day and has been declining ever since. M. King Hubbert similarly estimated also the future of oil production worldwide - predicting peak production sometime between 1995-2010 (now!) at a level of 25 to 35 billion barrels per year. Current worldwide production is ~ 27 billion barrels per year. Thus because about half of the oil in earth has already been discovered, the world is destined to face more and bigger conflicts over the control of global supplies. Although many economists and political scientists tend to dismiss the significance of Hubbert's thinking about the finiteness of recoverable oil as well as the consequent implications, it appears that without careful management these conflicts could turn into wars much bigger than in Kuwait in 1991 or in Iraq in 2003. It is therefore imperative for us as earth scientist to try to educate the public and our leaders about the basic geological reality of finite fossil energy resources, and the serious consequences of this fact.

Development of an internet based system for modeling biotin metabolism using Bayesian networks.

PubMed

Zhou, Jinglei; Wang, Dong; Schlegel, Vicki; Zempleni, Janos

2011-11-01

Biotin is an essential water-soluble vitamin crucial for maintaining normal body functions. The importance of biotin for human health has been under-appreciated but there is plenty of opportunity for future research with great importance for human health. Currently, carrying out predictions of biotin metabolism involves tedious manual manipulations. In this paper, we report the development of BiotinNet, an internet based program that uses Bayesian networks to integrate published data on various aspects of biotin metabolism. Users can provide a combination of values on the levels of biotin related metabolites to obtain the predictions on other metabolites that are not specified. As an inherent feature of Bayesian networks, the uncertainty of the prediction is also quantified and reported to the user. This program enables convenient in silico experiments regarding biotin metabolism, which can help researchers design future experiments while new data can be continuously incorporated. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Longitudinal motor performance development in early adolescence and its relationship to adult success: An 8-year prospective study of highly talented soccer players

PubMed Central

Kelava, Augustin; Raabe, Johannes; Höner, Oliver

2018-01-01

Several talent identification and development (TID) programs in soccer have implemented diagnostics to measure players’ motor performance. Yet, there is a lack of research investigating the relationship between motor development in adolescence and future, adult performance. This longitudinal study analyzed the three-year development of highly talented young soccer players’ speed abilities and technical skills and examined the relevance of this development to their adult success. The current research sample consisted of N = 1,134 players born between 1993 and 1995 who were selected for the German Soccer Association’s TID program and participated in nationwide motor diagnostics (sprinting, agility, dribbling, ball control, shooting) four times between the Under 12 (U12) and Under 15 (U15) age class. Relative age (RA) was assessed for all players, and a total motor score was calculated based on performances in the individual tests. In order to investigate players’ future success, participants were divided into two groups according to their adult performance level (APL) in the 2014/2015 season: Elite (1st-5th German division; N = 145, 12.8%) and non-elite players (lower divisions; N = 989, 87.2%). Using multilevel regression analyses each motor performance was predicted by Time, Time2 (level-1 predictors), APL, and RA (level-2 covariates) with simultaneous consideration for interaction effects between the respective variables. Time and Time2 were significant predictors for each test performance. A predictive value for RA was confirmed for sprinting and the total motor score. A significant relationship between APL and the motor score as well as between APL and agility, dribbling, ball control, and shooting emerged. Interaction effects distinctly failed to reach significance. The study found a non-linear improvement in players’ performance for all considered motor performance factors over a three-year period from early to middle adolescence. While their predictive value for future success was confirmed by a significant relationship between APL and most of the considered factors, there was no significant interaction between APL and Time. These findings indicate that future elite players had already been better at the beginning of the TID program and maintained this high level throughout their promotion from U12 to U15. PMID:29723200

Longitudinal motor performance development in early adolescence and its relationship to adult success: An 8-year prospective study of highly talented soccer players.

PubMed

Leyhr, Daniel; Kelava, Augustin; Raabe, Johannes; Höner, Oliver

2018-01-01

Several talent identification and development (TID) programs in soccer have implemented diagnostics to measure players' motor performance. Yet, there is a lack of research investigating the relationship between motor development in adolescence and future, adult performance. This longitudinal study analyzed the three-year development of highly talented young soccer players' speed abilities and technical skills and examined the relevance of this development to their adult success. The current research sample consisted of N = 1,134 players born between 1993 and 1995 who were selected for the German Soccer Association's TID program and participated in nationwide motor diagnostics (sprinting, agility, dribbling, ball control, shooting) four times between the Under 12 (U12) and Under 15 (U15) age class. Relative age (RA) was assessed for all players, and a total motor score was calculated based on performances in the individual tests. In order to investigate players' future success, participants were divided into two groups according to their adult performance level (APL) in the 2014/2015 season: Elite (1st-5th German division; N = 145, 12.8%) and non-elite players (lower divisions; N = 989, 87.2%). Using multilevel regression analyses each motor performance was predicted by Time, Time2 (level-1 predictors), APL, and RA (level-2 covariates) with simultaneous consideration for interaction effects between the respective variables. Time and Time2 were significant predictors for each test performance. A predictive value for RA was confirmed for sprinting and the total motor score. A significant relationship between APL and the motor score as well as between APL and agility, dribbling, ball control, and shooting emerged. Interaction effects distinctly failed to reach significance. The study found a non-linear improvement in players' performance for all considered motor performance factors over a three-year period from early to middle adolescence. While their predictive value for future success was confirmed by a significant relationship between APL and most of the considered factors, there was no significant interaction between APL and Time. These findings indicate that future elite players had already been better at the beginning of the TID program and maintained this high level throughout their promotion from U12 to U15.

Prognostic value of choline and betaine depends on intestinal microbiota-generated metabolite trimethylamine-N-oxide.

PubMed

Wang, Zeneng; Tang, W H Wilson; Buffa, Jennifer A; Fu, Xiaoming; Britt, Earl B; Koeth, Robert A; Levison, Bruce S; Fan, Yiying; Wu, Yuping; Hazen, Stanley L

2014-04-01

Recent metabolomics and animal model studies show trimethylamine-N-oxide (TMAO), an intestinal microbiota-dependent metabolite formed from dietary trimethylamine-containing nutrients such as phosphatidylcholine (PC), choline, and carnitine, is linked to coronary artery disease pathogenesis. Our aim was to examine the prognostic value of systemic choline and betaine levels in stable cardiac patients. We examined the relationship between fasting plasma choline and betaine levels and risk of major adverse cardiac events (MACE = death, myocardial infraction, stroke) in relation to TMAO over 3 years of follow-up in 3903 sequential stable subjects undergoing elective diagnostic coronary angiography. In our study cohort, median (IQR) TMAO, choline, and betaine levels were 3.7 (2.4-6.2)μM, 9.8 (7.9-12.2)μM, and 41.1 (32.5-52.1)μM, respectively. Modest but statistically significant correlations were noted between TMAO and choline (r = 0.33, P < 0.001) and less between TMAO and betaine (r = 0.09, P < 0.001). Higher plasma choline and betaine levels were associated with a 1.9-fold and 1.4-fold increased risk of MACE, respectively (Quartiles 4 vs. 1; P < 0.01, each). Following adjustments for traditional cardiovascular risk factors and high-sensitivity C-reactive protein, elevated choline [1.34 (1.03-1.74), P < 0.05], and betaine levels [1.33 (1.03-1.73), P < 0.05] each predicted increased MACE risk. Neither choline nor betaine predicted MACE risk when TMAO was added to the adjustment model, and choline and betaine predicted future risk for MACE only when TMAO was elevated. Elevated plasma levels of choline and betaine are each associated with incident MACE risk independent of traditional risk factors. However, high choline and betaine levels are only associated with higher risk of future MACE with concomitant increase in TMAO.

Prognostic value of choline and betaine depends on intestinal microbiota-generated metabolite trimethylamine-N-oxide

PubMed Central

Wang, Zeneng; Tang, W. H. Wilson; Buffa, Jennifer A.; Fu, Xiaoming; Britt, Earl B.; Koeth, Robert A.; Levison, Bruce S.; Fan, Yiying; Wu, Yuping; Hazen, Stanley L.

2014-01-01

Aims Recent metabolomics and animal model studies show trimethylamine-N-oxide (TMAO), an intestinal microbiota-dependent metabolite formed from dietary trimethylamine-containing nutrients such as phosphatidylcholine (PC), choline, and carnitine, is linked to coronary artery disease pathogenesis. Our aim was to examine the prognostic value of systemic choline and betaine levels in stable cardiac patients. Methods and results We examined the relationship between fasting plasma choline and betaine levels and risk of major adverse cardiac events (MACE = death, myocardial infraction, stroke) in relation to TMAO over 3 years of follow-up in 3903 sequential stable subjects undergoing elective diagnostic coronary angiography. In our study cohort, median (IQR) TMAO, choline, and betaine levels were 3.7 (2.4–6.2)μM, 9.8 (7.9–12.2)μM, and 41.1 (32.5–52.1)μM, respectively. Modest but statistically significant correlations were noted between TMAO and choline (r = 0.33, P < 0.001) and less between TMAO and betaine (r = 0.09, P < 0.001). Higher plasma choline and betaine levels were associated with a 1.9-fold and 1.4-fold increased risk of MACE, respectively (Quartiles 4 vs. 1; P < 0.01, each). Following adjustments for traditional cardiovascular risk factors and high-sensitivity C-reactive protein, elevated choline [1.34 (1.03–1.74), P < 0.05], and betaine levels [1.33 (1.03–1.73), P < 0.05] each predicted increased MACE risk. Neither choline nor betaine predicted MACE risk when TMAO was added to the adjustment model, and choline and betaine predicted future risk for MACE only when TMAO was elevated. Conclusion Elevated plasma levels of choline and betaine are each associated with incident MACE risk independent of traditional risk factors. However, high choline and betaine levels are only associated with higher risk of future MACE with concomitant increase in TMAO. PMID:24497336

Does the nature of schools matter? An exploration of selected school ecology factors on adolescent perceptions of school connectedness.

PubMed

Waters, Stacey; Cross, Donna; Shaw, Therese

2010-09-01

Connectedness to school is a significant predictor of adolescent health and academic outcomes. While individual predictors of connectedness have been well-described, little is known about school-level factors which may influence connectedness. A school's ecology, or its structural, functional, and built aspects, coupled with interpersonal interactions, may also help to enhance adolescent connectedness. This study aims to identify school ecological characteristics which predict enhanced connectedness in secondary school. Data from 5,159 Grade 8 students (12-13 years) from 39 randomly selected schools were tracked until the end of Grade 9 (13-14 years). Students' self-reported school, teacher, and family connectedness, mental health and peer relationships were measured at two time points. Accounting for school-level clustering, student- and school-level ecological characteristics were modelled on self-reported school connectedness in Grades 8 and 9. Students' higher school connectedness in Grades 8 and 9 was influenced by greater levels of family connectedness, fewer classroom and peer problems, less difficult secondary school transition, fewer emotional problems, and greater prosocial skills. Seven school-level ecological variables were significantly associated with school connectedness after controlling for student-level predictors. At the school-level, priority for pastoral care and students' aggregated writing skills scores significantly predicted concurrent and future enhanced connectedness. Interventions to improve students' school connectedness should address individual student characteristics and school functional features such as pastoral care strategies and helping students to achieve greater academic outcomes. Future studies should focus on the cumulative longitudinal influence of school ecological and student-level predictors of school connectedness.

Time series analysis of malaria in Afghanistan: using ARIMA models to predict future trends in incidence.

PubMed

Anwar, Mohammad Y; Lewnard, Joseph A; Parikh, Sunil; Pitzer, Virginia E

2016-11-22

Malaria remains endemic in Afghanistan. National control and prevention strategies would be greatly enhanced through a better ability to forecast future trends in disease incidence. It is, therefore, of interest to develop a predictive tool for malaria patterns based on the current passive and affordable surveillance system in this resource-limited region. This study employs data from Ministry of Public Health monthly reports from January 2005 to September 2015. Malaria incidence in Afghanistan was forecasted using autoregressive integrated moving average (ARIMA) models in order to build a predictive tool for malaria surveillance. Environmental and climate data were incorporated to assess whether they improve predictive power of models. Two models were identified, each appropriate for different time horizons. For near-term forecasts, malaria incidence can be predicted based on the number of cases in the four previous months and 12 months prior (Model 1); for longer-term prediction, malaria incidence can be predicted using the rates 1 and 12 months prior (Model 2). Next, climate and environmental variables were incorporated to assess whether the predictive power of proposed models could be improved. Enhanced vegetation index was found to have increased the predictive accuracy of longer-term forecasts. Results indicate ARIMA models can be applied to forecast malaria patterns in Afghanistan, complementing current surveillance systems. The models provide a means to better understand malaria dynamics in a resource-limited context with minimal data input, yielding forecasts that can be used for public health planning at the national level.

First Trimester Urine and Serum Metabolomics for Prediction of Preeclampsia and Gestational Hypertension: A Prospective Screening Study.

PubMed

Austdal, Marie; Tangerås, Line H; Skråstad, Ragnhild B; Salvesen, Kjell; Austgulen, Rigmor; Iversen, Ann-Charlotte; Bathen, Tone F

2015-09-08

Hypertensive disorders of pregnancy, including preeclampsia, are major contributors to maternal morbidity. The goal of this study was to evaluate the potential of metabolomics to predict preeclampsia and gestational hypertension from urine and serum samples in early pregnancy, and elucidate the metabolic changes related to the diseases. Metabolic profiles were obtained by nuclear magnetic resonance spectroscopy of serum and urine samples from 599 women at medium to high risk of preeclampsia (nulliparous or previous preeclampsia/gestational hypertension). Preeclampsia developed in 26 (4.3%) and gestational hypertension in 21 (3.5%) women. Multivariate analyses of the metabolic profiles were performed to establish prediction models for the hypertensive disorders individually and combined. Urinary metabolomic profiles predicted preeclampsia and gestational hypertension at 51.3% and 40% sensitivity, respectively, at 10% false positive rate, with hippurate as the most important metabolite for the prediction. Serum metabolomic profiles predicted preeclampsia and gestational hypertension at 15% and 33% sensitivity, respectively, with increased lipid levels and an atherogenic lipid profile as most important for the prediction. Combining maternal characteristics with the urinary hippurate/creatinine level improved the prediction rates of preeclampsia in a logistic regression model. The study indicates a potential future role of clinical importance for metabolomic analysis of urine in prediction of preeclampsia.

Sputum-to-serum hydrogen sulfide ratio as a novel biomarker of predicting future risks of asthma exacerbation.

PubMed

Suzuki, Yasuhito; Saito, Junpei; Kikuchi, Masami; Uematsu, Manabu; Fukuhara, Atsuro; Sato, Suguru; Munakata, Mitsuru

2018-05-14

Increased level of hydrogen sulfide (H 2 S) in sputum is reported to be a new biomarker of neutrophilic airway inflammation in chronic airway disorders. However, the relationship between H 2 S and disease activity remains unclear. We investigated whether H 2 S levels could vary during different conditions in asthma. H 2 S levels in sputum and serum were measured using a sulfide-sensitive electrode in 47 stable asthmatic subjects (S-BA), 21 uncontrolled asthmatic subjects (UC-BA), 26 asthmatic subjects with acute exacerbation (AE-BA), and 15 healthy subjects. Of these, H 2 S levels during stable, as well as exacerbation states were obtained in 13 asthmatic subjects. Sputum H 2 S levels were significantly higher in the AE-BA subjects compared to the UC-BA and healthy subjects (p<0.05). However, serum H 2 S levels in the AE-BA subjects were lower than in the S-BA subjects (p<0.001) and similar to those in healthy subjects. Thus, the sputum-to-serum ratio of H 2 S (H 2 S ratio) in the AE-BA subjects was significantly higher than in the S-BA, UC-BA and healthy subjects (p<0.05). Among all subjects, sputum H 2 S levels showed a trend to decrease with FEV 1% predicted, and significantly positive correlations with sputum neutrophils (%), sputum IL-8, and serum IL-8. A multiple linear regression analysis showed that sputum H 2 S was independently associated with increased sputum neutrophils (%) and decreased FEV 1% predicted (p<0.05) The cut-off level of H 2 S ratio to indicate an exacerbation was ≥0.34 (area under the curve; 0.88, with a sensitivity of 81.8% and specificity of 72.7%, p<0.001). Furthermore, half of the asthmatic subjects with H 2 S ratios higher than the cutoff level experienced asthma exacerbations over the following 3 months after enrollment. The H 2 S ratio may provide useful information on predicting future risks of asthma exacerbation, as well as on obstructive neutrophilic airway inflammation as one of the non-Th2 biomarkers, in asthma. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

The relationship between separation anxiety and impairment

PubMed Central

Foley, Debra L; Rowe, Richard; Maes, Hermine; Silberg, Judy; Eaves, Lindon; Pickles, Andrew

2009-01-01

The goal of this study was to characterize the contemporaneous and prognostic relationship between symptoms of separation anxiety disorder (SAD) and associated functional impairment. The sample comprised n=2067 8–16 year-old twins from a community-based registry. Juvenile subjects and their parents completed a personal interview on two occasions, separated by an average follow-up period of 18 months, about the subject’s current history of SAD and associated functional impairment. Results showed that SAD symptoms typically caused very little impairment but demonstrated significant continuity over time. Older youth had significantly more persistent symptoms than younger children. Prior symptom level independently predicted future symptom level and diagnostic symptom threshold, with and without impairment. Neither diagnostic threshold nor severity of impairment independently predicted outcomes after taking account of prior symptom levels. The results indicate that impairment may index current treatment need but symptom levels provide the best information about severity and prognosis. PMID:17658718

Background Noise Analysis in a Few-Photon-Level Qubit Memory

NASA Astrophysics Data System (ADS)

Mittiga, Thomas; Kupchak, Connor; Jordaan, Bertus; Namazi, Mehdi; Nolleke, Christian; Figeroa, Eden

2014-05-01

We have developed an Electromagnetically Induced Transparency based polarization qubit memory. The device is composed of a dual-rail probe field polarization setup colinear with an intense control field to store and retrieve any arbitrary polarization state by addressing a Λ-type energy level scheme in a 87Rb vapor cell. To achieve a signal-to-background ratio at the few photon level sufficient for polarization tomography of the retrieved state, the intense control field is filtered out through an etalon filtrating system. We have developed an analytical model predicting the influence of the signal-to-background ratio on the fidelities and compared it to experimental data. Experimentally measured global fidelities have been found to follow closely the theoretical prediction as signal-to-background decreases. These results suggest the plausibility of employing room temperature memories to store photonic qubits at the single photon level and for future applications in long distance quantum communication schemes.

Sub-Doppler Rovibrational Spectroscopy of the H_3^+ Cation and Isotopologues

NASA Astrophysics Data System (ADS)

Markus, Charles R.; McCollum, Jefferson E.; Dieter, Thomas S.; Kocheril, Philip A.; McCall, Benjamin J.

2017-06-01

Molecular ions play a central role in the chemistry of the interstellar medium (ISM) and act as benchmarks for state of the art ab initio theory. The molecular ion H_3^+ initiates a chain of ion-neutral reactions which drives chemistry in the ISM, and observing it either directly or indirectly through its isotopologues is valuable for understanding interstellar chemistry. Improving the accuracy of laboratory measurements will assist future astronomical observations. H_3^+ is also one of a few systems whose rovibrational transitions can be predicted to spectroscopic accuracy (<1 cm^{-1}), and with careful treatment of adiabatic, nonadiabatic, and quantum electrodynamic corrections to the potential energy surface, predictions of low lying rovibrational states can rival the uncertainty of experimental measurements New experimental data will be needed to benchmark future treatment of these corrections. Previously we have reported 26 transitions within the fundamental band of H_3^+ with MHz-level uncertainties. With recent improvements to our overall sensitivity, we have expanded this survey to include additional transitions within the fundamental band and the first hot band. These new data will ultimately be used to predict ground state rovibrational energy levels through combination differences which will act as benchmarks for ab initio theory and predict forbidden rotational transitions of H_3^+. We will also discuss progress in measuring rovibrational transitions of the isotopologues H_2D^+ and D_2H^+, which will be used to assist in future THz astronomical observations. New experimental data will be needed to benchmark future treatment of these corrections. J. N. Hodges, A. J. Perry, P. A. Jenkins II, B. M. Siller, and B. J. McCall, J. Chem. Phys. (2013), 139, 164201. A. J. Perry, J. N. Hodges, C. R. Markus, G. S. Kocheril, and B. J. McCall, J. Mol. Spectrosc. (2015), 317, 71-73. A. J. Perry, C. R. Markus, J. N. Hodges, G. S. Kocheril, and B. J. McCall, 71st International Symposium on Molecular Spectroscopy (2016), MH03. C. R. Markus, A. J. Perry, J. N. Hodges, and B. J. McCall, Opt. Express (2017), 25, 3709-3721.

If We Can't Predict Solar Cycle 24, What About Solar Cycle 34?

NASA Technical Reports Server (NTRS)

Pesnell. William Dean

2008-01-01

Predictions of solar activity in Solar Cycle 24 range from 50% larger than SC 23 to the onset of a Grand Minimum. Because low levels of solar activity are associated with global cooling in paleoclimate and isotopic records, anticipating these extremes is required in any longterm extrapolation of climate variability. Climate models often look forward 100 or more years, which would mean 10 solar cycles into the future. Predictions of solar activity are derived from a number of methods, most of which, such as climatology and physics-based models, will be familiar to atmospheric scientists. More than 50 predictions of the maximum amplitude of SC 24 published before solar minimum will be discussed. Descriptions of several methods that result in the extreme predictions and some anticipation of even longer term predictions will be presented.

Future irrigation expansion outweigh groundwater recharge gains from climate change in semi-arid India.

PubMed

Sishodia, Rajendra P; Shukla, Sanjay; Wani, Suhas P; Graham, Wendy D; Jones, James W

2018-09-01

Simultaneous effects of future climate and irrigation intensification on surface and groundwater systems are not well understood. Efforts are needed to understand the future groundwater availability and associated surface flows under business-as-usual management to formulate policy changes to improve water sustainability. We combine measurements with integrated modeling (MIKE SHE/MIKE11) to evaluate the effects of future climate (2040-2069), with and without irrigation expansion, on water levels and flows in an agricultural watershed in low-storage crystalline aquifer region of south India. Demand and supply management changes, including improved efficiency of irrigation water as well as energy uses, were evaluated. Increased future rainfall (7-43%, from 5 Global Climate Models) with no further expansion of irrigation wells increased the groundwater recharge (10-55%); however, most of the recharge moved out of watershed as increased baseflow (17-154%) with a small increase in net recharge (+0.2mm/year). When increased rainfall was considered with projected increase in irrigation withdrawals, both hydrologic extremes of well drying and flooding were predicted. A 100-year flow event was predicted to be a 5-year event in the future. If irrigation expansion follows the historical trends, earlier and more frequent well drying, a source of farmers' distress in India, was predicted to worsen in the future despite the recharge gains from increased rainfall. Storage and use of excess flows, improved irrigation efficiency with flood to drip conversion in 25% of irrigated area, and reduced energy subsidy (free electricity for 3.5h compared to 7h/day; $1 billion savings) provided sufficient water savings to support future expansion in irrigated areas while mitigating well drying as well as flooding. Reductions in energy subsidy to fund the implementation of economically desirable (high benefit-cost ratio) demand (drip irrigation) and supply (water capture and storage) management was recommended to achieve a sustainable food-water-energy nexus in semi-arid regions. Copyright © 2018 Elsevier B.V. All rights reserved.

Climate, CO2, and demographic impacts on global wildfire emissions

NASA Astrophysics Data System (ADS)

Knorr, W.; Jiang, L.; Arneth, A.

2015-09-01

Wildfires are by far the largest contributor to global biomass burning and constitute a large global source of atmospheric traces gases and aerosols. Such emissions have a considerable impact on air quality and constitute a major health hazard. Biomass burning also influences the radiative balance of the atmosphere and is thus not only of societal, but also of significant scientific interest. There is a common perception that climate change will lead to an increase in emissions as hot and dry weather events that promote wildfire will become more common. However, even though a few studies have found that the inclusion of CO2 fertilization of photosynthesis and changes in human population patterns will tend to somewhat lower predictions of future wildfire emissions, no such study has included full ensemble ranges of both climate predictions and population projections, including the effect of different degrees of urbanisation. Here, we present a series of 124 simulations with the LPJ-GUESS-SIMFIRE global dynamic vegetation - wildfire model, including a semi-empirical formulation for the prediction of burned area based on fire weather, fuel continuity and human population density. The simulations comprise Climate Model Intercomparison Project 5 (CMIP5) climate predictions from eight Earth system models using two Representative Concentration Pathways (RCPs) and five scenarios of future human population density based on the series of Shared Socioeconomic Pathways (SSPs), sensitivity tests for the effect of climate and CO2, as well as a sensitivity analysis using two alternative parameterisations of the semi-empirical burned-area model. Contrary to previous work, we find no clear future trend of global wildfire emissions for the moderate emissions and climate change scenario based on the RCP 4.5. Only historical population change introduces a decline by around 15 % since 1900. Future emissions could either increase for low population growth and fast urbanisation, or continue to decline for high population growth and slow urbanisation. Only for high future climate change (RCP8.5), wildfire emissions start to rise again after ca. 2020 but are unlikely to reach the levels of 1900 by the end of the 21st century. We find that climate warming will generally increase the risk of fire, but that this is only one of several equally important factors driving future levels of wildfire emissions, which include population change, CO2 fertilisation causing woody thickening, increased productivity and fuel load, and faster litter turnover in a warmer climate.

Climate, CO2 and human population impacts on global wildfire emissions

NASA Astrophysics Data System (ADS)

Knorr, W.; Jiang, L.; Arneth, A.

2016-01-01

Wildfires are by far the largest contributor to global biomass burning and constitute a large global source of atmospheric traces gases and aerosols. Such emissions have a considerable impact on air quality and constitute a major health hazard. Biomass burning also influences the radiative balance of the atmosphere and is thus not only of societal, but also of significant scientific interest. There is a common perception that climate change will lead to an increase in emissions as hot and dry weather events that promote wildfire will become more common. However, even though a few studies have found that the inclusion of CO2 fertilisation of photosynthesis and changes in human population patterns will tend to somewhat lower predictions of future wildfire emissions, no such study has included full ensemble ranges of both climate predictions and population projections, including the effect of different degrees of urbanisation.

Here, we present a series of 124 simulations with the LPJ-GUESS-SIMFIRE global dynamic vegetation-wildfire model, including a semi-empirical formulation for the prediction of burned area based on fire weather, fuel continuity and human population density. The simulations use Climate Model Intercomparison Project 5 (CMIP5) climate predictions from eight Earth system models. These were combined with two Representative Concentration Pathways (RCPs) and five scenarios of future human population density based on the series of Shared Socioeconomic Pathways (SSPs) to assess the sensitivity of emissions to the effect of climate, CO2 and humans. In addition, two alternative parameterisations of the semi-empirical burned-area model were applied. Contrary to previous work, we find no clear future trend of global wildfire emissions for the moderate emissions and climate change scenario based on the RCP 4.5. Only historical population change introduces a decline by around 15 % since 1900. Future emissions could either increase for low population growth and fast urbanisation, or continue to decline for high population growth and slow urbanisation. Only for high future climate change (RCP8.5), wildfire emissions start to rise again after ca. 2020 but are unlikely to reach the levels of 1900 by the end of the 21st century. We find that climate warming will generally increase the risk of fire, but that this is only one of several equally important factors driving future levels of wildfire emissions, which include population change, CO2 fertilisation causing woody thickening, increased productivity and fuel load and faster litter turnover in a warmer climate.

Why Is It Difficult to Predict Language Impairment and Outcome in Patients with Aphasia after Stroke?

PubMed Central

Kasselimis, Dimitrios; Varkanitsa, Maria; Selai, Caroline; Potagas, Constantin; Evdokimidis, Ioannis

2014-01-01

One of the most devastating consequences of stroke is aphasia. Communication problems after stroke can severely impair the patient's quality of life and make even simple everyday tasks challenging. Despite intense research in the field of aphasiology, the type of language impairment has not yet been localized and correlated with brain damage, making it difficult to predict the language outcome for stroke patients with aphasia. Our primary objective is to present the available evidence that highlights the difficulties of predicting language impairment after stroke. The different levels of complexity involved in predicting the lesion site from language impairment and ultimately predicting the long-term outcome in stroke patients with aphasia were explored. Future directions and potential implications for research and clinical practice are highlighted. PMID:24829592

Universality of quantum gravity corrections.

PubMed

Das, Saurya; Vagenas, Elias C

2008-11-28

We show that the existence of a minimum measurable length and the related generalized uncertainty principle (GUP), predicted by theories of quantum gravity, influence all quantum Hamiltonians. Thus, they predict quantum gravity corrections to various quantum phenomena. We compute such corrections to the Lamb shift, the Landau levels, and the tunneling current in a scanning tunneling microscope. We show that these corrections can be interpreted in two ways: (a) either that they are exceedingly small, beyond the reach of current experiments, or (b) that they predict upper bounds on the quantum gravity parameter in the GUP, compatible with experiments at the electroweak scale. Thus, more accurate measurements in the future should either be able to test these predictions, or further tighten the above bounds and predict an intermediate length scale between the electroweak and the Planck scale.

A systematic model to compare nurses' optimal and actual competencies in the clinical setting.

PubMed

Meretoja, Riitta; Koponen, Leena

2012-02-01

This paper is a report of a study to develop a model to compare nurses' optimal and actual competencies in the clinical setting.   Although future challenge is to focus the developmental and educational targets in health care, limited information is available on methods for how to predict optimal competencies. A multidisciplinary group of 24 experts on perioperative care were recruited to this study. They anticipated the effects of future challenges on perioperative care and specified the level of optimal competencies by using the Nurse Competence Scale before and after group discussions. The expert group consensus discussions were held to achieve the highest possible agreement on the overall level of optimal competencies. Registered Nurses (n = 87) and their nurse managers from five different units conducted assessments of the actual level of nurse competence with the Nurse Competence Scale instrument. Data were collected in 2006-2007. Group consensus discussions solidified experts' anticipations about the optimal competence level. This optimal competence level was significantly higher than the nurses' self-reported actual or nurse managers' assessed level of actual competence. The study revealed some competence items that were seen as key challenges for future education of professional nursing practice. It is important that the multidisciplinary experts in a particular care context develop a share understanding of the future competency requirements of patient care. Combining optimal competence profiles to systematic competence assessments contribute to targeted continual learning and educational interventions. © 2011 Blackwell Publishing Ltd.

Predictability of tick-borne encephalitis fluctuations.

PubMed

Zeman, P

2017-10-01

Tick-borne encephalitis is a serious arboviral infection with unstable dynamics and profound inter-annual fluctuations in case numbers. A dependable predictive model has been sought since the discovery of the disease. The present study demonstrates that four superimposed cycles, approximately 2·4, 3, 5·4, and 10·4 years long, can account for three-fifths of the variation in the disease fluctuations over central Europe. Using harmonic regression, these cycles can be projected into the future, yielding forecasts of sufficient accuracy for up to 4 years ahead. For the years 2016-2018, this model predicts elevated incidence levels in most parts of the region.

Integrating Self-Determination and Job Demands-Resources Theory in Predicting Mental Health Provider Burnout.

PubMed

Dreison, Kimberly C; White, Dominique A; Bauer, Sarah M; Salyers, Michelle P; McGuire, Alan B

2018-01-01

Limited progress has been made in reducing burnout in mental health professionals. Accordingly, we identified factors that might protect against burnout and could be productive focal areas for future interventions. Guided by self-determination theory, we examined whether supervisor autonomy support, self-efficacy, and staff cohesion predict provider burnout. 358 staff from 13 agencies completed surveys. Higher levels of supervisor autonomy support, self-efficacy, and staff cohesion were predictive of lower burnout, even after accounting for job demands. Although administrators may be limited in their ability to reduce job demands, our findings suggest that increasing core job resources may be a viable alternative.

Acoustic Prediction State of the Art Assessment

NASA Technical Reports Server (NTRS)

Dahl, Milo D.

2007-01-01

The acoustic assessment task for both the Subsonic Fixed Wing and the Supersonic projects under NASA s Fundamental Aeronautics Program was designed to assess the current state-of-the-art in noise prediction capability and to establish baselines for gauging future progress. The documentation of our current capabilities included quantifying the differences between predictions of noise from computer codes and measurements of noise from experimental tests. Quantifying the accuracy of both the computed and experimental results further enhanced the credibility of the assessment. This presentation gives sample results from codes representative of NASA s capabilities in aircraft noise prediction both for systems and components. These include semi-empirical, statistical, analytical, and numerical codes. System level results are shown for both aircraft and engines. Component level results are shown for a landing gear prototype, for fan broadband noise, for jet noise from a subsonic round nozzle, and for propulsion airframe aeroacoustic interactions. Additional results are shown for modeling of the acoustic behavior of duct acoustic lining and the attenuation of sound in lined ducts with flow.

Identifying water price and population criteria for meeting future urban water demand targets

NASA Astrophysics Data System (ADS)

Ashoori, Negin; Dzombak, David A.; Small, Mitchell J.

2017-12-01

Predictive models for urban water demand can help identify the set of factors that must be satisfied in order to meet future targets for water demand. Some of the explanatory variables used in such models, such as service area population and changing temperature and rainfall rates, are outside the immediate control of water planners and managers. Others, such as water pricing and the intensity of voluntary water conservation efforts, are subject to decisions and programs implemented by the water utility. In order to understand this relationship, a multiple regression model fit to 44 years of monthly demand data (1970-2014) for Los Angeles, California was applied to predict possible future demand through 2050 under alternative scenarios for the explanatory variables: population, price, voluntary conservation efforts, and temperature and precipitation outcomes predicted by four global climate models with two CO2 emission scenarios. Future residential water demand in Los Angeles is projected to be largely driven by price and population rather than climate change and conservation. A median projection for the year 2050 indicates that residential water demand in Los Angeles will increase by approximately 36 percent, to a level of 620 million m3 per year. The Monte Carlo simulations of the fitted model for water demand were then used to find the set of conditions in the future for which water demand is predicted to be above or below the Los Angeles Department of Water and Power 2035 goal to reduce residential water demand by 25%. Results indicate that increases in price can not ensure that the 2035 water demand target can be met when population increases. Los Angeles must rely on furthering their conservation initiatives and increasing their use of stormwater capture, recycled water, and expanding their groundwater storage. The forecasting approach developed in this study can be utilized by other cities to understand the future of water demand in water-stressed areas. Improving water demand forecasts will help planners understand and optimize future investments in water supply infrastructure and related programs.

Prediction of future uniform milk prices in Florida federal milk marketing order 6 from milk futures markets.

PubMed

De Vries, A; Feleke, S

2008-12-01

This study assessed the accuracy of 3 methods that predict the uniform milk price in Federal Milk Marketing Order 6 (Florida). Predictions were made for 1 to 12 mo into the future. Data were from January 2003 to May 2007. The CURRENT method assumed that future uniform milk prices were equal to the last announced uniform milk price. The F+BASIS and F+UTIL methods were based on the milk futures markets because the futures prices reflect the market's expectation of the class III and class IV cash prices that are announced monthly by USDA. The F+BASIS method added an exponentially weighted moving average of the difference between the class III cash price and the historical uniform milk price (also known as basis) to the class III futures price. The F+UTIL method used the class III and class IV futures prices, the most recently announced butter price, and historical utilizations to predict the skim milk prices, butterfat prices, and utilizations in all 4 classes. Predictions of future utilizations were made with a Holt-Winters smoothing method. Federal Milk Marketing Order 6 had high class I utilization (85 +/- 4.8%). Mean and standard deviation of the class III and class IV cash prices were $13.39 +/- 2.40/cwt (1 cwt = 45.36 kg) and $12.06 +/- 1.80/cwt, respectively. The actual uniform price in Tampa, Florida, was $16.62 +/- 2.16/cwt. The basis was $3.23 +/- 1.23/cwt. The F+BASIS and F+UTIL predictions were generally too low during the period considered because the class III cash prices were greater than the corresponding class III futures prices. For the 1- to 6-mo-ahead predictions, the root of the mean squared prediction errors from the F+BASIS method were $1.12, $1.20, $1.55, $1.91, $2.16, and $2.34/cwt, respectively. The root of the mean squared prediction errors ranged from $2.50 to $2.73/cwt for predictions up to 12 mo ahead. Results from the F+UTIL method were similar. The accuracies of the F+BASIS and F+UTIL methods for all 12 fore-cast horizons were not significantly different. Application of the modified Mariano-Diebold tests showed that no method included all the information contained in the other methods. In conclusion, both F+BASIS and F+UTIL methods tended to more accurately predict the future uniform milk prices than the CURRENT method, but prediction errors could be substantial even a few months into the future. The majority of the prediction error was caused by the inefficiency of the futures markets to predict the class III cash prices.

A hierarchical anatomical classification schema for prediction of phenotypic side effects

PubMed Central

Kanji, Rakesh

2018-01-01

Prediction of adverse drug reactions is an important problem in drug discovery endeavors which can be addressed with data-driven strategies. SIDER is one of the most reliable and frequently used datasets for identification of key features as well as building machine learning models for side effects prediction. The inherently unbalanced nature of this data presents with a difficult multi-label multi-class problem towards prediction of drug side effects. We highlight the intrinsic issue with SIDER data and methodological flaws in relying on performance measures such as AUC while attempting to predict side effects.We argue for the use of metrics that are robust to class imbalance for evaluation of classifiers. Importantly, we present a ‘hierarchical anatomical classification schema’ which aggregates side effects into organs, sub-systems, and systems. With the help of a weighted performance measure, using 5-fold cross-validation we show that this strategy facilitates biologically meaningful side effects prediction at different levels of anatomical hierarchy. By implementing various machine learning classifiers we show that Random Forest model yields best classification accuracy at each level of coarse-graining. The manually curated, hierarchical schema for side effects can also serve as the basis of future studies towards prediction of adverse reactions and identification of key features linked to specific organ systems. Our study provides a strategy for hierarchical classification of side effects rooted in the anatomy and can pave the way for calibrated expert systems for multi-level prediction of side effects. PMID:29494708

A hierarchical anatomical classification schema for prediction of phenotypic side effects.

PubMed

Wadhwa, Somin; Gupta, Aishwarya; Dokania, Shubham; Kanji, Rakesh; Bagler, Ganesh

2018-01-01

Prediction of adverse drug reactions is an important problem in drug discovery endeavors which can be addressed with data-driven strategies. SIDER is one of the most reliable and frequently used datasets for identification of key features as well as building machine learning models for side effects prediction. The inherently unbalanced nature of this data presents with a difficult multi-label multi-class problem towards prediction of drug side effects. We highlight the intrinsic issue with SIDER data and methodological flaws in relying on performance measures such as AUC while attempting to predict side effects.We argue for the use of metrics that are robust to class imbalance for evaluation of classifiers. Importantly, we present a 'hierarchical anatomical classification schema' which aggregates side effects into organs, sub-systems, and systems. With the help of a weighted performance measure, using 5-fold cross-validation we show that this strategy facilitates biologically meaningful side effects prediction at different levels of anatomical hierarchy. By implementing various machine learning classifiers we show that Random Forest model yields best classification accuracy at each level of coarse-graining. The manually curated, hierarchical schema for side effects can also serve as the basis of future studies towards prediction of adverse reactions and identification of key features linked to specific organ systems. Our study provides a strategy for hierarchical classification of side effects rooted in the anatomy and can pave the way for calibrated expert systems for multi-level prediction of side effects.

Effects of climate change on forest insect and disease outbreaks

Treesearch

David W. Williams; Robert P. Long; Philip M. Wargo; Andrew M. Liebhold

2000-01-01

General circulation models (GCMs) predict dramatic future changes in climate for the northeastern and north central United States under doubled carbon dioxide (CO2) levels (Hansen et al., 1984; Manabe and Wetherald, 1987; Wilson and Mitchell, 1987; Cubasch and Cess, 1990; Mitchell et al., 1990). January temperatures are projected to rise as much...

Modelling Question Difficulty in an A Level Physics Examination

ERIC Educational Resources Information Center

Crisp, Victoria; Grayson, Rebecca

2013-01-01

"Item difficulty modelling" is a technique used for a number of purposes such as to support future item development, to explore validity in relation to the constructs that influence difficulty and to predict the difficulty of items. This research attempted to explore the factors influencing question difficulty in a general qualification…

Analysis of the Transport and Fate of Metals Released From ...

EPA Pesticide Factsheets

This project’s objectives were to provide analysis of water quality following the release of acid mine drainage in the Animas and San Juan Rivers in a timely manner to 1) generate a comprehensive picture of the plume at the river system level, 2) help inform future monitoring efforts and 3) to predict potential secondary effects that could occur from materials that may remain stored within the system. The project focuses on assessing metals contamination during the plume and in the first month following the event. This project’s objectives were to provide analysis of water quality following the release of acid mine drainage from the Gold King Mine in the Animas and San Juan Rivers in a timely manner to 1) generate a comprehensive picture of the plume at the river system level, 2) help inform future monitoring efforts and 3) to predict potential secondary effects that could occur from materials that may remain stored within the system. The project focuses on assessing metals contamination during the plume and in the first month following the event.

Utility of the triglyceride level for predicting incident diabetes mellitus according to the fasting status and body mass index category: the Ibaraki Prefectural Health Study.

PubMed

Fujihara, Kazuya; Sugawara, Ayumi; Heianza, Yoriko; Sairenchi, Toshimi; Irie, Fujiko; Iso, Hiroyasu; Doi, Mikio; Shimano, Hitoshi; Watanabe, Hiroshi; Sone, Hirohito; Ota, Hitoshi

2014-01-01

The levels of lipids, especially triglycerides (TG), and obesity are associated with diabetes mellitus (DM). Although typically measured in fasting individuals, non-fasting lipid measurements play an important role in predicting future DM. This study compared the predictive efficacy of lipid variables according to the fasting status and body mass index (BMI) category. Data were collected for 39,196 nondiabetic men and 87,980 nondiabetic women 40-79years of age who underwent health checkups in Ibaraki-Prefecture, Japan in 1993 and were followed through 2007. The hazard ratios (HRs) for DM in relation to sex, the fasting status and BMI were estimated using a Cox proportional hazards model. A total of 8,867 participants, 4,012 men and 4,855 women, developed DM during a mean follow-up of 5.5 years. TG was found to be an independent predictor of incident DM in both fasting and non-fasting men and non-fasting women. The multivariable-adjusted HR for DM according to the TG quartile (Q) 4 vs. Q1 was 1.18 (95% confidence interval (CI): 1.05, 1.34) in the non-fasting men with a normal BMI (18.5-24.9). This trend was also observed in the non-fasting women with a normal BMI. That is, the multivariable-adjusted HRs for DM for TG Q2, Q3 and Q4 compared with Q1 were 1.07 (95% CI: 0.94, 1.23), 1.17 (95%CI: 1.03, 1.34) and 1.48 (95%CI: 1.30, 1.69), respectively. The fasting and non-fasting TG levels in men and non-fasting TG levels in women are predictive of future DM among those with a normal BMI. Clinicians must pay attention to those individuals at high risk for DM.

Remote sensing and GIS analysis for demarcation of coastal hazard line along the highly eroding Krishna-Godavari delta front

NASA Astrophysics Data System (ADS)

Kallepalli, Akhil; Kakani, Nageswara Rao; James, David B.

2016-10-01

Coastal regions, especially river deltas are highly resourceful and hence densely populated; but these extremely low-lying lands are vulnerable to rising sea levels due to global warming threatening the life and property in these regions. Recent IPCC (2013) predictions of 26-82cm global sea level rise are now considered conservative as subsequent investigations such as by Met Office, UK indicated a vertical rise of about 190cm, which would displace 10% of the world's population living within 10 meters above the sea level. Therefore, predictive models showing the hazard line are necessary for efficient coastal zone management. Remote sensing and GIS technologies form the mainstay of such predictive models on coastal retreat and inundation to future sea-level rise. This study is an attempt to estimate the varying trends along the Krishna-Godavari (K-G) delta region. Detailed maps showing various coastal landforms in the K-G delta region were prepared using the IRS-P6 LISS 3 images. The rate of shoreline shift during a 31-year period along different sectors of the 330km long K-G delta coast was estimated using Landsat-2 and IRS-P6 LISS 3 images between 1977 and 2008. With reference to a selected baseline from along an inland position, End Point Rate (EPR), Shoreline Change Envelope (SCE) and Net Shoreline Movement (NSM) were calculated, using a GIS-based Digital Shoreline Analysis System (DSAS). The results showed that the shoreline migrated landward up to a maximum distance of 3.13km resulting in a net loss of about 42.10km2 area during this 31-year period. Further, considering the nature of landforms and EPR, the future hazard line is predicted for the area, which also indicated a net erosion of about 57.68km2 along the K-G delta coast by 2050 AD.

Storm surge and tidal range energy

NASA Astrophysics Data System (ADS)

Lewis, Matthew; Angeloudis, Athanasios; Robins, Peter; Evans, Paul; Neill, Simon

2017-04-01

The need to reduce carbon-based energy sources whilst increasing renewable energy forms has led to concerns of intermittency within a national electricity supply strategy. The regular rise and fall of the tide makes prediction almost entirely deterministic compared to other stochastic renewable energy forms; therefore, tidal range energy is often stated as a predictable and firm renewable energy source. Storm surge is the term used for the non-astronomical forcing of tidal elevation, and is synonymous with coastal flooding because positive storm surges can elevate water-levels above the height of coastal flood defences. We hypothesis storm surges will affect the reliability of the tidal range energy resource; with negative surge events reducing the tidal range, and conversely, positive surge events increasing the available resource. Moreover, tide-surge interaction, which results in positive storm surges more likely to occur on a flooding tide, will reduce the annual tidal range energy resource estimate. Water-level data (2000-2012) at nine UK tide gauges, where the mean tidal amplitude is above 2.5m and thus suitable for tidal-range energy development (e.g. Bristol Channel), were used to predict tidal range power with a 0D modelling approach. Storm surge affected the annual resource estimate by between -5% to +3%, due to inter-annual variability. Instantaneous power output were significantly affected (Normalised Root Mean Squared Error: 3%-8%, Scatter Index: 15%-41%) with spatial variability and variability due to operational strategy. We therefore find a storm surge affects the theoretical reliability of tidal range power, such that a prediction system may be required for any future electricity generation scenario that includes large amounts of tidal-range energy; however, annual resource estimation from astronomical tides alone appears sufficient for resource estimation. Future work should investigate water-level uncertainties on the reliability and predictability of tidal range energy with 2D hydrodynamic models.

The Predicted Influence of Climate Change on Lesser Prairie-Chicken Reproductive Parameters

PubMed Central

Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, Dawn M.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001–2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter’s linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival. PMID:23874549

Associations of Affective Responses During Free-Living Physical Activity and Future Physical Activity Levels: an Ecological Momentary Assessment Study.

PubMed

Liao, Yue; Chou, Chih-Ping; Huh, Jimi; Leventhal, Adam; Dunton, Genevieve

2017-08-01

Affective response during physical activity may influence motivation to perform future physical activity behavior. However, affective response during physical activity is often assessed under controlled laboratory conditions. The current study used ecological momentary assessment (EMA) to capture affective responses during free-living physical activity performed by adults, and determined whether these affective responses predict future moderate-to-vigorous physical activity (MVPA) levels after 6 and 12 months. At baseline, electronic EMA surveys were randomly prompted across 4 days asking about current activities and affective states (e.g., happy, stressed, energetic, tired). Affective response during physical activity was operationalized as the level of positive or negative affect reported when concurrent physical activity (e.g., exercise or sports) was also reported. Data were available for 82 adults. Future levels of moderate-to-vigorous physical activity (MVPA) were measured using accelerometers, worn for seven consecutive days at 6 and 12 months after the baseline assessment. Feeling more energetic during physical activity was associated with performing more minutes of daily MVPA after both 6 and 12 months. Feeling less negative affect during physical activity was associated with engaging in more daily MVPA minutes after 12 months only. This study demonstrated how EMA can be used to capture affective responses during free-living physical activity. Results found that feelings more energetic and less negative during physical activity were associated with more future physical activity, suggesting that positive emotional benefits may reinforce behavior.

Awareness Programs and Change in Taste-Based Caste Prejudice

PubMed Central

Banerjee, Ritwik; Datta Gupta, Nabanita

2015-01-01

Becker's theory of taste-based discrimination predicts that relative employment of the discriminated social group will improve if there is a decrease in the level of prejudice for the marginally discriminating employer. In this paper we experimentally test this prediction offered by Garry Becker in his seminal work on taste based discrimination, in the context of caste in India, with management students (potential employers in the near future) as subjects. First, we measure caste prejudice and show that awareness through a TV social program reduces implicit prejudice against the lower caste and the reduction is sustained over time. Second, we find that the treatment reduces the prejudice levels of those in the left tail of the prejudice distribution - the group which can potentially affect real outcomes as predicted by the theory. And finally, a larger share of the treatment group subjects exhibit favorable opinion about reservation in jobs for the lower caste. PMID:25902290

A unifying theory for top-heavy ecosystem structure in the ocean.

PubMed

Woodson, C Brock; Schramski, John R; Joye, Samantha B

2018-01-02

Size generally dictates metabolic requirements, trophic level, and consequently, ecosystem structure, where inefficient energy transfer leads to bottom-heavy ecosystem structure and biomass decreases as individual size (or trophic level) increases. However, many animals deviate from simple size-based predictions by either adopting generalist predatory behavior, or feeding lower in the trophic web than predicted from their size. Here we show that generalist predatory behavior and lower trophic feeding at large body size increase overall biomass and shift ecosystems from a bottom-heavy pyramid to a top-heavy hourglass shape, with the most biomass accounted for by the largest animals. These effects could be especially dramatic in the ocean, where primary producers are the smallest components of the ecosystem. This approach makes it possible to explore and predict, in the past and in the future, the structure of ocean ecosystems without biomass extraction and other impacts.

Awareness programs and change in taste-based caste prejudice.

PubMed

Banerjee, Ritwik; Datta Gupta, Nabanita

2015-01-01

Becker's theory of taste-based discrimination predicts that relative employment of the discriminated social group will improve if there is a decrease in the level of prejudice for the marginally discriminating employer. In this paper we experimentally test this prediction offered by Garry Becker in his seminal work on taste based discrimination, in the context of caste in India, with management students (potential employers in the near future) as subjects. First, we measure caste prejudice and show that awareness through a TV social program reduces implicit prejudice against the lower caste and the reduction is sustained over time. Second, we find that the treatment reduces the prejudice levels of those in the left tail of the prejudice distribution--the group which can potentially affect real outcomes as predicted by the theory. And finally, a larger share of the treatment group subjects exhibit favorable opinion about reservation in jobs for the lower caste.

First trimester PAPP-A levels correlate with sFlt-1 levels longitudinally in pregnant women with and without preeclampsia.

PubMed

Saxena, Aditi R; Seely, Ellen W; Rich-Edwards, Janet W; Wilkins-Haug, Louise E; Karumanchi, S Ananth; McElrath, Thomas F

2013-04-04

First trimester Pregnancy Associated Plasma Protein A (PAPP-A) levels, routinely measured for aneuploidy screening, may predict development of preeclampsia. This study tests the hypothesis that first trimester PAPP-A levels correlate with soluble fms-like tyrosine kinase-1 (sFlt-1) levels, an angiogenic marker associated with preeclampsia, throughout pregnancy. sFlt-1 levels were measured longitudinally in 427 women with singleton pregnancies in all three trimesters. First trimester PAPP-A and PAPP-A Multiples of Median (MOM) were measured. Student's T and Wilcoxon tests compared preeclamptic and normal pregnancies. A linear mixed model assessed the relationship between log PAPP-A and serial log sFlt-1 levels. PAPP-A and PAPP-A MOM levels were significantly lower in preeclamptic (n = 19), versus normal pregnancies (p = 0.02). Although mean third trimester sFlt-1 levels were significantly higher in preeclampsia (p = 0.002), first trimester sFlt-1 levels were lower in women who developed preeclampsia, compared with normal pregnancies (p = 0.03). PAPP-A levels correlated significantly with serial sFlt-1 levels. Importantly, low first trimester PAPP-A MOM predicted decreased odds of normal pregnancy (OR 0.2, p = 0.002). Low first trimester PAPP-A levels suggests increased future risk of preeclampsia and correlate with serial sFlt-1 levels throughout pregnancy. Furthermore, low first trimester PAPP-A status significantly predicted decreased odds of normal pregnancy.

Teacher literacy expectations for kindergarten children with cerebral palsy in special education.

PubMed

Peeters, Marieke; Verhoeven, Ludo; de Moor, Jan

2009-09-01

Teacher expectations are important for the literacy development of children. The goal of this study was to investigate to what extent teacher expectations for future literacy success at the end of elementary school differed for children with cerebral palsy (CP) as compared with peers without disabilities in kindergarten. In addition, we investigated to what extent teacher literacy expectations of children with CP were related to additional impairments such as speech, intellectual and physical impairments, and to the current level of emergent literacy skills. Forty-nine teachers of children with CP and 71 teachers of non-disabled children responded to the questionnaire. The results showed that teacher expectations for future reading and writing success of children with CP were lower (all P values are <0.001) but also of a different nature, as eight teachers had no idea what to expect for the future reading development, and 12 teachers did not know what to expect for the future writing development of the child with CP. Multiple regression analysis showed that teacher reading expectations could best be predicted by both intelligence and emergent literacy skills (P<0.001), whereas teacher writing skills could best be predicted by intelligence (P<0.001).

Forecast of jet engine exhaust emissions for future high altitude commercial aircraft

NASA Technical Reports Server (NTRS)

Grobman, J.; Ingebo, R. D.

1974-01-01

Projected minimum levels of engine exhaust emissions that may be practicably achievable for future commercial aircraft operating at high altitude cruise conditions are presented. The forecasts are based on: (1) current knowledge of emission characteristics of combustors and augmentors; (2) the current status of combustion research in emission reduction technology; (3) predictable trends in combustion systems and operating conditions as required for projected engine designs that are candidates for advanced subsonic or supersonic commercial aircraft. Results are presented for cruise conditions in terms of an emission index, g pollutant/kg fuel. Two sets of engine exhaust emission predictions are presented: the first, based on an independent NASA study and the second, based on the consensus of an ad hoc committee composed of industry, university, and government representatives. The consensus forecasts are in general agreement with the NASA forecasts.

Forecast of jet engine exhaust emissions for future high altitude commercial aircraft

NASA Technical Reports Server (NTRS)

Grobman, J.; Ingebo, R. D.

1974-01-01

Projected minimum levels of engine exhaust emissions that may be practicably achievable for future commercial aircraft operating at high altitude cruise conditions are presented. The forecasts are based on: (1) current knowledge of emission characteristics of combustors and augmentors; (2) the current status of combustion research in emission reduction technology; and (3) predictable trends in combustion systems and operating conditions as required for projected engine designs that are candidates for advanced subsonic or supersonic commercial aircraft. Results are presented for cruise conditions in terms of an emission index, g pollutant/kg fuel. Two sets of engine exhaust emission predictions are presented: the first, based on an independent NASA study and the second, based on the consensus of an ad hoc committee composed of industry, university, and government representatives. The consensus forecasts are in general agreement with the NASA forecasts.

The future is in the numbers: the power of predictive analysis in the biomedical educational environment.

PubMed

Gullo, Charles A

2016-01-01

Biomedical programs have a potential treasure trove of data they can mine to assist admissions committees in identification of students who are likely to do well and help educational committees in the identification of students who are likely to do poorly on standardized national exams and who may need remediation. In this article, we provide a step-by-step approach that schools can utilize to generate data that are useful when predicting the future performance of current students in any given program. We discuss the use of linear regression analysis as the means of generating that data and highlight some of the limitations. Finally, we lament on how the combination of these institution-specific data sets are not being fully utilized at the national level where these data could greatly assist programs at large.

Low bioavailable testosterone levels predict future height loss in postmenopausal women.

PubMed

Jassal, S K; Barrett-Connor, E; Edelstein, S L

1995-04-01

The objective of this study was to examine the relation of endogenous sex hormones to subsequent height loss in postmenopausal women, in whom height loss is usually a surrogate for osteoporotic vertebral fractures. This was a prospective, community-based study. The site chosen was Rancho Bernardo, an upper middle class community in Southern California. A total of 170 postmenopausal women participated, aged 55-80 years. None of them were taking exogenous estrogen between 1972 and 1974. Plasma was obtained for sex hormone and sex hormone-binding globulin (SHBG) assays. Estradiol/SHBG and testosterone/SHBG ratios were used to estimate biologically available hormone levels; bioavailable (non-SHBG-bound) testosterone was measured directly in 60 women. Height loss was based on height measurements taken 16 years apart. Height loss was strongly correlated with age (p = 0.001). These women lost an average 0.22 cm/year in height. Neither estrone nor estradiol levels were significantly and independently related to height loss. Both estimated bioavailable testosterone (testosterone/SHBG ratio) and measured bioavailable testosterone levels predicted future height loss (p = 0.02 and 0.08, respectively) independent of age, obesity, cigarette smoking, alcohol intake, and use of thiazides and estrogen. We conclude that bioavailable testosterone is an independent predictor of height loss in elderly postmenopausal women. The reduced height loss is compatible with a direct effect of testosterone on bone mineral density or bone remodeling.

Land Use Planning and Wildfire: Development Policies Influence Future Probability of Housing Loss

PubMed Central

Syphard, Alexandra D.; Bar Massada, Avi; Butsic, Van; Keeley, Jon E.

2013-01-01

Increasing numbers of homes are being destroyed by wildfire in the wildland-urban interface. With projections of climate change and housing growth potentially exacerbating the threat of wildfire to homes and property, effective fire-risk reduction alternatives are needed as part of a comprehensive fire management plan. Land use planning represents a shift in traditional thinking from trying to eliminate wildfires, or even increasing resilience to them, toward avoiding exposure to them through the informed placement of new residential structures. For land use planning to be effective, it needs to be based on solid understanding of where and how to locate and arrange new homes. We simulated three scenarios of future residential development and projected landscape-level wildfire risk to residential structures in a rapidly urbanizing, fire-prone region in southern California. We based all future development on an econometric subdivision model, but we varied the emphasis of subdivision decision-making based on three broad and common growth types: infill, expansion, and leapfrog. Simulation results showed that decision-making based on these growth types, when applied locally for subdivision of individual parcels, produced substantial landscape-level differences in pattern, location, and extent of development. These differences in development, in turn, affected the area and proportion of structures at risk from burning in wildfires. Scenarios with lower housing density and larger numbers of small, isolated clusters of development, i.e., resulting from leapfrog development, were generally predicted to have the highest predicted fire risk to the largest proportion of structures in the study area, and infill development was predicted to have the lowest risk. These results suggest that land use planning should be considered an important component to fire risk management and that consistently applied policies based on residential pattern may provide substantial benefits for future risk reduction. PMID:23977120

Longitudinal study of Stenotrophomonas maltophilia antibody levels and outcomes in cystic fibrosis patients.

PubMed

Wettlaufer, Jillian; Klingel, Michelle; Yau, Yvonne; Stanojevic, Sanja; Tullis, Elizabeth; Ratjen, Felix; Waters, Valerie

2017-01-01

Previous studies have shown an association between higher Stenotrophomonas maltophilia antibody levels and decreased lung function in patients with cystic fibrosis (CF). The purpose of this study was to assess the serologic response to S. maltophilia over time and to determine whether changes in antibody levels could predict clinical outcomes. Changes in S. maltophilia antibody levels in adult and pediatric patients with CF from 2008 to 2014 were assessed between groups of infection patterns. Regression models accounting for repeated measures were used to assess whether antibody levels could predict subsequent S. maltophilia microbiological status, and whether they are associated with lung function and subsequent pulmonary exacerbation. A total of 409 S. maltophilia antibody samples from 135 CF patients showed that antibody levels did not change significantly between study visits, regardless of infection group. Higher antibody levels were independently associated with future culture positivity (OR 1.62; 95% CI 1.09, 2.41; p=0.02). While higher antibody levels were not independently associated with decreases in FEV 1 % predicted, they were associated with an increased hazard ratio for subsequent pulmonary exacerbation (HR 1.3; 95% CI 1.1, 1.6; p<0.001). S. maltophilia antibody levels may be helpful to identify individuals at risk of exacerbation who may benefit from earlier antimicrobial treatment. Copyright © 2016 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.

The Impacts of 3-D Earth Structure on GIA-Induced Crustal Deformation and Future Sea-Level Change in the Antarctic

NASA Astrophysics Data System (ADS)

Powell, E. M.; Hay, C.; Latychev, K.; Gomez, N. A.; Mitrovica, J. X.

2016-12-01

Glacial Isostatic Adjustment (GIA) models used to constrain the extent of past ice sheets and viscoelastic Earth structure, or to correct geodetic and geological observables for ice age effects, generally only consider depth-dependent variations in Earth viscosity and lithospheric structure. A et al. [2013] argued that 3-D Earth structure could impact GIA observables in Antarctica, but concluded that the presence of such structure contributes less to GIA uncertainty than do differences in Antarctic deglaciation histories. New seismic and geological evidence, however, indicates the Antarctic is underlain by complex, high amplitude variability in viscoelastic structure, including a low viscosity zone (LVZ) under West Antarctica. Hay et al. [2016] showed that sea-level fingerprints of modern melting calculated using such Earth models differ from those based on elastic or 1-D viscoelastic Earth models within decades of melting. Our investigation is motivated by two questions: (1) How does 3-D Earth structure, especially this LVZ, impact observations of GIA-induced crustal deformation associated with the last deglaciation? (2) How will 3-D Earth structure affect predictions of future sea-level rise in Antarctica? We compute the gravitationally self-consistent sea level, uplift, and gravity changes using the finite volume treatment of Latychev et al. [2005]. We consider four viscoelastic Earth models: a global 1-D model; a regional, West Antarctic-like 1-D model; a 3-D model where the lithospheric thickness varies laterally; and a 3-D model where both viscosity and lithospheric thickness vary laterally. For our Last Glacial Maximum to present investigations we employ ICE6g [Peltier et al., 2015]. For our present-future investigations we consider a melt scenario consistent with GRACE satellite gravity derived solutions [Harig et al., 2015]. Our calculations indicate that predictions of crustal deformations due to both GIA and ongoing melting are strongly influenced by 3-D lithospheric thickness and viscosity structure. Future sea level change due to ongoing melting is primarily influenced by 3-D viscosity structure. We show that 1-D Earth models built using regional inferences of viscosity and lithospheric thickness do not accurately capture the variability introduced by 3-D Earth structure.

The Impacts of 3-D Earth Structure on GIA-Induced Crustal Deformation and Future Sea-Level Change in the Antarctic

NASA Astrophysics Data System (ADS)

Powell, E. M.; Hay, C.; Latychev, K.; Gomez, N. A.; Mitrovica, J. X.

2017-12-01

Glacial Isostatic Adjustment (GIA) models used to constrain the extent of past ice sheets and viscoelastic Earth structure, or to correct geodetic and geological observables for ice age effects, generally only consider depth-dependent variations in Earth viscosity and lithospheric structure. A et al. [2013] argued that 3-D Earth structure could impact GIA observables in Antarctica, but concluded that the presence of such structure contributes less to GIA uncertainty than do differences in Antarctic deglaciation histories. New seismic and geological evidence, however, indicates the Antarctic is underlain by complex, high amplitude variability in viscoelastic structure, including a low viscosity zone (LVZ) under West Antarctica. Hay et al. [2016] showed that sea-level fingerprints of modern melting calculated using such Earth models differ from those based on elastic or 1-D viscoelastic Earth models within decades of melting. Our investigation is motivated by two questions: (1) How does 3-D Earth structure, especially this LVZ, impact observations of GIA-induced crustal deformation associated with the last deglaciation? (2) How will 3-D Earth structure affect predictions of future sea-level rise in Antarctica? We compute the gravitationally self-consistent sea level, uplift, and gravity changes using the finite volume treatment of Latychev et al. [2005]. We consider four viscoelastic Earth models: a global 1-D model; a regional, West Antarctic-like 1-D model; a 3-D model where the lithospheric thickness varies laterally; and a 3-D model where both viscosity and lithospheric thickness vary laterally. For our Last Glacial Maximum to present investigations we employ ICE6g [Peltier et al., 2015]. For our present-future investigations we consider a melt scenario consistent with GRACE satellite gravity derived solutions [Harig et al., 2015]. Our calculations indicate that predictions of crustal deformations due to both GIA and ongoing melting are strongly influenced by 3-D lithospheric thickness and viscosity structure. Future sea level change due to ongoing melting is primarily influenced by 3-D viscosity structure. We show that 1-D Earth models built using regional inferences of viscosity and lithospheric thickness do not accurately capture the variability introduced by 3-D Earth structure.

Incorporating Infrastructure and Vegetation Effects on Sea Level Rise Predictions in Low-Gradient Coastal Landscapes

NASA Astrophysics Data System (ADS)

Rodriguez, J. F.; Sandi Rojas, S.; Trivisonno, F.; Saco, P. M.; Riccardi, G.

2015-12-01

At the regional and global scales, coastal management and planning for future sea level rise scenarios is typically supported by modelling tools that predict the expected inundation extent. These tools rely on a number of simplifying assumptions that, in some cases, may result in important overestimation or underestimation of the inundation extent. One of such cases is coastal wetlands, where vegetation strongly affects both the magnitude and the timing of inundation. Many coastal wetlands display other forms of flow restrictions due to, for example, infrastructure or drainage works, which also alters the inundation patterns. In this contribution we explore the effects of flow restrictions on inundation patterns under sea level rise conditions in coastal wetlands. We use a dynamic wetland evolution model that not only incorporates the effects of flow restrictions due to culverts, bridges and weirs as well as vegetation, but also considers that vegetation changes as a consequence of increasing inundation. We apply our model to a coastal wetland in Australia and compare predictions of our model to predictions using conventional approaches. We found that some restrictions accentuate detrimental effects of sea level rise while others moderate them. We also found that some management strategies based on flow redistribution that provide short term solution may result more damaging in the long term if sea level rise is considered.

Using modelling to predict impacts of sea level rise and increased turbidity on seagrass distributions in estuarine embayments

NASA Astrophysics Data System (ADS)

Davis, Tom R.; Harasti, David; Smith, Stephen D. A.; Kelaher, Brendan P.

2016-11-01

Climate change induced sea level rise will affect shallow estuarine habitats, which are already under threat from multiple anthropogenic stressors. Here, we present the results of modelling to predict potential impacts of climate change associated processes on seagrass distributions. We use a novel application of relative environmental suitability (RES) modelling to examine relationships between variables of physiological importance to seagrasses (light availability, wave exposure, and current flow) and seagrass distributions within 5 estuarine embayments. Models were constructed separately for Posidonia australis and Zostera muelleri subsp. capricorni using seagrass data from Port Stephens estuary, New South Wales, Australia. Subsequent testing of models used independent datasets from four other estuarine embayments (Wallis Lake, Lake Illawarra, Merimbula Lake, and Pambula Lake) distributed along 570 km of the east Australian coast. Relative environmental suitability models provided adequate predictions for seagrass distributions within Port Stephens and the other estuarine embayments, indicating that they may have broad regional application. Under the predictions of RES models, both sea level rise and increased turbidity are predicted to cause substantial seagrass losses in deeper estuarine areas, resulting in a net shoreward movement of seagrass beds. Seagrass species distribution models developed in this study provide a valuable tool to predict future shifts in estuarine seagrass distributions, allowing identification of areas for protection, monitoring and rehabilitation.

Ice2sea - the future glacial contribution to sea-level rise

NASA Astrophysics Data System (ADS)

Vaughan, D. G.; Ice2sea Consortium

2009-04-01

The melting of continental ice (glaciers, ice caps and ice sheets) is a substantial source of current sea-level rise, and one that is accelerating more rapidly than was predicted even a few years ago. Indeed, the most recent report from Intergovernmental Panel on Climate Change highlighted that the uncertainty in projections of future sea-level rise is dominated by uncertainty concerning continental ice, and that understanding of the key processes that will lead to loss of continental ice must be improved before reliable projections of sea-level rise can be produced. Such projections are urgently required for effective sea-defence management and coastal adaptation planning. Ice2sea is a consortium of European institutes and international partners seeking European funding to support an integrated scientific programme to improve understanding concerning the future glacial contribution to sea-level rise. This includes improving understanding of the processes that control, past, current and future sea-level rise, and generation of improved estimates of the contribution of glacial components to sea-level rise over the next 200 years. The programme will include targeted studies of key processes in mountain glacier systems and ice caps (e.g. Svalbard), and in ice sheets in both polar regions (Greenland and Antarctica) to improve understanding of how these systems will respond to future climate change. It will include fieldwork and remote sensing studies, and develop a suite of new, cross-validated glacier and ice-sheet model. Ice2sea will deliver these results in forms accessible to scientists, policy-makers and the general public, which will include clear presentations of the sources of uncertainty. Our aim is both, to provide improved projections of the glacial contribution to sea-level rise, and to leave a legacy of improved tools and techniques that will form the basis of ongoing refinements in sea-level projection. Ice2sea will provide exciting opportunities for many early-career glaciologists and ice-modellers in a variety of host institutes.

The fate of threatened coastal dune habitats in Italy under climate change scenarios.

PubMed

Prisco, Irene; Carboni, Marta; Acosta, Alicia T R

2013-01-01

Coastal dunes worldwide harbor threatened habitats characterized by high diversity in terms of plant communities. In Italy, recent assessments have highlighted the insufficient state of conservation of these habitats as defined by the EU Habitats Directive. The effects of predicted climate change could have dramatic consequences for coastal environments in the near future. An assessment of the efficacy of protection measures under climate change is thus a priority. Here, we have developed environmental envelope models for the most widespread dune habitats in Italy, following two complementary approaches: an "indirect" plant-species-based one and a simple "direct" one. We analyzed how habitats distribution will be altered under the effects of two climate change scenarios and evaluated if the current Italian network of protected areas will be effective in the future after distribution shifts. While modeling dune habitats with the "direct" approach was unsatisfactory, "indirect" models had a good predictive performance, highlighting the importance of using species' responses to climate change for modeling these habitats. The results showed that habitats closer to the sea may even increase their geographical distribution in the near future. The transition dune habitat is projected to remain stable, although mobile and fixed dune habitats are projected to lose most of their actual geographical distribution, the latter being more sensitive to climate change effects. Gap analysis highlighted that the habitats' distribution is currently adequately covered by protected areas, achieving the conservation target. However, according to predictions, protection level for mobile and fixed dune habitats is predicted to drop drastically under the climate change scenarios which we examined. Our results provide useful insights for setting management priorities and better addressing conservation efforts to preserve these threatened habitats in future.

The Fate of Threatened Coastal Dune Habitats in Italy under Climate Change Scenarios

PubMed Central

Prisco, Irene; Carboni, Marta; Acosta, Alicia T. R.

2013-01-01

Coastal dunes worldwide harbor threatened habitats characterized by high diversity in terms of plant communities. In Italy, recent assessments have highlighted the insufficient state of conservation of these habitats as defined by the EU Habitats Directive. The effects of predicted climate change could have dramatic consequences for coastal environments in the near future. An assessment of the efficacy of protection measures under climate change is thus a priority. Here, we have developed environmental envelope models for the most widespread dune habitats in Italy, following two complementary approaches: an “indirect” plant-species-based one and a simple “direct” one. We analyzed how habitats distribution will be altered under the effects of two climate change scenarios and evaluated if the current Italian network of protected areas will be effective in the future after distribution shifts. While modeling dune habitats with the “direct” approach was unsatisfactory, “indirect” models had a good predictive performance, highlighting the importance of using species’ responses to climate change for modeling these habitats. The results showed that habitats closer to the sea may even increase their geographical distribution in the near future. The transition dune habitat is projected to remain stable, although mobile and fixed dune habitats are projected to lose most of their actual geographical distribution, the latter being more sensitive to climate change effects. Gap analysis highlighted that the habitats’ distribution is currently adequately covered by protected areas, achieving the conservation target. However, according to predictions, protection level for mobile and fixed dune habitats is predicted to drop drastically under the climate change scenarios which we examined. Our results provide useful insights for setting management priorities and better addressing conservation efforts to preserve these threatened habitats in future. PMID:23874787

The cognitive bases of the development of past and future episodic cognition in preschoolers.

PubMed

Ünal, Gülten; Hohenberger, Annette

2017-10-01

The aim of this study was to use a minimalist framework to examine the joint development of past and future episodic cognition and their underlying cognitive abilities in 3- to 5-year-old Turkish preschoolers. Participants engaged in two main tasks, a what-where-when (www) task to measure episodic memory and a future prediction task to measure episodic future thinking. Three additional tasks were used for predicting children's performance in the two main tasks: a temporal language task, an executive function task, and a spatial working memory task. Results indicated that past and future episodic tasks were significantly correlated with each other even after controlling for age. Hierarchical multiple regressions showed that, after controlling for age, the www task was predicted by executive functions, possibly supporting binding of episodic information and by linguistic abilities. The future prediction task was predicted by linguistic abilities alone, underlining the importance of language for episodic past and future thinking. Copyright © 2017 Elsevier Inc. All rights reserved.

Risk and the physics of clinical prediction.

PubMed

McEvoy, John W; Diamond, George A; Detrano, Robert C; Kaul, Sanjay; Blaha, Michael J; Blumenthal, Roger S; Jones, Steven R

2014-04-15

The current paradigm of primary prevention in cardiology uses traditional risk factors to estimate future cardiovascular risk. These risk estimates are based on prediction models derived from prospective cohort studies and are incorporated into guideline-based initiation algorithms for commonly used preventive pharmacologic treatments, such as aspirin and statins. However, risk estimates are more accurate for populations of similar patients than they are for any individual patient. It may be hazardous to presume that the point estimate of risk derived from a population model represents the most accurate estimate for a given patient. In this review, we exploit principles derived from physics as a metaphor for the distinction between predictions regarding populations versus patients. We identify the following: (1) predictions of risk are accurate at the level of populations but do not translate directly to patients, (2) perfect accuracy of individual risk estimation is unobtainable even with the addition of multiple novel risk factors, and (3) direct measurement of subclinical disease (screening) affords far greater certainty regarding the personalized treatment of patients, whereas risk estimates often remain uncertain for patients. In conclusion, shifting our focus from prediction of events to detection of disease could improve personalized decision-making and outcomes. We also discuss innovative future strategies for risk estimation and treatment allocation in preventive cardiology. Copyright © 2014 Elsevier Inc. All rights reserved.

Intelligent aircraft/airspace systems

NASA Technical Reports Server (NTRS)

Wangermann, John P.

1995-01-01

Projections of future air traffic predict at least a doubling of the number of revenue passenger miles flown by the year 2025. To meet this demand, an Intelligent Aircraft/Airspace System (IAAS) has been proposed. The IAAS operates on the basis of principled negotiation between intelligent agents. The aircraft/airspace system today consists of many agents, such as airlines, control facilities, and aircraft. All the agents are becoming increasingly capable as technology develops. These capabilities should be exploited to create an Intelligent Aircraft/Airspace System (IAAS) that would meet the predicted traffic levels of 2005.

Single-Event Effects Ground Testing and On-Orbit Rate Prediction Methods: The Past, Present and Future

NASA Technical Reports Server (NTRS)

Reed, Robert A.; Kinnison, Jim; Pickel, Jim; Buchner, Stephen; Marshall, Paul W.; Kniffin, Scott; LaBel, Kenneth A.

2003-01-01

Over the past 27 years, or so, increased concern over single event effects in spacecraft systems has resulted in research, development and engineering activities centered around a better understanding of the space radiation environment, single event effects predictive methods, ground test protocols, and test facility developments. This research has led to fairly well developed methods for assessing the impact of the space radiation environment on systems that contain SEE sensitive devices and the development of mitigation strategies either at the system or device level.

Electrical Systems Analysis at NASA Glenn Research Center: Status and Prospects

NASA Technical Reports Server (NTRS)

Freeh, Joshua E.; Liang, Anita D.; Berton, Jeffrey J.; Wickenheiser, Timothy J.

2003-01-01

An analysis of an electrical power and propulsion system for a 2-place general aviation aircraft is presented to provide a status of such modeling at NASA Glenn Research Center. The thermodynamic/ electrical model and mass prediction tools are described and the resulting system power and mass are shown. Three technology levels are used to predict the effect of advancements in component technology. Methods of fuel storage are compared by mass and volume. Prospects for future model development and validation at NASA as well as possible applications are also summarized.

Using GRACE and climate model simulations to predict mass loss of Alaskan glaciers through 2100

DOE PAGES

Wahr, John; Burgess, Evan; Swenson, Sean

2016-05-30

Glaciers in Alaska are currently losing mass at a rate of ~–50 Gt a –1, one of the largest ice loss rates of any regional collection of mountain glaciers on Earth. Existing projections of Alaska's future sea-level contributions tend to be divergent and are not tied directly to regional observations. Here we develop a simple, regional observation-based projection of Alaska's future sea-level contribution. We compute a time series of recent Alaska glacier mass variability using monthly GRACE gravity fields from August 2002 through December 2014. We also construct a three-parameter model of Alaska glacier mass variability based on monthly ERA-Interimmore » snowfall and temperature fields. When these three model parameters are fitted to the GRACE time series, the model explains 94% of the variance of the GRACE data. Using these parameter values, we then apply the model to simulated fields of monthly temperature and snowfall from the Community Earth System Model, to obtain predictions of mass variations through 2100. Here, we conclude that mass loss rates may increase between –80 and –110 Gt a –1by 2100, with a total sea-level rise contribution of 19 ± 4 mm during the 21st century.« less

The Future of the Mississippi Delta: Shifting Baselines, Diminishing Resilience, and Growing Non-Sustainability

NASA Astrophysics Data System (ADS)

Detrick, R. S.; Hafner, K.; Davis, J. P.; Wilson, D.; Woodward, R.

2016-12-01

Ecosystems and human communities of the Mississippi delta developed with predictable basin inputs, stable sea level, and as an open system with a high degree of interaction among drainage basin inputs, deltaic plain, and the coastal sea. Human activity changed altered the coast and lowered predictability. Management has become very energy intensive and dependent on cheap resources with more hard engineering and less ecological engineering. Pervasive alteration of the basin and delta and global change have altered the baseline and change is accelerating. Climate change projections include not only sea-level rise, but also more stronger hurricanes, increased large river floods, and more intense rainfall events and droughts. A sustainable Mississippi is outside of the boundaries of the current CMP.

A water balance model to estimate flow through the Old and Middle River corridor

USGS Publications Warehouse

Andrews, Stephen W.; Gross, Edward S.; Hutton, Paul H.

2016-01-01

We applied a water balance model to predict tidally averaged (subtidal) flows through the Old River and Middle River corridor in the Sacramento–San Joaquin Delta. We reviewed the dynamics that govern subtidal flows and water levels and adopted a simplified representation. In this water balance approach, we estimated ungaged flows as linear functions of known (or specified) flows. We assumed that subtidal storage within the control volume varies because of fortnightly variation in subtidal water level, Delta inflow, and barometric pressure. The water balance model effectively predicts subtidal flows and approaches the accuracy of a 1–D Delta hydrodynamic model. We explore the potential to improve the approach by representing more complex dynamics and identify possible future improvements.

Accounting for the Down syndrome advantage?

PubMed

Esbensen, Anna J; Seltzer, Marsha Mailick

2011-01-01

The authors examined factors that could explain the higher levels of psychosocial well being observed in past research in mothers of individuals with Down syndrome compared with mothers of individuals with other types of intellectual disabilities. The authors studied 155 mothers of adults with Down syndrome, contrasting factors that might validly account for the ?Down syndrome advantage? (behavioral phenotype) with those that have been portrayed in past research as artifactual (maternal age, social supports). The behavioral phenotype predicted less pessimism, more life satisfaction, and a better quality of the mother?child relationship. However, younger maternal age and fewer social supports, as well as the behavioral phenotype, predicted higher levels of caregiving burden. Implications for future research on families of individuals with Down syndrome are discussed.

The Future of the Mississippi Delta: Shifting Baselines, Diminishing Resilience, and Growing Non-Sustainability

NASA Astrophysics Data System (ADS)

Day, J.

2017-12-01

Ecosystems and human communities of the Mississippi delta developed with predictable basin inputs, stable sea level, and as an open system with a high degree of interaction among drainage basin inputs, deltaic plain, and the coastal sea. Human activity changed altered the coast and lowered predictability. Management has become very energy intensive and dependent on cheap resources with more hard engineering and less ecological engineering. Pervasive alteration of the basin and delta and global change have altered the baseline and change is accelerating. Climate change projections include not only sea-level rise, but also more stronger hurricanes, increased large river floods, and more intense rainfall events and droughts. A sustainable Mississippi is outside of the boundaries of the current CMP.

Multiple stressors and the potential for synergistic loss of New England salt marshes

PubMed Central

Angelini, Christine; Bertness, Mark D.

2017-01-01

Climate change and other anthropogenic stressors are converging on coastal ecosystems worldwide. Understanding how these stressors interact to affect ecosystem structure and function has immediate implications for coastal planning, however few studies quantify stressor interactions. We examined past and potential future interactions between two leading stressors on New England salt marshes: sea-level rise and marsh crab (Sesarma reticulatum) grazing driven low marsh die-off. Geospatial analyses reveal that crab-driven die-off has led to an order of magnitude more marsh loss than sea-level rise between 2005 and 2013. However, field transplant experimental results suggest that sea-level rise will facilitate crab expansion into higher elevation marsh platforms by inundating and gradually softening now-tough high marsh peat, exposing large areas to crab-driven die-off. Taking interactive effects of marsh softening and concomitant overgrazing into account, we estimate that even modest levels of sea-level rise will lead to levels of salt marsh habitat loss that are 3x greater than the additive effects of sea-level rise and crab-driven die-off would predict. These findings highlight the importance of multiple stressor studies in enhancing mechanistic understanding of ecosystem vulnerabilities to future stress scenarios and encourage managers to focus on ameliorating local stressors to break detrimental synergisms, reduce future ecosystem loss, and enhance ecosystem resilience to global change. PMID:28859097

Multiple stressors and the potential for synergistic loss of New England salt marshes.

PubMed

Crotty, Sinead M; Angelini, Christine; Bertness, Mark D

2017-01-01

Climate change and other anthropogenic stressors are converging on coastal ecosystems worldwide. Understanding how these stressors interact to affect ecosystem structure and function has immediate implications for coastal planning, however few studies quantify stressor interactions. We examined past and potential future interactions between two leading stressors on New England salt marshes: sea-level rise and marsh crab (Sesarma reticulatum) grazing driven low marsh die-off. Geospatial analyses reveal that crab-driven die-off has led to an order of magnitude more marsh loss than sea-level rise between 2005 and 2013. However, field transplant experimental results suggest that sea-level rise will facilitate crab expansion into higher elevation marsh platforms by inundating and gradually softening now-tough high marsh peat, exposing large areas to crab-driven die-off. Taking interactive effects of marsh softening and concomitant overgrazing into account, we estimate that even modest levels of sea-level rise will lead to levels of salt marsh habitat loss that are 3x greater than the additive effects of sea-level rise and crab-driven die-off would predict. These findings highlight the importance of multiple stressor studies in enhancing mechanistic understanding of ecosystem vulnerabilities to future stress scenarios and encourage managers to focus on ameliorating local stressors to break detrimental synergisms, reduce future ecosystem loss, and enhance ecosystem resilience to global change.

Predicting Liver Transplant Capacity Using Discrete Event Simulation.

PubMed

Toro-Díaz, Hector; Mayorga, Maria E; Barritt, A Sidney; Orman, Eric S; Wheeler, Stephanie B

2015-08-01

The number of liver transplants (LTs) performed in the US increased until 2006 but has since declined despite an ongoing increase in demand. This decline may be due in part to decreased donor liver quality and increasing discard of poor-quality livers. We constructed a discrete event simulation (DES) model informed by current donor characteristics to predict future LT trends through the year 2030. The data source for our model is the United Network for Organ Sharing database, which contains patient-level information on all organ transplants performed in the US. Previous analysis showed that liver discard is increasing and that discarded organs are more often from donors who are older, are obese, have diabetes, and donated after cardiac death. Given that the prevalence of these factors is increasing, the DES model quantifies the reduction in the number of LTs performed through 2030. In addition, the model estimatesthe total number of future donors needed to maintain the current volume of LTs and the effect of a hypothetical scenario of improved reperfusion technology.We also forecast the number of patients on the waiting list and compare this with the estimated number of LTs to illustrate the impact that decreased LTs will have on patients needing transplants. By altering assumptions about the future donor pool, this model can be used to develop policy interventions to prevent a further decline in this lifesaving therapy. To our knowledge, there are no similar predictive models of future LT use based on epidemiological trends. © The Author(s) 2014.

Predicting Liver Transplant Capacity Using Discrete Event Simulation

PubMed Central

Diaz, Hector Toro; Mayorga, Maria; Barritt, A. Sidney; Orman, Eric S.; Wheeler, Stephanie B.

2014-01-01

The number of liver transplants (LTs) performed in the US increased until 2006, but has since declined despite an ongoing increase in demand. This decline may be due in part to decreased donor liver quality and increasing discard of poor quality livers. We constructed a Discrete Event Simulation (DES) model informed by current donor characteristics to predict future LT trends through the year 2030. The data source for our model is the United Network for Organ Sharing database, which contains patient level information on all organ transplants performed in the US. Previous analysis showed that liver discard is increasing and that discarded organs are more often from donors who are older, obese, have diabetes, and donated after cardiac death. Given that the prevalence of these factors is increasing, the DES model quantifies the reduction in the number of LTs performed through 2030. In addition, the model estimates the total number of future donors needed to maintain the current volume of LTs, and the effect of a hypothetical scenario of improved reperfusion technology. We also forecast the number of patients on the waiting list and compare this to the estimated number of LTs to illustrate the impact that decreased LTs will have on patients needing transplants. By altering assumptions about the future donor pool, this model can be used to develop policy interventions to prevent a further decline in this life saving therapy. To our knowledge, there are no similar predictive models of future LT use based on epidemiologic trends. PMID:25391681

Perceptions of vulnerability to a future outbreak: a study of horse managers affected by the first Australian equine influenza outbreak

PubMed Central

2013-01-01

Background A growing body of work shows the benefits of applying social cognitive behavioural theory to investigate infection control and biosecurity practices. Protection motivation theory has been used to predict protective health behaviours. The theory outlines that a perception of a lack of vulnerability to a disease contributes to a reduced threat appraisal, which results in poorer motivation, and is linked to poorer compliance with advised health protective behaviours. This study, conducted following the first-ever outbreak of equine influenza in Australia in 2007, identified factors associated with horse managers’ perceived vulnerability to a future equine influenza outbreak. Results Of the 200 respondents, 31.9% perceived themselves to be very vulnerable, 36.6% vulnerable and 31.4% not vulnerable to a future outbreak of equine influenza. Multivariable logistic regression modelling revealed that managers involved in horse racing and those on rural horse premises perceived themselves to have low levels of vulnerability. Managers of horse premises that experienced infection in their horses in 2007 and those seeking infection control information from specific sources reported increased levels of perceived vulnerability to a future outbreak. Conclusion Different groups across the horse industry perceived differing levels of vulnerability to a future outbreak. Increased vulnerability contributes to favourable infection control behaviour and hence these findings are important for understanding uptake of recommended infection control measures. Future biosecurity communication strategies should be delivered through information sources suitable for the horse racing and rural sectors. PMID:23902718

Perceptions of vulnerability to a future outbreak: a study of horse managers affected by the first Australian equine influenza outbreak.

PubMed

Schemann, Kathrin; Firestone, Simon M; Taylor, Melanie R; Toribio, Jenny-Ann L M L; Ward, Michael P; Dhand, Navneet K

2013-07-31

A growing body of work shows the benefits of applying social cognitive behavioural theory to investigate infection control and biosecurity practices. Protection motivation theory has been used to predict protective health behaviours. The theory outlines that a perception of a lack of vulnerability to a disease contributes to a reduced threat appraisal, which results in poorer motivation, and is linked to poorer compliance with advised health protective behaviours. This study, conducted following the first-ever outbreak of equine influenza in Australia in 2007, identified factors associated with horse managers' perceived vulnerability to a future equine influenza outbreak. Of the 200 respondents, 31.9% perceived themselves to be very vulnerable, 36.6% vulnerable and 31.4% not vulnerable to a future outbreak of equine influenza. Multivariable logistic regression modelling revealed that managers involved in horse racing and those on rural horse premises perceived themselves to have low levels of vulnerability. Managers of horse premises that experienced infection in their horses in 2007 and those seeking infection control information from specific sources reported increased levels of perceived vulnerability to a future outbreak. Different groups across the horse industry perceived differing levels of vulnerability to a future outbreak. Increased vulnerability contributes to favourable infection control behaviour and hence these findings are important for understanding uptake of recommended infection control measures. Future biosecurity communication strategies should be delivered through information sources suitable for the horse racing and rural sectors.

Using Formal Grammars to Predict I/O Behaviors in HPC: The Omnisc'IO Approach

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

Dorier, Matthieu; Ibrahim, Shadi; Antoniu, Gabriel

2016-08-01

The increasing gap between the computation performance of post-petascale machines and the performance of their I/O subsystem has motivated many I/O optimizations including prefetching, caching, and scheduling. In order to further improve these techniques, modeling and predicting spatial and temporal I/O patterns of HPC applications as they run has become crucial. In this paper we present Omnisc'IO, an approach that builds a grammar-based model of the I/O behavior of HPC applications and uses it to predict when future I/O operations will occur, and where and how much data will be accessed. To infer grammars, Omnisc'IO is based on StarSequitur, amore » novel algorithm extending Nevill-Manning's Sequitur algorithm. Omnisc'IO is transparently integrated into the POSIX and MPI I/O stacks and does not require any modification in applications or higher-level I/O libraries. It works without any prior knowledge of the application and converges to accurate predictions of any N future I/O operations within a couple of iterations. Its implementation is efficient in both computation time and memory footprint.« less

The Behavioral Economics of Young Adult Substance Abuse

PubMed Central

Murphy, James G.; Dennhardt, Ashley A.

2016-01-01

Alcohol and drug use peaks during young adulthood and can interfere with critical developmental tasks and set the stage for chronic substance misuse and associated social, educational, and health-related outcomes. There is a need for novel, theory-based approaches to guide substance abuse prevention efforts during this critical developmental period. This paper discusses the particular relevance of behavioral economic theory to young adult alcohol and drug misuse, and reviews available literature on prevention and intervention strategies that are consistent with behavioral economic theory. Behavioral economic theory predicts that decisions to use drugs and alcohol are related to the relative availability and price of both alcohol and substance-free alternative activities, and the extent to which reinforcement from delayed substance-free outcomes is devalued relative to the immediate reinforcement associated with drugs. Behavioral economic measures of motivation for substance use are based on relative levels of behavioral and economic resource allocation towards drug versus alternatives, and have been shown to predict change in substance use over time. Policy and individual level prevention approaches that are consistent with behavioral economic theory are discussed, including brief interventions that increase future orientation and engagement in rewarding alternatives to substance use. Prevention approaches that increase engagement in constructive future-oriented activities among young adults (e.g., educational/vocational success) have the potential to reduce future health disparities associated with both substance abuse and poor educational/vocational outcomes. PMID:27151545

Multilevel landscape utilization of the Siberian flying squirrel: Scale effects on species habitat use.

PubMed

Remm, Jaanus; Hanski, Ilpo K; Tuominen, Sakari; Selonen, Vesa

2017-10-01

Animals use and select habitat at multiple hierarchical levels and at different spatial scales within each level. Still, there is little knowledge on the scale effects at different spatial levels of species occupancy patterns. The objective of this study was to examine nonlinear effects and optimal-scale landscape characteristics that affect occupancy of the Siberian flying squirrel, Pteromys volans , in South- and Mid-Finland. We used presence-absence data ( n  = 10,032 plots of 9 ha) and novel approach to separate the effects on site-, landscape-, and regional-level occupancy patterns. Our main results were: landscape variables predicted the placement of population patches at least twice as well as they predicted the occupancy of particular sites; the clear optimal value of preferred habitat cover for species landscape-level abundance is a surprisingly low value (10% within a 4 km buffer); landscape metrics exert different effects on species occupancy and abundance in high versus low population density regions of our study area. We conclude that knowledge of regional variation in landscape utilization will be essential for successful conservation of the species. The results also support the view that large-scale landscape variables have high predictive power in explaining species abundance. Our study demonstrates the complex response of species occurrence at different levels of population configuration on landscape structure. The study also highlights the need for data in large spatial scale to increase the precision of biodiversity mapping and prediction of future trends.

Projected climate-induced faunal change in the Western Hemisphere

USGS Publications Warehouse

Lawler, J.J.; Shafer, S.L.; White, D.; Kareiva, P.; Maurer, E.P.; Blaustein, A.R.; Bartlein, P.J.

2009-01-01

Climate change is predicted to be one of the greatest drivers of ecological change in the coming century. Increases in temperature over the last century have clearly been linked to shifts in species distributions. Given the magnitude of projected future climatic changes, we can expect even larger range shifts in the coming century. These changes will, in turn, alter ecological communities and the functioning of ecosystems. Despite the seriousness of predicted climate change, the uncertainty in climate-change projections makes it difficult for conservation managers and planners to proactively respond to climate stresses. To address one aspect of this uncertainty, we identified predictions of faunal change for which a high level of consensus was exhibited by different climate models. Specifically, we assessed the potential effects of 30 coupled atmosphere-ocean general circulation model (AOGCM) future-climate simulations on the geographic ranges of 2954 species of birds, mammals, and amphibians in the Western Hemisphere. Eighty percent of the climate projections based on a relatively low greenhouse-gas emissions scenario result in the local loss of at least 10% of the vertebrate fauna over much of North and South America. The largest changes in fauna are predicted for the tundra, Central America, and the Andes Mountains where, assuming no dispersal constraints, specific areas are likely to experience over 90% turnover, so that faunal distributions in the future will bear little resemblance to those of today. ?? 2009 by the Ecological Society of America.

Implications of next generation attenuation ground motion prediction equations for site coefficients used in earthquake resistant design

USGS Publications Warehouse

Borcherdt, Roger D.

2014-01-01

Proposals are developed to update Tables 11.4-1 and 11.4-2 of Minimum Design Loads for Buildings and Other Structures published as American Society of Civil Engineers Structural Engineering Institute standard 7-10 (ASCE/SEI 7–10). The updates are mean next generation attenuation (NGA) site coefficients inferred directly from the four NGA ground motion prediction equations used to derive the maximum considered earthquake response maps adopted in ASCE/SEI 7–10. Proposals include the recommendation to use straight-line interpolation to infer site coefficients at intermediate values of (average shear velocity to 30-m depth). The NGA coefficients are shown to agree well with adopted site coefficients at low levels of input motion (0.1 g) and those observed from the Loma Prieta earthquake. For higher levels of input motion, the majority of the adopted values are within the 95% epistemic-uncertainty limits implied by the NGA estimates with the exceptions being the mid-period site coefficient, Fv, for site class D and the short-period coefficient, Fa, for site class C, both of which are slightly less than the corresponding 95% limit. The NGA data base shows that the median value  of 913 m/s for site class B is more typical than 760 m/s as a value to characterize firm to hard rock sites as the uniform ground condition for future maximum considered earthquake response ground motion estimates. Future updates of NGA ground motion prediction equations can be incorporated easily into future adjustments of adopted site coefficients using procedures presented herein. 

The influence of current and future climate on the spatial distribution of coccidioidomycosis in the southwestern United States

NASA Astrophysics Data System (ADS)

Gorris, M. E.; Hoffman, F. M.; Zender, C. S.; Treseder, K. K.; Randerson, J. T.

2017-12-01

Coccidioidomycosis, otherwise known as valley fever, is an infectious fungal disease currently endemic to the southwestern U.S. The magnitude, spatial distribution, and seasonality of valley fever incidence is shaped by variations in regional climate. As such, climate change may cause new communities to become at risk for contracting this disease. Humans contract valley fever by inhaling fungal spores of the genus Coccidioides. Coccidioides grow in the soil as a mycelium, and when stressed, autolyze into spores 2-5 µm in length. Spores can become airborne from any natural or anthropogenic soil disturbance, which can be exacerbated by dry soil conditions. Understanding the relationship between climate and valley fever incidence is critical for future disease risk management. We explored several multivariate techniques to create a predictive model of county-level valley fever incidence throughout the southwestern U.S., including Arizona, California, New Mexico, Nevada, and Utah. We incorporated surface air temperature, precipitation, soil moisture, surface dust concentrations, leaf area index, and the amount of agricultural land, all of which influence valley fever incidence. A log-linear regression model that incorporated surface air temperature, soil moisture, surface dust concentration, and the amount of agricultural land explained 34% of the county-level variance in annual average valley fever incidence. We used this model to predict valley fever incidence for the Representative Concentration Pathway 8.5 using simulation output from the Community Earth System Model. In our analysis, we describe how regional hotspots of valley fever incidence may shift with sustained warming and drying in the southwestern U.S. Our predictive model of valley fever incidence may help mitigate future health impacts of valley fever by informing health officials and policy makers of the climate conditions suitable for disease outbreak.

Linking climate, gross primary productivity, and site index across forests of the western United States

Treesearch

Aaron R. Weiskittel; Nicholas L. Crookston; Philip J. Radtke

2011-01-01

Assessing forest productivity is important for developing effective management regimes and predicting future growth. Despite some important limitations, the most common means for quantifying forest stand-level potential productivity is site index (SI). Another measure of productivity is gross primary production (GPP). In this paper, SI is compared with GPP estimates...

A Generic Service-Oriented Cost Model for Student Admissions Registration

ERIC Educational Resources Information Center

Pena, Philip Edward

2017-01-01

State support of community colleges has been reduced in recent years and is not expected to recover to previous levels, even though costs continue to rise. While many colleges have increased tuition in response to this situation, students cannot afford endless increases in tuition. While predicting the future is difficult, it is likely that…

Risk of Future Suicide Attempts in Adolescent Psychiatric Inpatients at 18-Month Follow-Up.

ERIC Educational Resources Information Center

Brinkman-Sull, David C.; Overholser, James C.; Silverman, Eden

2000-01-01

Investigates potential predictors of suicidal behavior in adolescent psychiatric patients (N=60) during an 18-month follow-up period. Follow-up suicidality was most strongly predicted by high intake levels of hopelessness, and an increase in or persistent problems with depression. Proposes a model in which the impact of family functioning on…

West Antarctic Ice Sheet Initiative. Volume 2: Discipline Reviews

NASA Technical Reports Server (NTRS)

Bindschadler, Robert A. (Editor)

1991-01-01

Seven discipline review papers are presented on the state of the knowledge of West Antarctica and opinions on how that knowledge must be increased to predict the future behavior of this ice sheet and to assess its potential to collapse, rapidly raising the global sea level. These are the goals of the West Antarctic Ice Sheet Initiative (WAIS).

Psychosocial Stress Predicts Future Symptom Severities in Children and Adolescents with Tourette Syndrome and/or Obsessive-Compulsive Disorder

ERIC Educational Resources Information Center

Lin, Haiqun; Katsovich, Liliya; Ghebremichael, Musie; Findley, Diane B.; Grantz, Heidi; Lombroso, Paul J.; King, Robert A.; Zhang, Heping; Leckman, James F.

2007-01-01

Background: The goals of this prospective longitudinal study were to monitor levels of psychosocial stress in children and adolescents with Tourette syndrome (TS) and/or obsessive-compulsive disorder (OCD) compared to healthy control subjects and to examine the relationship between measures of psychosocial stress and fluctuations in tic,…

Autistic Symptoms in Childhood Arrestees: Longitudinal Association with Delinquent Behavior

ERIC Educational Resources Information Center

Geluk, Charlotte A. M. L.; Jansen, Lucres M. C.; Vermeiren, Robert; Doreleijers, Theo A. H.; van Domburgh, Lieke; de Bildt, Annelies; Twisk, Jos W. R.; Hartman, Catharina A.

2012-01-01

Background: To compare childhood arrestees with matched comparison groups on levels of autistic symptoms and to assess the unique predictive value of autistic symptoms for future delinquent behavior in childhood arrestees. Methods: Childhood first-time arrestees (n = 308, baseline age 10.7 plus or minus 1.5 years) were followed up for 2 years.…

Future Directions in Vulnerability to Depression among Youth: Integrating Risk Factors and Processes across Multiple Levels of Analysis

PubMed Central

Hankin, Benjamin L.

2014-01-01

Depression is a developmental phenomenon. Considerable progress has been made in describing the syndrome, establishing its prevalence and features, providing clues as to its etiology, and developing evidence-based treatment and prevention options. Despite considerable headway in distinct lines of vulnerability research, there is an explanatory gap in the field ability to more comprehensively explain and predict who is likely to become depressed, when, and why. Still, despite clear success in predicting moderate variance for future depression, especially with empirically rigorous methods and designs, the heterogeneous and multi-determined nature of depression suggests that additional etiologies need to be included to advance knowledge on developmental pathways to depression. This paper advocates for a multiple levels of analysis approach to investigating vulnerability to depression across the lifespan and providing a more comprehensive understanding of its etiology. One example of a multiple levels of analysis model of vulnerabilities to depression is provided that integrates the most accessible, observable factors (e.g., cognitive and temperament risks), intermediate processes and endophenotypes (e.g., information processing biases, biological stress physiology, and neural activation and connectivity), and genetic influences (e.g., candidate genes and epigenetics). Evidence for each of these factors as well as their cross-level integration is provided. Methodological and conceptual considerations important for conducting integrative, multiple levels of depression vulnerability research are discussed. Finally, translational implications for how a multiple levels of analysis perspective may confer additional leverage to reduce the global burden of depression and improve care are considered. PMID:22900513

Future Orientation, Social Support, and Psychological Adjustment among Left-behind Children in Rural China: A Longitudinal Study.

PubMed

Su, Shaobing; Li, Xiaoming; Lin, Danhua; Zhu, Maoling

2017-01-01

Existing research has found that parental migration may negatively impact the psychological adjustment of left-behind children. However, limited longitudinal research has examined if and how future orientation (individual protective factor) and social support (contextual protective factor) are associated with the indicators of psychological adjustment (i.e., life satisfaction, school satisfaction, happiness, and loneliness) of left-behind children. In the current longitudinal study, we examined the differences in psychological adjustment between left-behind children and non-left behind children (comparison children) in rural areas, and explored the protective roles of future orientation and social support on the immediate (cross-sectional effects) and subsequent (lagged effects) status of psychological adjustment for both groups of children, respectively. The sample included 897 rural children ( M age = 14.09, SD = 1.40) who participated in two waves of surveys across six months. Among the participants, 227 were left-behind children with two parents migrating, 176 were with one parent migrating, and 485 were comparison children. Results showed that, (1) left-behind children reported lower levels of life satisfaction, school satisfaction, and happiness, as well as a higher level of loneliness in both waves; (2) After controlling for several demographics and characteristics of parental migration among left-behind children, future orientation significantly predicted life satisfaction, school satisfaction, and happiness in both cross-sectional and longitudinal regression models, as well as loneliness in the longitudinal regression analysis. Social support predicted immediate life satisfaction, school satisfaction, and happiness, as well as subsequent school satisfaction. Similar to left-behind children, comparison children who reported higher scores in future orientation, especially future expectation, were likely to have higher scores in most indicators of psychological adjustment measured at the same time and subsequently. However, social support seemed not exhibit as important in the immediate status of psychological adjustment of comparison children as that of left-behind children. Findings, implications, and limitations of the present study were discussed.

Risk levels of invasive Fusarium oxysporum f. sp. in areas suitable for date palm (Phoenix dactylifera) cultivation under various climate change projections.

PubMed

Shabani, Farzin; Kumar, Lalit

2013-01-01

Global climate model outputs involve uncertainties in prediction, which could be reduced by identifying agreements between the output results of different models, covering all assumptions included in each. Fusarium oxysporum f.sp. is an invasive pathogen that poses risk to date palm cultivation, among other crops. Therefore, in this study, the future distribution of invasive Fusarium oxysporum f.sp., confirmed by CSIRO-Mk3.0 (CS) and MIROC-H (MR) GCMs, was modeled and combined with the future distribution of date palm predicted by the same GCMs, to identify areas suitable for date palm cultivation with different risk levels of invasive Fusarium oxysporum f.sp., for 2030, 2050, 2070 and 2100. Results showed that 40%, 37%, 33% and 28% areas projected to become highly conducive to date palm are under high risk of its lethal fungus, compared with 37%, 39%, 43% and 42% under low risk, for the chosen years respectively. Our study also indicates that areas with marginal risk will be limited to 231, 212, 186 and 172 million hectares by 2030, 2050, 2070 and 2100. The study further demonstrates that CLIMEX outputs refined by a combination of different GCMs results of different species that have symbiosis or parasite relationship, ensure that the predictions become robust, rather than producing hypothetical findings, limited purely to publication.

Risk Levels of Invasive Fusarium oxysporum f. sp. in Areas Suitable for Date Palm (Phoenix dactylifera) Cultivation under Various Climate Change Projections

PubMed Central

Shabani, Farzin; Kumar, Lalit

2013-01-01

Global climate model outputs involve uncertainties in prediction, which could be reduced by identifying agreements between the output results of different models, covering all assumptions included in each. Fusarium oxysporum f.sp. is an invasive pathogen that poses risk to date palm cultivation, among other crops. Therefore, in this study, the future distribution of invasive Fusarium oxysporum f.sp., confirmed by CSIRO-Mk3.0 (CS) and MIROC-H (MR) GCMs, was modeled and combined with the future distribution of date palm predicted by the same GCMs, to identify areas suitable for date palm cultivation with different risk levels of invasive Fusarium oxysporum f.sp., for 2030, 2050, 2070 and 2100. Results showed that 40%, 37%, 33% and 28% areas projected to become highly conducive to date palm are under high risk of its lethal fungus, compared with 37%, 39%, 43% and 42% under low risk, for the chosen years respectively. Our study also indicates that areas with marginal risk will be limited to 231, 212, 186 and 172 million hectares by 2030, 2050, 2070 and 2100. The study further demonstrates that CLIMEX outputs refined by a combination of different GCMs results of different species that have symbiosis or parasite relationship, ensure that the predictions become robust, rather than producing hypothetical findings, limited purely to publication. PMID:24340100

DNDO Report: Predicting Solar Modulation Potentials for Modeling Cosmic Background Radiation

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

Behne, Patrick Alan

The modeling of the detectability of special nuclear material (SNM) at ports and border crossings requires accurate knowledge of the background radiation at those locations. Background radiation originates from two main sources, cosmic and terrestrial. Cosmic background is produced by high-energy galactic cosmic rays (GCR) entering the atmosphere and inducing a cascade of particles that eventually impact the earth’s surface. The solar modulation potential represents one of the primary inputs to modeling cosmic background radiation. Usosokin et al. formally define solar modulation potential as “the mean energy loss [per unit charge] of a cosmic ray particle inside the heliosphere…” Modulationmore » potential, a function of elevation, location, and time, shares an inverse relationship with cosmic background radiation. As a result, radiation detector thresholds require adjustment to account for differing background levels, caused partly by differing solar modulations. Failure to do so can result in higher rates of false positives and failed detection of SNM for low and high levels of solar modulation potential, respectively. This study focuses on solar modulation’s time dependence, and seeks the best method to predict modulation for future dates using Python. To address the task of predicting future solar modulation, we utilize both non-linear least squares sinusoidal curve fitting and cubic spline interpolation. This material will be published in transactions of the ANS winter meeting of November, 2016.« less

Forecasting the probability of future groundwater levels declining below specified low thresholds in the conterminous U.S.

USGS Publications Warehouse

Dudley, Robert W.; Hodgkins, Glenn A.; Dickinson, Jesse

2017-01-01

We present a logistic regression approach for forecasting the probability of future groundwater levels declining or maintaining below specific groundwater-level thresholds. We tested our approach on 102 groundwater wells in different climatic regions and aquifers of the United States that are part of the U.S. Geological Survey Groundwater Climate Response Network. We evaluated the importance of current groundwater levels, precipitation, streamflow, seasonal variability, Palmer Drought Severity Index, and atmosphere/ocean indices for developing the logistic regression equations. Several diagnostics of model fit were used to evaluate the regression equations, including testing of autocorrelation of residuals, goodness-of-fit metrics, and bootstrap validation testing. The probabilistic predictions were most successful at wells with high persistence (low month-to-month variability) in their groundwater records and at wells where the groundwater level remained below the defined low threshold for sustained periods (generally three months or longer). The model fit was weakest at wells with strong seasonal variability in levels and with shorter duration low-threshold events. We identified challenges in deriving probabilistic-forecasting models and possible approaches for addressing those challenges.

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach-A Case Study for the City of Wuhan in China.

PubMed

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-06-15

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study-simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.

Social stress, economic hardship, and psychological distress as predictors of sustained abstinence from substance use after treatment.

PubMed

Wahler, Elizabeth A; Otis, Melanie D

2014-11-01

Social characteristics associated with disadvantage, such as racial/ethnic minority status, female gender, and low socioeconomic status (SES), are often associated with increased psychological distress and substance use disorders. This project tests a conceptual model derived from Pearlin's social stress theory for predicting abstinence from substance use between baseline and 1-year follow-up in secondary data from a large statewide sample of Kentucky substance abuse treatment participants (N = 1,123). Racial minority status, employment, and higher education level were predictive of substance use at follow-up, while female gender was predictive of abstinence. Limitations, implications for practice, and suggestions for future research are discussed.

Effects of ocean acidification and sea-level rise on coral reefs

USGS Publications Warehouse

Yates, K.K.; Moyer, R.P.

2010-01-01

U.S. Geological Survey (USGS) scientists are developing comprehensive records of historical and modern coral reef growth and calcification rates relative to changing seawater chemistry resulting from increasing atmospheric CO2 from the pre-industrial period to the present. These records will provide the scientific foundation for predicting future impacts of ocean acidification and sea-level rise on coral reef growth. Changes in coral growth rates in response to past changes in seawater pH are being examined by using cores from coral colonies.

Wildlife habitat connectivity in the changing climate of New York's Hudson Valley.

PubMed

Howard, Timothy G; Schlesinger, Matthew D

2013-09-01

Maintaining and restoring connectivity are key adaptation strategies for biodiversity conservation under climate change. We present a novel combination of species distribution and connectivity modeling using current and future climate regimes to prioritize connections among populations of 26 rare species in New York's Hudson Valley. We modeled patches for each species for each time period and modeled potential connections among habitat patches by finding the least-cost path for every patch-to-patch connection. Finally, we aggregated these patches and paths to the tax parcel, commonly the primary unit of conservation action. Under future climate regimes, suitable habitat was predicted to contract or appear upslope and farther north. On average, predicted patches were nine times smaller and paths were twice as long under future climate. Parcels within the Hudson Highlands, Shawangunk Ridge, Catskill Mountains, and Harlem Valley had high species overlap, with areas upslope and northward increasing in importance over time. We envision that land managers and conservation planners can use these results to help prioritize parcel-level conservation and management and thus support biodiversity adaptation to climate change. © 2013 New York Academy of Sciences.

Assessing Risk for Future Firearms Violence in Young People Who Present to ED.

PubMed

2017-06-01

A new clinical index tool designed specifically for the emergency environment predicts the risk for future firearms violence in young people 14-24 years of age. The approach employs a brief, 10-point instrument that can be administered in one to two minutes, according to investigators. They also note that while the tool is based on data from a single ED in Flint, Ml, the tool should be applicable to urban EDs in regions that have similar characteristics. To create the tool, investigators used data from the Flint Youth Injury Study, an investigation of a group of patients 14-24 years of age who reported using drugs in the previous six months and accessed care at a Level I trauma center. Using a machine learning classification approach, investigators combed through the data, finding that the most predictive factors for firearm violence could be categorized into four domains: peer and partner violence victimization, community violence exposure, peer/family influences, and fighting. Ideally, investigators note the tool will be employed along with interventions targeted toward patients at high risk for future firearms violence.

Elevated CO2 maintains grassland net carbon uptake under a future heat and drought extreme

PubMed Central

Roy, Jacques; Picon-Cochard, Catherine; Augusti, Angela; Benot, Marie-Lise; Thiery, Lionel; Darsonville, Olivier; Landais, Damien; Piel, Clément; Defossez, Marc; Devidal, Sébastien; Escape, Christophe; Ravel, Olivier; Fromin, Nathalie; Volaire, Florence; Milcu, Alexandru; Bahn, Michael; Soussana, Jean-François

2016-01-01

Extreme climatic events (ECEs) such as droughts and heat waves are predicted to increase in intensity and frequency and impact the terrestrial carbon balance. However, we lack direct experimental evidence of how the net carbon uptake of ecosystems is affected by ECEs under future elevated atmospheric CO2 concentrations (eCO2). Taking advantage of an advanced controlled environment facility for ecosystem research (Ecotron), we simulated eCO2 and extreme cooccurring heat and drought events as projected for the 2050s and analyzed their effects on the ecosystem-level carbon and water fluxes in a C3 grassland. Our results indicate that eCO2 not only slows down the decline of ecosystem carbon uptake during the ECE but also enhances its recovery after the ECE, as mediated by increases of root growth and plant nitrogen uptake induced by the ECE. These findings indicate that, in the predicted near future climate, eCO2 could mitigate the effects of extreme droughts and heat waves on ecosystem net carbon uptake. PMID:27185934

Future Weather Forecasting in the Year 2020-Investing in Technology Today: Improving Weather and Environmental Predictions

NASA Technical Reports Server (NTRS)

Anthes, Richard; Schoeberl, Mark

2000-01-01

Fast-forward twenty years to the nightly simultaneous TV/webcast. Accurate 8-14 day regional forecasts will be available as will be a whole host of linked products including economic impact, travel, energy usage, etc. On-demand, personalized street-level forecasts will be downloaded into your PDA. Your home system will automatically update the products of interest to you (e.g. severe storm forecasts, hurricane predictions, etc). Short and long range climate forecasts will be used by your "Quicken 2020" to make suggest changes in your "futures" investment portfolio. Through a lively and informative multi-media presentation, leading Space-Earth Science Researchers and Technologists will share their vision for the year 2020, offering a possible futuristic forecast enabled through the application of new technologies under development today. Copies of the 'broadcast' will be available on Beta Tape for your own future use. If sufficient interest exists, the program may also be made available for broadcasters wishing to do stand-ups with roll-ins from the San Francisco meeting for their viewers back home.

Bioinformatic analyses to select phenotype affecting polymorphisms in HTR2C gene.

PubMed

Piva, Francesco; Giulietti, Matteo; Baldelli, Luisa; Nardi, Bernardo; Bellantuono, Cesario; Armeni, Tatiana; Saccucci, Franca; Principato, Giovanni

2011-08-01

Single nucleotide polymorphisms (SNPs) in serotonin related genes influence mental disorders, responses to pharmacological and psychotherapeutic treatments. In planning association studies, researchers that want to investigate new SNPs have to select some among a large number of candidates. Our aim is to guide researchers in the selection of the most likely phenotype affecting polymorphisms. Here, we studied serotonin receptor 2C (HTR2C) SNPs because, till now, only relatively few of about 2000 are investigated. We used the most updated and assessed bioinformatic tools to predict which variations can give rise to biological effects among 2450 HTR2C SNPs. We suggest 48 SNPs that are worth considering in future association studies in the field of psychiatry, psychology and pharmacogenomics. Moreover, our analyses point out the biological level probably affected, such as transcription, splicing, miRNA regulation and protein structure, thus allowing to suggest future molecular investigations. Although few association studies are available in literature, their results are in agreement with our predictions, showing that our selection methods can help to guide future association studies. Copyright © 2011 John Wiley & Sons, Ltd.

Prospective associations between adolescent mental health problems and positive mental wellbeing in early old age.

PubMed

Nishida, Atsushi; Richards, Marcus; Stafford, Mai

2016-01-01

Mental health problems in adolescence are predictive of future mental distress and psychopathology; however, few studies investigated adolescent mental health problems in relation to future mental wellbeing and none with follow-up to older age. To test prospective associations between adolescent mental health problems and mental wellbeing and life satisfaction in early old age. A total of 1561 men and women were drawn from the Medical Research Council National Survey of Health and Development (the British 1946 birth cohort). Teachers had previously completed rating scales to assess emotional adjustment and behaviours, which allowed us to extract factors of mental health problems measuring self-organisation, behavioural problems, and emotional problems during adolescence. Between the ages of 60-64 years, mental wellbeing was assessed using the Warwick-Edinburgh Mental Well-being Scale (WEMWBS) and life satisfaction was self-reported using the Satisfaction with Life Scale (SWLS). After controlling for gender, social class of origin, childhood cognitive ability, and educational attainment, adolescent emotional problems were independently inversely associated with mental wellbeing and with life satisfaction. Symptoms of anxiety/depression at 60-64 years explained the association with life satisfaction but not with mental wellbeing. Associations between adolescent self-organisation and conduct problems and mental wellbeing and life satisfaction were of negligible magnitude, but higher childhood cognitive ability significantly predicted poor life satisfaction in early old age. Adolescent self-organisation and conduct problems may not be predictive of future mental wellbeing and life satisfaction. Adolescent emotional problems may be inversely associated with future wellbeing, and may be associated with lower levels of future life satisfaction through symptoms of anxiety/depression in early old age. Initiatives to prevent and treat emotional problems in adolescence may have long-term benefits which extend into older age.

A Theory of Sex Differences in Technical Aptitude and Some Supporting Evidence.

PubMed

Schmidt, Frank L

2011-11-01

In this article, I present a theory that explains the origin of sex differences in technical aptitudes. The theory takes as proven that there are no sex differences in general mental ability (GMA), and it postulates that sex differences in technical aptitude (TA) stem from differences in experience in technical areas, which is in turn based on sex differences in technical interests. Using a large data set, I tested and found support for four predictions made by this theory: (a) the construct level correlation between technical aptitude and GMA is larger for females than males, (b) the observed and true score variability of technical aptitude is greater among males than females, (c) at every level of GMA females have lower levels of technical aptitude, and (d) technical aptitude measures used as estimates of GMA for decision purposes would result in underestimation of GMA levels for girls and women. Given that GMA carries the weight of prediction of job performance, the support found for this last prediction suggests that, for many jobs, technical aptitude tests may underpredict the job performance of female applicants and employees. Future research should examine this question. © Association for Psychological Science 2011.

Intolerance of uncertainty as a predictor of post-traumatic stress symptoms following a traumatic event.

PubMed

Oglesby, Mary E; Boffa, Joseph W; Short, Nicole A; Raines, Amanda M; Schmidt, Norman B

2016-06-01

Intolerance of uncertainty (IU) has been associated with elevated post-traumatic stress symptoms (PTSS) in the extant literature. However, no research to date has investigated whether pre-trauma IU predicts PTSS following trauma exposure. The current study prospectively examined the relationship between IU and PTSS within a sample of individuals with various levels of exposure to a university campus shooting. We hypothesized that pre-trauma IU would predict elevated PTSS following a campus shooting, even after covarying for anxiety sensitivity (AS), a known correlate of PTSS. Participants included undergraduates (n=77) who completed a self-report battery in Introductory Psychology. After a campus shooting, they were invited to complete measures of PTSD symptoms and level of exposure to the shooting. As anticipated, results revealed pre-trauma IU as a significant predictor of elevated PTSS following the campus shooting. These results remained significant after covarying for pre-trauma levels of AS. Our results are the first to demonstrate that elevated pre-trauma levels of IU predict later PTSS following exposure to a traumatic event. This finding is discussed in terms of promising directions for future research and treatment strategies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Serum creatinine role in predicting outcome after cardiac surgery beyond acute kidney injury

PubMed Central

Najafi, Mahdi

2014-01-01

Serum creatinine is still the most important determinant in the assessment of perioperative renal function and in the prediction of adverse outcome in cardiac surgery. Many biomarkers have been studied to date; still, there is no surrogate for serum creatinine measurement in clinical practice because it is feasible and inexpensive. High levels of serum creatinine and its equivalents have been the most important preoperative risk factor for postoperative renal injury. Moreover, creatinine is the mainstay in predicting risk models and risk factor reduction has enhanced its importance in outcome prediction. The future perspective is the development of new definitions and novel tools for the early diagnosis of acute kidney injury largely based on serum creatinine and a panel of novel biomarkers. PMID:25276301

PRODUCTION AND ECONOMIC OPTIMIZATION OF DIETARY PROTEIN AND CARBOHYDRATE IN THE CULTURE OF JUVENILE SEA URCHIN Lytechinus variegatus

PubMed Central

Heflin, Laura E.; Makowsky, Robert; Taylor, J. Christopher; Williams, Michael B.; Lawrence, Addison L.; Watts, Stephen A.

2016-01-01

Juvenile Lytechinus variegatus (ca. 3.95± 0.54 g) were fed one of 10 formulated diets with different protein (ranging from 11- 43%) and carbohydrate (12 or 18%; brackets determined from previous studies) levels. Urchins (n= 16 per treatment) were fed a daily sub-satiation ration equivalent to 2.0% of average body weight for 10 weeks. Our objective was (1) to create predictive models of growth, production and efficiency outcomes and (2) to generate economic analysis models in relation to these dietary outcomes for juvenile L. variegatus held in culture. At dietary protein levels below ca. 30%, models for most growth and production outcomes predicted increased rates of growth and production among urchins fed diets containing 18% dietary carbohydrate levels as compared to urchins fed diets containing 12% dietary carbohydrate. For most outcomes, growth and production was predicted to increase with increasing level of dietary protein up to ca. 30%, after which, no further increase in growth and production were predicted. Likewise, dry matter production efficiency was predicted to increase with increasing protein level up to ca. 30%, with urchins fed diets with 18% carbohydrate exhibiting greater efficiency than those fed diets with 12% carbohydrate. The energetic cost of dry matter production was optimal at protein levels less than those required for maximal weight gain and gonad production, suggesting an increased energetic cost (decreased energy efficiency) is required to increase gonad production relative to somatic growth. Economic analysis models predict when cost of feed ingredients are low, the lowest cost per gram of wet weight gain will occur at 18% dietary carbohydrate and ca. 25- 30% dietary protein. In contrast, lowest cost per gram of wet weight gain will occur at 12% dietary carbohydrate and ca. 35- 40% dietary protein when feed ingredient costs are high or average. For both 18 and 12% levels of dietary carbohydrate, cost per gram of wet weight gain is predicted to be maximized at low dietary protein levels, regardless of feed ingredient costs. These models will compare dietary requirements and growth outcomes in relation to economic costs and provide insight for future commercialization of sea urchin aquaculture. PMID:28082753

PRODUCTION AND ECONOMIC OPTIMIZATION OF DIETARY PROTEIN AND CARBOHYDRATE IN THE CULTURE OF JUVENILE SEA URCHIN Lytechinus variegatus.

PubMed

Heflin, Laura E; Makowsky, Robert; Taylor, J Christopher; Williams, Michael B; Lawrence, Addison L; Watts, Stephen A

2016-10-01

Juvenile Lytechinus variegatus (ca. 3.95± 0.54 g) were fed one of 10 formulated diets with different protein (ranging from 11- 43%) and carbohydrate (12 or 18%; brackets determined from previous studies) levels. Urchins (n= 16 per treatment) were fed a daily sub-satiation ration equivalent to 2.0% of average body weight for 10 weeks. Our objective was (1) to create predictive models of growth, production and efficiency outcomes and (2) to generate economic analysis models in relation to these dietary outcomes for juvenile L. variegatus held in culture. At dietary protein levels below ca. 30%, models for most growth and production outcomes predicted increased rates of growth and production among urchins fed diets containing 18% dietary carbohydrate levels as compared to urchins fed diets containing 12% dietary carbohydrate. For most outcomes, growth and production was predicted to increase with increasing level of dietary protein up to ca. 30%, after which, no further increase in growth and production were predicted. Likewise, dry matter production efficiency was predicted to increase with increasing protein level up to ca. 30%, with urchins fed diets with 18% carbohydrate exhibiting greater efficiency than those fed diets with 12% carbohydrate. The energetic cost of dry matter production was optimal at protein levels less than those required for maximal weight gain and gonad production, suggesting an increased energetic cost (decreased energy efficiency) is required to increase gonad production relative to somatic growth. Economic analysis models predict when cost of feed ingredients are low, the lowest cost per gram of wet weight gain will occur at 18% dietary carbohydrate and ca. 25- 30% dietary protein. In contrast, lowest cost per gram of wet weight gain will occur at 12% dietary carbohydrate and ca. 35- 40% dietary protein when feed ingredient costs are high or average. For both 18 and 12% levels of dietary carbohydrate, cost per gram of wet weight gain is predicted to be maximized at low dietary protein levels, regardless of feed ingredient costs. These models will compare dietary requirements and growth outcomes in relation to economic costs and provide insight for future commercialization of sea urchin aquaculture.

Preliminary design and analysis of an advanced rotorcraft transmission

NASA Technical Reports Server (NTRS)

Henry, Z. S.

1990-01-01

Future rotorcraft transmissions of the 1990s and beyond the year 2000 require the incorporation of key emerging material and component technologies using advanced and innovative design practices in order to meet the requirements for a reduced weight-to-power ratio, a decreased noise level, and a substantially increased reliability. The specific goals for future rotocraft transmissions when compared with current state-of-the-art transmissions are a 25 percent weight reduction, a 10-dB reduction in the transmitted noise level, and a system reliability of 5000 hours mean-time-between-removal for the transmission. This paper presents the results of the design studies conducted to meet the stated goals for an advanced rotorcraft transmission. These design studies include system configuration, planetary gear train selection, and reliability prediction methods.

Potential increase in coastal wetland vulnerability to sea-level rise suggested by considering hydrodynamic attenuation effects

PubMed Central

Rodríguez, José F.; Saco, Patricia M.; Sandi, Steven; Saintilan, Neil; Riccardi, Gerardo

2017-01-01

The future of coastal wetlands and their ecological value depend on their capacity to adapt to the interacting effects of human impacts and sea-level rise. Even though extensive wetland loss due to submergence is a possible scenario, its magnitude is highly uncertain due to limited understanding of hydrodynamic and bio-geomorphic interactions over time. In particular, the effect of man-made drainage modifications on hydrodynamic attenuation and consequent wetland evolution is poorly understood. Predictions are further complicated by the presence of a number of vegetation types that change over time and also contribute to flow attenuation. Here, we show that flow attenuation affects wetland vegetation by modifying its wetting-drying regime and inundation depth, increasing its vulnerability to sea-level rise. Our simulations for an Australian subtropical wetland predict much faster wetland loss than commonly used models that do not consider flow attenuation. PMID:28703130

Sex differences in the relation of weight loss self-efficacy, binge eating, and depressive symptoms to weight loss success in a residential obesity treatment program.

PubMed

Presnell, Katherine; Pells, Jennifer; Stout, Anna; Musante, Gerard

2008-04-01

The aim of the current study was to examine whether weight loss self-efficacy, binge eating, and depressive symptoms predicted weight loss during treatment, and whether gender moderates these associations with prospective data from 297 participants (223 women and 74 men) enrolled in a residential obesity treatment program. Men reported higher initial levels of self-efficacy than women, whereas women reported greater pre-treatment levels of binge eating and depressive symptoms. Higher pre-treatment levels of weight control self-efficacy, binge eating, and depressive symptoms predicted greater weight loss in men, but not in women. Results suggest that certain psychological and behavioral factors should be considered when implementing weight loss interventions, and indicate a need to consider gender differences in predictors of weight loss treatment. Future research should seek to identify predictors of weight loss among women.

Learning under uncertainty in smart home environments.

PubMed

Zhang, Shuai; McClean, Sally; Scotney, Bryan; Nugent, Chris

2008-01-01

Technologies and services for the home environment can provide levels of independence for elderly people to support 'ageing in place'. Learning inhabitants' patterns of carrying out daily activities is a crucial component of these technological solutions with sensor technologies being at the core of such smart environments. Nevertheless, identifying high-level activities from low-level sensor events can be a challenge, as information may be unreliable resulting in incomplete data. Our work addresses the issues of learning in the presence of incomplete data along with the identification and the prediction of inhabitants and their activities under such uncertainty. We show via the evaluation results that our approach also offers the ability to assess the impact of various sensors in the activity recognition process. The benefit of this work is that future predictions can be utilised in a proposed intervention mechanism in a real smart home environment.

Potential increase in coastal wetland vulnerability to sea-level rise suggested by considering hydrodynamic attenuation effects

NASA Astrophysics Data System (ADS)

Rodríguez, José F.; Saco, Patricia M.; Sandi, Steven; Saintilan, Neil; Riccardi, Gerardo

2017-07-01

The future of coastal wetlands and their ecological value depend on their capacity to adapt to the interacting effects of human impacts and sea-level rise. Even though extensive wetland loss due to submergence is a possible scenario, its magnitude is highly uncertain due to limited understanding of hydrodynamic and bio-geomorphic interactions over time. In particular, the effect of man-made drainage modifications on hydrodynamic attenuation and consequent wetland evolution is poorly understood. Predictions are further complicated by the presence of a number of vegetation types that change over time and also contribute to flow attenuation. Here, we show that flow attenuation affects wetland vegetation by modifying its wetting-drying regime and inundation depth, increasing its vulnerability to sea-level rise. Our simulations for an Australian subtropical wetland predict much faster wetland loss than commonly used models that do not consider flow attenuation.

The upper respiratory pyramid: early factors and later treatment utilization in World Trade Center exposed firefighters.

PubMed

Niles, Justin K; Webber, Mayris P; Liu, Xiaoxue; Zeig-Owens, Rachel; Hall, Charles B; Cohen, Hillel W; Glaser, Michelle S; Weakley, Jessica; Schwartz, Theresa M; Weiden, Michael D; Nolan, Anna; Aldrich, Thomas K; Glass, Lara; Kelly, Kerry J; Prezant, David J

2014-08-01

We investigated early post 9/11 factors that could predict rhinosinusitis healthcare utilization costs up to 11 years later in 8,079 World Trade Center-exposed rescue/recovery workers. We used bivariate and multivariate analytic techniques to investigate utilization outcomes; we also used a pyramid framework to describe rhinosinusitis healthcare groups at early (by 9/11/2005) and late (by 9/11/2012) time points. Multivariate models showed that pre-9/11/2005 chronic rhinosinusitis diagnoses and nasal symptoms predicted final year healthcare utilization outcomes more than a decade after WTC exposure. The relative proportion of workers on each pyramid level changed significantly during the study period. Diagnoses of chronic rhinosinusitis within 4 years of a major inhalation event only partially explain future healthcare utilization. Exposure intensity, early symptoms and other factors must also be considered when anticipating future healthcare needs. © 2014 Wiley Periodicals, Inc.

Antiangiogenic Therapy for Glioblastoma: Current Status and Future Prospects

PubMed Central

Batchelor, Tracy T.; Reardon, David A.; de Groot, John F.; Wick, Wolfgang; Weller, Michael

2014-01-01

Glioblastoma is characterized by high expression levels of pro-angiogenic cytokines and microvascular proliferation, highlighting the potential value of treatments targeting angiogenesis. Antiangiogenic treatment likely achieves a beneficial impact through multiple mechanisms of action. Ultimately, however, alternative pro-angiogenic signal transduction pathways are activated leading to the development of resistance, even in tumors that initially respond. The identification of biomarkers or imaging parameters to predict response and to herald resistance is of high priority. Despite promising phase 2 clinical trial results and patient benefit in terms of clinical improvement and longer progression-free survival, an overall survival benefit has not been demonstrated in 4 randomized phase 3 trials of bevacizumab or cilengitide in newly diagnosed glioblastoma or cediranib or enzastaurin recurrent glioblastoma. However, future studies are warranted: predictive markers may allow appropriate patient enrichment, combination with chemotherapy may ultimately prove successful in improving overall survival, and novel agents targeting multiple pro-angiogenic pathways may prove effective. PMID:25398844

The Upper Respiratory Pyramid: Early Factors and Later Treatment Utilization in World Trade Center Exposed Firefighters

PubMed Central

Niles, Justin K.; Webber, Mayris P.; Liu, Xiaoxue; Zeig-Owens, Rachel; Hall, Charles B.; Cohen, Hillel W.; Glaser, Michelle S.; Weakley, Jessica; Schwartz, Theresa M.; Weiden, Michael D.; Nolan, Anna; Aldrich, Thomas K.; Glass, Lara; Kelly, Kerry J.; Prezant, David J.

2015-01-01

Background We investigated early post 9/11 factors that could predict rhinosinusitis healthcare utilization costs up to 11 years later in 8,079 World Trade Center-exposed rescue/recovery workers. Methods We used bivariate and multivariate analytic techniques to investigate utilization outcomes; we also used a pyramid framework to describe rhinosinusitis healthcare groups at early (by 9/11/2005) and late (by 9/11/2012) time points. Results Multivariate models showed that pre-9/11/2005 chronic rhinosinusitis diagnoses and nasal symptoms predicted final year healthcare utilization outcomes more than a decade after WTC exposure. The relative proportion of workers on each pyramid level changed significantly during the study period. Conclusions Diagnoses of chronic rhinosinusitis within 4 years of a major inhalation event only partially explain future healthcare utilization. Exposure intensity, early symptoms and other factors must also be considered when anticipating future healthcare needs. PMID:24898816

The future is in the numbers: the power of predictive analysis in the biomedical educational environment

PubMed Central

Gullo, Charles A.

2016-01-01

Biomedical programs have a potential treasure trove of data they can mine to assist admissions committees in identification of students who are likely to do well and help educational committees in the identification of students who are likely to do poorly on standardized national exams and who may need remediation. In this article, we provide a step-by-step approach that schools can utilize to generate data that are useful when predicting the future performance of current students in any given program. We discuss the use of linear regression analysis as the means of generating that data and highlight some of the limitations. Finally, we lament on how the combination of these institution-specific data sets are not being fully utilized at the national level where these data could greatly assist programs at large. PMID:27374246

Modeling level change in Lake Urmia using hybrid artificial intelligence approaches

NASA Astrophysics Data System (ADS)

Esbati, M.; Ahmadieh Khanesar, M.; Shahzadi, Ali

2017-06-01

The investigation of water level fluctuations in lakes for protecting them regarding the importance of these water complexes in national and regional scales has found a special place among countries in recent years. The importance of the prediction of water level balance in Lake Urmia is necessary due to several-meter fluctuations in the last decade which help the prevention from possible future losses. For this purpose, in this paper, the performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the lake water level balance has been studied. In addition, for the training of the adaptive neuro-fuzzy inference system, particle swarm optimization (PSO) and hybrid backpropagation-recursive least square method algorithm have been used. Moreover, a hybrid method based on particle swarm optimization and recursive least square (PSO-RLS) training algorithm for the training of ANFIS structure is introduced. In order to have a more fare comparison, hybrid particle swarm optimization and gradient descent are also applied. The models have been trained, tested, and validated based on lake level data between 1991 and 2014. For performance evaluation, a comparison is made between these methods. Numerical results obtained show that the proposed methods with a reasonable error have a good performance in water level balance prediction. It is also clear that with continuing the current trend, Lake Urmia will experience more drop in the water level balance in the upcoming years.

Prediction and Prescription in Systems Modeling

DTIC Science & Technology

1988-06-30

are so fascinated by prediction of the future -- whether achieved through horoscopes or otherwise. The future is our future, or at least the future...entirely true , has enormous import for public policy, and could have been inferred from textbook treatments of linear dynamic systems without any

A Bayesian network approach to predicting nest presence of thefederally-threatened piping plover (Charadrius melodus) using barrier island features

USGS Publications Warehouse

Gieder, Katherina D.; Karpanty, Sarah M.; Fraser, James D.; Catlin, Daniel H.; Gutierrez, Benjamin T.; Plant, Nathaniel G.; Turecek, Aaron M.; Thieler, E. Robert

2014-01-01

Sea-level rise and human development pose significant threats to shorebirds, particularly for species that utilize barrier island habitat. The piping plover (Charadrius melodus) is a federally-listed shorebird that nests on barrier islands and rapidly responds to changes in its physical environment, making it an excellent species with which to model how shorebird species may respond to habitat change related to sea-level rise and human development. The uncertainty and complexity in predicting sea-level rise, the responses of barrier island habitats to sea-level rise, and the responses of species to sea-level rise and human development necessitate a modelling approach that can link species to the physical habitat features that will be altered by changes in sea level and human development. We used a Bayesian network framework to develop a model that links piping plover nest presence to the physical features of their nesting habitat on a barrier island that is impacted by sea-level rise and human development, using three years of data (1999, 2002, and 2008) from Assateague Island National Seashore in Maryland. Our model performance results showed that we were able to successfully predict nest presence given a wide range of physical conditions within the model’s dataset. We found that model predictions were more successful when the range of physical conditions included in model development was varied rather than when those physical conditions were narrow. We also found that all model predictions had fewer false negatives (nests predicted to be absent when they were actually present in the dataset) than false positives (nests predicted to be present when they were actually absent in the dataset), indicating that our model correctly predicted nest presence better than nest absence. These results indicated that our approach of using a Bayesian network to link specific physical features to nest presence will be useful for modelling impacts of sea-level rise- or human-related habitat change on barrier islands. We recommend that potential users of this method utilize multiple years of data that represent a wide range of physical conditions in model development, because the model performed less well when constructed using a narrow range of physical conditions. Further, given that there will always be some uncertainty in predictions of future physical habitat conditions related to sea-level rise and/or human development, predictive models will perform best when developed using multiple, varied years of data input.

Factors related to choosing psychiatry as a future medical career among medical students at the Faculty of Medicine of the University of Indonesia.

PubMed

Wiguna, T; Yap, K S; Tan, B W; Siew, T; Danaway, J

2012-06-01

OBJECTIVE. To identify factors related to choosing psychiatry as a future medical career and attitude towards psychiatry among medical students of the International Class Programme of the Faculty of Medicine, The University of Indonesia. METHODS. This was a cross-sectional design which included 225 data sets from first to sixth year medical students (n = 188) as well as the freshly graduated medical doctors (n = 37). The Attitude Towards Psychiatry-30 questionnaire (ATP-30) was adopted. Data including demographics, past experience in psychiatry, inclination to work in psychiatry, and 3 specialty choices for future medical career were collected. Independent t test and logistic regression were used in data analysis. RESULTS. The mean ATP-30 score from the fresh graduates was slightly higher compared with the medical students. Inclination to work in the field of psychiatry, past experience in psychiatry, and the ATP-30 score were significantly correlated and contributed 57% to the prediction of choosing psychiatry as a future medical career (p < 0.05). CONCLUSION. The greater inclination to work in the field of psychiatry, as well as a better attitude towards psychiatry can predict the choice of psychiatry as a future medical career. Therefore, it is very important to increase the quality of psychiatry teaching and to motivate medical students who show a high level of interest in psychiatry.

Gambling and the Reasoned Action Model: Predicting Past Behavior, Intentions, and Future Behavior.

PubMed

Dahl, Ethan; Tagler, Michael J; Hohman, Zachary P

2018-03-01

Gambling is a serious concern for society because it is highly addictive and is associated with a myriad of negative outcomes. The current study applied the Reasoned Action Model (RAM) to understand and predict gambling intentions and behavior. Although prior studies have taken a reasoned action approach to understand gambling, no prior study has fully applied the RAM or used the RAM to predict future gambling. Across two studies the RAM was used to predict intentions to gamble, past gambling behavior, and future gambling behavior. In study 1 the model significantly predicted intentions and past behavior in both a college student and Amazon Mechanical Turk sample. In study 2 the model predicted future gambling behavior, measured 2 weeks after initial measurement of the RAM constructs. This study stands as the first to show the utility of the RAM in predicting future gambling behavior. Across both studies, attitudes and perceived normative pressure were the strongest predictors of intentions to gamble. These findings provide increased understanding of gambling and inform the development of gambling interventions based on the RAM.

Effects of high CO2 levels on dynamic photosynthesis: carbon gain, mechanisms, and environmental interactions.

PubMed

Tomimatsu, Hajime; Tang, Yanhong

2016-05-01

Understanding the photosynthetic responses of terrestrial plants to environments with high levels of CO2 is essential to address the ecological effects of elevated atmospheric CO2. Most photosynthetic models used for global carbon issues are based on steady-state photosynthesis, whereby photosynthesis is measured under constant environmental conditions; however, terrestrial plant photosynthesis under natural conditions is highly dynamic, and photosynthetic rates change in response to rapid changes in environmental factors. To predict future contributions of photosynthesis to the global carbon cycle, it is necessary to understand the dynamic nature of photosynthesis in relation to high CO2 levels. In this review, we summarize the current body of knowledge on the photosynthetic response to changes in light intensity under experimentally elevated CO2 conditions. We found that short-term exposure to high CO2 enhances photosynthetic rate, reduces photosynthetic induction time, and reduces post-illumination CO2 burst, resulting in increased leaf carbon gain during dynamic photosynthesis. However, long-term exposure to high CO2 during plant growth has varying effects on dynamic photosynthesis. High levels of CO2 increase the carbon gain in photosynthetic induction in some species, but have no significant effects in other species. Some studies have shown that high CO2 levels reduce the biochemical limitation on RuBP regeneration and Rubisco activation during photosynthetic induction, whereas the effects of high levels of CO2 on stomatal conductance differ among species. Few studies have examined the influence of environmental factors on effects of high levels of CO2 on dynamic photosynthesis. We identified several knowledge gaps that should be addressed to aid future predictions of photosynthesis in high-CO2 environments.

Soluble urokinase plasminogen activator receptor level is an independent predictor of the presence and severity of coronary artery disease and of future adverse events.

PubMed

Eapen, Danny J; Manocha, Pankaj; Ghasemzadeh, Nima; Ghasemzedah, Nima; Patel, Riyaz S; Al Kassem, Hatem; Hammadah, Muhammad; Veledar, Emir; Le, Ngoc-Anh; Pielak, Tomasz; Thorball, Christian W; Velegraki, Aristea; Kremastinos, Dimitrios T; Lerakis, Stamatios; Sperling, Laurence; Quyyumi, Arshed A

2014-10-23

Soluble urokinase plasminogen activator receptor (suPAR) is an emerging inflammatory and immune biomarker. Whether suPAR level predicts the presence and the severity of coronary artery disease (CAD), and of incident death and myocardial infarction (MI) in subjects with suspected CAD, is unknown. We measured plasma suPAR levels in 3367 subjects (67% with CAD) recruited in the Emory Cardiovascular Biobank and followed them for adverse cardiovascular (CV) outcomes of death and MI over a mean 2.1±1.1 years. Presence of angiographic CAD (≥50% stenosis in ≥1 coronary artery) and its severity were quantitated using the Gensini score. Cox's proportional hazard survival and discrimination analyses were performed with models adjusted for established CV risk factors and C-reactive protein levels. Elevated suPAR levels were independently associated with the presence of CAD (P<0.0001) and its severity (P<0.0001). A plasma suPAR level ≥3.5 ng/mL (cutoff by Youden's index) predicted future risk of MI (hazard ratio [HR]=3.2; P<0.0001), cardiac death (HR=2.62; P<0.0001), and the combined endpoint of death and MI (HR=1.9; P<0.0001), even after adjustment of covariates. The C-statistic for a model based on traditional risk factors was improved from 0.72 to 0.74 (P=0.008) with the addition of suPAR. Elevated levels of plasma suPAR are associated with the presence and severity of CAD and are independent predictors of death and MI in patients with suspected or known CAD. © 2014 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Soluble Urokinase Plasminogen Activator Receptor Level Is an Independent Predictor of the Presence and Severity of Coronary Artery Disease and of Future Adverse Events

PubMed Central

Eapen, Danny J.; Manocha, Pankaj; Ghasemzedah, Nima; Patel, Riyaz S.; Al Kassem, Hatem; Hammadah, Muhammad; Veledar, Emir; Le, Ngoc‐Anh; Pielak, Tomasz; Thorball, Christian W.; Velegraki, Aristea; Kremastinos, Dimitrios T.; Lerakis, Stamatios; Sperling, Laurence; Quyyumi, Arshed A.

2014-01-01

Introduction Soluble urokinase plasminogen activator receptor (suPAR) is an emerging inflammatory and immune biomarker. Whether suPAR level predicts the presence and the severity of coronary artery disease (CAD), and of incident death and myocardial infarction (MI) in subjects with suspected CAD, is unknown. Methods and Results We measured plasma suPAR levels in 3367 subjects (67% with CAD) recruited in the Emory Cardiovascular Biobank and followed them for adverse cardiovascular (CV) outcomes of death and MI over a mean 2.1±1.1 years. Presence of angiographic CAD (≥50% stenosis in ≥1 coronary artery) and its severity were quantitated using the Gensini score. Cox's proportional hazard survival and discrimination analyses were performed with models adjusted for established CV risk factors and C‐reactive protein levels. Elevated suPAR levels were independently associated with the presence of CAD (P<0.0001) and its severity (P<0.0001). A plasma suPAR level ≥3.5 ng/mL (cutoff by Youden's index) predicted future risk of MI (hazard ratio [HR]=3.2; P<0.0001), cardiac death (HR=2.62; P<0.0001), and the combined endpoint of death and MI (HR=1.9; P<0.0001), even after adjustment of covariates. The C‐statistic for a model based on traditional risk factors was improved from 0.72 to 0.74 (P=0.008) with the addition of suPAR. Conclusion Elevated levels of plasma suPAR are associated with the presence and severity of CAD and are independent predictors of death and MI in patients with suspected or known CAD. PMID:25341887

Temporal effects in trend prediction: identifying the most popular nodes in the future.

PubMed

Zhou, Yanbo; Zeng, An; Wang, Wei-Hong

2015-01-01

Prediction is an important problem in different science domains. In this paper, we focus on trend prediction in complex networks, i.e. to identify the most popular nodes in the future. Due to the preferential attachment mechanism in real systems, nodes' recent degree and cumulative degree have been successfully applied to design trend prediction methods. Here we took into account more detailed information about the network evolution and proposed a temporal-based predictor (TBP). The TBP predicts the future trend by the node strength in the weighted network with the link weight equal to its exponential aging. Three data sets with time information are used to test the performance of the new method. We find that TBP have high general accuracy in predicting the future most popular nodes. More importantly, it can identify many potential objects with low popularity in the past but high popularity in the future. The effect of the decay speed in the exponential aging on the results is discussed in detail.

Temporal Effects in Trend Prediction: Identifying the Most Popular Nodes in the Future

PubMed Central

Zhou, Yanbo; Zeng, An; Wang, Wei-Hong

2015-01-01

Prediction is an important problem in different science domains. In this paper, we focus on trend prediction in complex networks, i.e. to identify the most popular nodes in the future. Due to the preferential attachment mechanism in real systems, nodes’ recent degree and cumulative degree have been successfully applied to design trend prediction methods. Here we took into account more detailed information about the network evolution and proposed a temporal-based predictor (TBP). The TBP predicts the future trend by the node strength in the weighted network with the link weight equal to its exponential aging. Three data sets with time information are used to test the performance of the new method. We find that TBP have high general accuracy in predicting the future most popular nodes. More importantly, it can identify many potential objects with low popularity in the past but high popularity in the future. The effect of the decay speed in the exponential aging on the results is discussed in detail. PMID:25806810

Coastline Mapping and Cultural Review to Predict Sea Level Rise Impact on Hawaiian Archeological Sites

NASA Astrophysics Data System (ADS)

Clinton, J.

2017-12-01

Much of Hawaii's history is recorded in archeological sites. Researchers and cultural practitioners have been studying and reconstructing significant archeological sites for generations. Climate change, and more specifically, sea level rise may threaten these sites. Our research records current sea levels and then projects possible consequences to these cultural monuments due to sea level rise. In this mixed methods study, research scientists, cultural practitioners, and secondary students use plane-table mapping techniques to create maps of coastlines and historic sites. Students compare historical records to these maps, analyze current sea level rise trends, and calculate future sea levels. They also gather data through interviews with community experts and kupuna (elders). If climate change continues at projected rates, some historic sites will be in danger of negative impact due to sea level rise. Knowing projected sea levels at specific sites allows for preventative action and contributes to raised awareness of the impacts of climate change to the Hawaiian Islands. Students will share results with the community and governmental agencies in hopes of inspiring action to minimize climate change. It will take collaboration between scientists and cultural communities to inspire future action on climate change.

Algorithms and the Future of Music Education: A Response to Shuler

ERIC Educational Resources Information Center

Thibeault, Matthew D.

2014-01-01

This article is a response to Shuler's 2001 article predicting the future of music education. The respondent assesses Shuler's predictions, finding that many have come true but critiquing Shuler's overall positive assessment. The respondent then goes on to make one prediction about the future of music education: that algorithms will…

A preliminary evaluation of nearhore extreme sea level and wave models for fringing reef environments

NASA Astrophysics Data System (ADS)

Hoeke, R. K.; Reyns, J.; O'Grady, J.; Becker, J. M.; Merrifield, M. A.; Roelvink, J. A.

2016-02-01

Oceanic islands are widely perceived as vulnerable to sea level rise and are characterized by steep nearshore topography and fringing reefs. In such settings, near shore dynamics and (non-tidal) water level variability tends to be dominated by wind-wave processes. These processes are highly sensitive to reef morphology and roughness and to regional wave climate. Thus sea level extremes tend to be highly localized and their likelihood can be expected to change in the future (beyond simple extrapolation of sea level rise scenarios): e.g. sea level rise may increase the effective mean depth of reef crests and flats and ocean acidification and/or increased temperatures may lead to changes in reef structure. The problem is sufficiently complex that analytic or numerical approaches are necessary to estimate current hazards and explore potential future changes. In this study, we evaluate the capacity of several analytic/empirical approaches and phase-averaged and phase-resolved numerical models at sites in the insular tropical Pacific. We consider their ability to predict time-averaged wave setup and instantaneous water level exceedance probability (or dynamic wave run-up) as well as computational cost; where possible, we compare the model results with in situ observations from a number of previous studies. Preliminary results indicate analytic approaches are by far the most computationally efficient, but tend to perform poorly when alongshore straight and parallel morphology cannot be assumed. Phase-averaged models tend to perform well with respect to wave setup in such situations, but are unable to predict processes related to individual waves or wave groups, such as infragravity motions or wave run-up. Phase-resolved models tend to perform best, but come at high computational cost, an important consideration when exploring possible future scenarios. A new approach of combining an unstructured computational grid with a quasi-phase averaged approach (i.e. only phase resolving motions below a frequency cutoff) shows promise as a good compromise between computational efficiency and resolving processes such as wave runup and overtopping in more complex bathymetric situations.

Helicopter Rotor Noise Prediction: Background, Current Status, and Future Direction

NASA Technical Reports Server (NTRS)

Brentner, Kenneth S.

1997-01-01

Helicopter noise prediction is increasingly important. The purpose of this viewgraph presentation is to: 1) Put into perspective the recent progress; 2) Outline current prediction capabilities; 3) Forecast direction of future prediction research; 4) Identify rotorcraft noise prediction needs. The presentation includes an historical perspective, a description of governing equations, and the current status of source noise prediction.

Contrasting effects of climate change on rabbit populations through reproduction.

PubMed

Tablado, Zulima; Revilla, Eloy

2012-01-01

Climate change is affecting many physical and biological processes worldwide. Anticipating its effects at the level of populations and species is imperative, especially for organisms of conservation or management concern. Previous studies have focused on estimating future species distributions and extinction probabilities directly from current climatic conditions within their geographical ranges. However, relationships between climate and population parameters may be so complex that to make these high-level predictions we need first to understand the underlying biological processes driving population size, as well as their individual response to climatic alterations. Therefore, the objective of this study is to investigate the influence that climate change may have on species population dynamics through altering breeding season. We used a mechanistic model based on drivers of rabbit reproductive physiology together with demographic simulations to show how future climate-driven changes in breeding season result in contrasting rabbit population trends across Europe. In the Iberian Peninsula, where rabbits are a native species of high ecological and economic value, breeding seasons will shorten and become more variable leading to population declines, higher extinction risk, and lower resilience to perturbations. Whereas towards north-eastern countries, rabbit numbers are expected to increase through longer and more stable reproductive periods, which augment the probability of new rabbit invasions in those areas. Our study reveals the type of mechanisms through which climate will cause alterations at the species level and emphasizes the need to focus on them in order to better foresee large-scale complex population trends. This is especially important in species like the European rabbit whose future responses may aggravate even further its dual keystone/pest problematic. Moreover, this approach allows us to predict not only distribution shifts but also future population status and growth, and to identify the demographic parameters on which to focus to mitigate global change effects.

Contrasting Effects of Climate Change on Rabbit Populations through Reproduction

PubMed Central

Tablado, Zulima; Revilla, Eloy

2012-01-01

Background Climate change is affecting many physical and biological processes worldwide. Anticipating its effects at the level of populations and species is imperative, especially for organisms of conservation or management concern. Previous studies have focused on estimating future species distributions and extinction probabilities directly from current climatic conditions within their geographical ranges. However, relationships between climate and population parameters may be so complex that to make these high-level predictions we need first to understand the underlying biological processes driving population size, as well as their individual response to climatic alterations. Therefore, the objective of this study is to investigate the influence that climate change may have on species population dynamics through altering breeding season. Methodology/Principal Findings We used a mechanistic model based on drivers of rabbit reproductive physiology together with demographic simulations to show how future climate-driven changes in breeding season result in contrasting rabbit population trends across Europe. In the Iberian Peninsula, where rabbits are a native species of high ecological and economic value, breeding seasons will shorten and become more variable leading to population declines, higher extinction risk, and lower resilience to perturbations. Whereas towards north-eastern countries, rabbit numbers are expected to increase through longer and more stable reproductive periods, which augment the probability of new rabbit invasions in those areas. Conclusions/Significance Our study reveals the type of mechanisms through which climate will cause alterations at the species level and emphasizes the need to focus on them in order to better foresee large-scale complex population trends. This is especially important in species like the European rabbit whose future responses may aggravate even further its dual keystone/pest problematic. Moreover, this approach allows us to predict not only distribution shifts but also future population status and growth, and to identify the demographic parameters on which to focus to mitigate global change effects. PMID:23152836

Construal level as a moderator of the role of affective and cognitive attitudes in the prediction of health-risk behavioural intentions.

PubMed

Carrera, Pilar; Caballero, Amparo; Muñoz, Dolores; González-Iraizoz, Marta; Fernández, Itziar

2014-12-01

In two preliminary control checks it was shown that affective attitudes presented greater abstraction than cognitive attitudes. Three further studies explored how construal level moderated the role of affective and cognitive attitudes in predicting one health-promoting behaviour (exercising) and two risk behaviours (sleep debt and binge drinking). There was a stronger influence of affective attitudes both when participants were in abstract (vs. concrete) mindsets induced by a priming task in Studies 1a and 1b, and when behavioural intentions were formed for the distant (vs. near) future in Study 2. In the case of concrete mindsets, the results were inconclusive; the interaction between construal level and cognitive attitudes was only marginally significant in Study 1b. The present research supports the assertion that in abstract mindsets (vs. concrete mindsets) people use more affective attitudes to construe their behavioural intentions. Practical implications for health promotion are discussed in the framework of construal-level theory. © 2014 The British Psychological Society.

Solar Cycle Predictions

NASA Technical Reports Server (NTRS)

Pesnell, William Dean

2012-01-01

Solar cycle predictions are needed to plan long-term space missions; just like weather predictions are needed to plan the launch. Fleets of satellites circle the Earth collecting many types of science data, protecting astronauts, and relaying information. All of these satellites are sensitive at some level to solar cycle effects. Predictions of drag on LEO spacecraft are one of the most important. Launching a satellite with less propellant can mean a higher orbit, but unanticipated solar activity and increased drag can make that a Pyrrhic victory as you consume the reduced propellant load more rapidly. Energetic events at the Sun can produce crippling radiation storms that endanger all assets in space. Solar cycle predictions also anticipate the shortwave emissions that cause degradation of solar panels. Testing solar dynamo theories by quantitative predictions of what will happen in 5-20 years is the next arena for solar cycle predictions. A summary and analysis of 75 predictions of the amplitude of the upcoming Solar Cycle 24 is presented. The current state of solar cycle predictions and some anticipations how those predictions could be made more accurate in the future will be discussed.

Project for Solar-Terrestrial Environment Prediction (PSTEP): Towards Predicting Next Solar Cycle

NASA Astrophysics Data System (ADS)

Imada, S.; Iijima, H.; Hotta, H.; Shiota, D.; Kanou, O.; Fujiyama, M.; Kusano, K.

2016-10-01

It is believed that the longer-term variations of the solar activity can affect the Earth's climate. Therefore, predicting the next solar cycle is crucial for the forecast of the "solar-terrestrial environment". To build prediction schemes for the activity level of the next solar cycle is a key for the long-term space weather study. Although three-years prediction can be almost achieved, the prediction of next solar cycle is very limited, so far. We are developing a five-years prediction scheme by combining the Surface Flux Transport (SFT) model and the most accurate measurements of solar magnetic fields as a part of the PSTEP (Project for Solar-Terrestrial Environment Prediction),. We estimate the meridional flow, differential rotation, and turbulent diffusivity from recent modern observations (Hinode and Solar Dynamics Observatory). These parameters are used in the SFT models to predict the polar magnetic fields strength at the solar minimum. In this presentation, we will explain the outline of our strategy to predict the next solar cycle. We also report the present status and the future perspective of our project.

Efficient search, mapping, and optimization of multi-protein genetic systems in diverse bacteria

PubMed Central

Farasat, Iman; Kushwaha, Manish; Collens, Jason; Easterbrook, Michael; Guido, Matthew; Salis, Howard M

2014-01-01

Developing predictive models of multi-protein genetic systems to understand and optimize their behavior remains a combinatorial challenge, particularly when measurement throughput is limited. We developed a computational approach to build predictive models and identify optimal sequences and expression levels, while circumventing combinatorial explosion. Maximally informative genetic system variants were first designed by the RBS Library Calculator, an algorithm to design sequences for efficiently searching a multi-protein expression space across a > 10,000-fold range with tailored search parameters and well-predicted translation rates. We validated the algorithm's predictions by characterizing 646 genetic system variants, encoded in plasmids and genomes, expressed in six gram-positive and gram-negative bacterial hosts. We then combined the search algorithm with system-level kinetic modeling, requiring the construction and characterization of 73 variants to build a sequence-expression-activity map (SEAMAP) for a biosynthesis pathway. Using model predictions, we designed and characterized 47 additional pathway variants to navigate its activity space, find optimal expression regions with desired activity response curves, and relieve rate-limiting steps in metabolism. Creating sequence-expression-activity maps accelerates the optimization of many protein systems and allows previous measurements to quantitatively inform future designs. PMID:24952589

Have We Entered a 21st Century Prolonged Minimum of Solar Activity? Updated Implications of a 1987 Prediction

NASA Astrophysics Data System (ADS)

Shirley, James H.

2009-05-01

Fairbridge and Shirley (1987) predicted that a new prolonged minimum of solar activity would be underway by the year 2013 (Solar Physics 110, 191). While it is much too early to tell if this prediction will be fully realized, recent observations document a striking reduction in the Sun's general level of activity. While other forecasts of reduced future activity levels on decadal time scales have appeared, the Fairbridge-Shirley (FS) prediction is unique in pinpointing the current epoch. We are unaware of any forecast method that shows a better correspondence with the actual behavior of the Sun to this point. The FS prediction was based on the present-day recurrence of two physical indicators that were correlated in time with the occurrence of the Wolf, Sporer, and Maunder Minima. The amplitude of the inertial revolution of the axis of symmetry of the Sun's orbital motion about the solar system barycenter, and the direction in space of that axis, each bear a relationship to the occurrence of the prolonged minima of the historic record. The FS prediction appeared before the importance of solar meridional flows was generally appreciated, and before the existence and role of the tachocline was suspected. We will update and restate some of the physical implications of the FS results, along with those of some more recent investigations, particularly with reference to orbit-spin coupling hypotheses (Shirley, 2006: M.N.R.A.S. 368, 280). New investigations combining and integrating modern dynamo models with physical solutions describing key aspects of the variability of the solar motion may lead to significant advances in our ability to forecast future changes in the Sun. Acknowledgement: This work was supported by the resources of the author. No part of this work was performed at the Jet Propulsion Laboratory under a contract from NASA.

Predictors of initial levels and trajectories of anxiety in women before and for 6 months after breast cancer surgery.

PubMed

Kyranou, Marianna; Puntillo, Kathleen; Dunn, Laura B; Aouizerat, Bradley E; Paul, Steven M; Cooper, Bruce A; Neuhaus, John; West, Claudia; Dodd, Marylin; Miaskowski, Christine

2014-01-01

The diagnosis of breast cancer, in combination with the anticipation of surgery, evokes fear, uncertainty, and anxiety in most women. Study purposes were to examine in patients who underwent breast cancer surgery how ratings of state anxiety changed from the time of the preoperative assessment to 6 months after surgery and to investigate whether specific demographic, clinical, symptom, and psychosocial adjustment characteristics predicted the preoperative levels of state anxiety and/or characteristics of the trajectories of state anxiety. Patients (n = 396) were enrolled preoperatively and completed the Spielberger State Anxiety inventory monthly for 6 months. Using hierarchical linear modeling, demographic, clinical, symptom, and psychosocial adjustment characteristics were evaluated as predictors of initial levels and trajectories of state anxiety. Patients experienced moderate levels of anxiety before surgery. Higher levels of depressive symptoms and uncertainty about the future, as well as lower levels of life satisfaction, less sense of control, and greater difficulty coping, predicted higher preoperative levels of state anxiety. Higher preoperative state anxiety, poorer physical health, decreased sense of control, and more feelings of isolation predicted higher state anxiety scores over time. Moderate levels of anxiety persist in women for 6 months after breast cancer surgery. Clinicians need to implement systematic assessments of anxiety to identify high-risk women who warrant more targeted interventions. In addition, ongoing follow-up is needed to prevent adverse postoperative outcomes and to support women to return to their preoperative levels of function.

Overestimation of marsh vulnerability to sea level rise

USGS Publications Warehouse

Kirwan, Matthew L.; Temmerman, Stijn; Skeehan, Emily E.; Guntenspergen, Glenn R.; Fagherazzi, Sergio

2016-01-01

Coastal marshes are considered to be among the most valuable and vulnerable ecosystems on Earth, where the imminent loss of ecosystem services is a feared consequence of sea level rise. However, we show with a meta-analysis that global measurements of marsh elevation change indicate that marshes are generally building at rates similar to or exceeding historical sea level rise, and that process-based models predict survival under a wide range of future sea level scenarios. We argue that marsh vulnerability tends to be overstated because assessment methods often fail to consider biophysical feedback processes known to accelerate soil building with sea level rise, and the potential for marshes to migrate inland.

Paradoxes and Dilemmas in Managing E-Learning in Higher Education. Research & Occasional Paper Series. CSHE.7.03

ERIC Educational Resources Information Center

Guri-Rosenblit, Sarah

2003-01-01

The new information and communication technologies (ICT) affect currently most spheres of life, including all educational levels. Their effects are most likely to grow in the future. However, many predictions in the last few years as to the sweeping impact of the ICT on restructuring the teaching/learning practices at universities and their high…

Humans, Topograpghy, and Wildland Fire: The Ingredients for Long-term Patterns in Ecosystems

Treesearch

Richard P. Guyette; Daniel C. Dey

2000-01-01

Three factors, human population density, topography, and culture interact to create temporal and spatial differences in the frequency of fire at the landscape level. These factors can be quantitatively related to fire frequency. The fire model can be used to reconstruct historic and to predict future frequency of fire in ecosystems, as well as to identify long-term...

Humans, topography, and wildland fire: The ingredients for long-term patterns in ecosystems

Treesearch

Richard P. Guyette; Daniel C. Dey

2000-01-01

Three factors, human population density, topography,and culture interact to create temporal and spatial differences in the frequency of fire at the landscape level. These facters can be quantitatively related to fire frequency. The fire model can be used to reconstruct historic and to predict future frequency of fire in ecosystems, as well as to identify long-term...

Predicting Commissary Store Success

DTIC Science & Technology

2014-12-01

that make any retail store successful: the number of shoppers, the price differential between a store and its competition, and the number of...the planning of future stores to maximize the return on taxpayers’ investment. 3 II. BACKGROUND A. COMMISSARY HISTORY Commissary stores began...Defense Commissary Agency (DeCA) in 1990. DeCA currently oversees all commissary stores ( History , n.d.). B. COMMISSARY REGULATIONS Top-level

Xylem recovery from drought-induced embolism: Where is the hydraulic point of no return?

Treesearch

Frederick C. Meinzer; Katherine A. McCulloh

2013-01-01

The hydraulic resilience of a species is determined by multiple physiological and structural traits. Understanding how these traits are integrated at the organismal level to yield adequate hydraulic fitness in a given environment would be a fertile area for future research. This type of information is essential for realistic predictions of species hydraulic limits...

Sustained Satellite Missions for Climate Data Records

NASA Technical Reports Server (NTRS)

Halpern, David

2012-01-01

Satellite CDRs possess the accuracy, longevity, and stability for sustained moni toring of critical variables to enhance understanding of the global integrated Earth system and predict future conditions. center dot Satellite CDRs are a critical element of a global climate observing system. center dot Satellite CDRs are a difficult challenge and require high - level managerial commitment, extensive intellectual capital, and adequate funding.

A Model of Academic Self-Concept: Perceived Difficulty and Social Comparison among Academically Accelerated Secondary School Students

ERIC Educational Resources Information Center

Wilson, Hope E.; Siegle, Del; McCoach, D. Betsy; Little, Catherine A.; Reis, Sally M.

2014-01-01

Academic self-concept predicts students' future goals and is affected by a student's relative success compared with his or her peer group. This exploratory study used structural equation modeling to examine the contributions of the perceived level of difficulty of the curriculum, in addition to the contributions of social comparison and…

Social skills and behavior problems of urban, African American preschoolers: role of parenting practices, family conflict, and maternal depression.

PubMed

Koblinsky, Sally A; Kuvalanka, Katherine A; Randolph, Suzanne M

2006-10-01

This study examined the role of parenting, family routines, family conflict, and maternal depression in predicting the social skills and behavior problems of low-income African American preschoolers. A sample of 184 African American mothers of Head Start children completed participant and child measures in a structured interview. Results of regression analyses revealed that mothers who utilized more positive parenting practices and engaged in more family routines had children who displayed higher levels of total prosocial skills. Positive parenting and lower levels of maternal depressive symptoms were predictive of fewer externalizing and internalizing child behavior problems. Lower family conflict was linked with fewer externalizing problems. Implications of the study for future research and intervention are discussed. (c) 2007 APA, all rights reserved

A Study in a New Test Facility on Indoor Annoyance Caused by Sonic Booms

NASA Technical Reports Server (NTRS)

Rathsam, Jonathan; Loubeau, Alexandra; Klos, Jacob

2012-01-01

A sonic-boom simulator at NASA Langley Research Center has been constructed to research the indoor human response to low-amplitude sonic booms. The research goal is the development of a psychoacoustic model for individual sonic booms to be validated by future community studies. The study in this report assessed the suitability of existing noise metrics for predicting indoor human annoyance. The test signals included a wide range of synthesized and recorded sonic-boom waveforms. Results indicated that no noise metric predicts indoor annoyance to sonic-boom sounds better than Perceived Level, PL. During the study it became apparent that structural vibrations induced by the test signals were contributing to annoyance, so the relationship between sound and vibration at levels of equivalent annoyance has been quantified.

Intentions of Chiropractic Interns Regarding use of Health Promotion in Practice: Applying Theory of Reasoned Action to Identify Attitudes, Beliefs, and Influencing Factors

PubMed Central

Evans, Marion W.; Ndetan, Harrison; Williams, Ronald D.

2009-01-01

Purpose: The theory of reasoned action is a health behavioral theory that has been used to predict personal health behaviors and intentions as well as those of providers delivering health care. The purpose of this study was to determine interns' future practices regarding the use of health promotion using this model to develop survey questions and to determine attitudes and perceived influences on their prospective behaviors in general, toward the use of health promotion once in practice. Methods: Across the course of one year, all graduating interns at a chiropractic college were queried with a 20 question survey designed using the theory of reasoned action. Frequencies and inferential statistics were performed including prediction modeling using logistic regression. Results: A majority (>85%) of interns indicated they would use health promotion in practice. Differences were noted based on perceived skill levels, perception of educational emphasis, various normative beliefs, and gender. Conclusion: Most interns will use some form of health promotion in practice. Normative influences including those seen as key influencers are as powerful a predictor as perceived education or skill levels on future practice of health promotion. PMID:19390679

Intentions of Chiropractic Interns Regarding use of Health Promotion in Practice: Applying Theory of Reasoned Action to Identify Attitudes, Beliefs, and Influencing Factors.

PubMed

Evans, Marion W; Ndetan, Harrison; Williams, Ronald D

2009-01-01

The theory of reasoned action is a health behavioral theory that has been used to predict personal health behaviors and intentions as well as those of providers delivering health care. The purpose of this study was to determine interns' future practices regarding the use of health promotion using this model to develop survey questions and to determine attitudes and perceived influences on their prospective behaviors in general, toward the use of health promotion once in practice. Across the course of one year, all graduating interns at a chiropractic college were queried with a 20 question survey designed using the theory of reasoned action. Frequencies and inferential statistics were performed including prediction modeling using logistic regression. A majority (>85%) of interns indicated they would use health promotion in practice. Differences were noted based on perceived skill levels, perception of educational emphasis, various normative beliefs, and gender. Most interns will use some form of health promotion in practice. Normative influences including those seen as key influencers are as powerful a predictor as perceived education or skill levels on future practice of health promotion.

Inequality matters: classroom status hierarchy and adolescents' bullying.

PubMed

Garandeau, Claire F; Lee, Ihno A; Salmivalli, Christina

2014-07-01

The natural emergence of status hierarchies in adolescent peer groups has long been assumed to help prevent future intragroup aggression. However, clear evidence of this beneficial influence is lacking. In fact, few studies have examined between-group differences in the degree of status hierarchy (defined as within-group variation in individual status) and how they are related to bullying, a widespread form of aggression in schools. Data from 11,296 eighth- and ninth-graders (mean age = 14.57, 50.6 % female) from 583 classes in 71 schools were used to determine the direction of the association between classroom degree of status hierarchy and bullying behaviors, and to investigate prospective relationships between these two variables over a 6-month period. Multilevel structural equation modeling analyses showed that higher levels of classroom status hierarchy were concurrently associated with higher levels of bullying at the end of the school year. Higher hierarchy in the middle of the school year predicted higher bullying later in the year. No evidence was found to indicate that initial bullying predicted future hierarchy. These findings highlight the importance of a shared balance of power in the classroom for the prevention of bullying among adolescents.

How ocean acidification can benefit calcifiers.

PubMed

Connell, Sean D; Doubleday, Zoë A; Hamlyn, Sarah B; Foster, Nicole R; Harley, Christopher D G; Helmuth, Brian; Kelaher, Brendan P; Nagelkerken, Ivan; Sarà, Gianluca; Russell, Bayden D

2017-02-06

Reduction in seawater pH due to rising levels of anthropogenic carbon dioxide (CO 2 ) in the world's oceans is a major force set to shape the future of marine ecosystems and the ecological services they provide [1,2]. In particular, ocean acidification is predicted to have a detrimental effect on the physiology of calcifying organisms [3]. Yet, the indirect effects of ocean acidification on calcifying organisms, which may counter or exacerbate direct effects, is uncertain. Using volcanic CO 2 vents, we tested the indirect effects of ocean acidification on a calcifying herbivore (gastropod) within the natural complexity of an ecological system. Contrary to predictions, the abundance of this calcifier was greater at vent sites (with near-future CO 2 levels). Furthermore, translocation experiments demonstrated that ocean acidification did not drive increases in gastropod abundance directly, but indirectly as a function of increased habitat and food (algal biomass). We conclude that the effect of ocean acidification on algae (primary producers) can have a strong, indirect positive influence on the abundance of some calcifying herbivores, which can overwhelm any direct negative effects. This finding points to the need to understand ecological processes that buffer the negative effects of environmental change. Copyright © 2017 Elsevier Ltd. All rights reserved.

Gender, Emotion Work, and Relationship Quality: A Daily Diary Study

PubMed Central

Curran, Melissa A.; McDaniel, Brandon T.; Pollitt, Amanda M.; Totenhagen, Casey J.

2015-01-01

We use the gender relations perspective from feminist theorizing to investigate how gender and daily emotion work predict daily relationship quality in 74 couples (148 individuals in dating, cohabiting, or married relationships) primarily from the southwest U.S. Emotion work is characterized by activities that enhance others’ emotional well-being. We examined emotion work two ways: trait (individuals’ average levels) and state (individuals’ daily fluctuations). We examined actor and partner effects of emotion work and tested for gender differences. As outcome variables, we included six types of daily relationship quality: love, commitment, satisfaction, closeness, ambivalence, and conflict. This approach allowed us to predict three aspects of relationship quality: average levels, daily fluctuations, and volatility (overall daily variability across a week). Three patterns emerged. First, emotion work predicted relationship quality in this diverse set of couples. Second, gender differences were minimal for fixed effects: Trait and state emotion work predicted higher average scores on, and positive daily increases in, individuals’ own positive relationship quality and lower average ambivalence. Third, gender differences were more robust for volatility: For partner effects, having a partner who reported higher average emotion work predicted lower volatility in love, satisfaction, and closeness for women versus greater volatility in love and commitment for men. Neither gender nor emotion work predicted average levels, daily fluctuations, or volatility in conflict. We discuss implications and future directions pertaining to the unique role of gender in understanding the associations between daily emotion work and volatility in daily relationship quality for relational partners. PMID:26508808

Gender, Emotion Work, and Relationship Quality: A Daily Diary Study.

PubMed

Curran, Melissa A; McDaniel, Brandon T; Pollitt, Amanda M; Totenhagen, Casey J

2015-08-01

We use the gender relations perspective from feminist theorizing to investigate how gender and daily emotion work predict daily relationship quality in 74 couples (148 individuals in dating, cohabiting, or married relationships) primarily from the southwest U.S. Emotion work is characterized by activities that enhance others' emotional well-being. We examined emotion work two ways: trait (individuals' average levels) and state (individuals' daily fluctuations). We examined actor and partner effects of emotion work and tested for gender differences. As outcome variables, we included six types of daily relationship quality: love, commitment, satisfaction, closeness, ambivalence, and conflict. This approach allowed us to predict three aspects of relationship quality: average levels, daily fluctuations, and volatility (overall daily variability across a week). Three patterns emerged. First, emotion work predicted relationship quality in this diverse set of couples. Second, gender differences were minimal for fixed effects: Trait and state emotion work predicted higher average scores on, and positive daily increases in, individuals' own positive relationship quality and lower average ambivalence. Third, gender differences were more robust for volatility: For partner effects, having a partner who reported higher average emotion work predicted lower volatility in love, satisfaction, and closeness for women versus greater volatility in love and commitment for men. Neither gender nor emotion work predicted average levels, daily fluctuations, or volatility in conflict. We discuss implications and future directions pertaining to the unique role of gender in understanding the associations between daily emotion work and volatility in daily relationship quality for relational partners.

Time Frame and Justice Motive: Future Perspective Moderates the Adaptive Function of General Belief in a Just World

PubMed Central

Wu, Michael Shengtao; Sutton, Robbie M.; Yan, Xiaodan; Zhou, Chan; Chen, Yiwen; Zhu, Zhuohong; Han, Buxin

2013-01-01

Background The human ability to envision the future, that is, to take a future perspective (FP), plays a key role in the justice motive and its function in transcending disadvantages and misfortunes. The present research investigated whether individual (Study 1) and situational (Study 2) differences in FP moderated the association of general belief in a just world (GBJW) with psychological resilience. Methodology/Principal Findings We investigated FP, GBJW, and resilience in sample of adolescents (n = 223) and disaster survivors (n = 218) in China. In Study 1, adolescents revealed stronger GBJW than PBJW, and GBJW uniquely predicted resilience in the daily lives of those with high FP (but not those with low FP). In Study 2, natural priming of FP (vs. no FP) facilitated the association of GBJW with resilience after disaster. Conclusions/Significance Supporting predictions, participants endorsed GBJW more strongly than PBJW. Further, GBJW interacted with FP in both studies, such that there was an association between GBJW and resilience at high but not low levels of FP. The results corroborate recent findings suggesting that GBJW may be more psychologically adaptive than PBJW among some populations. They also confirm that focusing on the future is an important aspect of the adaptive function of just-world beliefs. PMID:24312235

Distributional dynamics of a vulnerable species in response to past and future climate change: a window for conservation prospects

PubMed Central

Bai, Yunjun; Wei, Xueping

2018-01-01

Background The ongoing change in climate is predicted to exert unprecedented effects on Earth’s biodiversity at all levels of organization. Biological conservation is important to prevent biodiversity loss, especially for species facing a high risk of extinction. Understanding the past responses of species to climate change is helpful for revealing response mechanisms, which will contribute to the development of effective conservation strategies in the future. Methods In this study, we modelled the distributional dynamics of a ‘Vulnerable’ species, Pseudolarix amabilis, in response to late Quaternary glacial-interglacial cycles and future 2080 climate change using an ecological niche model (MaxEnt). We also performed migration vector analysis to reveal the potential migration of the population over time. Results Historical modelling indicates that the range dynamics of P. amabilis is highly sensitive to climate change and that its long-distance dispersal ability and potential for evolutionary adaption are limited. Compared to the current climatically suitable areas for this species, future modelling showed significant migration northward towards future potential climatically suitable areas. Discussion In combination with the predicted future distribution, the mechanism revealed by the historical response suggests that this species will not be able to fully occupy the future expanded areas of suitable climate or adapt to the unsuitable climate across the future contraction regions. As a result, we suggest assisted migration as an effective supplementary means of conserving this vulnerable species in the face of the unprecedentedly rapid climate change of the 21st century. As a study case, this work highlights the significance of introducing historical perspectives while researching species conservation, especially for currently vulnerable or endangered taxa that once had a wider distribution in geological time. PMID:29362700

Distributional dynamics of a vulnerable species in response to past and future climate change: a window for conservation prospects.

PubMed

Bai, Yunjun; Wei, Xueping; Li, Xiaoqiang

2018-01-01

The ongoing change in climate is predicted to exert unprecedented effects on Earth's biodiversity at all levels of organization. Biological conservation is important to prevent biodiversity loss, especially for species facing a high risk of extinction. Understanding the past responses of species to climate change is helpful for revealing response mechanisms, which will contribute to the development of effective conservation strategies in the future. In this study, we modelled the distributional dynamics of a 'Vulnerable' species, Pseudolarix amabilis , in response to late Quaternary glacial-interglacial cycles and future 2080 climate change using an ecological niche model (MaxEnt). We also performed migration vector analysis to reveal the potential migration of the population over time. Historical modelling indicates that the range dynamics of P. amabilis is highly sensitive to climate change and that its long-distance dispersal ability and potential for evolutionary adaption are limited. Compared to the current climatically suitable areas for this species, future modelling showed significant migration northward towards future potential climatically suitable areas. In combination with the predicted future distribution, the mechanism revealed by the historical response suggests that this species will not be able to fully occupy the future expanded areas of suitable climate or adapt to the unsuitable climate across the future contraction regions. As a result, we suggest assisted migration as an effective supplementary means of conserving this vulnerable species in the face of the unprecedentedly rapid climate change of the 21st century. As a study case, this work highlights the significance of introducing historical perspectives while researching species conservation, especially for currently vulnerable or endangered taxa that once had a wider distribution in geological time.

Short- versus long-term responses to changing CO2 in a coastal dinoflagellate bloom: implications for interspecific competitive interactions and community structure.

PubMed

Tatters, Avery O; Schnetzer, Astrid; Fu, Feixue; Lie, Alle Y A; Caron, David A; Hutchins, David A

2013-07-01

Increasing pCO2 (partial pressure of CO2 ) in an "acidified" ocean will affect phytoplankton community structure, but manipulation experiments with assemblages briefly acclimated to simulated future conditions may not accurately predict the long-term evolutionary shifts that could affect inter-specific competitive success. We assessed community structure changes in a natural mixed dinoflagellate bloom incubated at three pCO2 levels (230, 433, and 765 ppm) in a short-term experiment (2 weeks). The four dominant species were then isolated from each treatment into clonal cultures, and maintained at all three pCO2 levels for approximately 1 year. Periodically (4, 8, and 12 months), these pCO2 -conditioned clones were recombined into artificial communities, and allowed to compete at their conditioning pCO2 level or at higher and lower levels. The dominant species in these artificial communities of CO2 -conditioned clones differed from those in the original short-term experiment, but individual species relative abundance trends across pCO2 treatments were often similar. Specific growth rates showed no strong evidence for fitness increases attributable to conditioning pCO2 level. Although pCO2 significantly structured our experimental communities, conditioning time and biotic interactions like mixotrophy also had major roles in determining competitive outcomes. New methods of carrying out extended mixed species experiments are needed to accurately predict future long-term phytoplankton community responses to changing pCO2 . © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Prolactin stress response does not predict brood desertion in a polyandrous shorebird.

PubMed

Kosztolányi, András; Küpper, Clemens; Chastel, Olivier; Parenteau, Charline; Yılmaz, K Tuluhan; Miklósi, Adám; Székely, Tamás; Lendvai, Adám Z

2012-05-01

One of the fundamental principles of the life-history theory is that parents need to balance their resources between current and future offspring. Deserting the dependent young is a radical life-history decision that saves resources for future reproduction but that may cause the current brood to fail. Despite the importance of desertion for reproductive success, and thus fitness, the neuroendocrine mechanisms of brood desertion are largely unknown. We investigated two candidate hormones that may influence brood desertion in the Kentish plover Charadrius alexandrinus: prolactin ('parental hormone') and corticosterone ('stress hormone'). Kentish plovers exhibit an unusually diverse mating and parental care system: brood desertion occurs naturally since either parent (the male or the female) may desert the brood after the chicks hatch and mate with a new partner shortly after. We measured the hormone levels of parents at hatching using the standard capture and restraint protocol. We subsequently followed the broods to determine whether a parent deserted the chicks. We found no evidence that either baseline or stress-induced prolactin levels of male or female parents predicted brood desertion. Although stress-induced corticosterone levels were generally higher in females compared with males, individual corticosterone levels did not explain the probability of brood desertion. We suggest that, in this species, low prolactin levels do not trigger brood desertion. In general, we propose that the prolactin stress response does not reflect overall parental investment in a species where different parts of the breeding cycle are characterized by contrasting individual investment strategies. Copyright © 2012 Elsevier Inc. All rights reserved.

Limitations on scientific prediction and how they could affect repository licensing

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

Van Konynenburg, R.A.

The best possibility for gaining an understanding of the likely future behavior of a high level nuclear waste disposal system is to use the scientific method. However, the scientific approach has inherent limitations when it comes to making long-term predictions with confidence. This paper examines some of these limiting factors as well as the criteria for admissibility of scientific evidence in the legal arena, and concludes that the prospects are doubtful for successful licensing of a potential repository under the regulations that are now being reconsidered. Suggestions am made for remedying this situation.

Changes in lactate dehydrogenase are associated with central gray matter lesions in newborns with hypoxic-ischemic encephalopathy.

PubMed

Yum, Sook Kyung; Moon, Cheong-Jun; Youn, Young-Ah; Sung, In Kyung

2017-05-01

Biomarkers may predict neurological prognosis in infants with hypoxic-ischemic encephalopathy (HIE). We evaluated the relationship between serum lactate dehydrogenase (LDH) and brain magnetic resonance imaging (MRI), which predicts neurodevelopmental outcomes, in order to assess whether LDH levels are similarly predictive. Medical records were reviewed for infants with HIE and LDH levels were assessed on the first (LDH 1 ) and third (LDH 3 ) days following birth. Receiver operating characteristic curves were obtained in relation to central gray matter hypoxic-ischemic lesions. Of 92 patients, 52 (56.5%) had hypoxic-ischemic lesions on brain MRI, and 21 of these infants (40.4%) had central gray matter lesions. LDH 1 and LDH 3 did not differ; however, the percentage change (ΔLDH%) was significantly higher in infants with central gray matter lesions (36.9% versus 6.6%, p = 0.006). With cutoffs of 187 (IU/L, ΔLDH) and 19.4 (%, ΔLDH%), the sensitivity, specificity, positive predictive value and negative predictive value were 71.4, 69.0, 40.5 and 89.1%, respectively. The relative risk was 5.57 (p = 0.001). Changes in serum LDH may be a useful biomarker for predicting future neurodevelopmental prognosis in infants with HIE.

Acoustics Research of Propulsion Systems

NASA Technical Reports Server (NTRS)

Gao, Ximing; Houston, Janice

2014-01-01

The liftoff phase induces high acoustic loading over a broad frequency range for a launch vehicle. These external acoustic environments are used in the prediction of the internal vibration responses of the vehicle and components. Present liftoff vehicle acoustic environment prediction methods utilize stationary data from previously conducted hold-down tests to generate 1/3 octave band Sound Pressure Level (SPL) spectra. In an effort to update the accuracy and quality of liftoff acoustic loading predictions, non-stationary flight data from the Ares I-X were processed in PC-Signal in two flight phases: simulated hold-down and liftoff. In conjunction, the Prediction of Acoustic Vehicle Environments (PAVE) program was developed in MATLAB to allow for efficient predictions of sound pressure levels (SPLs) as a function of station number along the vehicle using semi-empirical methods. This consisted of generating the Dimensionless Spectrum Function (DSF) and Dimensionless Source Location (DSL) curves from the Ares I-X flight data. These are then used in the MATLAB program to generate the 1/3 octave band SPL spectra. Concluding results show major differences in SPLs between the hold-down test data and the processed Ares I-X flight data making the Ares I-X flight data more practical for future vehicle acoustic environment predictions.

Prediction of Driving Safety in Individuals with Homonymous Hemianopia and Quadrantanopia from Clinical Neuroimaging

PubMed Central

Vaphiades, Michael S.; Kline, Lanning B.; McGwin, Gerald; Owsley, Cynthia; Shah, Ritu; Wood, Joanne M.

2014-01-01

Background. This study aimed to determine whether it is possible to predict driving safety of individuals with homonymous hemianopia or quadrantanopia based upon a clinical review of neuroimages that are routinely available in clinical practice. Methods. Two experienced neuroophthalmologists viewed a summary report of the CT/MRI scans of 16 participants with homonymous hemianopic or quadrantanopic field defects which indicated the site and extent of the lesion and they made predictions regarding whether participants would be safe/unsafe to drive. Driving safety was independently defined at the time of the study using state-recorded motor vehicle crashes (all crashes and at-fault) for the previous 5 years and ratings of driving safety determined through a standardized on-road driving assessment by a certified driving rehabilitation specialist. Results. The ability to predict driving safety was highly variable regardless of the driving safety measure, ranging from 31% to 63% (kappa levels ranged from −0.29 to 0.04). The level of agreement between the neuroophthalmologists was only fair (kappa = 0.28). Conclusions. Clinical evaluation of summary reports of currently available neuroimages by neuroophthalmologists is not predictive of driving safety. Future research should be directed at identifying and/or developing alternative tests or strategies to better enable clinicians to make these predictions. PMID:24683493

Prediction of driving safety in individuals with homonymous hemianopia and quadrantanopia from clinical neuroimaging.

PubMed

Vaphiades, Michael S; Kline, Lanning B; McGwin, Gerald; Owsley, Cynthia; Shah, Ritu; Wood, Joanne M

2014-01-01

Background. This study aimed to determine whether it is possible to predict driving safety of individuals with homonymous hemianopia or quadrantanopia based upon a clinical review of neuroimages that are routinely available in clinical practice. Methods. Two experienced neuroophthalmologists viewed a summary report of the CT/MRI scans of 16 participants with homonymous hemianopic or quadrantanopic field defects which indicated the site and extent of the lesion and they made predictions regarding whether participants would be safe/unsafe to drive. Driving safety was independently defined at the time of the study using state-recorded motor vehicle crashes (all crashes and at-fault) for the previous 5 years and ratings of driving safety determined through a standardized on-road driving assessment by a certified driving rehabilitation specialist. Results. The ability to predict driving safety was highly variable regardless of the driving safety measure, ranging from 31% to 63% (kappa levels ranged from -0.29 to 0.04). The level of agreement between the neuroophthalmologists was only fair (kappa = 0.28). Conclusions. Clinical evaluation of summary reports of currently available neuroimages by neuroophthalmologists is not predictive of driving safety. Future research should be directed at identifying and/or developing alternative tests or strategies to better enable clinicians to make these predictions.

Modeling the potential impacts of climate change on the water table level of selected forested wetlands in the southeastern United States

NASA Astrophysics Data System (ADS)

Zhu, Jie; Sun, Ge; Li, Wenhong; Zhang, Yu; Miao, Guofang; Noormets, Asko; McNulty, Steve G.; King, John S.; Kumar, Mukesh; Wang, Xuan

2017-12-01

The southeastern United States hosts extensive forested wetlands, providing ecosystem services including carbon sequestration, water quality improvement, groundwater recharge, and wildlife habitat. However, these wetland ecosystems are dependent on local climate and hydrology, and are therefore at risk due to climate and land use change. This study develops site-specific empirical hydrologic models for five forested wetlands with different characteristics by analyzing long-term observed meteorological and hydrological data. These wetlands represent typical cypress ponds/swamps, Carolina bays, pine flatwoods, drained pocosins, and natural bottomland hardwood ecosystems. The validated empirical models are then applied at each wetland to predict future water table changes using climate projections from 20 general circulation models (GCMs) participating in Coupled Model Inter-comparison Project 5 (CMIP5) under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios. We show that combined future changes in precipitation and potential evapotranspiration would significantly alter wetland hydrology including groundwater dynamics by the end of the 21st century. Compared to the historical period, all five wetlands are predicted to become drier over time. The mean water table depth is predicted to drop by 4 to 22 cm in response to the decrease in water availability (i.e., precipitation minus potential evapotranspiration) by the year 2100. Among the five examined wetlands, the depressional wetland in hot and humid Florida appears to be most vulnerable to future climate change. This study provides quantitative information on the potential magnitude of wetland hydrological response to future climate change in typical forested wetlands in the southeastern US.

Computational methods for a three-dimensional model of the petroleum-discovery process

USGS Publications Warehouse

Schuenemeyer, J.H.; Bawiec, W.J.; Drew, L.J.

1980-01-01

A discovery-process model devised by Drew, Schuenemeyer, and Root can be used to predict the amount of petroleum to be discovered in a basin from some future level of exploratory effort: the predictions are based on historical drilling and discovery data. Because marginal costs of discovery and production are a function of field size, the model can be used to make estimates of future discoveries within deposit size classes. The modeling approach is a geometric one in which the area searched is a function of the size and shape of the targets being sought. A high correlation is assumed between the surface-projection area of the fields and the volume of petroleum. To predict how much oil remains to be found, the area searched must be computed, and the basin size and discovery efficiency must be estimated. The basin is assumed to be explored randomly rather than by pattern drilling. The model may be used to compute independent estimates of future oil at different depth intervals for a play involving multiple producing horizons. We have written FORTRAN computer programs that are used with Drew, Schuenemeyer, and Root's model to merge the discovery and drilling information and perform the necessary computations to estimate undiscovered petroleum. These program may be modified easily for the estimation of remaining quantities of commodities other than petroleum. ?? 1980.

The vegetation outlook (VegOut): a new method for predicting vegetation seasonal greenness

USGS Publications Warehouse

Tadesse, T.; Wardlow, B.; Hayes, M.; Svoboda, M.; Brown, J.

2010-01-01

The vegetation outlook (VegOut) is a geospatial tool for predicting general vegetation condition patterns across large areas. VegOut predicts a standardized seasonal greenness (SSG) measure, which represents a general indicator of relative vegetation health. VegOut predicts SSG values at multiple time steps (two to six weeks into the future) based on the analysis of "historical patterns" (i.e., patterns at each 1 km grid cell and time of the year) of satellite, climate, and oceanic data over an 18-year period (1989 to 2006). The model underlying VegOut capitalizes on historical climate-vegetation interactions and ocean-climate teleconnections (such as El Niño and the Southern Oscillation, ENSO) expressed over the 18-year data record and also considers several environmental characteristics (e.g., land use/cover type and soils) that influence vegetation's response to weather conditions to produce 1 km maps that depict future general vegetation conditions. VegOut provides regionallevel vegetation monitoring capabilities with local-scale information (e.g., county to sub-county level) that can complement more traditional remote sensing-based approaches that monitor "current" vegetation conditions. In this paper, the VegOut approach is discussed and a case study over the central United States for selected periods of the 2008 growing season is presented to demonstrate the potential of this new tool for assessing and predicting vegetation conditions.

Addressing the Future in Ancient and Modern Times.

ERIC Educational Resources Information Center

Roshwald, Mordecai

1982-01-01

Explores the similarities between ancient prophecy and modern futures prediction. The article suggests that the perceived degree of certainty in predictions of the future affects the patterns of emotional and rational responses in those receiving them. (AM)

Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing

PubMed Central

Schoppe, Oliver; King, Andrew J.; Schnupp, Jan W.H.; Harper, Nicol S.

2016-01-01

Adaptation to stimulus statistics, such as the mean level and contrast of recently heard sounds, has been demonstrated at various levels of the auditory pathway. It allows the nervous system to operate over the wide range of intensities and contrasts found in the natural world. Yet current standard models of the response properties of auditory neurons do not incorporate such adaptation. Here we present a model of neural responses in the ferret auditory cortex (the IC Adaptation model), which takes into account adaptation to mean sound level at a lower level of processing: the inferior colliculus (IC). The model performs high-pass filtering with frequency-dependent time constants on the sound spectrogram, followed by half-wave rectification, and passes the output to a standard linear–nonlinear (LN) model. We find that the IC Adaptation model consistently predicts cortical responses better than the standard LN model for a range of synthetic and natural stimuli. The IC Adaptation model introduces no extra free parameters, so it improves predictions without sacrificing parsimony. Furthermore, the time constants of adaptation in the IC appear to be matched to the statistics of natural sounds, suggesting that neurons in the auditory midbrain predict the mean level of future sounds and adapt their responses appropriately. SIGNIFICANCE STATEMENT An ability to accurately predict how sensory neurons respond to novel stimuli is critical if we are to fully characterize their response properties. Attempts to model these responses have had a distinguished history, but it has proven difficult to improve their predictive power significantly beyond that of simple, mostly linear receptive field models. Here we show that auditory cortex receptive field models benefit from a nonlinear preprocessing stage that replicates known adaptation properties of the auditory midbrain. This improves their predictive power across a wide range of stimuli but keeps model complexity low as it introduces no new free parameters. Incorporating the adaptive coding properties of neurons will likely improve receptive field models in other sensory modalities too. PMID:26758822

Predictions of Solar Cycle 24: How are We Doing?

NASA Technical Reports Server (NTRS)

Pesnell, William D.

2016-01-01

Predictions of solar activity are an essential part of our Space Weather forecast capability. Users are requiring usable predictions of an upcoming solar cycle to be delivered several years before solar minimum. A set of predictions of the amplitude of Solar Cycle 24 accumulated in 2008 ranged from zero to unprecedented levels of solar activity. The predictions formed an almost normal distribution, centered on the average amplitude of all preceding solar cycles. The average of the current compilation of 105 predictions of the annual-average sunspot number is 106 +/- 31, slightly lower than earlier compilations but still with a wide distribution. Solar Cycle 24 is on track to have a below-average amplitude, peaking at an annual sunspot number of about 80. Our need for solar activity predictions and our desire for those predictions to be made ever earlier in the preceding solar cycle will be discussed. Solar Cycle 24 has been a below-average sunspot cycle. There were peaks in the daily and monthly averaged sunspot number in the Northern Hemisphere in 2011 and in the Southern Hemisphere in 2014. With the rapid increase in solar data and capability of numerical models of the solar convection zone we are developing the ability to forecast the level of the next sunspot cycle. But predictions based only on the statistics of the sunspot number are not adequate for predicting the next solar maximum. I will describe how we did in predicting the amplitude of Solar Cycle 24 and describe how solar polar field predictions could be made more accurate in the future.

Do patterns of change during treatment for panic disorder predict future panic symptoms?

PubMed Central

Steinman, Shari A.; Hunter, Michael D.; Teachman, Bethany A.

2012-01-01

Background and Objectives Cognitive-behavioral therapies are currently the gold standard for panic disorder treatment, with well-documented treatment response. However, following interventions, some individuals continue to improve, while others experience a return of symptoms. The field lacks reliable ways to predict follow-up symptomology. In the current study, a cluster analysis with a repeated measures design was conducted to examine change patterns over 12 weeks of cognitive behavioral group therapy for panic disorder. The central aim of the study was to evaluate if change patterns predict level of panic symptom severity at a six month follow-up in this sample. Methods Individuals with panic disorder (N = 36) completed a measure of panic symptoms (Panic Disorder Severity Scale) at the outset of every therapy session and at a six month follow-up. Results Results revealed three patterns of change in this specific trial, which significantly predicted level of panic symptoms six months post-treatment, beyond initial or final level of panic symptoms, and beyond total symptom change. Limitations Given the relatively small, lab-based sample, replications in other settings and samples will be important. Conclusions Overall, results provide initial evidence that change patterns are meaningful predictors of panic symptom severity well after the final session of treatment. PMID:23187115

A method for neighborhood-level surveillance of food purchasing.

PubMed

Buckeridge, David L; Charland, Katia; Labban, Alice; Ma, Yu

2014-12-01

Added sugar, particularly in carbonated soft drinks (CSDs), represents a considerable proportion of caloric intake in North America. Interventions to decrease the intake of added sugar have been proposed, but monitoring their effectiveness can be difficult due to the costs and limitations of dietary surveys. We developed, assessed the accuracy of, and took an initial step toward validating an indicator of neighborhood-level purchases of CSDs using automatically captured store scanner data in Montreal, Canada, between 2008 and 2010 and census data describing neighborhood socioeconomic characteristics. Our indicator predicted total monthly neighborhood sales based on historical sales and promotions and characteristics of the stores and neighborhoods. The prediction error for monthly sales in sampled stores was low (2.2%), and we demonstrated a negative association between predicted total sales and median personal income. For each $10,000 decrease in median personal income, we observed a fivefold increase in predicted monthly sales of CSDs. This indicator can be used by public health agencies to implement automated systems for neighborhood-level monitoring of an important upstream determinant of health. Future refinement of this indicator is possible to account for factors such as store catchment areas and to incorporate nutritional information about products. © 2014 New York Academy of Sciences.

Regional sea level variability in a high-resolution global coupled climate model

NASA Astrophysics Data System (ADS)

Palko, D.; Kirtman, B. P.

2016-12-01

The prediction of trends at regional scales is essential in order to adapt to and prepare for the effects of climate change. However, GCMs are unable to make reliable predictions at regional scales. The prediction of local sea level trends is particularly critical. The main goal of this research is to utilize high-resolution (HR) (0.1° resolution in the ocean) coupled model runs of CCSM4 to analyze regional sea surface height (SSH) trends. Unlike typical, lower resolution (1.0°) GCM runs these HR runs resolve features in the ocean, like the Gulf Stream, which may have a large effect on regional sea level. We characterize the variability of regional SSH along the Atlantic coast of the US using tide gauge observations along with fixed radiative forcing runs of CCSM4 and HR interactive ensemble runs. The interactive ensemble couples an ensemble mean atmosphere with a single ocean realization. This coupling results in a 30% decrease in the strength of the Atlantic meridional overturning circulation; therefore, the HR interactive ensemble is analogous to a HR hosing experiment. By characterizing the variability in these high-resolution GCM runs and observations we seek to understand what processes influence coastal SSH along the Eastern Coast of the United States and better predict future SLR.

Determinants and definition of abdominal obesity as related to risk of diabetes, metabolic syndrome and coronary disease in Turkish men: a prospective cohort study.

PubMed

Onat, Altan; Uyarel, Hüseyin; Hergenç, Gülay; Karabulut, Ahmet; Albayrak, Sinan; Can, Günay

2007-03-01

We aimed to investigate determinants of abdominal obesity and its clinical impact on metabolic syndrome (MS), diabetes (DM) and coronary heart disease (CHD) in men. Prospective evaluation of 1638 male participants (aged 48.5+/-12.3), representative of Turkey's men who have a high prevalence of MS. For components of MS, criteria of NCEP guidelines were adopted, modified for abdominal obesity. Follow-up constituted 9650 person-years. Insulin level (relative risk [RR] 1.40 for doubling), C-reactive protein (CRP) and heavy smoking (protective) were independent predictors of newly developing abdominal obesity. High triglyceride and low HDL-cholesterol were significantly associated already with waist girth quartile II, apolipoprotein B with quartile III. Waist girth significantly predicted future MS from quartile II on, independent of insulin resistance (IR) by homeostatic model assessment, whereby its hazard ratio (HR, 2.6) exceeded double that of HOMA. CRP independently predicted MS. Age-adjusted HR of waist girth (1.59) was significant in predicting DM. Age- and smoking-adjusted top waist quartile conferred significant risk for incident CHD (RR 1.71) but not for overall mortality. As judged by sensitivity and specificity rates for future CHD, DM and MS, abdominal obesity was most appropriately defined with a waist girth of >or=95 cm, and an action level 1 of >or=87 cm was proposed for MS in this population. Serum insulin, CRP levels and (inversely) heavy smoking are predictors for abdominal obesity in Turkish men. Atherogenic dyslipidemia and elevated blood pressure are associated significantly already with modest rises in waist girth adjusted for age and smoking. Abdominal obesity shows substantial independence of IR in the development of MS. Increasing waist girth was predictive of MS, more strongly than of DM. Risk for CHD imparted by abdominal obesity is essentially mediated by risk factors it induces.

A spatiotemporal land-use regression model of winter fine particulate levels in residential neighbourhoods.

PubMed

Smargiassi, Audrey; Brand, Allan; Fournier, Michel; Tessier, François; Goudreau, Sophie; Rousseau, Jacques; Benjamin, Mario

2012-07-01

Residential wood burning can be a significant wintertime source of ambient fine particles in urban and suburban areas. We developed a statistical model to predict minute (min) levels of particles with median diameter of <1 μm (PM1) from mobile monitoring on evenings of winter weekends at different residential locations in Quebec, Canada, considering wood burning emissions. The 6 s PM1 levels were concurrently measured on 10 preselected routes travelled 3 to 24 times during the winters of 2008-2009 and 2009-2010 by vehicles equipped with a GRIMM or a dataRAM sampler and a Global Positioning System device. Route-specific and global land-use regression (LUR) models were developed using the following spatial and temporal covariates to predict 1-min-averaged PM1 levels: chimney density from property assessment data at sampling locations, PM2.5 "regional background" levels of particles with median diameter of <2.5 μm (PM2.5) and temperature and wind speed at hour of sampling, elevation at sampling locations and day of the week. In the various routes travelled, between 49% and 94% of the variability in PM1 levels was explained by the selected covariates. The effect of chimney density was not negligible in "cottage areas." The R(2) for the global model including all routes was 0.40. This LUR is the first to predict PM1 levels in both space and time with consideration of the effects of wood burning emissions. We show that the influence of chimney density, a proxy for wood burning emissions, varies by regions and that a global model cannot be used to predict PM in regions that were not measured. Future work should consider using both survey data on wood burning intensity and information from numerical air quality forecast models, in LUR models, to improve the generalisation of the prediction of fine particulate levels.

The Predictive Value of Indocyanine Green Clearance in Future Liver Remnant for Posthepatectomy Liver Failure Following Hepatectomy with Extrahepatic Bile Duct Resection.

PubMed

Yokoyama, Yukihiro; Ebata, Tomoki; Igami, Tsuyoshi; Sugawara, Gen; Mizuno, Takashi; Yamaguchi, Junpei; Nagino, Masato

2016-06-01

Postoperative liver failure (PHLF) is one of the most common complications following major hepatectomy. The preoperative assessment of future liver remnant (FLR) function is critical to predict the incidence of PHLF. To determine the efficacy of the plasma clearance rate of indocyanine green clearance of FLR (ICGK-F) in predicting PHLF in cases of highly invasive hepatectomy with extrahepatic bile duct resection. Five hundred and eighty-five patients who underwent major hepatectomy with extrahepatic bile duct resection, from 2002 to 2014 in a single institution, were evaluated. Among them, 192 patients (33 %) had PHLF. The predictive value of ICGK-F for PHLF was determined and compared with other risk factors for PHLF. The incidence of PHLF was inversely proportional to the level of ICGK-F. With multivariate logistic regression analysis, ICGK-F, combined pancreatoduodenectomy, the operation time, and blood loss were identified as independent risk factors of PHLF. The risk of PHLF increased according to the decrement of ICGK-F (the odds ratio of ICGK-F for each decrement of 0.01 was 1.22; 95 % confidence interval 1.12-1.33; P < 0.001). Low ICGK-F was also identified as an independent risk factor predicting the postoperative mortality. ICGK-F is useful in predicting the PHLF and mortality in patients undergoing major hepatectomy with extrahepatic bile duct resection. This criterion may be useful for highly invasive hepatectomy, such as that with extrahepatic bile duct resection.

Process-based modelling to evaluate simulated groundwater levels and frequencies in a Chalk catchment in south-western England

NASA Astrophysics Data System (ADS)

Brenner, Simon; Coxon, Gemma; Howden, Nicholas J. K.; Freer, Jim; Hartmann, Andreas

2018-02-01

Chalk aquifers are an important source of drinking water in the UK. Due to their properties, they are particularly vulnerable to groundwater-related hazards like floods and droughts. Understanding and predicting groundwater levels is therefore important for effective and safe water management. Chalk is known for its high porosity and, due to its dissolvability, exposed to karstification and strong subsurface heterogeneity. To cope with the karstic heterogeneity and limited data availability, specialised modelling approaches are required that balance model complexity and data availability. In this study, we present a novel approach to evaluate simulated groundwater level frequencies derived from a semi-distributed karst model that represents subsurface heterogeneity by distribution functions. Simulated groundwater storages are transferred into groundwater levels using evidence from different observations wells. Using a percentile approach we can assess the number of days exceeding or falling below selected groundwater level percentiles. Firstly, we evaluate the performance of the model when simulating groundwater level time series using a spilt sample test and parameter identifiability analysis. Secondly, we apply a split sample test to the simulated groundwater level percentiles to explore the performance in predicting groundwater level exceedances. We show that the model provides robust simulations of discharge and groundwater levels at three observation wells at a test site in a chalk-dominated catchment in south-western England. The second split sample test also indicates that the percentile approach is able to reliably predict groundwater level exceedances across all considered timescales up to their 75th percentile. However, when looking at the 90th percentile, it only provides acceptable predictions for long time periods and it fails when the 95th percentile of groundwater exceedance levels is considered. By modifying the historic forcings of our model according to expected future climate changes, we create simple climate scenarios and we show that the projected climate changes may lead to generally lower groundwater levels and a reduction of exceedances of high groundwater level percentiles.

Effective Mitigation and Adaptation Strategies for Public Health Impacts of Heatwaves for Brookline, MA

NASA Astrophysics Data System (ADS)

Jalalzadeh Fard, B.; Hassanzadeh, H.; Bhatia, U.; Ganguly, A. R.

2016-12-01

Studies on urban areas show a significant increase in frequency and intensity of heatwaves over the past decades, and predict the same trend for future. Since heatwaves have been responsible for a large number of life losses, urgent adaptation and mitigation strategies are required in the policy and decision making level for a sustainable urban planning. The Sustainability and Data Sciences Laboratory at Northeastern University, under the aegis of Thriving Earth Exchange of AGU, is working with the town of Brookline to understand the potential public health impacts of anticipated heatwaves. We consider the most important social and physical factors to obtain vulnerability and exposure parameters for each census block group of the town. Utilizing remote sensing data, we locate Urban Heat Islands (UHIs) during a recent heatwave event, as the hazard parameter. We then create priority risk map using the risk framework. Our analyses show spatial correlations between the UHIs and social factors such as poverty, and physical factors such as land cover variations. Furthermore, we investigate the future heatwave frequency and intensity increases by analyzing the climate models predictions. For future changes of UHIs, land cover changes are investigated using available predictive data. Also, socioeconomic predictions are carried out to complete the futuristic models of heatwave risks. Considering plausible scenarios for Brookline, we develop different risk maps based on the vulnerability, exposure and hazard parameters. Eventually, we suggest guidelines for Heatwave Action Plans for prioritizing effective mitigation and adaptation strategies in urban planning for the town of Brookline.

Studies on free stream turbulence as related to gas turbine heat transfer. A review of authors' past work and future implications.

PubMed

Yavuzkurt, S; Iyer, G R

2001-05-01

A review of the past work done on free stream turbulence (FST) as applied to gas turbine heat transfer and its implications for future studies are presented. It is a comprehensive approach to the results of many individual studies in order to derive the general conclusions that could be inferred from all rather than discussing the results of each individual study. Three experimental and four modeling studies are reviewed. The first study was on prediction of heat transfer for film cooled gas turbine blades. An injection model was devised and used along with a 2-D low Reynolds number k-epsilon model of turbulence for the calculations. Reasonable predictions of heat transfer coefficients were obtained for turbulence intensity levels up to 7%. Following this modeling study a series of experimental studies were undertaken. The objective of these studies was to gain a fundamental understanding of mechanisms through which FST augments the surface heat transfer. Experiments were carried out in the boundary layer and in the free stream downstream of a gas turbine combustor simulator, which produced initial FST levels of 25.7% and large length scales (About 5-10 cm for a boundary layer 4-5 cm thick). This result showed that one possible mechanism through which FST caused an increase in heat transfer is by increasing the number of ejection events. In a number of modeling studies several well-known k-epsilon models were compared for their predictive capability of heat transfer and skin friction coefficients under moderate and high FST. Two data sets, one with moderate levels of FST (about 7%) and one with high levels of FST (about 25%) were used for this purpose. Although the models did fine in their predictions of cases with no FST (baseline cases) they failed one by one as FST levels were increased. Under high FST (25.7% initial intensity) predictions of Stanton number were between 35-100% in error compared to the measured values. Later a new additional production term indicating the interaction between the turbulent kinetic energy (TKE) and mean velocity gradients was introduced into the TKE equation. The predicted results of skin friction coefficient and Stanton number were excellent both in moderate and high FST cases. In fact these model also gave good predictions of TKE profiles whereas earlier unmodified models did not predict the correct TKE profiles even under moderate turbulence intensities. Although this new production term seems to achieve the purpose, it is the authors' belief that it is diffusion term of the TKE equation, which needs to be modified in order to fit the physical events in high FST boundary layer flows. The results of these studies are currently being used to come up with new diffusion model for the TKE equation.

Prediction in complex systems: The case of the international trade network

NASA Astrophysics Data System (ADS)

Vidmer, Alexandre; Zeng, An; Medo, Matúš; Zhang, Yi-Cheng

2015-10-01

Predicting the future evolution of complex systems is one of the main challenges in complexity science. Based on a current snapshot of a network, link prediction algorithms aim to predict its future evolution. We apply here link prediction algorithms to data on the international trade between countries. This data can be represented as a complex network where links connect countries with the products that they export. Link prediction techniques based on heat and mass diffusion processes are employed to obtain predictions for products exported in the future. These baseline predictions are improved using a recent metric of country fitness and product similarity. The overall best results are achieved with a newly developed metric of product similarity which takes advantage of causality in the network evolution.

Development of the Coastal Storm Modeling System (CoSMoS) for predicting the impact of storms on high-energy, active-margin coasts

USGS Publications Warehouse

Barnard, Patrick; Maarten van Ormondt,; Erikson, Li H.; Jodi Eshleman,; Hapke, Cheryl J.; Peter Ruggiero,; Peter Adams,; Foxgrover, Amy C.

2014-01-01

The Coastal Storm Modeling System (CoSMoS) applies a predominantly deterministic framework to make detailed predictions (meter scale) of storm-induced coastal flooding, erosion, and cliff failures over large geographic scales (100s of kilometers). CoSMoS was developed for hindcast studies, operational applications (i.e., nowcasts and multiday forecasts), and future climate scenarios (i.e., sea-level rise + storms) to provide emergency responders and coastal planners with critical storm hazards information that may be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. The prototype system, developed for the California coast, uses the global WAVEWATCH III wave model, the TOPEX/Poseidon satellite altimetry-based global tide model, and atmospheric-forcing data from either the US National Weather Service (operational mode) or Global Climate Models (future climate mode), to determine regional wave and water-level boundary conditions. These physical processes are dynamically downscaled using a series of nested Delft3D-WAVE (SWAN) and Delft3D-FLOW (FLOW) models and linked at the coast to tightly spaced XBeach (eXtreme Beach) cross-shore profile models and a Bayesian probabilistic cliff failure model. Hindcast testing demonstrates that, despite uncertainties in preexisting beach morphology over the ~500 km alongshore extent of the pilot study area, CoSMoS effectively identifies discrete sections of the coast (100s of meters) that are vulnerable to coastal hazards under a range of current and future oceanographic forcing conditions, and is therefore an effective tool for operational and future climate scenario planning.

The antecedents and consequences of a beyond-choice view of decision situations: A construal level theory perspective.

PubMed

Halamish, Vered; Borovoi, Leah; Liberman, Nira

2017-02-01

Evaluating alternatives and comparing them to each other are integral to decision-making. In addition, however, decision makers may adopt a view that goes beyond choice and make inferences about the entire set of alternatives, about the dimensions that are relevant in similar decisions, and about the range of values on a specific dimension. We examined some antecedents and consequences of adopting a beyond-choice view of decision situations. Based on Construal Level Theory we suggest that a beyond-choice view entails high (vs. low) level of construal of the decision situation and hence is more likely to occur for decisions that are more psychologically distant. We further suggest that a consequence of a beyond-choice view might be a later difficulty to remember which attribute belongs to which alternative. To examine these predictions we conducted an experiment in which participants evaluated decision scenarios that were described as being relevant for the distant (vs. the near) future. One day later they answered a decision-related source recognition test in which they were asked to remember which attribute belongs to which alternative. As predicted, people had more source-memory errors in the distant than in the near future condition. These results suggest that a beyond-choice view of decision situations is an important consequence of psychological distance (vs. proximity). Copyright © 2016 Elsevier B.V. All rights reserved.

Is there scale-dependent bias in single-field inflation?

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

De Putter, Roland; Doré, Olivier; Green, Daniel, E-mail: rdputter@caltech.edu, E-mail: Olivier.P.Dore@jpl.nasa.gov, E-mail: drgreen@cita.utoronto.ca

2015-10-01

Scale-dependent halo bias due to local primordial non-Gaussianity provides a strong test of single-field inflation. While it is universally understood that single-field inflation predicts negligible scale-dependent bias compared to current observational uncertainties, there is still disagreement on the exact level of scale-dependent bias at a level that could strongly impact inferences made from future surveys. In this paper, we clarify this confusion and derive in various ways that there is exactly zero scale-dependent bias in single-field inflation. Much of the current confusion follows from the fact that single-field inflation does predict a mode coupling of matter perturbations at the levelmore » of f{sub NL}{sup local}; ≈ −5/3, which naively would lead to scale-dependent bias. However, we show explicitly that this mode coupling cancels out when perturbations are evaluated at a fixed physical scale rather than fixed coordinate scale. Furthermore, we show how the absence of scale-dependent bias can be derived easily in any gauge. This result can then be incorporated into a complete description of the observed galaxy clustering, including the previously studied general relativistic terms, which are important at the same level as scale-dependent bias of order f{sub NL}{sup local} ∼ 1. This description will allow us to draw unbiased conclusions about inflation from future galaxy clustering data.« less

A Coastal Hazards Data Base for the U.S. East Coast (1992) (NDP-043a)

DOE Data Explorer

Gornitz, Vivien M. [NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States); White, Tammy W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

1992-01-01

This NDP presents data on coastal geology, geomorphology, elevation, erosion, wave heights, tide ranges, and sea levels for the U.S. east coast. These data may be used either by nongeographic database management systems or by raster or vector geographic information systems (GISs). The database integrates several data sets (originally obtained as point, line, and polygon data) for the east coast into 0.25°-latitude by 0.25°-longitude grid cells. Each coastal grid cell contains 28 data variables. This NDP may be used to predict the response of coastal zones on the U.S. east coast to changes in local or global sea levels. Information on the geologic, geomorphic, and erosional states of the coast provides the basic data needed to predict the behavior of the coastal zone into the far future. Thus, these data may be seen as providing a baseline for the calculation of the relative vulnerability of the east coast to projected sea-level rises. This data will also be useful to research, educational, governmental, and private organizations interested in the present and future vulnerability of coastal areas to erosion and inundation. The data are in 13 files, the largest of which is 1.42 MB; the entire data base takes up 3.29 MB, excluding the ARC/INFO^TM files.

Cerebrospinal Fluid Biomarkers and Reserve Variables as Predictors of Future "Non-Cognitive" Outcomes of Alzheimer's Disease.

PubMed

Ingber, Adam P; Hassenstab, Jason; Fagan, Anne M; Benzinger, Tammie L S; Grant, Elizabeth A; Holtzman, David M; Morris, John C; Roe, Catherine M

2016-01-01

The influence of reserve variables and Alzheimer's disease (AD) biomarkers on cognitive test performance has been fairly well-characterized. However, less is known about the influence of these factors on "non-cognitive" outcomes, including functional abilities and mood. We examined whether cognitive and brain reserve variables mediate how AD biomarker levels in cognitively normal persons predict future changes in function, mood, and neuropsychiatric behavior. Non-cognitive outcomes were examined in 328 individuals 50 years and older enrolled in ongoing studies of aging and dementia at the Knight Alzheimer Disease Research Center (ADRC). All participants were cognitively normal at baseline (Clinical Dementia Rating [CDR] 0), completed cerebrospinal fluid (CSF) and structural neuroimaging studies within one year of baseline, and were followed for an average of 4.6 annual visits. Linear mixed effects models explored how cognitive reserve and brain reserve variables mediate the relationships between AD biomarker levels and changes in function, mood, and neuropsychiatric behavior in cognitively normal participants. Education levels did not have a significant effect on predicting non-cognitive decline. However, participants with smaller brain volumes exhibited the worst outcomes on measures of mood, functional abilities, and behavioral disturbance. This effect was most pronounced in individuals who also had abnormal CSF biomarkers. The findings suggest that brain reserve plays a stronger, or earlier, role than cognitive reserve in protecting against non-cognitive impairment in AD.

Satellite markers: a simple method for ground truth car pose on stereo video

NASA Astrophysics Data System (ADS)

Gil, Gustavo; Savino, Giovanni; Piantini, Simone; Pierini, Marco

2018-04-01

Artificial prediction of future location of other cars in the context of advanced safety systems is a must. The remote estimation of car pose and particularly its heading angle is key to predict its future location. Stereo vision systems allow to get the 3D information of a scene. Ground truth in this specific context is associated with referential information about the depth, shape and orientation of the objects present in the traffic scene. Creating 3D ground truth is a measurement and data fusion task associated with the combination of different kinds of sensors. The novelty of this paper is the method to generate ground truth car pose only from video data. When the method is applied to stereo video, it also provides the extrinsic camera parameters for each camera at frame level which are key to quantify the performance of a stereo vision system when it is moving because the system is subjected to undesired vibrations and/or leaning. We developed a video post-processing technique which employs a common camera calibration tool for the 3D ground truth generation. In our case study, we focus in accurate car heading angle estimation of a moving car under realistic imagery. As outcomes, our satellite marker method provides accurate car pose at frame level, and the instantaneous spatial orientation for each camera at frame level.

A complete, multi-level conformational clustering of antibody complementarity-determining regions

PubMed Central

Nikoloudis, Dimitris; Pitts, Jim E.

2014-01-01

Classification of antibody complementarity-determining region (CDR) conformations is an important step that drives antibody modelling and engineering, prediction from sequence, directed mutagenesis and induced-fit studies, and allows inferences on sequence-to-structure relations. Most of the previous work performed conformational clustering on a reduced set of structures or after application of various structure pre-filtering criteria. In this study, it was judged that a clustering of every available CDR conformation would produce a complete and redundant repertoire, increase the number of sequence examples and allow better decisions on structure validity in the future. In order to cope with the potential increase in data noise, a first-level statistical clustering was performed using structure superposition Root-Mean-Square Deviation (RMSD) as a distance-criterion, coupled with second- and third-level clustering that employed Ramachandran regions for a deeper qualitative classification. The classification of a total of 12,712 CDR conformations is thus presented, along with rich annotation and cluster descriptions, and the results are compared to previous major studies. The present repertoire has procured an improved image of our current CDR Knowledge-Base, with a novel nesting of conformational sensitivity and specificity that can serve as a systematic framework for improved prediction from sequence as well as a number of future studies that would aid in knowledge-based antibody engineering such as humanisation. PMID:25071986

Cultural variation in the use of current life satisfaction to predict the future.

PubMed

Oishi, S; Wyer, R S; Colcombe, S J

2000-03-01

Three studies examined cultural and situational influences on the tendency for people to use their current life satisfaction to predict future life events. On the basis of the self-enhancement literature, it was predicted that either writing about a positive personal experience or reading about another's negative experience would lead European Americans to focus their attention on internal attributes and thus would lead them to use their current life satisfaction in predicting the future. Conversely, on the basis of the self-criticism literature, it was predicted that these same conditions would lead Asian Americans to focus their attention on external factors and, therefore, would decrease their likelihood of using their current life satisfaction to predict the future. Studies 1 and 2 supported these hypotheses. Study 3 showed that these patterns could be obtained by subliminally priming concepts associated with individualism and collectivism.

A temporal forecast of radiation environments for future space exploration missions.

PubMed

Kim, Myung-Hee Y; Cucinotta, Francis A; Wilson, John W

2007-06-01

The understanding of future space radiation environments is an important goal for space mission operations, design, and risk assessment. We have developed a solar cycle statistical model in which sunspot number is coupled to space-related quantities, such as the galactic cosmic radiation (GCR) deceleration potential (phi) and the mean occurrence frequency of solar particle events (SPEs). Future GCR fluxes were derived from a predictive model, in which the temporal dependence represented by phi was derived from GCR flux and ground-based Climax neutron monitor rate measurements over the last four decades. These results showed that the point dose equivalent inside a typical spacecraft in interplanetary space was influenced by solar modulation by up to a factor of three. It also has been shown that a strong relationship exists between large SPE occurrences and phi. For future space exploration missions, cumulative probabilities of SPEs at various integral fluence levels during short-period missions were defined using a database of proton fluences of past SPEs. Analytic energy spectra of SPEs at different ranks of the integral fluences for energies greater than 30 MeV were constructed over broad energy ranges extending out to GeV for the analysis of representative exposure levels at those fluences. Results will guide the design of protection systems for astronauts during future space exploration missions.

Family cumulative risk and at-risk kindergarteners' social competence: the mediating role of parent representations of the attachment relationship.

PubMed

Sparks, Lauren A; Trentacosta, Christopher J; Owusu, Erika; McLear, Caitlin; Smith-Darden, Joanne

2018-08-01

Secure attachment relationships have been linked to social competence in at-risk children. In the current study, we examined the role of parent secure base scripts in predicting at-risk kindergarteners' social competence. Parent representations of secure attachment were hypothesized to mediate the relationship between lower family cumulative risk and children's social competence. Participants included 106 kindergarteners and their primary caregivers recruited from three urban charter schools serving low-income families as a part of a longitudinal study. Lower levels of cumulative risk predicted greater secure attachment representations in parents, and scores on the secure base script assessment predicted children's social competence. An indirect relationship between lower cumulative risk and kindergarteners' social competence via parent secure base script scores was also supported. Parent script-based representations of the attachment relationship appear to be an important link between lower levels of cumulative risk and low-income kindergarteners' social competence. Implications of these findings for future interventions are discussed.

The nonlinear dynamics of family problem solving in adolescence: the predictive validity of a peaceful resolution attractor.

PubMed

Dishion, Thomas J; Forgatch, Marion; Van Ryzin, Mark; Winter, Charlotte

2012-07-01

In this study we examined the videotaped family interactions of a community sample of adolescents and their parents. Youths were assessed in early to late adolescence on their levels of antisocial behavior. At age 16-17, youths and their parents were videotaped interacting while completing a variety of tasks, including family problem solving. The interactions were coded and compared for three developmental patterns of antisocial behavior: early onset, persistent; adolescence onset; and typically developing. The mean duration of conflict bouts was the only interaction pattern that discriminated the 3 groups. In the prediction of future antisocial behavior, parent and youth reports of transition entropy and conflict resolution interacted to account for antisocial behavior at age 18-19. Families with low entropy and peaceful resolutions predicted low levels of youth antisocial behavior at age 18-19. These findings suggest the need to study both attractors and repellers to understand family dynamics associated with health and social and emotional development.

The Nonlinear Dynamics of Family Problem Solving in Adolescence: The Predictive Validity of a Peaceful Resolution Attractor

PubMed Central

Dishion, Thomas J.; Forgatch, Marion; Van Ryzin, Mark; Winter, Charlotte

2012-01-01

In this study we examined the videotaped family interactions of a community sample of adolescents and their parents. Youths were assessed in early to late adolescence on their levels of antisocial behavior. At age 16–17, youths and their parents were videotaped interacting while completing a variety of tasks, including family problem solving. The interactions were coded and compared for 3 developmental patterns of antisocial behavior: early onset, persistent; adolescence onset; and typically developing. The mean duration of conflict bouts was the only interaction pattern that discriminated the 3 groups. In the prediction of future antisocial behavior, parent and youth reports of transition entropy and conflict resolution interacted to account for antisocial behavior at age 18–19. Families with low entropy and peaceful resolutions predicted low levels of youth antisocial behavior at age 18–19. These findings suggest the need to study both attractors and repellers to understand family dynamics associated with health and social and emotional development. PMID:22695152

Generalized plasma skimming model for cells and drug carriers in the microvasculature.

PubMed

Lee, Tae-Rin; Yoo, Sung Sic; Yang, Jiho

2017-04-01

In microvascular transport, where both blood and drug carriers are involved, plasma skimming has a key role on changing hematocrit level and drug carrier concentration in capillary beds after continuous vessel bifurcation in the microvasculature. While there have been numerous studies on modeling the plasma skimming of blood, previous works lacked in consideration of its interaction with drug carriers. In this paper, a generalized plasma skimming model is suggested to predict the redistributions of both the cells and drug carriers at each bifurcation. In order to examine its applicability, this new model was applied on a single bifurcation system to predict the redistribution of red blood cells and drug carriers. Furthermore, this model was tested at microvascular network level under different plasma skimming conditions for predicting the concentration of drug carriers. Based on these results, the applicability of this generalized plasma skimming model is fully discussed and future works along with the model's limitations are summarized.

The Next Twenty-Five Years: It's Time to Plan.

ERIC Educational Resources Information Center

Jugenheimer, Donald W.

There is a need in the advertising industry for prediction--of the future in general, of the new communication technology, and of the implications for advertising. Studies of the future in other disciplines have identified at least four separate future trends relevant to prediction and preparation for the future in advertising: within specified…

The importance of measuring growth in response to intervention models: Testing a core assumption✩

PubMed Central

Schatschneider, Christopher; Wagner, Richard K.; Crawford, Elizabeth C.

2011-01-01

A core assumption of response to instruction or intervention (RTI) models is the importance of measuring growth in achievement over time in response to effective instruction or intervention. Many RTI models actively monitor growth for identifying individuals who need different levels of intervention. A large-scale (N=23,438), two-year longitudinal study of first grade children was carried out to compare the predictive validity of measures of achievement status, growth in achievement, and their combination for predicting future reading achievement. The results indicate that under typical conditions, measures of growth do not make a contribution to prediction that is independent of measures of achievement status. These results question the validity of a core assumption of RTI models. PMID:22224065

The behavioral economics of young adult substance abuse.

PubMed

Murphy, James G; Dennhardt, Ashley A

2016-11-01

Alcohol and drug use peaks during young adulthood and can interfere with critical developmental tasks and set the stage for chronic substance misuse and associated social, educational, and health-related outcomes. There is a need for novel, theory-based approaches to guide substance abuse prevention efforts during this critical developmental period. This paper discusses the particular relevance of behavioral economic theory to young adult alcohol and drug misuse, and reviews of available literature on prevention and intervention strategies that are consistent with behavioral economic theory. Behavioral economic theory predicts that decisions to use drugs and alcohol are related to the relative availability and price of both alcohol and substance-free alternative activities, and the extent to which reinforcement from delayed substance-free outcomes is devalued relative to the immediate reinforcement associated with drugs. Behavioral economic measures of motivation for substance use are based on relative levels of behavioral and economic resource allocation towards drug versus alternatives, and have been shown to predict change in substance use over time. Policy and individual level prevention approaches that are consistent with behavioral economic theory are discussed, including brief interventions that increase future orientation and engagement in rewarding alternatives to substance use. Prevention approaches that increase engagement in constructive future-oriented activities among young adults (e.g., educational/vocational success) have the potential to reduce future health disparities associated with both substance abuse and poor educational/vocational outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

Predicting who will major in a science discipline: Expectancy-value theory as part of an ecological model for studying academic communities

NASA Astrophysics Data System (ADS)

Sullins, Ellen S.; Hernandez, Delia; Fuller, Carol; Shiro Tashiro, Jay

Research on factors that shape recruitment and retention in undergraduate science majors currently is highly fragmented and in need of an integrative research framework. Such a framework should incorporate analyses of the various levels of organization that characterize academic communities (i.e., the broad institutional level, the departmental level, and the student level), and should also provide ways to study the interactions occurring within and between these structural levels. We propose that academic communities are analogous to ecosystems, and that the research paradigms of modern community ecology can provide the necessary framework, as well as new and innovative approaches to a very complex area. This article also presents the results of a pilot study that demonstrates the promise of this approach at the student level. We administered a questionnaire based on expectancy-value theory to undergraduates enrolled in introductory biology courses. Itself an integrative approach, expectancy-value theory views achievement-related behavior as a joint function of the person's expectancy of success in the behavior and the subjective value placed on such success. Our results indicated: (a) significant gender differences in the underlying factor structures of expectations and values related to the discipline of biology, (b) expectancy-value factors significantly distinguished biology majors from nonmajors, and (c) expectancy-value factors significantly predicted students' intent to enroll in future biology courses. We explore the expectancy-value framework as an operationally integrative framework in our ecological model for studying academic communities, especially in the context of assessing the underrepresentation of women and minorities in the sciences. Future research directions as well as practical implications are also discussed.

Exploring Change Processes in School-Based Mentoring for Bullied Children.

PubMed

Craig, James T; Gregus, Samantha J; Burton, Ally; Hernandez Rodriguez, Juventino; Blue, Mallory; Faith, Melissa A; Cavell, Timothy A

2016-02-01

We examined change processes associated with the school-based, lunchtime mentoring of bullied children. We used data from a one-semester open trial of Lunch Buddy (LB) mentoring (N = 24) to examine changes in bullied children's lunchtime peer relationships. We also tested whether these changes predicted key outcomes (i.e., peer victimization, social preference) post-mentoring. Results provided partial support that bullied children paired with LB mentors experienced improved lunchtime peer relationships and that gains in lunchtime relationships predicted post-mentoring levels of social preference and peer victimization. Neither child nor mentors' ratings of the mentoring relationship predicted post-mentoring outcomes; however, child-rated mentor support and conflict predicted improvements in lunchtime peer relationships. We discuss implications for future research on school-based mentoring as a form of selective intervention for bullied children.

Limitations of diagnostic precision and predictive utility in the individual case: a challenge for forensic practice.

PubMed

Cooke, David J; Michie, Christine

2010-08-01

Knowledge of group tendencies may not assist accurate predictions in the individual case. This has importance for forensic decision making and for the assessment tools routinely applied in forensic evaluations. In this article, we applied Monte Carlo methods to examine diagnostic agreement with different levels of inter-rater agreement given the distributional characteristics of PCL-R scores. Diagnostic agreement and score agreement were substantially less than expected. In addition, we examined the confidence intervals associated with individual predictions of violent recidivism. On the basis of empirical findings, statistical theory, and logic, we conclude that predictions of future offending cannot be achieved in the individual case with any degree of confidence. We discuss the problems identified in relation to the PCL-R in terms of the broader relevance to all instruments used in forensic decision making.

Climate change risk to forests in China associated with warming.

PubMed

Yin, Yunhe; Ma, Danyang; Wu, Shaohong

2018-01-11

Variations in forest net primary productivity (NPP) reflects the combined effects of key climate variables on ecosystem structure and function, especially on the carbon cycle. We performed risk analysis indicated by the magnitude of future negative anomalies in NPP in comparison with the natural interannual variability to investigate the impact of future climatic projections on forests in China. Results from the multi-model ensemble showed that climate change risk of decreases in forest NPP would be more significant in higher emission scenario in China. Under relatively low emission scenarios, the total area of risk was predicted to decline, while for RCP8.5, it was predicted to first decrease and then increase after the middle of 21st century. The rapid temperature increases predicted under the RCP8.5 scenario would be probably unfavorable for forest vegetation growth in the long term. High-level risk area was likely to increase except RCP2.6. The percentage area at high risk was predicted to increase from 5.39% (2021-2050) to 27.62% (2071-2099) under RCP8.5. Climate change risk to forests was mostly concentrated in southern subtropical and tropical regions, generally significant under high emission scenario of RCP8.5, which was mainly attributed to the intensified dryness in south China.

Cortical Thickness Predicts the First Onset of Major Depression in Adolescence

PubMed Central

Foland-Ross, Lara C.; Sacchet, Matthew D.; Prasad, Gautam; Gilbert, Brooke; Thompson, Paul M.; Gotlib, Ian H.

2015-01-01

Given the increasing prevalence of Major Depressive Disorder and recent advances in preventative treatments for this disorder, an important challenge in pediatric neuroimaging is the early identification of individuals at risk for depression. We examined whether machine learning can be used to predict the onset of depression at the individual level. Thirty-three never-disordered adolescents (10–15 years old) underwent structural MRI. Participants were followed for 5 years to monitor the emergence of clinically significant depressive symptoms. We used support vector machines (SVMs) to test whether baseline cortical thickness could reliably distinguish adolescents who develop depression from adolescents who remained free of any Axis I disorder. Accuracies from subsampled cross-validated classification were used to assess classifier performance. Baseline cortical thickness correctly predicted the future onset of depression with an overall accuracy of 70% (69% sensitivity, 70% specificity; p = 0.021). Examination of SVM feature weights indicated that the right medial orbitofrontal, right precentral, left anterior cingulate, and bilateral insular cortex contributed most strongly to this classification. These findings indicate that cortical gray matter structure can predict the subsequent onset of depression. An important direction for future research is to elucidate mechanisms by which these anomalies in gray matter structure increase risk for developing this disorder. PMID:26315399

Cortical thickness predicts the first onset of major depression in adolescence.

PubMed

Foland-Ross, Lara C; Sacchet, Matthew D; Prasad, Gautam; Gilbert, Brooke; Thompson, Paul M; Gotlib, Ian H

2015-11-01

Given the increasing prevalence of Major Depressive Disorder and recent advances in preventative treatments for this disorder, an important challenge in pediatric neuroimaging is the early identification of individuals at risk for depression. We examined whether machine learning can be used to predict the onset of depression at the individual level. Thirty-three never-disordered adolescents (10-15 years old) underwent structural MRI. Participants were followed for 5 years to monitor the emergence of clinically significant depressive symptoms. We used support vector machines (SVMs) to test whether baseline cortical thickness could reliably distinguish adolescents who develop depression from adolescents who remained free of any Axis I disorder. Accuracies from subsampled cross-validated classification were used to assess classifier performance. Baseline cortical thickness correctly predicted the future onset of depression with an overall accuracy of 70% (69% sensitivity, 70% specificity; p=0.021). Examination of SVM feature weights indicated that the right medial orbitofrontal, right precentral, left anterior cingulate, and bilateral insular cortex contributed most strongly to this classification. These findings indicate that cortical gray matter structure can predict the subsequent onset of depression. An important direction for future research is to elucidate mechanisms by which these anomalies in gray matter structure increase risk for developing this disorder. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identifying Future Scientists: Predicting Persistence into Research Training

PubMed Central

2007-01-01

This study used semistructured interviews and grounded theory to look for characteristics among college undergraduates that predicted persistence into Ph.D. and M.D./Ph.D. training. Participants in the summer undergraduate and postbaccalaureate research programs at the Mayo Clinic College of Medicine were interviewed at the start, near the end, and 8–12 months after their research experience. Of more than 200 themes considered, five characteristics predicted those students who went on to Ph.D. and M.D./Ph.D. training or to M.D. training intending to do research: 1) Curiosity to discover the unknown, 2) Enjoyment of problem solving, 3) A high level of independence, 4) The desire to help others indirectly through research, and 5) A flexible, minimally structured approach to the future. Web-based surveys with different students confirmed the high frequency of curiosity and/or problem solving as the primary reason students planned research careers. No evidence was found for differences among men, women, and minority and nonminority students. Although these results seem logical compared with successful scientists, their constancy, predictive capabilities, and sharp contrast to students who chose clinical medicine were striking. These results provide important insights into selection and motivation of potential biomedical scientists and the early experiences that will motivate them toward research careers. PMID:18056303

Concepts and tools for predictive modeling of microbial dynamics.

PubMed

Bernaerts, Kristel; Dens, Els; Vereecken, Karen; Geeraerd, Annemie H; Standaert, Arnout R; Devlieghere, Frank; Debevere, Johan; Van Impe, Jan F

2004-09-01

Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models.

Identifying future scientists: predicting persistence into research training.

PubMed

McGee, Richard; Keller, Jill L

2007-01-01

This study used semistructured interviews and grounded theory to look for characteristics among college undergraduates that predicted persistence into Ph.D. and M.D./Ph.D. training. Participants in the summer undergraduate and postbaccalaureate research programs at the Mayo Clinic College of Medicine were interviewed at the start, near the end, and 8-12 months after their research experience. Of more than 200 themes considered, five characteristics predicted those students who went on to Ph.D. and M.D./Ph.D. training or to M.D. training intending to do research: 1) Curiosity to discover the unknown, 2) Enjoyment of problem solving, 3) A high level of independence, 4) The desire to help others indirectly through research, and 5) A flexible, minimally structured approach to the future. Web-based surveys with different students confirmed the high frequency of curiosity and/or problem solving as the primary reason students planned research careers. No evidence was found for differences among men, women, and minority and nonminority students. Although these results seem logical compared with successful scientists, their constancy, predictive capabilities, and sharp contrast to students who chose clinical medicine were striking. These results provide important insights into selection and motivation of potential biomedical scientists and the early experiences that will motivate them toward research careers.

Combining a Spatial Model and Demand Forecasts to Map Future Surface Coal Mining in Appalachia

PubMed Central

Strager, Michael P.; Strager, Jacquelyn M.; Evans, Jeffrey S.; Dunscomb, Judy K.; Kreps, Brad J.; Maxwell, Aaron E.

2015-01-01

Predicting the locations of future surface coal mining in Appalachia is challenging for a number of reasons. Economic and regulatory factors impact the coal mining industry and forecasts of future coal production do not specifically predict changes in location of future coal production. With the potential environmental impacts from surface coal mining, prediction of the location of future activity would be valuable to decision makers. The goal of this study was to provide a method for predicting future surface coal mining extents under changing economic and regulatory forecasts through the year 2035. This was accomplished by integrating a spatial model with production demand forecasts to predict (1 km2) gridded cell size land cover change. Combining these two inputs was possible with a ratio which linked coal extraction quantities to a unit area extent. The result was a spatial distribution of probabilities allocated over forecasted demand for the Appalachian region including northern, central, southern, and eastern Illinois coal regions. The results can be used to better plan for land use alterations and potential cumulative impacts. PMID:26090883

Testing predictive models of positive and negative affect with psychosocial, acculturation, and coping variables in a multiethnic undergraduate sample.

PubMed

Kuo, Ben Ch; Kwantes, Catherine T

2014-01-01

Despite the prevalence and popularity of research on positive and negative affect within the field of psychology, there is currently little research on affect involving the examination of cultural variables and with participants of diverse cultural and ethnic backgrounds. To the authors' knowledge, currently no empirical studies have comprehensively examined predictive models of positive and negative affect based specifically on multiple psychosocial, acculturation, and coping variables as predictors with any sample populations. Therefore, the purpose of the present study was to test the predictive power of perceived stress, social support, bidirectional acculturation (i.e., Canadian acculturation and heritage acculturation), religious coping and cultural coping (i.e., collective, avoidance, and engagement coping) in explaining positive and negative affect in a multiethnic sample of 301 undergraduate students in Canada. Two hierarchal multiple regressions were conducted, one for each affect as the dependent variable, with the above described predictors. The results supported the hypotheses and showed the two overall models to be significant in predicting affect of both kinds. Specifically, a higher level of positive affect was predicted by a lower level of perceived stress, less use of religious coping, and more use of engagement coping in dealing with stress by the participants. Higher level of negative affect, however, was predicted by a higher level of perceived stress and more use of avoidance coping in responding to stress. The current findings highlight the value and relevance of empirically examining the stress-coping-adaptation experiences of diverse populations from an affective conceptual framework, particularly with the inclusion of positive affect. Implications and recommendations for advancing future research and theoretical works in this area are considered and presented.

Predicting past and future diameter growth for trees in the northeastern United States

Treesearch

James A. Westfall

2006-01-01

Tree diameter growth models are widely used in forestry applications, often to predict tree size at a future point in time. Also, there are instances where projections of past diameters are needed. A relative diameter growth model was developed to allow prediction of both future and past growth rates. Coefficients were estimated for 15 species groups that cover most...

IMF Prediction with Cosmic Rays

NASA Astrophysics Data System (ADS)

Bieber, J. W.; Evenson, P. A.; Kuwabara, T.; Pei, C.

2013-12-01

Cosmic rays impacting Earth have passed through and interacted with the interplanetary magnetic field (IMF) surrounding Earth, and in some sense they carry information on the three-dimensional structure of that field. This work uses neutron monitor data in an effort to extract that information and use it to predict the future behavior of the IMF, especially the north-south component (Bz) which is so crucial in determining geomagnetic activity. We consider 161 events from a published list of interplanetary coronal mass ejections and compare hourly averages of the predicted field with the actual field measured later. We find that the percentage of events with 'good' predictions of Bz (in the sense of having a positive correlation between the prediction and the subsequent measurement) varies from about 85% for predictions 1 hour into the future to about 60% for predictions 4 hours into the future. We present several ideas for how the method might be improved in future implementations. Supported by NASA grant NNX08AQ01G and NSF grant ANT-0739620.

Individual to Community-Level Faunal Responses to Environmental Change from a Marine Fossil Record of Early Miocene Global Warming

PubMed Central

Belanger, Christina L.

2012-01-01

Modern climate change has a strong potential to shift earth systems and biological communities into novel states that have no present-day analog, leaving ecologists with no observational basis to predict the likely biotic effects. Fossil records contain long time-series of past environmental changes outside the range of modern observation, which are vital for predicting future ecological responses, and are capable of (a) providing detailed information on rates of ecological change, (b) illuminating the environmental drivers of those changes, and (c) recording the effects of environmental change on individual physiological rates. Outcrops of Early Miocene Newport Member of the Astoria Formation (Oregon) provide one such time series. This record of benthic foraminiferal and molluscan community change from continental shelf depths spans a past interval environmental change (∼20.3-16.7 mya) during which the region warmed 2.1–4.5°C, surface productivity and benthic organic carbon flux increased, and benthic oxygenation decreased, perhaps driven by intensified upwelling as on the modern Oregon coast. The Newport Member record shows that (a) ecological responses to natural environmental change can be abrupt, (b) productivity can be the primary driver of faunal change during global warming, (c) molluscs had a threshold response to productivity change while foraminifera changed gradually, and (d) changes in bivalve body size and growth rates parallel changes in taxonomic composition at the community level, indicating that, either directly or indirectly through some other biological parameter, the physiological tolerances of species do influence community change. Ecological studies in modern and fossil records that consider multiple ecological levels, environmental parameters, and taxonomic groups can provide critical information for predicting future ecological change and evaluating species vulnerability. PMID:22558424

FY10 Report on Multi-scale Simulation of Solvent Extraction Processes: Molecular-scale and Continuum-scale Studies

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

Wardle, Kent E.; Frey, Kurt; Pereira, Candido

2014-02-02

This task is aimed at predictive modeling of solvent extraction processes in typical extraction equipment through multiple simulation methods at various scales of resolution. We have conducted detailed continuum fluid dynamics simulation on the process unit level as well as simulations of the molecular-level physical interactions which govern extraction chemistry. Through combination of information gained through simulations at each of these two tiers along with advanced techniques such as the Lattice Boltzmann Method (LBM) which can bridge these two scales, we can develop the tools to work towards predictive simulation for solvent extraction on the equipment scale (Figure 1). Themore » goal of such a tool-along with enabling optimized design and operation of extraction units-would be to allow prediction of stage extraction effrciency under specified conditions. Simulation efforts on each of the two scales will be described below. As the initial application of FELBM in the work performed during FYl0 has been on annular mixing it will be discussed in context of the continuum-scale. In the future, however, it is anticipated that the real value of FELBM will be in its use as a tool for sub-grid model development through highly refined DNS-like multiphase simulations facilitating exploration and development of droplet models including breakup and coalescence which will be needed for the large-scale simulations where droplet level physics cannot be resolved. In this area, it can have a significant advantage over traditional CFD methods as its high computational efficiency allows exploration of significantly greater physical detail especially as computational resources increase in the future.« less

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach—A Case Study for the City of Wuhan in China

PubMed Central

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-01-01

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study—simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan. PMID:28617348

Predicting body temperature and activity of adult Polyommatus icarus using neural network models under current and projected climate scenarios.

PubMed

Howe, P D; Bryant, S R; Shreeve, T G

2007-10-01

We use field observations in two geographic regions within the British Isles and regression and neural network models to examine the relationship between microhabitat use, thoracic temperatures and activity in a widespread lycaenid butterfly, Polyommatus icarus. We also make predictions for future activity under climate change scenarios. Individuals from a univoltine northern population initiated flight with significantly lower thoracic temperatures than individuals from a bivoltine southern population. Activity is dependent on body temperature and neural network models of body temperature are better at predicting body temperature than generalized linear models. Neural network models of activity with a sole input of predicted body temperature (using weather and microclimate variables) are good predictors of observed activity and were better predictors than generalized linear models. By modelling activity under climate change scenarios for 2080 we predict differences in activity in relation to both regional differences of climate change and differing body temperature requirements for activity in different populations. Under average conditions for low-emission scenarios there will be little change in the activity of individuals from central-southern Britain and a reduction in northwest Scotland from 2003 activity levels. Under high-emission scenarios, flight-dependent activity in northwest Scotland will increase the greatest, despite smaller predicted increases in temperature and decreases in cloud cover. We suggest that neural network models are an effective way of predicting future activity in changing climates for microhabitat-specialist butterflies and that regional differences in the thermoregulatory response of populations will have profound effects on how they respond to climate change.

The Theory of Planned Behavior as a Predictor of Growth in Risky College Drinking*

PubMed Central

Collins, Susan E.; Witkiewitz, Katie; Larimer, Mary E.

2011-01-01

Objective: This study tested the Theory of Planned Behavior (TPB) as a predictor of growth in risky college drinking over a 3-month period. As predicted by the TPB model, it was hypothesized that attitudes, subjective norms, and perceived behavioral control would predict intention to engage in risky drinking, which would in turn predict growth in future risky drinking. Method: Participants were 837 college drinkers (64.2% female) who were randomly selected from two U.S. West Coast universities to participate in a larger study on college drinking norms. This study used latent growth analyses to test the ability of the TPB to predict baseline levels of as well as linear and quadratic growth in risky college drinking (i.e., heavy episodic drinking and peak drinking quantity). Results: Chi-square tests and fit indices indicated close fit for the final structural models. Self-efficacy, attitudes, and subjective norms significantly predicted baseline intention, which in turn predicted future heavy episodic drinking. Self-efficacy and attitudes were also related to intention in the model of peak drinking; however, subjective norms were not a significant predictor of intention in the peak drinking model. Mediation analyses showed that intention to engage in risky drinking mediated the effects of self-efficacy and attitudes on growth in risky drinking. Conclusions: Findings supported the TPB in predicting risky college drinking. Although the current findings should be replicated before definitive conclusions are drawn, results suggest that feedback on self-efficacy, attitudes, and intentions to engage in risky drinking may be a helpful addition to personalized feedback interventions for this population. PMID:21388605

Prediction of Exposure Level of Energetic Solar Particle Events

NASA Astrophysics Data System (ADS)

Kim, M. H. Y.; Blattnig, S.

2016-12-01

The potential for exposure to large solar particle events (SPEs) with fluxes that extend to high energies is a major concern during interplanetary transfer and extravehicular activities (EVAs) on the lunar and Martian surfaces. Prediction of sporadic occurrence of SPEs is not accurate for near or long-term scales, while the expected frequency of such events is strongly influenced by solar cycle activity. In the development of NASA's operational strategies real-time estimation of exposure to SPEs has been considered so that adequate responses can be applied in a timely manner to reduce exposures to well below the exposure limits. Previously, the organ doses of large historical SPEs had been calculated by using the complete energy spectra of each event and then developing a prediction model for blood-forming organ (BFO) dose based solely on an assumed value of integrated fluence above 30 MeV (Φ30) for an otherwise unspecified future SPE. While BFO dose is determined primarily by solar protons with high energies, it was reasoned that more accurate BFO dose prediction models could be developed using integrated fluence above 60 MeV (Φ60) and above 100 MeV (Φ100) as predictors instead of Φ30. In the current study, re-analysis of major SPEs (in which the proton spectra of the ground level enhancement [GLE] events since 1956 are correctly described by Band functions) has been used in evaluation of exposure levels. More accurate prediction models for BFO dose and NASA effective dose are then developed using integrated fluence above 200 MeV (Φ200), which by far have the most weight in the calculation of doses for deep-seated organs from exposure to extreme SPEs (GLEs or sub-GLEs). The unconditional probability of a BFO dose exceeding a pre-specified BFO dose limit is simultaneously calculated by taking into account the distribution of the predictor (Φ30, Φ60, Φ100, or Φ200) as estimated from historical SPEs. These results can be applied to the development of approaches to improve radiation protection of astronauts and the optimization of mission planning for future space missions.

Peer Deviance, Parental Divorce, and Genetic Risk in the Prediction of Drug Abuse in a Nationwide Swedish Sample

PubMed Central

Kendler, Kenneth S.; Ohlsson, Henrik; Sundquist, Kristina; Sundquist, Jan

2014-01-01

IMPORTANCE Peer deviance (PD) strongly predicts externalizing psychopathologic conditions but has not been previously assessable in population cohorts. We sought to develop such an index of PD and to clarify its effects on risk of drug abuse (DA). OBJECTIVES To examine how strongly PD increases the risk of DA and whether this community-level liability indicator interacts with key DA risk factors at the individual and family levels. DESIGN, SETTING, AND PARTICIPANTS Studies of future DA registration in 1 401 698 Swedish probands born from January 1, 1970, through December 31, 1985, and their adolescent peers in approximately 9200 small community areas. Peer deviance was defined as the proportion of individuals born within 5 years of the proband living in the same small community when the proband was 15 years old who eventually were registered for DA. MAIN OUTCOMES AND MEASURES Drug abuse recorded in medical, legal, or pharmacy registry records. RESULTS Peer deviance was associated with future DA in the proband, with rates of DA in older and male peers more strongly predictive than in younger or female peers. The predictive power of PD was only slightly attenuated by adding measures of community deprivation, collective efficacy, or family socioeconomic status. Probands whose parents were divorced were more sensitive to the pathogenic effects of high PD environments. A robust positive interaction was also seen between genetic risk of DA (indexed by rates of DA in first-, second-, and third-degree relatives) and PD exposure. CONCLUSIONS AND RELEVANCE With sufficient data, PD can be measured in populations and strongly predicts DA. In a nationwide sample, risk factors at the level of the individual (genetic vulnerability), family (parental loss), and community (PD) contribute substantially to risk of DA. Individuals at elevated DA risk because of parental divorce or high genetic liability are more sensitive to the pathogenic effects of PD. Although the effect of our PD measure on DA liability cannot be explained by standard measures of community or family risk, we cannot, with available data, discriminate definitively between the effect of true peer effects and other unmeasured risk factors. PMID:24576925

Peer deviance, parental divorce, and genetic risk in the prediction of drug abuse in a nationwide Swedish sample: evidence of environment-environment and gene-environment interaction.

PubMed

Kendler, Kenneth S; Ohlsson, Henrik; Sundquist, Kristina; Sundquist, Jan

2014-04-01

Peer deviance (PD) strongly predicts externalizing psychopathologic conditions but has not been previously assessable in population cohorts. We sought to develop such an index of PD and to clarify its effects on risk of drug abuse (DA). To examine how strongly PD increases the risk of DA and whether this community-level liability indicator interacts with key DA risk factors at the individual and family levels. Studies of future DA registration in 1,401,698 Swedish probands born from January 1, 1970, through December 31, 1985, and their adolescent peers in approximately 9200 small community areas. Peer deviance was defined as the proportion of individuals born within 5 years of the proband living in the same small community when the proband was 15 years old who eventually were registered for DA. Drug abuse recorded in medical, legal, or pharmacy registry records. Peer deviance was associated with future DA in the proband, with rates of DA in older and male peers more strongly predictive than in younger or female peers. The predictive power of PD was only slightly attenuated by adding measures of community deprivation, collective efficacy, or family socioeconomic status. Probands whose parents were divorced were more sensitive to the pathogenic effects of high PD environments. A robust positive interaction was also seen between genetic risk of DA (indexed by rates of DA in first-, second-, and third-degree relatives) and PD exposure. With sufficient data, PD can be measured in populations and strongly predicts DA. In a nationwide sample, risk factors at the level of the individual (genetic vulnerability), family (parental loss), and community (PD) contribute substantially to risk of DA. Individuals at elevated DA risk because of parental divorce or high genetic liability are more sensitive to the pathogenic effects of PD. Although the effect of our PD measure on DA liability cannot be explained by standard measures of community or family risk, we cannot, with available data, discriminate definitively between the effect of true peer effects and other unmeasured risk factors.

Evaluation of Non-Laboratory and Laboratory Prediction Models for Current and Future Diabetes Mellitus: A Cross-Sectional and Retrospective Cohort Study

PubMed Central

Hahn, Seokyung; Moon, Min Kyong; Park, Kyong Soo; Cho, Young Min

2016-01-01

Background Various diabetes risk scores composed of non-laboratory parameters have been developed, but only a few studies performed cross-validation of these scores and a comparison with laboratory parameters. We evaluated the performance of diabetes risk scores composed of non-laboratory parameters, including a recently published Korean risk score (KRS), and compared them with laboratory parameters. Methods The data of 26,675 individuals who visited the Seoul National University Hospital Healthcare System Gangnam Center for a health screening program were reviewed for cross-sectional validation. The data of 3,029 individuals with a mean of 6.2 years of follow-up were reviewed for longitudinal validation. The KRS and 16 other risk scores were evaluated and compared with a laboratory prediction model developed by logistic regression analysis. Results For the screening of undiagnosed diabetes, the KRS exhibited a sensitivity of 81%, a specificity of 58%, and an area under the receiver operating characteristic curve (AROC) of 0.754. Other scores showed AROCs that ranged from 0.697 to 0.782. For the prediction of future diabetes, the KRS exhibited a sensitivity of 74%, a specificity of 54%, and an AROC of 0.696. Other scores had AROCs ranging from 0.630 to 0.721. The laboratory prediction model composed of fasting plasma glucose and hemoglobin A1c levels showed a significantly higher AROC (0.838, P < 0.001) than the KRS. The addition of the KRS to the laboratory prediction model increased the AROC (0.849, P = 0.016) without a significant improvement in the risk classification (net reclassification index: 4.6%, P = 0.264). Conclusions The non-laboratory risk scores, including KRS, are useful to estimate the risk of undiagnosed diabetes but are inferior to the laboratory parameters for predicting future diabetes. PMID:27214034

Bayesian Analysis for Inference of an Emerging Epidemic: Citrus Canker in Urban Landscapes

PubMed Central

Neri, Franco M.; Cook, Alex R.; Gibson, Gavin J.; Gottwald, Tim R.; Gilligan, Christopher A.

2014-01-01

Outbreaks of infectious diseases require a rapid response from policy makers. The choice of an adequate level of response relies upon available knowledge of the spatial and temporal parameters governing pathogen spread, affecting, amongst others, the predicted severity of the epidemic. Yet, when a new pathogen is introduced into an alien environment, such information is often lacking or of no use, and epidemiological parameters must be estimated from the first observations of the epidemic. This poses a challenge to epidemiologists: how quickly can the parameters of an emerging disease be estimated? How soon can the future progress of the epidemic be reliably predicted? We investigate these issues using a unique, spatially and temporally resolved dataset for the invasion of a plant disease, Asiatic citrus canker in urban Miami. We use epidemiological models, Bayesian Markov-chain Monte Carlo, and advanced spatial statistical methods to analyse rates and extent of spread of the disease. A rich and complex epidemic behaviour is revealed. The spatial scale of spread is approximately constant over time and can be estimated rapidly with great precision (although the evidence for long-range transmission is inconclusive). In contrast, the rate of infection is characterised by strong monthly fluctuations that we associate with extreme weather events. Uninformed predictions from the early stages of the epidemic, assuming complete ignorance of the future environmental drivers, fail because of the unpredictable variability of the infection rate. Conversely, predictions improve dramatically if we assume prior knowledge of either the main environmental trend, or the main environmental events. A contrast emerges between the high detail attained by modelling in the spatiotemporal description of the epidemic and the bottleneck imposed on epidemic prediction by the limits of meteorological predictability. We argue that identifying such bottlenecks will be a fundamental step in future modelling of weather-driven epidemics. PMID:24762851

Mapping, Bayesian Geostatistical Analysis and Spatial Prediction of Lymphatic Filariasis Prevalence in Africa

PubMed Central

Slater, Hannah; Michael, Edwin

2013-01-01

There is increasing interest to control or eradicate the major neglected tropical diseases. Accurate modelling of the geographic distributions of parasitic infections will be crucial to this endeavour. We used 664 community level infection prevalence data collated from the published literature in conjunction with eight environmental variables, altitude and population density, and a multivariate Bayesian generalized linear spatial model that allows explicit accounting for spatial autocorrelation and incorporation of uncertainty in input data and model parameters, to construct the first spatially-explicit map describing LF prevalence distribution in Africa. We also ran the best-fit model against predictions made by the HADCM3 and CCCMA climate models for 2050 to predict the likely distributions of LF under future climate and population changes. We show that LF prevalence is strongly influenced by spatial autocorrelation between locations but is only weakly associated with environmental covariates. Infection prevalence, however, is found to be related to variations in population density. All associations with key environmental/demographic variables appear to be complex and non-linear. LF prevalence is predicted to be highly heterogenous across Africa, with high prevalences (>20%) estimated to occur primarily along coastal West and East Africa, and lowest prevalences predicted for the central part of the continent. Error maps, however, indicate a need for further surveys to overcome problems with data scarcity in the latter and other regions. Analysis of future changes in prevalence indicates that population growth rather than climate change per se will represent the dominant factor in the predicted increase/decrease and spread of LF on the continent. We indicate that these results could play an important role in aiding the development of strategies that are best able to achieve the goals of parasite elimination locally and globally in a manner that may also account for the effects of future climate change on parasitic infection. PMID:23951194

Europa's small impactor flux and seismic detection predictions

NASA Astrophysics Data System (ADS)

Tsuji, Daisuke; Teanby, Nicholas A.

2016-10-01

Europa is an attractive target for future lander missions due to its dynamic surface and potentially habitable sub-surface environment. Seismology has the potential to provide powerful new constraints on the internal structure using natural sources such as faults or meteorite impacts. Here we predict how many meteorite impacts are likely to be detected using a single seismic station on Europa to inform future mission planning efforts. To this end, we derive: (1) the current small impactor flux on Europa from Jupiter impact rate observations and models; (2) a crater diameter versus impactor energy scaling relation for icy moons by merging previous experiments and simulations; and (3) scaling relations for seismic signal amplitudes as a function of distance from the impact site for a given crater size, based on analogue explosive data obtained on Earth's ice sheets. Finally, seismic amplitudes are compared to predicted noise levels and seismometer performance to determine detection rates. We predict detection of 0.002-20 small local impacts per year based on P-waves travelling directly through the ice crust. Larger regional and global-scale impact events, detected through mantle-refracted waves, are predicted to be extremely rare (10-8-1 detections per year), so are unlikely to be detected by a short duration mission. Estimated ranges include uncertainties from internal seismic attenuation, impactor flux, and seismic amplitude scaling. Internal attenuation is the most significant unknown and produces extreme uncertainties in the mantle-refracted P-wave amplitudes. Our nominal best-guess attenuation model predicts 0.002-5 local direct P detections and 6 × 10-6-0.2 mantle-refracted detections per year. Given that a plausible Europa landed mission will only last around 30 days, we conclude that impacts should not be relied upon for a seismic exploration of Europa. For future seismic exploration, faulting due to stresses in the rigid outer ice shell is likely to be a much more viable mechanism for probing Europa's interior.

pCO2 effects on species composition and growth of an estuarine phytoplankton community

NASA Astrophysics Data System (ADS)

Grear, Jason S.; Rynearson, Tatiana A.; Montalbano, Amanda L.; Govenar, Breea; Menden-Deuer, Susanne

2017-05-01

The effects of ongoing changes in ocean carbonate chemistry on plankton ecology have important implications for food webs and biogeochemical cycling. However, conflicting results have emerged regarding species-specific responses to pCO2 enrichment and thus community responses have been difficult to predict. To assess community level effects (e.g., production) of altered carbonate chemistry, studies are needed that capitalize on the benefits of controlled experiments but also retain features of intact ecosystems that may exacerbate or ameliorate the effects observed in single-species or single cohort experiments. We performed incubations of natural plankton communities from Narragansett Bay, RI, USA in winter at ambient bay temperatures (5-13 °C), light and nutrient concentrations. Three levels of controlled and constant CO2 concentrations were imposed, simulating past, present and future conditions at mean pCO2 levels of 224, 361, and 724 μatm respectively. Samples for carbonate analysis, chlorophyll a, plankton size-abundance, and plankton species composition were collected daily and phytoplankton growth rates in three different size fractions (<5, 5-20, and >20 μm) were measured at the end of the 7-day incubation period. Community composition changed during the incubation period with major increases in relative diatom abundance, which were similar across pCO2 treatments. At the end of the experiment, 24-hr growth responses to pCO2 levels varied as a function of cell size. The smallest size fraction (<5 μm) grew faster at the elevated pCO2 level. In contrast, the 5-20 μm size fraction grew fastest in the Present treatment and there were no significant differences in growth rate among treatments in the >20 μm size fraction. Cell size distribution shifted toward smaller cells in both the Past and Future treatments but remained unchanged in the Present treatment. Similarity in Past and Future treatments for cell size distribution and growth rate (5-20 μm size fraction) illustrate non-monotonic effects of altered pCO2 on ecological indicators and may be related to opposing physiological effects of high CO2 and low pH both within and among species. Interaction of these effects with other factors (e.g., nutrients, light, temperature, grazing, initial species composition) may explain variability among published studies. The absence of clear treatment-specific effects at the community level suggests that extrapolation of species-specific responses or experiments with only present day and future pCO2 treatments levels could produce misleading predictions of ocean acidification impacts on plankton production.

Examining the moderating role of family cohesion on the relationship between witnessed community violence and delinquency in a national sample of adolescents.

PubMed

Barr, Simone C; Hanson, Rochelle; Begle, Angela M; Kilpatrick, Dean G; Saunders, Benjamin; Resnick, Heidi; Amstadter, Ananda

2012-01-01

Witnessed community violence has been linked to a number of internalizing and externalizing problems in adolescents. Guided by Cicchetti and Lynch's (1993) ecological-transactional model, this study aimed to examine the impact that family-level factors had on negative outcomes associated with witnessed community violence. Using a nationally representative sample, we explored the moderational role of family cohesion in the relationship between witnessing community violence and delinquent behavior while taking demographic variables into account. Results from the investigation suggested that low levels of family cohesion were predictive of delinquency after controlling for race, gender, past delinquency, and direct trauma. In addition, the findings suggested that family cohesion moderated the impact of witnessed community violence on future delinquent behavior. Future directions for research and implications for practice were also discussed.

Imagining the future in health anxiety: the impact of rumination on the specificity of illness-related memory and future thinking.

PubMed

Sansom-Daly, Ursula M; Bryant, Richard A; Cohn, Richard J; Wakefield, Claire E

2014-01-01

Individuals with health anxiety experience catastrophic fears relating to future illness. However, little research has explored cognitive processes involved in how health anxious individuals picture the future. Ruminative thinking has been shown to impede the ability to recall specific autobiographical memories, which in turn is related to maladaptive, categoric future thinking processes. This study examined the impact of rumination on memory and future thinking among 60 undergraduate participants with varying health anxiety (35% clinical-level health anxiety). Participants were randomized to experiential/ruminative self-focus conditions, then completed an Autobiographical Memory Test and Future Imaginings Task. Responses were coded for specificity and the presence of illness concerns. Rumination led to more specific illness-concerned memories overall, yet at the same time led to more categoric illness-related future imaginings. Rumination and health anxiety together best predicted overgeneral illness-related future imaginings. Highly specific illness-related memories may be maintained due to their personal salience. However, more overgeneral illness-related future imaginings may reflect cognitive avoidance in response to the threat of future illness. This divergent pattern of results between memory and future imaginings may exacerbate health anxiety, and may also serve to maintain maladaptive responses among individuals with realistic medical concerns, such as individuals living with chronic illness.

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

USGS Publications Warehouse

McGowan, Conor P.; Allan, Nathan; Servoss, Jeff; Hedwall, Shaula J.; Wooldridge, Brian

2017-01-01

Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

Prediction of psychological functioning one year after the predictive test for Huntington's disease and impact of the test result on reproductive decision making.

PubMed Central

Decruyenaere, M; Evers-Kiebooms, G; Boogaerts, A; Cassiman, J J; Cloostermans, T; Demyttenaere, K; Dom, R; Fryns, J P; Van den Berghe, H

1996-01-01

For people at risk for Huntington's disease, the anxiety and uncertainty about the future may be very burdensome and may be an obstacle to personal decision making about important life issues, for example, procreation. For some at risk persons, this situation is the reason for requesting predictive DNA testing. The aim of this paper is two-fold. First, we want to evaluate whether knowing one's carrier status reduces anxiety and uncertainty and whether it facilitates decision making about procreation. Second, we endeavour to identify pretest predictors of psychological adaptation one year after the predictive test (psychometric evaluation of general anxiety, depression level, and ego strength). The impact of the predictive test result was assessed in 53 subjects tested, using pre- and post-test psychometric measurement and self-report data of follow up interviews. Mean anxiety and depression levels were significantly decreased one year after a good test result; there was no significant change in the case of a bad test result. The mean personality profile, including ego strength, remained unchanged one year after the test. The study further shows that the test result had a definite impact on reproductive decision making. Stepwise multiple regression analyses were used to select the best predictors of the subject's post-test reactions. The results indicate that a careful evaluation of pretest ego strength, depression level, and coping strategies may be helpful in predicting post-test reactions, independently of the carrier status. Test result (carrier/ non-carrier), gender, and age did not significantly contribute to the prediction. About one third of the variance of post-test anxiety and depression level and more than half of the variance of ego strength was explained, implying that other psychological or social aspects should also be taken into account when predicting individual post-test reactions. PMID:8880572

PROGNOSIS OF GLEs OF RELATIVISTIC SOLAR PROTONS

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

Pérez-Peraza, Jorge; Juárez-Zuñiga, Alan, E-mail: perperaz@geofisica.unam.mx, E-mail: z.alan.z@hotmail.com

Ground level enhancements (GLEs) are relativistic solar particles measured at ground level by the worldwide network of cosmic ray detectors. These sporadic events are associated with solar flares and are assumed to be of a quasi-random nature. Studying them gives information about their source and propagation processes, the maximum capacity of the Sun as a particle accelerator engine, the magnetic structure of the medium traversed, etc. Space vehicles, as well as electric transformers and gas pipes at high latitudes may be damaged by this kind of radiation. As a result, their prediction has turned out to be very important, butmore » because of their random occurrence, up to now few efforts toward this goal have been made. The results of these efforts have been limited to possible warnings in real time, just before a GLE occurrence, but no specific dates have been predicted well enough in advance to prevent possible hazards. In this study we show that, in spite of the quasi-stochastic nature of GLEs, it is possible to predict them with relative precision, even for future solar cycles. Additionally, a previous study establishing synchronization among some periodicities of several layers of solar atmosphere argues against the full randomness of the phenomenon of relativistic particle production. Therefore, by means of wavelet spectral analysis combined with fuzzy logic tools, we reproduce previous known GLE events and present results for future events. The next GLE is expected to occur in the first semester of 2016.« less