Sample records for predict individual efficiency
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De Loof, Esther; Van Opstal, Filip; Verguts, Tom
2016-04-01
Theories on visual awareness claim that predicted stimuli reach awareness faster than unpredicted ones. In the current study, we disentangle whether prior information about the upcoming stimulus affects visual awareness of stimulus location (i.e., individuation) by modulating processing efficiency or threshold setting. Analogous research on stimulus identification revealed that prior information modulates threshold setting. However, as identification and individuation are two functionally and neurally distinct processes, the mechanisms underlying identification cannot simply be extrapolated directly to individuation. The goal of this study was therefore to investigate how individuation is influenced by prior information about the upcoming stimulus. To do so, a drift diffusion model was fitted to estimate the processing efficiency and threshold setting for predicted versus unpredicted stimuli in a cued individuation paradigm. Participants were asked to locate a picture, following a cue that was congruent, incongruent or neutral with respect to the picture's identity. Pictures were individuated faster in the congruent and neutral condition compared to the incongruent condition. In the diffusion model analysis, the processing efficiency was not significantly different across conditions. However, the threshold setting was significantly higher following an incongruent cue compared to both congruent and neutral cues. Our results indicate that predictive information about the upcoming stimulus influences visual awareness by shifting the threshold for individuation rather than by enhancing processing efficiency. Copyright © 2016 Elsevier Ltd. All rights reserved.
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McParland, S; Lewis, E; Kennedy, E; Moore, S G; McCarthy, B; O'Donovan, M; Butler, S T; Pryce, J E; Berry, D P
2014-09-01
Interest is increasing in the feed intake complex of individual dairy cows, both for management and animal breeding. However, energy intake data on an individual-cow basis are not routinely available. The objective of the present study was to quantify the ability of routinely undertaken mid-infrared (MIR) spectroscopy analysis of individual cow milk samples to predict individual cow energy intake and efficiency. Feed efficiency in the present study was described by residual feed intake (RFI), which is the difference between actual energy intake and energy used (e.g., milk production, maintenance, and body tissue anabolism) or supplied from body tissue mobilization. A total of 1,535 records for energy intake, RFI, and milk MIR spectral data were available from an Irish research herd across 36 different test days from 535 lactations on 378 cows. Partial least squares regression analyses were used to relate the milk MIR spectral data to either energy intake or efficiency. The coefficient of correlation (REX) of models to predict RFI across lactation ranged from 0.48 to 0.60 in an external validation data set; the predictive ability was, however, strongest (REX=0.65) in early lactation (<60 d in milk). The inclusion of milk yield as a predictor variable improved the accuracy of predicting energy intake across lactation (REX=0.70). The correlation between measured RFI and measured energy balance across lactation was 0.85, whereas the correlation between RFI and energy balance, both predicted from the MIR spectrum, was 0.65. Milk MIR spectral data are routinely generated for individual cows throughout lactation and, therefore, the prediction equations developed in the present study can be immediately (and retrospectively where MIR spectral data have been stored) applied to predict energy intake and efficiency to aid in management and breeding decisions. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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Wilson, Mark; Smith, Nickolas C; Chattington, Mark; Ford, Mike; Marple-Horvat, Dilwyn E
2006-11-01
We tested some of the key predictions of processing efficiency theory using a simulated rally driving task. Two groups of participants were classified as either dispositionally high or low anxious based on trait anxiety scores and trained on a simulated driving task. Participants then raced individually on two similar courses under counterbalanced experimental conditions designed to manipulate the level of anxiety experienced. The effort exerted on the driving tasks was assessed though self-report (RSME), psychophysiological measures (pupil dilation) and visual gaze data. Efficiency was measured in terms of efficiency of visual processing (search rate) and driving control (variability of wheel and accelerator pedal) indices. Driving performance was measured as the time taken to complete the course. As predicted, increased anxiety had a negative effect on processing efficiency as indexed by the self-report, pupillary response and variability of gaze data. Predicted differences due to dispositional levels of anxiety were also found in the driving control and effort data. Although both groups of drivers performed worse under the threatening condition, the performance of the high trait anxious individuals was affected to a greater extent by the anxiety manipulation than the performance of the low trait anxious drivers. The findings suggest that processing efficiency theory holds promise as a theoretical framework for examining the relationship between anxiety and performance in sport.
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Specialization Does Not Predict Individual Efficiency in an Ant
Dornhaus, Anna
2008-01-01
The ecological success of social insects is often attributed to an increase in efficiency achieved through division of labor between workers in a colony. Much research has therefore focused on the mechanism by which a division of labor is implemented, i.e., on how tasks are allocated to workers. However, the important assumption that specialists are indeed more efficient at their work than generalist individuals—the “Jack-of-all-trades is master of none” hypothesis—has rarely been tested. Here, I quantify worker efficiency, measured as work completed per time, in four different tasks in the ant Temnothorax albipennis: honey and protein foraging, collection of nest-building material, and brood transports in a colony emigration. I show that individual efficiency is not predicted by how specialized workers were on the respective task. Worker efficiency is also not consistently predicted by that worker's overall activity or delay to begin the task. Even when only the worker's rank relative to nestmates in the same colony was used, specialization did not predict efficiency in three out of the four tasks, and more specialized workers actually performed worse than others in the fourth task (collection of sand grains). I also show that the above relationships, as well as median individual efficiency, do not change with colony size. My results demonstrate that in an ant species without morphologically differentiated worker castes, workers may nevertheless differ in their ability to perform different tasks. Surprisingly, this variation is not utilized by the colony—worker allocation to tasks is unrelated to their ability to perform them. What, then, are the adaptive benefits of behavioral specialization, and why do workers choose tasks without regard for whether they can perform them well? We are still far from an understanding of the adaptive benefits of division of labor in social insects. PMID:19018663
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Tobler, Philippe N.
2015-01-01
When we are learning to associate novel cues with outcomes, learning is more efficient if we take advantage of previously learned associations and thereby avoid redundant learning. The blocking effect represents this sort of efficiency mechanism and refers to the phenomenon in which a novel stimulus is blocked from learning when it is associated with a fully predicted outcome. Although there is sufficient evidence that this effect manifests itself when individuals learn about their own rewards, it remains unclear whether it also does when they learn about others’ rewards. We employed behavioral and neuroimaging methods to address this question. We demonstrate that blocking does indeed occur in the social domain and it does so to a similar degree as observed in the individual domain. On the neural level, activations in the medial prefrontal cortex (mPFC) show a specific contribution to blocking and learning-related prediction errors in the social domain. These findings suggest that the efficiency principle that applies to reward learning in the individual domain also applies to that in the social domain, with the mPFC playing a central role in implementing it. PMID:25326037
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Marchetti, Igor; Shumake, Jason; Grahek, Ivan; Koster, Ernst H W
2018-08-01
Temperamental effortful control and attentional networks are increasingly viewed as important underlying processes in depression and anxiety. However, it is still unknown whether these factors facilitate depressive and anxiety symptoms in the general population and, more specifically, in remitted depressed individuals. We investigated to what extent effortful control and attentional networks (i.e., Attention Network Task) explain concurrent depressive and anxious symptoms in healthy individuals (n = 270) and remitted depressed individuals (n = 90). Both samples were highly representative of the US population. Increased effortful control predicted a substantial decrease in symptoms of both depression and anxiety in the whole sample, whereas decreased efficiency of executive attention predicted a modest increase in depressive symptoms. Remitted depressed individuals did not show less effortful control nor less efficient attentional networks than healthy individuals. Moreover, clinical status did not moderate the relationship between temperamental factors and either depressive or anxiety symptoms. Limitations include the cross-sectional nature of the study. Our study shows that temperamental effortful control represents an important transdiagnostic process for depressive and anxiety symptoms in adults. Copyright © 2018 Elsevier B.V. All rights reserved.
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T.Z. Ye; K.J.S. Jayawickrama; G.R. Johnson
2004-01-01
BLUP (Best linear unbiased prediction) method has been widely used in forest tree improvement programs. Since one of the properties of BLUP is that related individuals contribute to the predictions of each other, it seems logical that integrating data from all generations and from all populations would improve both the precision and accuracy in predicting genetic...
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Seid-Fatemi, Azade; Tobler, Philippe N
2015-05-01
When we are learning to associate novel cues with outcomes, learning is more efficient if we take advantage of previously learned associations and thereby avoid redundant learning. The blocking effect represents this sort of efficiency mechanism and refers to the phenomenon in which a novel stimulus is blocked from learning when it is associated with a fully predicted outcome. Although there is sufficient evidence that this effect manifests itself when individuals learn about their own rewards, it remains unclear whether it also does when they learn about others' rewards. We employed behavioral and neuroimaging methods to address this question. We demonstrate that blocking does indeed occur in the social domain and it does so to a similar degree as observed in the individual domain. On the neural level, activations in the medial prefrontal cortex (mPFC) show a specific contribution to blocking and learning-related prediction errors in the social domain. These findings suggest that the efficiency principle that applies to reward learning in the individual domain also applies to that in the social domain, with the mPFC playing a central role in implementing it. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
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Masting promotes individual- and population-level reproduction by increasing pollination efficiency.
Moreira, Xoaquín; Abdala-Roberts, Luis; Linhart, Yan B; Mooney, Kailen A
2014-04-01
Masting is a reproductive strategy defined as the intermittent and synchronized production of large seed crops by a plant population. The pollination efficiency hypothesis proposes that masting increases pollination success in plants. Despite its general appeal, no previous studies have used long-term data together with population- and individual-level analyses to assess pollination efficiency between mast and non-mast events. Here we rigorously tested the pollination efficiency hypothesis in ponderosa pine (Pinus ponderosa), a long-lived monoecious, wind-pollinated species, using a data set on 217 trees monitored annually for 20 years. Relative investment in male and female function by individual trees did not vary between mast and non-mast years. At both the population and individual level, the rate of production of mature female cones relative to male strobili production was higher in mast than non-mast years, consistent with the predicted benefit of reproductive synchrony on reproductive success. In addition, at the individual level we found a higher conversion of unfertilized female conelets into mature female cones during a mast year compared to a non-mast year. Collectively, parallel results at the population and individual tree level provide robust evidence for the ecological, and potentially also evolutionary, benefits of masting through increased pollination efficiency.
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McParland, S; Berry, D P
2016-05-01
Knowledge of animal-level and herd-level energy intake, energy balance, and feed efficiency affect day-to-day herd management strategies; information on these traits at an individual animal level is also useful in animal breeding programs. A paucity of data (especially at the individual cow level), of feed intake in particular, hinders the inclusion of such attributes in herd management decision-support tools and breeding programs. Dairy producers have access to an individual cow milk sample at least once daily during lactation, and consequently any low-cost phenotyping strategy should consider exploiting measureable properties in this biological sample, reflecting the physiological status and performance of the cow. Infrared spectroscopy is the study of the interaction of an electromagnetic wave with matter and it is used globally to predict milk quality parameters on routinely acquired individual cow milk samples and bulk tank samples. Thus, exploiting infrared spectroscopy in next-generation phenotyping will ensure potentially rapid application globally with a negligible additional implementation cost as the infrastructure already exists. Fourier-transform infrared spectroscopy (FTIRS) analysis is already used to predict milk fat and protein concentrations, the ratio of which has been proposed as an indicator of energy balance. Milk FTIRS is also able to predict the concentration of various fatty acids in milk, the composition of which is known to change when body tissue is mobilized; that is, when the cow is in negative energy balance. Energy balance is mathematically very similar to residual energy intake (REI), a suggested measure of feed efficiency. Therefore, the prediction of energy intake, energy balance, and feed efficiency (i.e., REI) from milk FTIRS seems logical. In fact, the accuracy of predicting (i.e., correlation between predicted and actual values; root mean square error in parentheses) energy intake, energy balance, and REI from milk FTIRS in dairy cows was 0.88 (20.0MJ), 0.78 (18.6MJ), and 0.63 (22.0MJ), respectively, based on cross-validation. These studies, however, are limited to results from one research group based on data from 2 contrasting production systems in the United Kingdom and Ireland and would need to be replicated, especially in a range of production systems because the prediction equations are not accurate when the variability used in validation is not represented in the calibration data set. Heritable genetic variation exists for all predicted traits. Phenotypic differences in energy intake also exists among animals stratified based on genetic merit for energy intake predicted from milk FTIRS, substantiating the usefulness of such FTIR-predicted phenotypes not only for day-to-day herd management, but also as part of a breeding strategy to improve cow performance. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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Auditory processing efficiency deficits in children with developmental language impairments
NASA Astrophysics Data System (ADS)
Hartley, Douglas E. H.; Moore, David R.
2002-12-01
The ``temporal processing hypothesis'' suggests that individuals with specific language impairments (SLIs) and dyslexia have severe deficits in processing rapidly presented or brief sensory information, both within the auditory and visual domains. This hypothesis has been supported through evidence that language-impaired individuals have excess auditory backward masking. This paper presents an analysis of masking results from several studies in terms of a model of temporal resolution. Results from this modeling suggest that the masking results can be better explained by an ``auditory efficiency'' hypothesis. If impaired or immature listeners have a normal temporal window, but require a higher signal-to-noise level (poor processing efficiency), this hypothesis predicts the observed small deficits in the simultaneous masking task, and the much larger deficits in backward and forward masking tasks amongst those listeners. The difference in performance on these masking tasks is predictable from the compressive nonlinearity of the basilar membrane. The model also correctly predicts that backward masking (i) is more prone to training effects, (ii) has greater inter- and intrasubject variability, and (iii) increases less with masker level than do other masking tasks. These findings provide a new perspective on the mechanisms underlying communication disorders and auditory masking.
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Cognitive control predicted by color vision, and vice versa.
Colzato, Lorenza S; Sellaro, Roberta; Hulka, Lea M; Quednow, Boris B; Hommel, Bernhard
2014-09-01
One of the most important functions of cognitive control is to continuously adapt cognitive processes to changing and often conflicting demands of the environment. Dopamine (DA) has been suggested to play a key role in the signaling and resolution of such response conflict. Given that DA is found in high concentration in the retina, color vision discrimination has been suggested as an index of DA functioning and in particular blue-yellow color vision impairment (CVI) has been used to indicate a central hypodopaminergic state. We used color discrimination (indexed by the total color distance score; TCDS) to predict individual differences in the cognitive control of response conflict, as reflected by conflict-resolution efficiency in an auditory Simon task. As expected, participants showing better color discrimination were more efficient in resolving response conflict. Interestingly, participants showing a blue-yellow CVI were associated with less efficiency in handling response conflict. Our findings indicate that color vision discrimination might represent a promising predictor of cognitive controlability in healthy individuals. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Induced optimism as mental rehearsal to decrease depressive predictive certainty.
Miranda, Regina; Weierich, Mariann; Khait, Valerie; Jurska, Justyna; Andersen, Susan M
2017-03-01
The present study examined whether practice in making optimistic future-event predictions would result in change in the hopelessness-related cognitions that characterize depression. Individuals (N = 170) with low, mild, and moderate-to-severe depressive symptoms were randomly assigned to a condition in which they practiced making optimistic future-event predictions or to a control condition in which they viewed the same stimuli but practiced determining whether a given phrase contained an adjective. Overall, individuals in the induced optimism condition showed increases in optimistic predictions, relative to the control condition, as a result of practice, but only individuals with moderate-to-severe symptoms of depression who practiced making optimistic future-event predictions showed decreases in depressive predictive certainty, relative to the control condition. In addition, they showed gains in efficiency in making optimistic predictions over the practice blocks, as assessed by response time. There was no difference in depressed mood by practice condition. Mental rehearsal might be one way of changing the hopelessness-related cognitions that characterize depression. Copyright © 2016 Elsevier Ltd. All rights reserved.
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A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.
Ashraf, M Irfan; Meng, Fan-Rui; Bourque, Charles P-A; MacLean, David A
2015-01-01
Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA) and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model). Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS) of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2) 5-year(-1) and volume: 0.0008 m(3) 5-year(-1)). Model variability described by root mean squared error (RMSE) in basal area prediction was 40.53 cm(2) 5-year(-1) and 0.0393 m(3) 5-year(-1) in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence technology has substantial potential in forest modelling.
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A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change
Ashraf, M. Irfan; Meng, Fan-Rui; Bourque, Charles P.-A.; MacLean, David A.
2015-01-01
Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA) and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model). Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS) of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm2 5-year-1 and volume: 0.0008 m3 5-year-1). Model variability described by root mean squared error (RMSE) in basal area prediction was 40.53 cm2 5-year-1 and 0.0393 m3 5-year-1 in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence technology has substantial potential in forest modelling. PMID:26173081
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Validation of NE-TWIGS for tolerant hardwood stands in Ontario
Jacek Bankowski; Daniel C. Dey; Eric Boysen; Murray Woods; Jim Rice
1996-01-01
The individual-tree, distance-independent stand growth simulator NE-TWIGS has been tested for Ontario's tolerant hardwood stands using data from long-term permanent sample plots. NE-TWIGS provides reliable short-term (5-year) predictions of stand basal area (modelling efficiency from 77% to 99%), but in longer projections the efficiency of the model drops...
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Changes in Brain Network Efficiency and Working Memory Performance in Aging
Stanley, Matthew L.; Simpson, Sean L.; Dagenbach, Dale; Lyday, Robert G.; Burdette, Jonathan H.; Laurienti, Paul J.
2015-01-01
Working memory is a complex psychological construct referring to the temporary storage and active processing of information. We used functional connectivity brain network metrics quantifying local and global efficiency of information transfer for predicting individual variability in working memory performance on an n-back task in both young (n = 14) and older (n = 15) adults. Individual differences in both local and global efficiency during the working memory task were significant predictors of working memory performance in addition to age (and an interaction between age and global efficiency). Decreases in local efficiency during the working memory task were associated with better working memory performance in both age cohorts. In contrast, increases in global efficiency were associated with much better working performance for young participants; however, increases in global efficiency were associated with a slight decrease in working memory performance for older participants. Individual differences in local and global efficiency during resting-state sessions were not significant predictors of working memory performance. Significant group whole-brain functional network decreases in local efficiency also were observed during the working memory task compared to rest, whereas no significant differences were observed in network global efficiency. These results are discussed in relation to recently developed models of age-related differences in working memory. PMID:25875001
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Changes in brain network efficiency and working memory performance in aging.
Stanley, Matthew L; Simpson, Sean L; Dagenbach, Dale; Lyday, Robert G; Burdette, Jonathan H; Laurienti, Paul J
2015-01-01
Working memory is a complex psychological construct referring to the temporary storage and active processing of information. We used functional connectivity brain network metrics quantifying local and global efficiency of information transfer for predicting individual variability in working memory performance on an n-back task in both young (n = 14) and older (n = 15) adults. Individual differences in both local and global efficiency during the working memory task were significant predictors of working memory performance in addition to age (and an interaction between age and global efficiency). Decreases in local efficiency during the working memory task were associated with better working memory performance in both age cohorts. In contrast, increases in global efficiency were associated with much better working performance for young participants; however, increases in global efficiency were associated with a slight decrease in working memory performance for older participants. Individual differences in local and global efficiency during resting-state sessions were not significant predictors of working memory performance. Significant group whole-brain functional network decreases in local efficiency also were observed during the working memory task compared to rest, whereas no significant differences were observed in network global efficiency. These results are discussed in relation to recently developed models of age-related differences in working memory.
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Prediction of chronic post-operative pain: pre-operative DNIC testing identifies patients at risk.
Yarnitsky, David; Crispel, Yonathan; Eisenberg, Elon; Granovsky, Yelena; Ben-Nun, Alon; Sprecher, Elliot; Best, Lael-Anson; Granot, Michal
2008-08-15
Surgical and medical procedures, mainly those associated with nerve injuries, may lead to chronic persistent pain. Currently, one cannot predict which patients undergoing such procedures are 'at risk' to develop chronic pain. We hypothesized that the endogenous analgesia system is key to determining the pattern of handling noxious events, and therefore testing diffuse noxious inhibitory control (DNIC) will predict susceptibility to develop chronic post-thoracotomy pain (CPTP). Pre-operative psychophysical tests, including DNIC assessment (pain reduction during exposure to another noxious stimulus at remote body area), were conducted in 62 patients, who were followed 29.0+/-16.9 weeks after thoracotomy. Logistic regression revealed that pre-operatively assessed DNIC efficiency and acute post-operative pain intensity were two independent predictors for CPTP. Efficient DNIC predicted lower risk of CPTP, with OR 0.52 (0.33-0.77 95% CI, p=0.0024), i.e., a 10-point numerical pain scale (NPS) reduction halves the chance to develop chronic pain. Higher acute pain intensity indicated OR of 1.80 (1.28-2.77, p=0.0024) predicting nearly a double chance to develop chronic pain for each 10-point increase. The other psychophysical measures, pain thresholds and supra-threshold pain magnitudes, did not predict CPTP. For prediction of acute post-operative pain intensity, DNIC efficiency was not found significant. Effectiveness of the endogenous analgesia system obtained at a pain-free state, therefore, seems to reflect the individual's ability to tackle noxious events, identifying patients 'at risk' to develop post-intervention chronic pain. Applying this diagnostic approach before procedures that might generate pain may allow individually tailored pain prevention and management, which may substantially reduce suffering.
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Multi-agent cooperation rescue algorithm based on influence degree and state prediction
NASA Astrophysics Data System (ADS)
Zheng, Yanbin; Ma, Guangfu; Wang, Linlin; Xi, Pengxue
2018-04-01
Aiming at the multi-agent cooperative rescue in disaster, a multi-agent cooperative rescue algorithm based on impact degree and state prediction is proposed. Firstly, based on the influence of the information in the scene on the collaborative task, the influence degree function is used to filter the information. Secondly, using the selected information to predict the state of the system and Agent behavior. Finally, according to the result of the forecast, the cooperative behavior of Agent is guided and improved the efficiency of individual collaboration. The simulation results show that this algorithm can effectively solve the cooperative rescue problem of multi-agent and ensure the efficient completion of the task.
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Size Dependent Mechanical Properties of Monolayer Densely Arranged Polystyrene Nanospheres.
Huang, Peng; Zhang, Lijing; Yan, Qingfeng; Guo, Dan; Xie, Guoxin
2016-12-13
In contrast to macroscopic materials, the mechanical properties of polymer nanospheres show fascinating scientific and application values. However, the experimental measurements of individual nanospheres and quantitative analysis of theoretical mechanisms remain less well performed and understood. We provide a highly efficient and accurate method with monolayer densely arranged honeycomb polystyrene (PS) nanospheres for the quantitatively mechanical characterization of individual nanospheres on the basis of atomic force microscopy (AFM) nanoindentation. The efficiency is improved by 1-2 orders, and the accuracy is also enhanced almost by half-order. The elastic modulus measured in the experiments increases with decreasing radius to the smallest nanospheres (25-35 nm in radius). A core-shell model is introduced to predict the size dependent elasticity of PS nanospheres, and the theoretical prediction agrees reasonably well with the experimental results and also shows a peak modulus value.
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Assessing Soldier Individual Differences to Enable Tailored Training
2010-04-01
upon effective and efficient training. However, there is ample evidence that learning-related individual differences exist ( Thorndike , 1985; Jensen...in both civilian and military settings (Schmidt, Hunter, & Outerbridge, 1986; Thorndike , 1985). Prior knowledge or knowledge of facts and...predictive power ( Thorndike , 1985; Jensen, 1998). Further, there is a good deal of evidence that general mental ability impacts performance largely
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Manafiazar, G; McFadden, T; Goonewardene, L; Okine, E; Basarab, J; Li, P; Wang, Z
2013-01-01
Residual Feed Intake (RFI) is a measure of energy efficiency. Developing an appropriate model to predict expected energy intake while accounting for multifunctional energy requirements of metabolic body weight (MBW), empty body weight (EBW), milk production energy requirements (MPER), and their nonlinear lactation profiles, is the key to successful prediction of RFI in dairy cattle. Individual daily actual energy intake and monthly body weight of 281 first-lactation dairy cows from 1 to 305 d in milk were recorded at the Dairy Research and Technology Centre of the University of Alberta (Edmonton, AB, Canada); individual monthly milk yield and compositions were obtained from the Dairy Herd Improvement Program. Combinations of different orders (1-5) of fixed (F) and random (R) factors were fitted using Legendre polynomial regression to model the nonlinear lactation profiles of MBW, EBW, and MPER over 301 d. The F5R3, F5R3, and F5R2 (subscripts indicate the order fitted) models were selected, based on the combination of the log-likelihood ratio test and the Bayesian information criterion, as the best prediction equations for MBW, EBW, and MPER, respectively. The selected models were used to predict daily individual values for these traits. To consider the body reserve changes, the differences of predicted EBW between 2 consecutive days were considered as the EBW change between these days. The smoothed total 301-d actual energy intake was then linearly regressed on the total 301-d predicted traits of MBW, EBW change, and MPER to obtain the first-lactation RFI (coefficient of determination=0.68). The mean of predicted daily average lactation RFI was 0 and ranged from -6.58 to 8.64 Mcal of NE(L)/d. Fifty-one percent of the animals had an RFI value below the mean (efficient) and 49% of them had an RFI value above the mean (inefficient). These results indicate that the first-lactation RFI can be predicted from its component traits with a reasonable coefficient of determination. The predicted RFI could be used in the dairy breeding program to increase profitability by selecting animals that are genetically superior in energy efficiency based on RFI, or through routinely measured traits, which are genetically correlated with RFI. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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Driving Green: Toward the Prediction and Influence of Efficient Driving Behavior
NASA Astrophysics Data System (ADS)
Newsome, William D.
Sub-optimal efficiency in activities involving the consumption of fossil fuels, such as driving, contribute to a miscellany of negative environmental, political, economic and social externalities. Demonstrations of the effectiveness of feedback interventions can be found in countless organizational settings, as can demonstrations of individual differences in sensitivity to feedback interventions. Mechanisms providing feedback to drivers about fuel economy are becoming standard equipment in most new vehicles, but vary considerably in their constitution. A keystone of Radical Behaviorism is the acknowledgement that verbal behavior appears to play a role in mediating apparent susceptibility to influence by contingencies of varying delay. In the current study, samples of verbal behavior (rules) were collected in the context of a feedback intervention to improve driving efficiency. In an analysis of differences in individual responsiveness to the feedback intervention, the rate of novel rules per week generated by drivers is revealed to account for a substantial proportion of the variability in relative efficiency gains across participants. The predictive utility of conceptual tools, such as the basic distinction among contingency-shaped and rule governed behavior, the elaboration of direct-acting and indirect-acting contingencies, and the psychological flexibility model, is bolstered by these findings.
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Bouchez, A; Goffinet, B
1990-02-01
Selection indices can be used to predict one trait from information available on several traits in order to improve the prediction accuracy. Plant or animal breeders are interested in selecting only the best individuals, and need to compare the efficiency of different trait combinations in order to choose the index ensuring the best prediction quality for individual values. As the usual tools for index evaluation do not remain unbiased in all cases, we propose a robust way of evaluation by means of an estimator of the mean-square error of prediction (EMSEP). This estimator remains valid even when parameters are not known, as usually assumed, but are estimated. EMSEP is applied to the choice of an indirect multitrait selection index at the F5 generation of a classical breeding scheme for soybeans. Best predictions for precocity are obtained by means of indices using only part of the available information.
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Wang, Zengjian; Zhang, Delong; Liang, Bishan; Chang, Song; Pan, Jinghua; Huang, Ruiwang; Liu, Ming
2016-01-01
Biological motion perception (BMP) refers to the ability to perceive the moving form of a human figure from a limited amount of stimuli, such as from a few point lights located on the joints of a moving body. BMP is commonplace and important, but there is great inter-individual variability in this ability. This study used multiple regression model analysis to explore the association between BMP performance and intrinsic brain activity, in order to investigate the neural substrates underlying inter-individual variability of BMP performance. The resting-state functional magnetic resonance imaging (rs-fMRI) and BMP performance data were collected from 24 healthy participants, for whom intrinsic brain networks were constructed, and a graph-based network efficiency metric was measured. Then, a multiple linear regression model was used to explore the association between network regional efficiency and BMP performance. We found that the local and global network efficiency of many regions was significantly correlated with BMP performance. Further analysis showed that the local efficiency rather than global efficiency could be used to explain most of the BMP inter-individual variability, and the regions involved were predominately located in the Default Mode Network (DMN). Additionally, discrimination analysis showed that the local efficiency of certain regions such as the thalamus could be used to classify BMP performance across participants. Notably, the association pattern between network nodal efficiency and BMP was different from the association pattern of static directional/gender information perception. Overall, these findings show that intrinsic brain network efficiency may be considered a neural factor that explains BMP inter-individual variability. PMID:27853427
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Mehrkam, Lindsay R; Dorey, Nicole R
2015-01-01
Environmental enrichment is widely used in the management of zoo animals, and is an essential strategy for increasing the behavioral welfare of these populations. It may be difficult, however, to identify potentially effective enrichment strategies that are also cost-effective and readily available. An animal's preference for a potential enrichment item may be a reliable predictor of whether that individual will reliably interact with that item, and subsequently enable staff to evaluate the effects of that enrichment strategy. The aim of the present study was to assess the utility of preference assessments for identifying potential enrichment items across six different species--each representing a different taxonomic group. In addition, we evaluated the agreement between zoo personnel's predictions of animals' enrichment preferences and stimuli selected via a preference assessment. Five out of six species (nine out of 11 individuals) exhibited clear, systematic preferences for specific stimuli. Similarities in enrichment preferences were observed among all individuals of primates, whereas individuals within ungulate and avian species displayed individual differences in enrichment preferences. Overall, zoo personnel, regardless of experience level, were significantly more accurate at predicting least-preferred stimuli than most-preferred stimuli across species, and tended to make the same predictions for all individuals within a species. Preference assessments may therefore be a useful, efficient husbandry strategy for identifying viable enrichment items at both the individual and species levels. © 2015 Wiley Periodicals, Inc.
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A new technique for thermodynamic engine modeling
NASA Astrophysics Data System (ADS)
Matthews, R. D.; Peters, J. E.; Beckel, S. A.; Shizhi, M.
1983-12-01
Reference is made to the equations given by Matthews (1983) for piston engine performance, which show that this performance depends on four fundamental engine efficiencies (combustion, thermodynamic cycle or indicated thermal, volumetric, and mechanical) as well as on engine operation and design parameters. This set of equations is seen to suggest a different technique for engine modeling; that is, that each efficiency should be modeled individually and the efficiency submodels then combined to obtain an overall engine model. A simple method for predicting the combustion efficiency of piston engines is therefore required. Various methods are proposed here and compared with experimental results. These combustion efficiency models are then combined with various models for the volumetric, mechanical, and indicated thermal efficiencies to yield three different engine models of varying degrees of sophistication. Comparisons are then made of the predictions of the resulting engine models with experimental data. It is found that combustion efficiency is almost independent of load, speed, and compression ratio and is not strongly dependent on fuel type, at least so long as the hydrogen-to-carbon ratio is reasonably close to that for isooctane.
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Caffò, Alessandro O; Lopez, Antonella; Spano, Giuseppina; Saracino, Giuseppe; Stasolla, Fabrizio; Ciriello, Giuseppe; Grattagliano, Ignazio; Lancioni, Giulio E; Bosco, Andrea
2016-12-01
Models of cognitive reserve in aging suggest that individual's life experience (education, working activity, and leisure) can exert a neuroprotective effect against cognitive decline and may represent an important contribution to successful aging. The objective of the present study is to investigate the role of cognitive reserve, pre-morbid intelligence, age, and education level, in predicting cognitive efficiency in a sample of healthy aged individuals and with probable mild cognitive impairment. Two hundred and eight aging participants recruited from the provincial region of Bari (Apulia, Italy) took part in the study. A battery of standardized tests was administered to them to measure cognitive reserve, pre-morbid intelligence, and cognitive efficiency. Protocols for 10 participants were excluded since they did not meet inclusion criteria, and statistical analyses were conducted on data from the remaining 198 participants. A path analysis was used to test the following model: age, education level, and intelligence directly influence cognitive reserve and cognitive efficiency; cognitive reserve mediates the influence of age, education level, and intelligence on cognitive efficiency. Cognitive reserve fully mediates the relationship between pre-morbid intelligence and education level and cognitive efficiency, while age maintains a direct effect on cognitive efficiency. Cognitive reserve appears to exert a protective effect regarding cognitive decline in normal and pathological populations, thus masking, at least in the early phases of neurodegeneration, the decline of memory, orientation, attention, language, and reasoning skills. The assessment of cognitive reserve may represent a useful evaluation supplement in neuropsychological screening protocols of cognitive decline.
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Gao, Yong-Ming; Wan, Ping
2002-06-01
Screening markers efficiently is the foundation of mapping QTLs by composite interval mapping. Main and interaction markers distinguished, besides using background control for genetic variation, could also be used to construct intervals of two-way searching for mapping QTLs with epistasis, which can save a lot of calculation time. Therefore, the efficiency of marker screening would affect power and precision of QTL mapping. A doubled haploid population with 200 individuals and 5 chromosomes was constructed, with 50 markers evenly distributed at 10 cM space. Among a total of 6 QTLs, one was placed on chromosome I, two linked on chromosome II, and the other three linked on chromosome IV. QTL setting included additive effects and epistatic effects of additive x additive, the corresponding QTL interaction effects were set if data were collected under multiple environments. The heritability was assumed to be 0.5 if no special declaration. The power of marker screening by stepwise regression, forward regression, and three methods for random effect prediction, e.g. best linear unbiased prediction (BLUP), linear unbiased prediction (LUP) and adjusted unbiased prediction (AUP), was studied and compared through 100 Monte Carlo simulations. The results indicated that the marker screening power by stepwise regression at 0.1, 0.05 and 0.01 significant level changed from 2% to 68%, the power changed from 2% to 72% by forward regression. The larger the QTL effects, the higher the marker screening power. While the power of marker screening by three random effect prediction was very low, the maximum was only 13%. That suggested that regression methods were much better than those by using the approaches of random effect prediction to identify efficient markers flanking QTLs, and forward selection method was more simple and efficient. The results of simulation study on heritability showed that heightening of both general heritability and interaction heritability of genotype x environments could enhance marker screening power, the former had a greater influence on QTLs with larger main and/or epistatic effects, while the later on QTLs with small main and/or epistatic effects. The simulation of 100 times was also conducted to study the influence of different marker number and density on marker screening power. It is indicated that the marker screening power would decrease if there were too many markers, especially with high density in a mapping population, which suggested that a mapping population with definite individuals could only hold limited markers. According to the simulation study, the reasonable number of markers should not be more than individuals. The simulation study of marker screening under multiple environments showed high total power of marker screening. In order to relieve the problem that marker screening power restricted the efficiency of QTL mapping, markers identified in multiple environments could be used to construct two search intervals.
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A side-by-side comparison of CPV module and system performance
DOE Office of Scientific and Technical Information (OSTI.GOV)
Muller, Matthew; Marion, Bill; Kurtz, Sarah
A side-by-side comparison is made between concentrator photovoltaic module and system direct current aperture efficiency data with a focus on quantifying system performance losses. The individual losses measured/calculated, when combined, are in good agreement with the total loss seen between the module and the system. Results indicate that for the given test period, the largest individual loss of 3.7% relative is due to the baseline performance difference between the individual module and the average for the 200 modules in the system. A basic empirical model is derived based on module spectral performance data and the tabulated losses between the modulemore » and the system. The model predicts instantaneous system direct current aperture efficiency with a root mean square error of 2.3% relative.« less
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Green, T C; Jago, J G; Macdonald, K A; Waghorn, G C
2013-05-01
Residual feed intake (RFI) is a measure of an individual's efficiency in utilizing feed for maintenance and production during growth or lactation, and is defined as the difference between the actual and predicted feed intake of that individual. The objective of this study was to relate RFI to feeding behavior and to identify behavioral differences between animals with divergent RFI. The intakes and body weight (BW) of 1,049 growing dairy heifers (aged 5-9 mo; 195 ± 25.8 kg of BW) in 5 cohorts were measured for 42 to 49 d to ascertain individual RFI. Animals were housed in an outdoor feeding facility comprising 28 pens, each with 8 animals and 1 feeder per pen, and were fed a dried, cubed alfalfa diet. This forage diet was chosen because most dairy cows in New Zealand are grazed on ryegrass-dominant pastures, without grain or concentrates. An electronic feed monitoring system measured the intake and feeding behavior of individuals. Feeding behavior was summarized as daily intake, daily feeding duration, meal frequency, feeding rate, meal size, meal duration, and temporal feeding patterns. The RFI was moderately to strongly correlated with intake in all cohorts (r=0.54-0.74), indicating that efficient animals ate less than inefficient animals, but relationships with feeding behavior traits (meal frequency, feeding duration, and feeding rate) were weak (r=0.14-0.26), indicating that feeding behavior cannot reliably predict RFI in growing dairy heifers. Comparison of the extremes of RFI (10% most and 10% least efficient) demonstrated similar BW and average daily gain for both groups, but efficient animals ate less; had fewer, longer meals; shorter daily feeding duration; and ate more slowly than the least-efficient animals. These groups also differed in their feeding patterns over 24h, with the most efficient animals eating less and having fewer meals during daylight (0600 to 2100 h), especially during the afternoon (1200 to 1800 h), but ate for a longer time during the night (0000-0600 h) than the least-efficient animals. In summary, correlations between RFI and feeding behavior were weak. Small differences in feeding behavior were observed between the most- and least-efficient animals but adverse behavioral effects associated with such selection in growing dairy heifers are unlikely. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
2016-06-01
The Connected Traveler framework seeks to boost the energy efficiency of personal travel and the overall transportation system by maximizing the accuracy of predicted traveler behavior in response to real-time feedback and incentives. It is anticipated that this approach will establish a feedback loop that 'learns' traveler preferences and customizes incentives to meet or exceed energy efficiency targets by empowering individual travelers with information needed to make energy-efficient choices and reducing the complexity required to validate transportation system energy savings. This handout provides an overview of NREL's Connected Traveler project, including graphics, milestones, and contact information.
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Predicting Recovery Potential for Individual Stroke Patients Increases Rehabilitation Efficiency.
Stinear, Cathy M; Byblow, Winston D; Ackerley, Suzanne J; Barber, P Alan; Smith, Marie-Claire
2017-04-01
Several clinical measures and biomarkers are associated with motor recovery after stroke, but none are used to guide rehabilitation for individual patients. The objective of this study was to evaluate the implementation of upper limb predictions in stroke rehabilitation, by combining clinical measures and biomarkers using the Predict Recovery Potential (PREP) algorithm. Predictions were provided for patients in the implementation group (n=110) and withheld from the comparison group (n=82). Predictions guided rehabilitation therapy focus for patients in the implementation group. The effects of predictive information on clinical practice (length of stay, therapist confidence, therapy content, and dose) were evaluated. Clinical outcomes (upper limb function, impairment and use, independence, and quality of life) were measured 3 and 6 months poststroke. The primary clinical practice outcome was inpatient length of stay. The primary clinical outcome was Action Research Arm Test score 3 months poststroke. Length of stay was 1 week shorter for the implementation group (11 days; 95% confidence interval, 9-13 days) than the comparison group (17 days; 95% confidence interval, 14-21 days; P =0.001), controlling for upper limb impairment, age, sex, and comorbidities. Therapists were more confident ( P =0.004) and modified therapy content according to predictions for the implementation group ( P <0.05). The algorithm correctly predicted the primary clinical outcome for 80% of patients in both groups. There were no adverse effects of algorithm implementation on patient outcomes at 3 or 6 months poststroke. PREP algorithm predictions modify therapy content and increase rehabilitation efficiency after stroke without compromising clinical outcome. URL: http://anzctr.org.au. Unique identifier: ACTRN12611000755932. © 2017 American Heart Association, Inc.
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Social learning and evolution: the cultural intelligence hypothesis
van Schaik, Carel P.; Burkart, Judith M.
2011-01-01
If social learning is more efficient than independent individual exploration, animals should learn vital cultural skills exclusively, and routine skills faster, through social learning, provided they actually use social learning preferentially. Animals with opportunities for social learning indeed do so. Moreover, more frequent opportunities for social learning should boost an individual's repertoire of learned skills. This prediction is confirmed by comparisons among wild great ape populations and by social deprivation and enculturation experiments. These findings shaped the cultural intelligence hypothesis, which complements the traditional benefit hypotheses for the evolution of intelligence by specifying the conditions in which these benefits can be reaped. The evolutionary version of the hypothesis argues that species with frequent opportunities for social learning should more readily respond to selection for a greater number of learned skills. Because improved social learning also improves asocial learning, the hypothesis predicts a positive interspecific correlation between social-learning performance and individual learning ability. Variation among primates supports this prediction. The hypothesis also predicts that more heavily cultural species should be more intelligent. Preliminary tests involving birds and mammals support this prediction too. The cultural intelligence hypothesis can also account for the unusual cognitive abilities of humans, as well as our unique mechanisms of skill transfer. PMID:21357223
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Social learning and evolution: the cultural intelligence hypothesis.
van Schaik, Carel P; Burkart, Judith M
2011-04-12
If social learning is more efficient than independent individual exploration, animals should learn vital cultural skills exclusively, and routine skills faster, through social learning, provided they actually use social learning preferentially. Animals with opportunities for social learning indeed do so. Moreover, more frequent opportunities for social learning should boost an individual's repertoire of learned skills. This prediction is confirmed by comparisons among wild great ape populations and by social deprivation and enculturation experiments. These findings shaped the cultural intelligence hypothesis, which complements the traditional benefit hypotheses for the evolution of intelligence by specifying the conditions in which these benefits can be reaped. The evolutionary version of the hypothesis argues that species with frequent opportunities for social learning should more readily respond to selection for a greater number of learned skills. Because improved social learning also improves asocial learning, the hypothesis predicts a positive interspecific correlation between social-learning performance and individual learning ability. Variation among primates supports this prediction. The hypothesis also predicts that more heavily cultural species should be more intelligent. Preliminary tests involving birds and mammals support this prediction too. The cultural intelligence hypothesis can also account for the unusual cognitive abilities of humans, as well as our unique mechanisms of skill transfer.
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Formation of the predicted training parameters in the form of a discrete information stream
NASA Astrophysics Data System (ADS)
Smolentseva, T. E.; Sumin, V. I.; Zolnikov, V. K.; Lavlinsky, V. V.
2018-03-01
In work process of training in the form of a discrete information stream is considered. On each of stages of the considered process portions of the training information and quality of their assimilation are analysed. Individual characteristics and reaction trained for every portion of information on appropriate sections are defined. The control algorithm of training with the predicted number of control checks of the trainee who allows to define what operating influence is considered it is necessary to create for the trainee. On the basis of this algorithm the vector of probabilities of ignorance of elements of the training information is received. As a result of the conducted researches the algorithm on formation of the predicted training parameters is developed. In work the task of comparison of duration of training received experimentally with predicted on the basis of it is solved the conclusion is drawn on efficiency of formation of the predicted training parameters. The program complex on the basis of the values of individual parameters received as a result of experiments on each trainee who allows to calculate individual characteristics is developed, to form rating and to monitor process of change of parameters of training.
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Carvajal, Guido; Roser, David J; Sisson, Scott A; Keegan, Alexandra; Khan, Stuart J
2015-11-15
Risk management for wastewater treatment and reuse have led to growing interest in understanding and optimising pathogen reduction during biological treatment processes. However, modelling pathogen reduction is often limited by poor characterization of the relationships between variables and incomplete knowledge of removal mechanisms. The aim of this paper was to assess the applicability of Bayesian belief network models to represent associations between pathogen reduction, and operating conditions and monitoring parameters and predict AS performance. Naïve Bayes and semi-naïve Bayes networks were constructed from an activated sludge dataset including operating and monitoring parameters, and removal efficiencies for two pathogens (native Giardia lamblia and seeded Cryptosporidium parvum) and five native microbial indicators (F-RNA bacteriophage, Clostridium perfringens, Escherichia coli, coliforms and enterococci). First we defined the Bayesian network structures for the two pathogen log10 reduction values (LRVs) class nodes discretized into two states (< and ≥ 1 LRV) using two different learning algorithms. Eight metrics, such as Prediction Accuracy (PA) and Area Under the receiver operating Curve (AUC), provided a comparison of model prediction performance, certainty and goodness of fit. This comparison was used to select the optimum models. The optimum Tree Augmented naïve models predicted removal efficiency with high AUC when all system parameters were used simultaneously (AUCs for C. parvum and G. lamblia LRVs of 0.95 and 0.87 respectively). However, metrics for individual system parameters showed only the C. parvum model was reliable. By contrast individual parameters for G. lamblia LRV prediction typically obtained low AUC scores (AUC < 0.81). Useful predictors for C. parvum LRV included solids retention time, turbidity and total coliform LRV. The methodology developed appears applicable for predicting pathogen removal efficiency in water treatment systems generally. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Taylor, J M; Law, N
1998-10-30
We investigate the importance of the assumed covariance structure for longitudinal modelling of CD4 counts. We examine how individual predictions of future CD4 counts are affected by the covariance structure. We consider four covariance structures: one based on an integrated Ornstein-Uhlenbeck stochastic process; one based on Brownian motion, and two derived from standard linear and quadratic random-effects models. Using data from the Multicenter AIDS Cohort Study and from a simulation study, we show that there is a noticeable deterioration in the coverage rate of confidence intervals if we assume the wrong covariance. There is also a loss in efficiency. The quadratic random-effects model is found to be the best in terms of correctly calibrated prediction intervals, but is substantially less efficient than the others. Incorrectly specifying the covariance structure as linear random effects gives too narrow prediction intervals with poor coverage rates. Fitting using the model based on the integrated Ornstein-Uhlenbeck stochastic process is the preferred one of the four considered because of its efficiency and robustness properties. We also use the difference between the future predicted and observed CD4 counts to assess an appropriate transformation of CD4 counts; a fourth root, cube root and square root all appear reasonable choices.
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GAPIT: genome association and prediction integrated tool.
Lipka, Alexander E; Tian, Feng; Wang, Qishan; Peiffer, Jason; Li, Meng; Bradbury, Peter J; Gore, Michael A; Buckler, Edward S; Zhang, Zhiwu
2012-09-15
Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. http://www.maizegenetics.net/GAPIT. zhiwu.zhang@cornell.edu Supplementary data are available at Bioinformatics online.
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Efficient prediction of human protein-protein interactions at a global scale.
Schoenrock, Andrew; Samanfar, Bahram; Pitre, Sylvain; Hooshyar, Mohsen; Jin, Ke; Phillips, Charles A; Wang, Hui; Phanse, Sadhna; Omidi, Katayoun; Gui, Yuan; Alamgir, Md; Wong, Alex; Barrenäs, Fredrik; Babu, Mohan; Benson, Mikael; Langston, Michael A; Green, James R; Dehne, Frank; Golshani, Ashkan
2014-12-10
Our knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods. On the basis of short co-occurring polypeptide regions, we developed a tool called MP-PIPE capable of predicting a global human PPI network within 3 months. With a recall of 23% at a precision of 82.1%, we predicted 172,132 putative PPIs. We demonstrate the usefulness of these predictions through a range of experiments. The speed and accuracy associated with MP-PIPE can make this a potential tool to study individual human PPI networks (from genomic sequences alone) for personalized medicine.
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Longitudinal decline in structural networks predicts dementia in cerebral small vessel disease
Lawrence, Andrew J.; Zeestraten, Eva A.; Benjamin, Philip; Lambert, Christian P.; Morris, Robin G.; Barrick, Thomas R.
2018-01-01
Objective To determine whether longitudinal change in white matter structural network integrity predicts dementia and future cognitive decline in cerebral small vessel disease (SVD). To investigate whether network disruption has a causal role in cognitive decline and mediates the association between conventional MRI markers of SVD with both cognitive decline and dementia. Methods In the prospective longitudinal SCANS (St George's Cognition and Neuroimaging in Stroke) Study, 97 dementia-free individuals with symptomatic lacunar stroke were followed with annual MRI for 3 years and annual cognitive assessment for 5 years. Conversion to dementia was recorded. Structural networks were constructed from diffusion tractography using a longitudinal registration pipeline, and network global efficiency was calculated. Linear mixed-effects regression was used to assess change over time. Results Seventeen individuals (17.5%) converted to dementia, and significant decline in global cognition occurred (p = 0.0016). Structural network measures declined over the 3-year MRI follow-up, but the degree of change varied markedly between individuals. The degree of reductions in network global efficiency was associated with conversion to dementia (B = −2.35, odds ratio = 0.095, p = 0.00056). Change in network global efficiency mediated much of the association of conventional MRI markers of SVD with cognitive decline and progression to dementia. Conclusions Network disruption has a central role in the pathogenesis of cognitive decline and dementia in SVD. It may be a useful disease marker to identify that subgroup of patients with SVD who progress to dementia. PMID:29695593
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Potter, Adam W; Blanchard, Laurie A; Friedl, Karl E; Cadarette, Bruce S; Hoyt, Reed W
2017-02-01
Physiological models provide useful summaries of complex interrelated regulatory functions. These can often be reduced to simple input requirements and simple predictions for pragmatic applications. This paper demonstrates this modeling efficiency by tracing the development of one such simple model, the Heat Strain Decision Aid (HSDA), originally developed to address Army needs. The HSDA, which derives from the Givoni-Goldman equilibrium body core temperature prediction model, uses 16 inputs from four elements: individual characteristics, physical activity, clothing biophysics, and environmental conditions. These inputs are used to mathematically predict core temperature (T c ) rise over time and can estimate water turnover from sweat loss. Based on a history of military applications such as derivation of training and mission planning tools, we conclude that the HSDA model is a robust integration of physiological rules that can guide a variety of useful predictions. The HSDA model is limited to generalized predictions of thermal strain and does not provide individualized predictions that could be obtained from physiological sensor data-driven predictive models. This fully transparent physiological model should be improved and extended with new findings and new challenging scenarios. Published by Elsevier Ltd.
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An evolutionary resolution of manipulation conflict.
González-Forero, Mauricio
2014-07-01
Individuals can manipulate the behavior of social partners. However, manipulation may conflict with the fitness interests of the manipulated individuals. Manipulated individuals can then be favored to resist manipulation, possibly reducing or eliminating the manipulated behavior in the long run. I use a mathematical model to show that conflicts where manipulation and resistance coevolve can disappear as a result of the coevolutionary process. I find that while manipulated individuals are selected to resist, they can simultaneously be favored to express the manipulated behavior at higher efficiency (i.e., providing increasing fitness effects to recipients of the manipulated behavior). Efficiency can increase to a point at which selection for resistance disappears. This process yields an efficient social behavior that is induced by social partners, and over which the inducing and induced individuals are no longer in conflict. A necessary factor is costly inefficiency. I develop the model to address the evolution of advanced eusociality via maternal manipulation (AEMM). The model predicts AEMM to be particularly likely in taxa with ancestrally imperfect resistance to maternal manipulation. Costly inefficiency occurs if the cost of delayed dispersal is larger than the benefit of exploiting the maternal patch. I discuss broader implications of the process. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.
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Repetition Suppression in the Left Inferior Frontal Gyrus Predicts Tone Learning Performance.
Asaridou, Salomi S; Takashima, Atsuko; Dediu, Dan; Hagoort, Peter; McQueen, James M
2016-06-01
Do individuals differ in how efficiently they process non-native sounds? To what extent do these differences relate to individual variability in sound-learning aptitude? We addressed these questions by assessing the sound-learning abilities of Dutch native speakers as they were trained on non-native tone contrasts. We used fMRI repetition suppression to the non-native tones to measure participants' neuronal processing efficiency before and after training. Although all participants improved in tone identification with training, there was large individual variability in learning performance. A repetition suppression effect to tone was found in the bilateral inferior frontal gyri (IFGs) before training. No whole-brain effect was found after training; a region-of-interest analysis, however, showed that, after training, repetition suppression to tone in the left IFG correlated positively with learning. That is, individuals who were better in learning the non-native tones showed larger repetition suppression in this area. Crucially, this was true even before training. These findings add to existing evidence that the left IFG plays an important role in sound learning and indicate that individual differences in learning aptitude stem from differences in the neuronal efficiency with which non-native sounds are processed. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Sadeh, Naomi; Bredemeier, Keith
2010-01-01
Attentional control theory (Eysenck et al., 2007) posits that taxing attentional resources impairs performance efficiency in anxious individuals. This theory, however, does not explicitly address if or how the relation between anxiety and attentional control depends upon the perceptual demands of the task at hand. Consequently, the present study examined the relation between trait anxiety and task performance using a perceptual load task (Maylor & Lavie, 1998). Sixty-eight male college students completed a visual search task that indexed processing of irrelevant distractors systematically across four levels of perceptual load. Results indicated that anxiety was related to difficulty suppressing the behavioral effects of irrelevant distractors (i.e., decreased reaction time efficiency) under high, but not low, perceptual loads. In contrast, anxiety was not associated with error rates on the task. These findings are consistent with the prediction that anxiety is associated with impairments in performance efficiency under conditions that tax attentional resources. PMID:21547776
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Sadeh, Naomi; Bredemeier, Keith
2011-06-01
Attentional control theory (Eysenck et al., 2007) posits that taxing attentional resources impairs performance efficiency in anxious individuals. This theory, however, does not explicitly address if or how the relation between anxiety and attentional control depends upon the perceptual demands of the task at hand. Consequently, the present study examined the relation between trait anxiety and task performance using a perceptual load task (Maylor & Lavie, 1998). Sixty-eight male college students completed a visual search task that indexed processing of irrelevant distractors systematically across four levels of perceptual load. Results indicated that anxiety was related to difficulty suppressing the behavioural effects of irrelevant distractors (i.e., decreased reaction time efficiency) under high, but not low, perceptual loads. In contrast, anxiety was not associated with error rates on the task. These findings are consistent with the prediction that anxiety is associated with impairments in performance efficiency under conditions that tax attentional resources.
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Wannakao, Sippakorn; Artrith, Nongnuch; Limtrakul, Jumras; Kolpak, Alexie M
2015-08-24
The design of catalysts for CO2 reduction is challenging because of the fundamental relationships between the binding energies of the reaction intermediates. Metal carbides have shown promise for transcending these relationships and enabling low-cost alternatives. Herein, we show that directional bonding arising from the mixed covalent/metallic character plays a critical role in governing the surface chemistry. This behavior can be described by consideration of individual d-band components. We use this model to predict efficient catalysts based on tungsten carbide with a sub-monolayer of iron adatoms. Our approach can be used to predict site-preference and binding-energy trends for complex catalyst surfaces. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Prediction of individual response to anticancer therapy: historical and future perspectives.
Unger, Florian T; Witte, Irene; David, Kerstin A
2015-02-01
Since the introduction of chemotherapy for cancer treatment in the early 20th century considerable efforts have been made to maximize drug efficiency and at the same time minimize side effects. As there is a great interpatient variability in response to chemotherapy, the development of predictive biomarkers is an ambitious aim for the rapidly growing research area of personalized molecular medicine. The individual prediction of response will improve treatment and thus increase survival and life quality of patients. In the past, cell cultures were used as in vitro models to predict in vivo response to chemotherapy. Several in vitro chemosensitivity assays served as tools to measure miscellaneous endpoints such as DNA damage, apoptosis and cytotoxicity or growth inhibition. Twenty years ago, the development of high-throughput technologies, e.g. cDNA microarrays enabled a more detailed analysis of drug responses. Thousands of genes were screened and expression levels were correlated to drug responses. In addition, mutation analysis became more and more important for the prediction of therapeutic success. Today, as research enters the area of -omics technologies, identification of signaling pathways is a tool to understand molecular mechanism underlying drug resistance. Combining new tissue models, e.g. 3D organoid cultures with modern technologies for biomarker discovery will offer new opportunities to identify new drug targets and in parallel predict individual responses to anticancer therapy. In this review, we present different currently used chemosensitivity assays including 2D and 3D cell culture models and several -omics approaches for the discovery of predictive biomarkers. Furthermore, we discuss the potential of these assays and biomarkers to predict the clinical outcome of individual patients and future perspectives.
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Conditioned pain modulation predicts duloxetine efficacy in painful diabetic neuropathy.
Yarnitsky, David; Granot, Michal; Nahman-Averbuch, Hadas; Khamaisi, Mogher; Granovsky, Yelena
2012-06-01
This study aims to individualize the selection of drugs for neuropathic pain by examining the potential coupling of a given drug's mechanism of action with the patient's pain modulation pattern. The latter is assessed by the conditioned pain modulation (CPM) and temporal summation (TS) protocols. We hypothesized that patients with a malfunctioning pain modulation pattern, such as less efficient CPM, would benefit more from drugs augmenting descending inhibitory pain control than would patients with a normal modulation pattern of efficient CPM. Thirty patients with painful diabetic neuropathy received 1 week of placebo, 1 week of 30 mg/d duloxetine, and 4 weeks of 60 mg/d duloxetine. Pain modulation was assessed psychophysically, both before and at the end of treatment. Patient assessment of drug efficacy, assessed weekly, was the study's primary outcome. Baseline CPM was found to be correlated with duloxetine efficacy (r=0.628, P<.001, efficient CPM is marked negative), such that less efficient CPM predicted efficacious use of duloxetine. Regression analysis (R(2)=0.673; P=.012) showed that drug efficacy was predicted only by CPM (P=.001) and not by pretreatment pain levels, neuropathy severity, depression level, or patient assessment of improvement by placebo. Furthermore, beyond its predictive value, the treatment-induced improvement in CPM was correlated with drug efficacy (r=-0.411, P=.033). However, this improvement occurred only in patients with less efficient CPM (16.8±16.0 to -1.1±15.5, P<.050). No predictive role was found for TS. In conclusion, the coupling of CPM and duloxetine efficacy highlights the importance of pain pathophysiology in the clinical decision-making process. This evaluative approach promotes personalized pain therapy. Copyright © 2012 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.
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Hou, YanBing; Luo, ChunYan; Yang, Jing; Ou, RuWei; Song, Wei; Wei, QianQian; Cao, Bei; Zhao, Bi; Wu, Ying; Shang, Hui-Fang; Gong, QiYong
2016-07-15
Neuroimaging holds the promise that it may one day aid the clinical assessment. However, the vast majority of studies using resting-state functional magnetic resonance imaging (fMRI) have reported average differences between Parkinson's disease (PD) patients and healthy controls, which do not permit inferences at the level of individuals. This study was to develop a model for the prediction of PD illness severity ratings from individual fMRI brain scan. The resting-state fMRI scans were obtained from 84 patients with PD and the Unified Parkinson's Disease Rating Scale-III (UPDRS-III) scores were obtained before scanning. The RVR method was used to predict clinical scores (UPDRS-III) from fMRI scans. The application of RVR to whole-brain resting-state fMRI data allowed prediction of UPDRS-III scores with statistically significant accuracy (correlation=0.35, P-value=0.001; mean sum of squares=222.17, P-value=0.002). This prediction was informed strongly by negative weight areas including prefrontal lobe and medial occipital lobe, and positive weight areas including medial parietal lobe. It was suggested that fMRI scans contained sufficient information about neurobiological change in patients with PD to permit accurate prediction about illness severity, on an individual subject basis. Our results provided preliminary evidence, as proof-of-concept, to support that fMRI might be possible to be a clinically useful quantitative assessment aid in PD at individual level. This may enable clinicians to target those uncooperative patients and machines to replace human for a more efficient use of health care resources. Copyright © 2016 Elsevier B.V. All rights reserved.
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The neural correlates of impaired inhibitory control in anxiety.
Ansari, Tahereh L; Derakshan, Nazanin
2011-04-01
According to Attentional Control Theory (Eysenck et al., 2007) anxiety impairs the inhibition function of working memory by increasing the influence of stimulus-driven processes over efficient top-down control. We investigated the neural correlates of impaired inhibitory control in anxiety using an antisaccade task. Low- and high-anxious participants performed anti- and prosaccade tasks and electrophysiological activity was recorded. Consistent with previous research high-anxious individuals had longer antisaccade latencies in response to the to-be-inhibited target, compared with low-anxious individuals. Central to our predictions, high-anxious individuals showed lower ERP activity, at frontocentral and central recording sites, than low anxious individuals, in the period immediately prior to onset of the to-be-inhibited target on correct antisaccade trials. Our findings indicate that anxiety interferes with the efficient recruitment of top-down mechanisms required for the suppression of prepotent responses. Implications are discussed within current models of attentional control in anxiety (Bishop, 2009; Eysenck et al., 2007). Copyright © 2011 Elsevier Ltd. All rights reserved.
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Expert Game experiment predicts emergence of trust in professional communication networks.
Bendtsen, Kristian Moss; Uekermann, Florian; Haerter, Jan O
2016-10-25
Strong social capital is increasingly recognized as an organizational advantage. Better knowledge sharing and reduced transaction costs increase work efficiency. To mimic the formation of the associated communication network, we propose the Expert Game, where each individual must find a specific expert and receive her help. Participants act in an impersonal environment and under time constraints that provide short-term incentives for noncooperative behavior. Despite these constraints, we observe cooperation between individuals and the self-organization of a sustained trust network, which facilitates efficient communication channels with increased information flow. We build a behavioral model that explains the experimental dynamics. Analysis of the model reveals an exploitation protection mechanism and measurable social capital, which quantitatively describe the economic utility of trust.
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Effect of Individual Component Life Distribution on Engine Life Prediction
NASA Technical Reports Server (NTRS)
Zaretsky, Erwin V.; Hendricks, Robert C.; Soditus, Sherry M.
2003-01-01
The effect of individual engine component life distributions on engine life prediction was determined. A Weibull-based life and reliability analysis of the NASA Energy Efficient Engine was conducted. The engine s life at a 95 and 99.9 percent probability of survival was determined based upon the engine manufacturer s original life calculations and assumed values of each of the component s cumulative life distributions as represented by a Weibull slope. The lives of the high-pressure turbine (HPT) disks and blades were also evaluated individually and as a system in a similar manner. Knowing the statistical cumulative distribution of each engine component with reasonable engineering certainty is a condition precedent to predicting the life and reliability of an entire engine. The life of a system at a given reliability will be less than the lowest-lived component in the system at the same reliability (probability of survival). Where Weibull slopes of all the engine components are equal, the Weibull slope had a minimal effect on engine L(sub 0.1) life prediction. However, at a probability of survival of 95 percent (L(sub 5) life), life decreased with increasing Weibull slope.
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Liu, Jixin; Ma, Shaohui; Mu, Junya; Chen, Tao; Xu, Qing; Dun, Wanghuan; Tian, Jie; Zhang, Ming
2017-10-01
Individual differences of brain changes of neural communication and integration in the modular architecture of the human brain network exist for the repeated migraine attack and physical or psychological stressors. However, whether the interindividual variability in the migraine brain connectome predicts placebo response to placebo treatment is still unclear. Using DTI and graph theory approaches, we systematically investigated the topological organization of white matter networks in 71 patients with migraine without aura (MO) and 50 matched healthy controls at three levels: global network measure, nodal efficiency, and nodal intramodule/intermodule efficiency. All patients participated in an 8-week sham acupuncture treatment to induce analgesia. In our results, 30% (n = 21) of patients had 50% change in migraine days from baseline after placebo treatment. At baseline, abnormal increased network integration was found in MO patients as compared with the HC group, and the increased global efficiency before starting clinical treatment was associated with their following placebo response. For nodal efficiency, significantly increased within-subnetwork nodal efficiency and intersubnetwork connectivity of the hippocampus and middle frontal gyrus in patients' white matter network were correlated with the responses of follow-up placebo treatment. Our findings suggested that the trait-like individual differences in pain-related maladaptive stress interfered with and diminished the capacity of chronic pain modulation differently, and the placebo response for treatment could be predicted from a prior white matter network modular structure in migraineurs. Hum Brain Mapp 38:5250-5259, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
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Chambert, Thierry; Rotella, Jay J; Higgs, Megan D
2014-01-01
The investigation of individual heterogeneity in vital rates has recently received growing attention among population ecologists. Individual heterogeneity in wild animal populations has been accounted for and quantified by including individually varying effects in models for mark–recapture data, but the real need for underlying individual effects to account for observed levels of individual variation has recently been questioned by the work of Tuljapurkar et al. (Ecology Letters, 12, 93, 2009) on dynamic heterogeneity. Model-selection approaches based on information criteria or Bayes factors have been used to address this question. Here, we suggest that, in addition to model-selection, model-checking methods can provide additional important insights to tackle this issue, as they allow one to evaluate a model's misfit in terms of ecologically meaningful measures. Specifically, we propose the use of posterior predictive checks to explicitly assess discrepancies between a model and the data, and we explain how to incorporate model checking into the inferential process used to assess the practical implications of ignoring individual heterogeneity. Posterior predictive checking is a straightforward and flexible approach for performing model checks in a Bayesian framework that is based on comparisons of observed data to model-generated replications of the data, where parameter uncertainty is incorporated through use of the posterior distribution. If discrepancy measures are chosen carefully and are relevant to the scientific context, posterior predictive checks can provide important information allowing for more efficient model refinement. We illustrate this approach using analyses of vital rates with long-term mark–recapture data for Weddell seals and emphasize its utility for identifying shortfalls or successes of a model at representing a biological process or pattern of interest. We show how posterior predictive checks can be used to strengthen inferences in ecological studies. We demonstrate the application of this method on analyses dealing with the question of individual reproductive heterogeneity in a population of Antarctic pinnipeds. PMID:24834335
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A COMPARATIVE STUDY OF DAY CLASS VS. INSTITUTIONALIZED EDUCABLE RETARDATES.
ERIC Educational Resources Information Center
REYNOLDS, MAYNARD C.; STUNKARD, CLAYTON L.
THE PRESENT STUDY REPRESENTS AN EXTENSION OF A STUDY WHICH DEALT WITH THE LATER ADJUSTMENT OF INDIVIDUALS DISCHARGED FROM A STATE INSTITUTION FOR THE MENTALLY RETARDED. THIS EFFORT REWORKED AVAILABLE DATA TO DEVELOP A MORE EFFICIENT TECHNIQUE OF PREDICTION AND TO STUDY FURTHER INTERACTIONS AMONG THE VARIOUS CHARACTERISTICS OF THE GROUP. IN…
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Developing the U.S. Wildland Fire Decision Support System
Erin Noonan-Wright; Tonja S. Opperman; Mark A. Finney; Tom Zimmerman; Robert C. Seli; Lisa M. Elenz; David E. Calkin; John R. Fiedler
2011-01-01
A new decision support tool, the Wildland Fire Decision Support System (WFDSS) has been developed to support risk-informed decision-making for individual fires in the United States. WFDSS accesses national weather data and forecasts, fire behavior prediction, economic assessment, smoke management assessment, and landscape databases to efficiently formulate and apply...
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Ant groups optimally amplify the effect of transiently informed individuals
NASA Astrophysics Data System (ADS)
Gelblum, Aviram; Pinkoviezky, Itai; Fonio, Ehud; Ghosh, Abhijit; Gov, Nir; Feinerman, Ofer
2015-07-01
To cooperatively transport a large load, it is important that carriers conform in their efforts and align their forces. A downside of behavioural conformism is that it may decrease the group's responsiveness to external information. Combining experiment and theory, we show how ants optimize collective transport. On the single-ant scale, optimization stems from decision rules that balance individuality and compliance. Macroscopically, these rules poise the system at the transition between random walk and ballistic motion where the collective response to the steering of a single informed ant is maximized. We relate this peak in response to the divergence of susceptibility at a phase transition. Our theoretical models predict that the ant-load system can be transitioned through the critical point of this mesoscopic system by varying its size; we present experiments supporting these predictions. Our findings show that efficient group-level processes can arise from transient amplification of individual-based knowledge.
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Ant groups optimally amplify the effect of transiently informed individuals
Gelblum, Aviram; Pinkoviezky, Itai; Fonio, Ehud; Ghosh, Abhijit; Gov, Nir; Feinerman, Ofer
2015-01-01
To cooperatively transport a large load, it is important that carriers conform in their efforts and align their forces. A downside of behavioural conformism is that it may decrease the group's responsiveness to external information. Combining experiment and theory, we show how ants optimize collective transport. On the single-ant scale, optimization stems from decision rules that balance individuality and compliance. Macroscopically, these rules poise the system at the transition between random walk and ballistic motion where the collective response to the steering of a single informed ant is maximized. We relate this peak in response to the divergence of susceptibility at a phase transition. Our theoretical models predict that the ant-load system can be transitioned through the critical point of this mesoscopic system by varying its size; we present experiments supporting these predictions. Our findings show that efficient group-level processes can arise from transient amplification of individual-based knowledge. PMID:26218613
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Imposing constraints on parameter values of a conceptual hydrological model using baseflow response
NASA Astrophysics Data System (ADS)
Dunn, S. M.
Calibration of conceptual hydrological models is frequently limited by a lack of data about the area that is being studied. The result is that a broad range of parameter values can be identified that will give an equally good calibration to the available observations, usually of stream flow. The use of total stream flow can bias analyses towards interpretation of rapid runoff, whereas water quality issues are more frequently associated with low flow condition. This paper demonstrates how model distinctions between surface an sub-surface runoff can be used to define a likelihood measure based on the sub-surface (or baseflow) response. This helps to provide more information about the model behaviour, constrain the acceptable parameter sets and reduce uncertainty in streamflow prediction. A conceptual model, DIY, is applied to two contrasting catchments in Scotland, the Ythan and the Carron Valley. Parameter ranges and envelopes of prediction are identified using criteria based on total flow efficiency, baseflow efficiency and combined efficiencies. The individual parameter ranges derived using the combined efficiency measures still cover relatively wide bands, but are better constrained for the Carron than the Ythan. This reflects the fact that hydrological behaviour in the Carron is dominated by a much flashier surface response than in the Ythan. Hence, the total flow efficiency is more strongly controlled by surface runoff in the Carron and there is a greater contrast with the baseflow efficiency. Comparisons of the predictions using different efficiency measures for the Ythan also suggest that there is a danger of confusing parameter uncertainties with data and model error, if inadequate likelihood measures are defined.
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Biomarkers for diet and cancer prevention research: potentials and challenges.
Davis, Cindy D; Milner, John A
2007-09-01
As cancer incidence is projected to increase for decades there is a need for effective preventive strategies. Fortunately, evidence continues to mount that altering dietary habits is an effective and cost-efficient approach for reducing cancer risk and for modifying the biological behavior of tumors. Predictive, validated and sensitive biomarkers, including those that reliably evaluate "intake" or exposure to a specific food or bioactive component, that assess one or more specific biological "effects" that are linked to cancer, and that effectively predict individual "susceptibility" as a function of nutrient-nutrient interactions and genetics, are fundamental to evaluating who will benefit most from dietary interventions. These biomarkers must be readily accessible, easily and reliably assayed, and predictive of a key process(es) involved in cancer. The response to a food is determined not only by the effective concentration of the bioactive food component(s) reaching the target tissue, but also by the amount of the target requiring modification. Thus, this threshold response to foods and their components will vary from individual to individual. The key to understanding a personalized response is a greater knowledge of nutrigenomics, proteomics and metabolomics.
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Vyas, Urvi; Ghanouni, Pejman; Halpern, Casey H; Elias, Jeff; Pauly, Kim Butts
2016-09-01
In transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) treatments, the acoustic and spatial heterogeneity of the skull cause reflection, absorption, and scattering of the acoustic beams. These effects depend on skull-specific parameters and can lead to patient-specific thermal responses to the same transducer power. In this work, the authors develop a simulation tool to help predict these different experimental responses using 3D heterogeneous tissue models based on the subject CT images. The authors then validate and compare the predicted skull efficiencies to an experimental metric based on the subject thermal responses during tcMRgFUS treatments in a dataset of seventeen human subjects. Seventeen human head CT scans were used to create tissue acoustic models, simulating the effects of reflection, absorption, and scattering of the acoustic beam as it propagates through a heterogeneous skull. The hybrid angular spectrum technique was used to model the acoustic beam propagation of the InSightec ExAblate 4000 head transducer for each subject, yielding maps of the specific absorption rate (SAR). The simulation assumed the transducer was geometrically focused to the thalamus of each subject, and the focal SAR at the target was used as a measure of the simulated skull efficiency. Experimental skull efficiency for each subject was calculated using the thermal temperature maps from the tcMRgFUS treatments. Axial temperature images (with no artifacts) were reconstructed with a single baseline, corrected using a referenceless algorithm. The experimental skull efficiency was calculated by dividing the reconstructed temperature rise 8.8 s after sonication by the applied acoustic power. The simulated skull efficiency using individual-specific heterogeneous models predicts well (R(2) = 0.84) the experimental energy efficiency. This paper presents a simulation model to predict the variation in thermal responses measured in clinical ctMRGFYS treatments while being computationally feasible.
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Vyas, Urvi; Ghanouni, Pejman; Halpern, Casey H.; Elias, Jeff; Pauly, Kim Butts
2016-01-01
Purpose: In transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) treatments, the acoustic and spatial heterogeneity of the skull cause reflection, absorption, and scattering of the acoustic beams. These effects depend on skull-specific parameters and can lead to patient-specific thermal responses to the same transducer power. In this work, the authors develop a simulation tool to help predict these different experimental responses using 3D heterogeneous tissue models based on the subject CT images. The authors then validate and compare the predicted skull efficiencies to an experimental metric based on the subject thermal responses during tcMRgFUS treatments in a dataset of seventeen human subjects. Methods: Seventeen human head CT scans were used to create tissue acoustic models, simulating the effects of reflection, absorption, and scattering of the acoustic beam as it propagates through a heterogeneous skull. The hybrid angular spectrum technique was used to model the acoustic beam propagation of the InSightec ExAblate 4000 head transducer for each subject, yielding maps of the specific absorption rate (SAR). The simulation assumed the transducer was geometrically focused to the thalamus of each subject, and the focal SAR at the target was used as a measure of the simulated skull efficiency. Experimental skull efficiency for each subject was calculated using the thermal temperature maps from the tcMRgFUS treatments. Axial temperature images (with no artifacts) were reconstructed with a single baseline, corrected using a referenceless algorithm. The experimental skull efficiency was calculated by dividing the reconstructed temperature rise 8.8 s after sonication by the applied acoustic power. Results: The simulated skull efficiency using individual-specific heterogeneous models predicts well (R2 = 0.84) the experimental energy efficiency. Conclusions: This paper presents a simulation model to predict the variation in thermal responses measured in clinical ctMRGFYS treatments while being computationally feasible. PMID:27587047
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Vyas, Urvi, E-mail: urvi.vyas@gmail.com; Ghanouni,
Purpose: In transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) treatments, the acoustic and spatial heterogeneity of the skull cause reflection, absorption, and scattering of the acoustic beams. These effects depend on skull-specific parameters and can lead to patient-specific thermal responses to the same transducer power. In this work, the authors develop a simulation tool to help predict these different experimental responses using 3D heterogeneous tissue models based on the subject CT images. The authors then validate and compare the predicted skull efficiencies to an experimental metric based on the subject thermal responses during tcMRgFUS treatments in a dataset of seventeen humanmore » subjects. Methods: Seventeen human head CT scans were used to create tissue acoustic models, simulating the effects of reflection, absorption, and scattering of the acoustic beam as it propagates through a heterogeneous skull. The hybrid angular spectrum technique was used to model the acoustic beam propagation of the InSightec ExAblate 4000 head transducer for each subject, yielding maps of the specific absorption rate (SAR). The simulation assumed the transducer was geometrically focused to the thalamus of each subject, and the focal SAR at the target was used as a measure of the simulated skull efficiency. Experimental skull efficiency for each subject was calculated using the thermal temperature maps from the tcMRgFUS treatments. Axial temperature images (with no artifacts) were reconstructed with a single baseline, corrected using a referenceless algorithm. The experimental skull efficiency was calculated by dividing the reconstructed temperature rise 8.8 s after sonication by the applied acoustic power. Results: The simulated skull efficiency using individual-specific heterogeneous models predicts well (R{sup 2} = 0.84) the experimental energy efficiency. Conclusions: This paper presents a simulation model to predict the variation in thermal responses measured in clinical ctMRGFYS treatments while being computationally feasible.« less
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NASA Astrophysics Data System (ADS)
Levy, M. C.
2012-12-01
Approximately 70% of global available freshwater supplies are used in the agricultural sector. Increased demands for water to meet growing population food requirements, and expected changes in the reliability of freshwater supplies due to climate change, threaten the sustainability of water supplies worldwide - not only on farms, but in connected cities and industries. Researchers concerned with agricultural water use sustainability use a variety of theoretical and empirical measures of efficiency and productivity to gain insight into the sustainability of agricultural water use. However, definitions of measures, or indices, vary between different natural and political boundaries, across regions, states and nations and between their respective research, industry, and environmental groups. Index development responds to local data availability and local agendas, and there is debate about the validity of various indices. However, real differences in empirical index measures are not well-understood across the multiple disciplines that study agricultural water use, including engineering and hydrology, agronomy, climate and soil sciences, and economics. Nevertheless reliable, accessible, and generalizable indices are required for planners and policymakers to promote sustainable water use systems. This study synthesizes a set of water use efficiency and productivity indices based on academic, industry and government literature in California and Australia, two locations with similarly water-stressed and valuable agricultural industries under pressure to achieve optimal water use efficiency and productivity. Empirical data at the irrigation district level from the California San Joaquin Valley and Murray Darling Basin states of Victoria and New South Wales in Australia are used to compute indices that estimate efficiency, yield productivity, and economic productivity of agricultural water use. Multiple index estimates of same time-series data demonstrate historical spread in efficiency and productivity measures in different agricultural regions. Individual indices consistently over- or under- estimate trends in efficiency and productivity by their construction, and may provide inaccurate results in years with extreme climatic events, such as droughts. By treating multiple indices as an "ensemble" of measures, analogous to the treatment of multiple climate model predictions, this study quantifies likely "true" states of efficiency and productivity in the selected agricultural regions, and error in individual indices. While different individual indices are preferable at different scales, and relative to the quality of available input data, ensemble indices can be more reliably used in comparative study across different agricultural regions, and for prediction.
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Retallick, K M; Faulkner, D B; Rodriguez-Zas, S L; Nkrumah, J D; Shike, D W
2013-12-01
A 4-yr study was conducted using 736 steers of known Angus, Simmental, or Simmental × Angus genetics to determine performance, carcass, and feed efficiency factors that explained variation in economic performance. Steers were pen fed and individual DMI was recorded using a GrowSafe automated feeding system (GrowSafe Systems Ltd., Airdrie, Alberta, Canada). Steers consumed a similar diet and received similar management each year. The objectives of this study were to: 1) determine current economic value of feed efficiency and 2) identify performance, carcass, and feed efficiency characteristics that predict: carcass value, profit, cost of gain, and feed costs. Economic data used were from 2011 values. Feed efficiency values investigated were: feed conversion ratio (FCR; feed to gain), residual feed intake (RFI), residual BW gain (RG), and residual intake and BW gain (RIG). Dependent variables were carcass value ($/steer), profit ($/steer), feed costs ($/steer • d(-1)), and cost of gain ($/kg). Independent variables were year, DMI, ADG, HCW, LM area, marbling, yield grade, dam breed, and sire breed. A 10% improvement in RG (P < 0.05) yielded the lowest cost of gain at $0.09/kg and highest carcass value at $17.92/steer. Carcass value increased (P < 0.05) as feed efficiency improved for FCR, RG, and RIG. Profit increased with a 10% improvement in feed efficiency (P < 0.05) with FCR at $34.65/steer, RG at $31.21/steer, RIG at $21.66/steer, and RFI at $11.47/steer. The carcass value prediction model explained 96% of the variation among carcasses and included HCW, marbling score, and yield grade. Average daily gain, marbling score, yield grade, DMI, HCW, and year born constituted 81% of the variation for prediction of profit. Eighty-five percent of the variation in cost of gain was explained by ADG, DMI, HCW, and year. Prediction equations were developed that excluded ADG and DMI, and included feed efficiency values. Using these equations, cost of gain was explained primarily by FCR (R(2) = 0.71). Seventy-three percent of profitability was explained, with 55% being accounted for by RG and marbling. These prediction equations represent the relative importance of factors contributing to economic success in feedlot cattle based on current prices.
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Statistical procedures for evaluating daily and monthly hydrologic model predictions
Coffey, M.E.; Workman, S.R.; Taraba, J.L.; Fogle, A.W.
2004-01-01
The overall study objective was to evaluate the applicability of different qualitative and quantitative methods for comparing daily and monthly SWAT computer model hydrologic streamflow predictions to observed data, and to recommend statistical methods for use in future model evaluations. Statistical methods were tested using daily streamflows and monthly equivalent runoff depths. The statistical techniques included linear regression, Nash-Sutcliffe efficiency, nonparametric tests, t-test, objective functions, autocorrelation, and cross-correlation. None of the methods specifically applied to the non-normal distribution and dependence between data points for the daily predicted and observed data. Of the tested methods, median objective functions, sign test, autocorrelation, and cross-correlation were most applicable for the daily data. The robust coefficient of determination (CD*) and robust modeling efficiency (EF*) objective functions were the preferred methods for daily model results due to the ease of comparing these values with a fixed ideal reference value of one. Predicted and observed monthly totals were more normally distributed, and there was less dependence between individual monthly totals than was observed for the corresponding predicted and observed daily values. More statistical methods were available for comparing SWAT model-predicted and observed monthly totals. The 1995 monthly SWAT model predictions and observed data had a regression Rr2 of 0.70, a Nash-Sutcliffe efficiency of 0.41, and the t-test failed to reject the equal data means hypothesis. The Nash-Sutcliffe coefficient and the R r2 coefficient were the preferred methods for monthly results due to the ability to compare these coefficients to a set ideal value of one.
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Unfolding the laws of star formation: the density distribution of molecular clouds.
Kainulainen, Jouni; Federrath, Christoph; Henning, Thomas
2014-04-11
The formation of stars shapes the structure and evolution of entire galaxies. The rate and efficiency of this process are affected substantially by the density structure of the individual molecular clouds in which stars form. The most fundamental measure of this structure is the probability density function of volume densities (ρ-PDF), which determines the star formation rates predicted with analytical models. This function has remained unconstrained by observations. We have developed an approach to quantify ρ-PDFs and establish their relation to star formation. The ρ-PDFs instigate a density threshold of star formation and allow us to quantify the star formation efficiency above it. The ρ-PDFs provide new constraints for star formation theories and correctly predict several key properties of the star-forming interstellar medium.
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Optimizing the recovery of copper from electroplating rinse bath solution by hollow fiber membrane.
Oskay, Kürşad Oğuz; Kul, Mehmet
2015-01-01
This study aimed to recover and remove copper from industrial model wastewater solution by non-dispersive solvent extraction (NDSX). Two mathematical models were developed to simulate the performance of an integrated extraction-stripping process, based on the use of hollow fiber contactors using the response surface method. The models allow one to predict the time dependent efficiencies of the two phases involved in individual extraction or stripping processes. The optimal recovery efficiency parameters were determined as 227 g/L of H2SO4 concentration, 1.22 feed/strip ratio, 450 mL/min flow rate (115.9 cm/min. flow velocity) and 15 volume % LIX 84-I concentration in 270 min by central composite design (CCD). At these optimum conditions, the experimental value of recovery efficiency was 95.88%, which was in close agreement with the 97.75% efficiency value predicted by the model. At the end of the process, almost all the copper in the model wastewater solution was removed and recovered as CuSO4.5H2O salt, which can be reused in the copper electroplating industry.
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Reproductive success is energetically linked to foraging efficiency in Antarctic fur seals
2017-01-01
The efficiency with which individuals extract energy from their environment defines their survival and reproductive success, and thus their selective contribution to the population. Individuals that forage more efficiently (i.e., when energy gained exceeds energy expended) are likely to be more successful at raising viable offspring than individuals that forage less efficiently. Our goal was to test this prediction in large long-lived mammals under free-ranging conditions. To do so, we equipped 20 lactating Antarctic fur seals (Arctocephalus gazella) breeding on Kerguelen Island in the Southern Ocean with tags that recorded GPS locations, depth and tri-axial acceleration to determine at-sea behaviours and detailed time-activity budgets during their foraging trips. We also simultaneously measured energy spent at sea using the doubly-labeled water (DLW) method, and estimated the energy acquired while foraging from 1) type and energy content of prey species present in scat remains, and 2) numbers of prey capture attempts determined from head acceleration. Finally, we followed the growth of 36 pups from birth until weaning (of which 20 were the offspring of our 20 tracked mothers), and used the relative differences in body mass of pups at weaning as an index of first year survival and thus the reproductive success of their mothers. Our results show that females with greater foraging efficiencies produced relatively bigger pups at weaning. These mothers achieved greater foraging efficiency by extracting more energy per minute of diving rather than by reducing energy expenditure. This strategy also resulted in the females spending less time diving and less time overall at sea, which allowed them to deliver higher quality milk to their pups, or allowed their pups to suckle more frequently, or both. The linkage we demonstrate between reproductive success and the quality of individuals as foragers provides an individual-based quantitative framework to investigate how changes in the availability and accessibility of prey can affect fitness of animals. PMID:28453563
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Threat facilitates subsequent executive control during anxious mood.
Birk, Jeffrey L; Dennis, Tracy A; Shin, Lisa M; Urry, Heather L
2011-12-01
Dual competition framework (DCF) posits that low-level threat may facilitate behavioral performance by influencing executive control functions. Anxiety is thought to strengthen this effect by enhancing threat's affective significance. To test these ideas directly, we examined the effects of low-level threat and experimentally induced anxiety on one executive control function, the efficiency of response inhibition. In Study 1, briefly presented stimuli that were mildly threatening (i.e., fearful faces) relative to nonthreatening (i.e., neutral faces) led to facilitated executive control efficiency during experimentally induced anxiety. No such effect was observed during an equally arousing, experimentally induced happy mood state. In Study 2, we assessed the effects of low-level threat, experimentally induced anxiety, and individual differences in trait anxiety on executive control efficiency. Consistent with Study 1, fearful relative to neutral faces led to facilitated executive control efficiency during experimentally induced anxiety. No such effect was observed during an experimentally induced neutral mood state. Moreover, individual differences in trait anxiety did not moderate the effects of threat and anxiety on executive control efficiency. The findings are partially consistent with the predictions of DCF in that low-level threat improved executive control, at least during a state of anxiety. (c) 2011 APA, all rights reserved.
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Raymond L. Czaplewski
1989-01-01
It is difficult to design systems for national and global resource inventory and analysis that efficiently satisfy changing, and increasingly complex objectives. It is proposed that individual inventory, monitoring, modeling, and remote sensing systems be specialized to achieve portions of the objectives. These separate systems can be statistically linked to accomplish...
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Repeatability of number of progeny born to bulls used in group mating of cows
USDA-ARS?s Scientific Manuscript database
The group mating of bulls in pasture situations is a management practice that might be more efficient if an individual bull’s ability to sire calves could be predicted. Retrospective data on numbers of progeny born to bulls from 4 populations (Angus and 3 composite breeds) in 4 consecutive years of...
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Basic Numerical Capacities and Prevalence of Developmental Dyscalculia: The Havana Survey
ERIC Educational Resources Information Center
Reigosa-Crespo, Vivian; Valdes-Sosa, Mitchell; Butterworth, Brian; Estevez, Nancy; Rodriguez, Marisol; Santos, Elsa; Torres, Paul; Suarez, Ramon; Lage, Agustin
2012-01-01
The association of enumeration and number comparison capacities with arithmetical competence was examined in a large sample of children from 2nd to 9th grades. It was found that efficiency on numerical capacities predicted separately more than 25% of the variance in the individual differences on a timed arithmetical test, and this occurred for…
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Jawdy, Sara S.; Gunter, Lee E.; Engle, Nancy L.
Here, the biological function of the plant-microbiome system is the result of contributions from the host plant and microbiome members. In this work we study the function of a simplified community consisting of Pseudomonas and Burkholderia bacterial strains isolated from Populus hosts and inoculated on axenic Populus cutting in controlled laboratory conditions. Inoculation individually with either bacterial isolate increased root growth relative to uninoculated controls. Root area, photosynthetic efficiency, gene expression and metabolite expression data in individual and dual inoculated treatments indicate that the effects of these bacteria are unique and additive, suggesting that the function of a microbiome communitymore » may be predicted from the additive functions of the individual members.« less
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Consistent differences in individual reactions to drugs and dummies
Joyce, C. R. B.
1959-01-01
The tendency of some individuals to report changes of physical and mental state after taking pharmacologically inert substances has been investigated experimentally. In a class of healthy medical students, those individuals who reported symptoms and those who did not made significantly different scores on a number of behavioural tests. The likely reactions of the members of a second class (containing none of the previous participants) to dummies were then predicted from their scores on the same tests, some of which were found to be much more efficient predictors than would have been expected by chance. Some implications for further research and for clinical medicine are discussed. PMID:14408028
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Van Dongen, Hans P. A.; Mott, Christopher G.; Huang, Jen-Kuang; Mollicone, Daniel J.; McKenzie, Frederic D.; Dinges, David F.
2007-01-01
Current biomathematical models of fatigue and performance do not accurately predict cognitive performance for individuals with a priori unknown degrees of trait vulnerability to sleep loss, do not predict performance reliably when initial conditions are uncertain, and do not yield statistically valid estimates of prediction accuracy. These limitations diminish their usefulness for predicting the performance of individuals in operational environments. To overcome these 3 limitations, a novel modeling approach was developed, based on the expansion of a statistical technique called Bayesian forecasting. The expanded Bayesian forecasting procedure was implemented in the two-process model of sleep regulation, which has been used to predict performance on the basis of the combination of a sleep homeostatic process and a circadian process. Employing the two-process model with the Bayesian forecasting procedure to predict performance for individual subjects in the face of unknown traits and uncertain states entailed subject-specific optimization of 3 trait parameters (homeostatic build-up rate, circadian amplitude, and basal performance level) and 2 initial state parameters (initial homeostatic state and circadian phase angle). Prior information about the distribution of the trait parameters in the population at large was extracted from psychomotor vigilance test (PVT) performance measurements in 10 subjects who had participated in a laboratory experiment with 88 h of total sleep deprivation. The PVT performance data of 3 additional subjects in this experiment were set aside beforehand for use in prospective computer simulations. The simulations involved updating the subject-specific model parameters every time the next performance measurement became available, and then predicting performance 24 h ahead. Comparison of the predictions to the subjects' actual data revealed that as more data became available for the individuals at hand, the performance predictions became increasingly more accurate and had progressively smaller 95% confidence intervals, as the model parameters converged efficiently to those that best characterized each individual. Even when more challenging simulations were run (mimicking a change in the initial homeostatic state; simulating the data to be sparse), the predictions were still considerably more accurate than would have been achieved by the two-process model alone. Although the work described here is still limited to periods of consolidated wakefulness with stable circadian rhythms, the results obtained thus far indicate that the Bayesian forecasting procedure can successfully overcome some of the major outstanding challenges for biomathematical prediction of cognitive performance in operational settings. Citation: Van Dongen HPA; Mott CG; Huang JK; Mollicone DJ; McKenzie FD; Dinges DF. Optimization of biomathematical model predictions for cognitive performance impairment in individuals: accounting for unknown traits and uncertain states in homeostatic and circadian processes. SLEEP 2007;30(9):1129-1143. PMID:17910385
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GenoMatrix: A Software Package for Pedigree-Based and Genomic Prediction Analyses on Complex Traits.
Nazarian, Alireza; Gezan, Salvador Alejandro
2016-07-01
Genomic and pedigree-based best linear unbiased prediction methodologies (G-BLUP and P-BLUP) have proven themselves efficient for partitioning the phenotypic variance of complex traits into its components, estimating the individuals' genetic merits, and predicting unobserved (or yet-to-be observed) phenotypes in many species and fields of study. The GenoMatrix software, presented here, is a user-friendly package to facilitate the process of using genome-wide marker data and parentage information for G-BLUP and P-BLUP analyses on complex traits. It provides users with a collection of applications which help them on a set of tasks from performing quality control on data to constructing and manipulating the genomic and pedigree-based relationship matrices and obtaining their inverses. Such matrices will be then used in downstream analyses by other statistical packages. The package also enables users to obtain predicted values for unobserved individuals based on the genetic values of observed related individuals. GenoMatrix is available to the research community as a Windows 64bit executable and can be downloaded free of charge at: http://compbio.ufl.edu/software/genomatrix/. © The American Genetic Association. 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Active optimal control strategies for increasing the efficiency of photovoltaic cells
NASA Astrophysics Data System (ADS)
Aljoaba, Sharif Zidan Ahmad
Energy consumption has increased drastically during the last century. Currently, the worldwide energy consumption is about 17.4 TW and is predicted to reach 25 TW by 2035. Solar energy has emerged as one of the potential renewable energy sources. Since its first physical recognition in 1887 by Adams and Day till nowadays, research in solar energy is continuously developing. This has lead to many achievements and milestones that introduced it as one of the most reliable and sustainable energy sources. Recently, the International Energy Agency declared that solar energy is predicted to be one of the major electricity production energy sources by 2035. Enhancing the efficiency and lifecycle of photovoltaic (PV) modules leads to significant cost reduction. Reducing the temperature of the PV module improves its efficiency and enhances its lifecycle. To better understand the PV module performance, it is important to study the interaction between the output power and the temperature. A model that is capable of predicting the PV module temperature and its effects on the output power considering the individual contribution of the solar spectrum wavelengths significantly advances the PV module edsigns toward higher efficiency. In this work, a thermoelectrical model is developed to predict the effects of the solar spectrum wavelengths on the PV module performance. The model is characterized and validated under real meteorological conditions where experimental temperature and output power of the PV module measurements are shown to agree with the predicted results. The model is used to validate the concept of active optical filtering. Since this model is wavelength-based, it is used to design an active optical filter for PV applications. Applying this filter to the PV module is expected to increase the output power of the module by filtering the spectrum wavelengths. The active filter performance is optimized, where different cutoff wavelengths are used to maximize the module output power. It is predicted that if the optimized active optical filter is applied to the PV module, the module efficiency is predicted to increase by about 1%. Different technologies are considered for physical implementation of the active optical filter.
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Phuong, H N; Blavy, P; Martin, O; Schmidely, P; Friggens, N C
2016-01-01
Reproductive success is a key component of lifetime efficiency - which is the ratio of energy in milk (MJ) to energy intake (MJ) over the lifespan, of cows. At the animal level, breeding and feeding management can substantially impact milk yield, body condition and energy balance of cows, which are known as major contributors to reproductive failure in dairy cattle. This study extended an existing lifetime performance model to incorporate the impacts that performance changes due to changing breeding and feeding strategies have on the probability of reproducing and thereby on the productive lifespan, and thus allow the prediction of a cow's lifetime efficiency. The model is dynamic and stochastic, with an individual cow being the unit modelled and one day being the unit of time. To evaluate the model, data from a French study including Holstein and Normande cows fed high-concentrate diets and data from a Scottish study including Holstein cows selected for high and average genetic merit for fat plus protein that were fed high- v. low-concentrate diets were used. Generally, the model consistently simulated productive and reproductive performance of various genotypes of cows across feeding systems. In the French data, the model adequately simulated the reproductive performance of Holsteins but significantly under-predicted that of Normande cows. In the Scottish data, conception to first service was comparably simulated, whereas interval traits were slightly under-predicted. Selection for greater milk production impaired the reproductive performance and lifespan but not lifetime efficiency. The definition of lifetime efficiency used in this model did not include associated costs or herd-level effects. Further works should include such economic indicators to allow more accurate simulation of lifetime profitability in different production scenarios.
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NASA Technical Reports Server (NTRS)
Rodionova, Olga; Sridhar, Banavar; Ng, Hok K.
2016-01-01
Air traffic in the North Atlantic oceanic airspace (NAT) experiences very strong winds caused by jet streams. Flying wind-optimal trajectories increases individual flight efficiency, which is advantageous when operating in the NAT. However, as the NAT is highly congested during peak hours, a large number of potential conflicts between flights are detected for the sets of wind-optimal trajectories. Conflict resolution performed at the strategic level of flight planning can significantly reduce the airspace congestion. However, being completed far in advance, strategic planning can only use predicted environmental conditions that may significantly differ from the real conditions experienced further by aircraft. The forecast uncertainties result in uncertainties in conflict prediction, and thus, conflict resolution becomes less efficient. This work considers wind uncertainties in order to improve the robustness of conflict resolution in the NAT. First, the influence of wind uncertainties on conflict prediction is investigated. Then, conflict resolution methods accounting for wind uncertainties are proposed.
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de la Vega, Alejandro; Brown, Mark S; Snyder, Hannah R; Singel, Debra; Munakata, Yuko; Banich, Marie T
2014-11-01
Individuals vary greatly in their ability to select one item or response when presented with a multitude of options. Here we investigate the neural underpinnings of these individual differences. Using magnetic resonance spectroscopy, we found that the balance of inhibitory versus excitatory neurotransmitters in pFC predicts the ability to select among task-relevant options in two language production tasks. The greater an individual's concentration of GABA relative to glutamate in the lateral pFC, the more quickly he or she could select a relevant word from among competing options. This outcome is consistent with our computational modeling of this task [Snyder, H. R., Hutchison, N., Nyhus, E., Curran, T., Banich, M. T., O'Reilly, R. C., et al. Neural inhibition enables selection during language processing. Proceedings of the National Academy of Sciences, U.S.A., 107, 16483-16488, 2010], which predicts that greater net inhibition in pFC increases the efficiency of resolving competition among task-relevant options. Moreover, the association with the GABA/glutamate ratio was specific to selection and was not observed for executive function ability in general. These findings are the first to link the balance of excitatory and inhibitory neural transmission in pFC to specific aspects of executive function.
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A simple device for efficient transfer and unit dose packaging of Xe-127: concise communication.
Kowalsky, R J; Dalton, D R; Saylor, W L
1978-04-01
An inexpensive system has been devised for the efficient transfer of Xe-127 gas from the manufacturer's ampule into individual dose vials for patient use. By displacing the gas with an aqueous solution, the initial transfer is made from an ampule of known activity into an evacuated serum vial of predetermined volume with transfer efficiency greater than 99%. A similar principle is used to transfer Xe-127 from the stock serum vial into individual dose vials, with total xenon recovery exceeding 98%. Ability to deliver the desired activity to each vial is within 90-110% of that predicted by calculation. Reproducibility in delivering a given activity was excellent, with all vials falling between 95 and 105% of the mean activity. Stability studies showed that 94% of the Xe-127 activity can be removed from the vials with only 6% absorbed in the rubber stopper after 5 wk of storage. The device costs less than $25.00 and can be constructed easily from common laboratory materials.
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Rincent, R; Laloë, D; Nicolas, S; Altmann, T; Brunel, D; Revilla, P; Rodríguez, V M; Moreno-Gonzalez, J; Melchinger, A; Bauer, E; Schoen, C-C; Meyer, N; Giauffret, C; Bauland, C; Jamin, P; Laborde, J; Monod, H; Flament, P; Charcosset, A; Moreau, L
2012-10-01
Genomic selection refers to the use of genotypic information for predicting breeding values of selection candidates. A prediction formula is calibrated with the genotypes and phenotypes of reference individuals constituting the calibration set. The size and the composition of this set are essential parameters affecting the prediction reliabilities. The objective of this study was to maximize reliabilities by optimizing the calibration set. Different criteria based on the diversity or on the prediction error variance (PEV) derived from the realized additive relationship matrix-best linear unbiased predictions model (RA-BLUP) were used to select the reference individuals. For the latter, we considered the mean of the PEV of the contrasts between each selection candidate and the mean of the population (PEVmean) and the mean of the expected reliabilities of the same contrasts (CDmean). These criteria were tested with phenotypic data collected on two diversity panels of maize (Zea mays L.) genotyped with a 50k SNPs array. In the two panels, samples chosen based on CDmean gave higher reliabilities than random samples for various calibration set sizes. CDmean also appeared superior to PEVmean, which can be explained by the fact that it takes into account the reduction of variance due to the relatedness between individuals. Selected samples were close to optimality for a wide range of trait heritabilities, which suggests that the strategy presented here can efficiently sample subsets in panels of inbred lines. A script to optimize reference samples based on CDmean is available on request.
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An individual risk prediction model for lung cancer based on a study in a Chinese population.
Wang, Xu; Ma, Kewei; Cui, Jiuwei; Chen, Xiao; Jin, Lina; Li, Wei
2015-01-01
Early detection and diagnosis remains an effective yet challenging approach to improve the clinical outcome of patients with cancer. Low-dose computed tomography screening has been suggested to improve the diagnosis of lung cancer in high-risk individuals. To make screening more efficient, it is necessary to identify individuals who are at high risk. We conducted a case-control study to develop a predictive model for identification of such high-risk individuals. Clinical data from 705 lung cancer patients and 988 population-based controls were used for the development and evaluation of the model. Associations between environmental variants and lung cancer risk were analyzed with a logistic regression model. The predictive accuracy of the model was determined by calculating the area under the receiver operating characteristic curve and the optimal operating point. Our results indicate that lung cancer risk factors included older age, male gender, lower education level, family history of cancer, history of chronic obstructive pulmonary disease, lower body mass index, smoking cigarettes, a diet with less seafood, vegetables, fruits, dairy products, soybean products and nuts, a diet rich in meat, and exposure to pesticides and cooking emissions. The area under the curve was 0.8851 and the optimal operating point was obtained. With a cutoff of 0.35, the false positive rate, true positive rate, and Youden index were 0.21, 0.87, and 0.66, respectively. The risk prediction model for lung cancer developed in this study could discriminate high-risk from low-risk individuals.
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Combining correlative and mechanistic habitat suitability models to improve ecological compensation.
Meineri, Eric; Deville, Anne-Sophie; Grémillet, David; Gauthier-Clerc, Michel; Béchet, Arnaud
2015-02-01
Only a few studies have shown positive impacts of ecological compensation on species dynamics affected by human activities. We argue that this is due to inappropriate methods used to forecast required compensation in environmental impact assessments. These assessments are mostly descriptive and only valid at limited spatial and temporal scales. However, habitat suitability models developed to predict the impacts of environmental changes on potential species' distributions should provide rigorous science-based tools for compensation planning. Here we describe the two main classes of predictive models: correlative models and individual-based mechanistic models. We show how these models can be used alone or synoptically to improve compensation planning. While correlative models are easier to implement, they tend to ignore underlying ecological processes and lack accuracy. On the contrary, individual-based mechanistic models can integrate biological interactions, dispersal ability and adaptation. Moreover, among mechanistic models, those considering animal energy balance are particularly efficient at predicting the impact of foraging habitat loss. However, mechanistic models require more field data compared to correlative models. Hence we present two approaches which combine both methods for compensation planning, especially in relation to the spatial scale considered. We show how the availability of biological databases and software enabling fast and accurate population projections could be advantageously used to assess ecological compensation requirement efficiently in environmental impact assessments. © 2014 The Authors. Biological Reviews © 2014 Cambridge Philosophical Society.
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Ye, Zheng; Rae, Charlotte L.; Nombela, Cristina; Ham, Timothy; Rittman, Timothy; Jones, Peter Simon; Rodríguez, Patricia Vázquez; Coyle‐Gilchrist, Ian; Regenthal, Ralf; Altena, Ellemarije; Housden, Charlotte R.; Maxwell, Helen; Sahakian, Barbara J.; Barker, Roger A.; Robbins, Trevor W.
2016-01-01
Abstract Recent studies indicate that selective noradrenergic (atomoxetine) and serotonergic (citalopram) reuptake inhibitors may improve response inhibition in selected patients with Parkinson's disease, restoring behavioral performance and brain activity. We reassessed the behavioral efficacy of these drugs in a larger cohort and developed predictive models to identify patient responders. We used a double‐blind randomized three‐way crossover design to investigate stopping efficiency in 34 patients with idiopathic Parkinson's disease after 40 mg atomoxetine, 30 mg citalopram, or placebo. Diffusion‐weighted and functional imaging measured microstructural properties and regional brain activations, respectively. We confirmed that Parkinson's disease impairs response inhibition. Overall, drug effects on response inhibition varied substantially across patients at both behavioral and brain activity levels. We therefore built binary classifiers with leave‐one‐out cross‐validation (LOOCV) to predict patients’ responses in terms of improved stopping efficiency. We identified two optimal models: (1) a “clinical” model that predicted the response of an individual patient with 77–79% accuracy for atomoxetine and citalopram, using clinically available information including age, cognitive status, and levodopa equivalent dose, and a simple diffusion‐weighted imaging scan; and (2) a “mechanistic” model that explained the behavioral response with 85% accuracy for each drug, using drug‐induced changes of brain activations in the striatum and presupplementary motor area from functional imaging. These data support growing evidence for the role of noradrenaline and serotonin in inhibitory control. Although noradrenergic and serotonergic drugs have highly variable effects in patients with Parkinson's disease, the individual patient's response to each drug can be predicted using a pattern of clinical and neuroimaging features. Hum Brain Mapp 37:1026–1037, 2016. © 2016 Wiley Periodicals, Inc. PMID:26757216
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Particle Swarm Optimization for Programming Deep Brain Stimulation Arrays
Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D.
2017-01-01
Objective Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main Results The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (≤9.2%) and ROA (≤1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n=3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies of <1% between approaches. Significance The PSO algorithm provides a computationally efficient way to program DBS systems especially those with higher electrode counts. PMID:28068291
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Particle swarm optimization for programming deep brain stimulation arrays
NASA Astrophysics Data System (ADS)
Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D.
2017-02-01
Objective. Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach. Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main results. The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (⩽9.2%) and ROA (⩽1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n = 3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies of <1% between approaches. Significance. The PSO algorithm provides a computationally efficient way to program DBS systems especially those with higher electrode counts.
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GOETZINGER, Katherine R.; ZHONG, Yan; CAHILL, Alison G.; ODIBO, Linda; MACONES, George A.; ODIBO, Anthony O.
2014-01-01
Objective To estimate the efficiency of first-trimester uterine artery Doppler, A-disintegrin and metalloprotease 12 (ADAM12), pregnancy-associated plasma protein A (PAPP-A) and maternal characteristics in the prediction of pre-eclampsia. Methods This is a prospective cohort study of patients presenting for first-trimester aneuploidy screening between 11-14 weeks’ gestation. Maternal serum ADAM12 and PAPP-A levels were measured by immunoassay, and mean uterine artery Doppler pulsatility indices (PI) were calculated. Outcomes of interest included pre-eclampsia, early pre-eclampsia, defined as requiring delivery at <34 weeks’ gestation, and gestational hypertension. Logistic regression analysis was used to model the prediction of pre-eclampsia using ADAM12 multiples of the median (MoM), PAPP-A MoM, and uterine artery Doppler PI MoM, either individually or in combination. Sensitivity, specificity, and area under the receiver-operating characteristic curves (AUC) were used to compare the screening efficiency of the models using non-parametric U-statistics. Results Of 578 patients with complete outcome data, there were 54 (9.3%) cases of preeclampsia and 13 (2.2%) cases of early pre-eclampsia. Median ADAM12 levels were significantly lower in patients who developed pre-eclampsia compared to those who did not. (0.81 v. 1.01 MoMs; p<0.04) For a fixed false positive rate (FPR) of 10%, ADAM12, PAPP-A, and uterine artery Doppler in combination with maternal characteristics identified 50%, 48%, and 52% of patients who developed pre-eclampsia, respectively. Combining these first-trimester parameters did not improve the predictive efficiency of the models. Conclusion First-trimester ADAM12, PAPP-A, and uterine artery Doppler are not sufficiently predictive of pre-eclampsia. Combinations of these parameters do not further improve their screening efficiency. PMID:23980220
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Pierce, Brandon L; Tong, Lin; Argos, Maria; Gao, Jianjun; Farzana, Jasmine; Roy, Shantanu; Paul-Brutus, Rachelle; Rahaman, Ronald; Rakibuz-Zaman, Muhammad; Parvez, Faruque; Ahmed, Alauddin; Quasem, Iftekhar; Hore, Samar K; Alam, Shafiul; Islam, Tariqul; Harjes, Judith; Sarwar, Golam; Slavkovich, Vesna; Gamble, Mary V; Chen, Yu; Yunus, Mohammad; Rahman, Mahfuzar; Baron, John A; Graziano, Joseph H; Ahsan, Habibul
2013-12-01
Arsenic exposure through drinking water is a serious global health issue. Observational studies suggest that individuals who metabolize arsenic efficiently are at lower risk for toxicities such as arsenical skin lesions. Using two single nucleotide polymorphisms(SNPs) in the 10q24.32 region (near AS3MT) that show independent associations with metabolism efficiency, Mendelian randomization can be used to assess whether the association between metabolism efficiency and skin lesions is likely to be causal. Using data on 2060 arsenic-exposed Bangladeshi individuals, we estimated associations for two 10q24.32 SNPs with relative concentrations of three urinary arsenic species (representing metabolism efficiency): inorganic arsenic (iAs), monomethylarsonic acid(MMA) and dimethylarsinic acid (DMA). SNP-based predictions of iAs%, MMA% and DMA% were tested for association with skin lesion status among 2483 cases and 2857 controls. Causal odds ratios for skin lesions were 0.90 (95% confidence interval[CI]: 0.87, 0.95), 1.19 (CI: 1.10, 1.28) and 1.23 (CI: 1.12, 1.36)for a one standard deviation increase in DMA%, MMA% and iAs%,respectively. We demonstrated genotype-arsenic interaction, with metabolism-related variants showing stronger associations with skin lesion risk among individuals with high arsenic exposure (synergy index: 1.37; CI: 1.11, 1.62). We provide strong evidence for a causal relationship between arsenic metabolism efficiency and skin lesion risk. Mendelian randomization can be used to assess the causal role of arsenic exposure and metabolism in a wide array of health conditions.exposure and metabolism in a wide array of health conditions.Developing interventions that increase arsenic metabolism efficiency are likely to reduce the impact of arsenic exposure on health.
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Crown structure and growth efficiency of red spruce in uneven-aged, mixed-species stands in Maine
Douglas A. Maguire; John C. Brissette; Lianhong. Gu
1998-01-01
Several hypotheses about the relationships among individual tree growth, tree leaf area, and relative tree size or position were tested with red spruce (Picea rubens Sarg.) growing in uneven-aged, mixed-species forests of south-central Maine, U.S.A. Based on data from 65 sample trees, predictive models were developed to (i)...
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ERIC Educational Resources Information Center
Fernald, Anne; Marchman, Virginia A.
2012-01-01
Using online measures of familiar word recognition in the looking-while-listening procedure, this prospective longitudinal study revealed robust links between processing efficiency and vocabulary growth from 18 to 30 months in children classified as typically developing (n = 46) and as "late talkers" (n = 36) at 18 months. Those late talkers who…
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USDA-ARS?s Scientific Manuscript database
Residual feed intake (RFI) is the amount by which the observed and predicted feed intakes differ, given growth and maintenance requirements of an individual animal. In purebred Yorkshire pigs, divergent selection for increased (Low RFI) and decreased (High RFI) feed efficiency was carried out over 1...
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Idiosyncratic species effects confound size-based predictions of responses to climate change.
Twomey, Marion; Brodte, Eva; Jacob, Ute; Brose, Ulrich; Crowe, Tasman P; Emmerson, Mark C
2012-11-05
Understanding and predicting the consequences of warming for complex ecosystems and indeed individual species remains a major ecological challenge. Here, we investigated the effect of increased seawater temperatures on the metabolic and consumption rates of five distinct marine species. The experimental species reflected different trophic positions within a typical benthic East Atlantic food web, and included a herbivorous gastropod, a scavenging decapod, a predatory echinoderm, a decapod and a benthic-feeding fish. We examined the metabolism-body mass and consumption-body mass scaling for each species, and assessed changes in their consumption efficiencies. Our results indicate that body mass and temperature effects on metabolism were inconsistent across species and that some species were unable to meet metabolic demand at higher temperatures, thus highlighting the vulnerability of individual species to warming. While body size explains a large proportion of the variation in species' physiological responses to warming, it is clear that idiosyncratic species responses, irrespective of body size, complicate predictions of population and ecosystem level response to future scenarios of climate change.
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Phuong, H N; Martin, O; de Boer, I J M; Ingvartsen, K L; Schmidely, Ph; Friggens, N C
2015-01-01
This study explored the ability of an existing lifetime nutrient partitioning model for simulating individual variability in genetic potentials of dairy cows. Generally, the model assumes a universal trajectory of dynamic partitioning of priority between life functions and genetic scaling parameters are then incorporated to simulate individual difference in performance. Data of 102 cows including 180 lactations of 3 breeds: Danish Red, Danish Holstein, and Jersey, which were completely independent from those used previously for model development, were used. Individual cow performance records through sequential lactations were used to derive genetic scaling parameters for each animal by calibrating the model to achieve best fit, cow by cow. The model was able to fit individual curves of body weight, and milk fat, milk protein, and milk lactose concentrations with a high degree of accuracy. Daily milk yield and dry matter intake were satisfactorily predicted in early and mid lactation, but underpredictions were found in late lactation. Breeds and parities did not significantly affect the prediction accuracy. The means of genetic scaling parameters between Danish Red and Danish Holstein were similar but significantly different from those of Jersey. The extent of correlations between the genetic scaling parameters was consistent with that reported in the literature. In conclusion, this model is of value as a tool to derive estimates of genetic potentials of milk yield, milk composition, body reserve usage, and growth for different genotypes of cow. Moreover, it can be used to separate genetic variability in performance between individual cows from environmental noise. The model enables simulation of the effects of a genetic selection strategy on lifetime efficiency of individual cows, which has a main advantage of including the rearing costs, and thus, can be used to explore the impact of future selection on animal performance and efficiency. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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Conomos, Matthew P; Miller, Michael B; Thornton, Timothy A
2015-05-01
Population structure inference with genetic data has been motivated by a variety of applications in population genetics and genetic association studies. Several approaches have been proposed for the identification of genetic ancestry differences in samples where study participants are assumed to be unrelated, including principal components analysis (PCA), multidimensional scaling (MDS), and model-based methods for proportional ancestry estimation. Many genetic studies, however, include individuals with some degree of relatedness, and existing methods for inferring genetic ancestry fail in related samples. We present a method, PC-AiR, for robust population structure inference in the presence of known or cryptic relatedness. PC-AiR utilizes genome-screen data and an efficient algorithm to identify a diverse subset of unrelated individuals that is representative of all ancestries in the sample. The PC-AiR method directly performs PCA on the identified ancestry representative subset and then predicts components of variation for all remaining individuals based on genetic similarities. In simulation studies and in applications to real data from Phase III of the HapMap Project, we demonstrate that PC-AiR provides a substantial improvement over existing approaches for population structure inference in related samples. We also demonstrate significant efficiency gains, where a single axis of variation from PC-AiR provides better prediction of ancestry in a variety of structure settings than using 10 (or more) components of variation from widely used PCA and MDS approaches. Finally, we illustrate that PC-AiR can provide improved population stratification correction over existing methods in genetic association studies with population structure and relatedness. © 2015 WILEY PERIODICALS, INC.
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NASA Technical Reports Server (NTRS)
Rockey, D. E.
1979-01-01
A general approach is developed for predicting the power output of a concentrator enhanced photovoltaic space array. A ray trace routine determines the concentrator intensity arriving at each solar cell. An iterative calculation determines the cell's operating temperature since cell temperature and cell efficiency are functions of one another. The end result of the iterative calculation is that the individual cell's power output is determined as a function of temperature and intensity. Circuit output is predicted by combining the individual cell outputs using the single diode model of a solar cell. Concentrated array characteristics such as uniformity of intensity and operating temperature at various points across the array are examined using computer modeling techniques. An illustrative example is given showing how the output of an array can be enhanced using solar concentration techniques.
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Wang, Zhiqiang; Ji, Mingfei; Deng, Jianming; Milne, Richard I; Ran, Jinzhi; Zhang, Qiang; Fan, Zhexuan; Zhang, Xiaowei; Li, Jiangtao; Huang, Heng; Cheng, Dongliang; Niklas, Karl J
2015-06-01
Simultaneous and accurate measurements of whole-plant instantaneous carbon-use efficiency (ICUE) and annual total carbon-use efficiency (TCUE) are difficult to make, especially for trees. One usually estimates ICUE based on the net photosynthetic rate or the assumed proportional relationship between growth efficiency and ICUE. However, thus far, protocols for easily estimating annual TCUE remain problematic. Here, we present a theoretical framework (based on the metabolic scaling theory) to predict whole-plant annual TCUE by directly measuring instantaneous net photosynthetic and respiratory rates. This framework makes four predictions, which were evaluated empirically using seedlings of nine Picea taxa: (i) the flux rates of CO(2) and energy will scale isometrically as a function of plant size, (ii) whole-plant net and gross photosynthetic rates and the net primary productivity will scale isometrically with respect to total leaf mass, (iii) these scaling relationships will be independent of ambient temperature and humidity fluctuations (as measured within an experimental chamber) regardless of the instantaneous net photosynthetic rate or dark respiratory rate, or overall growth rate and (iv) TCUE will scale isometrically with respect to instantaneous efficiency of carbon use (i.e., the latter can be used to predict the former) across diverse species. These predictions were experimentally verified. We also found that the ranking of the nine taxa based on net photosynthetic rates differed from ranking based on either ICUE or TCUE. In addition, the absolute values of ICUE and TCUE significantly differed among the nine taxa, with both ICUE and temperature-corrected ICUE being highest for Picea abies and lowest for Picea schrenkiana. Nevertheless, the data are consistent with the predictions of our general theoretical framework, which can be used to access annual carbon-use efficiency of different species at the level of an individual plant based on simple, direct measurements. Moreover, we believe that our approach provides a way to cope with the complexities of different ecosystems, provided that sufficient measurements are taken to calibrate our approach to that of the system being studied. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Dai, Wenrui; Xiong, Hongkai; Jiang, Xiaoqian; Chen, Chang Wen
2014-01-01
This paper proposes a novel model on intra coding for High Efficiency Video Coding (HEVC), which simultaneously predicts blocks of pixels with optimal rate distortion. It utilizes the spatial statistical correlation for the optimal prediction based on 2-D contexts, in addition to formulating the data-driven structural interdependences to make the prediction error coherent with the probability distribution, which is desirable for successful transform and coding. The structured set prediction model incorporates a max-margin Markov network (M3N) to regulate and optimize multiple block predictions. The model parameters are learned by discriminating the actual pixel value from other possible estimates to maximize the margin (i.e., decision boundary bandwidth). Compared to existing methods that focus on minimizing prediction error, the M3N-based model adaptively maintains the coherence for a set of predictions. Specifically, the proposed model concurrently optimizes a set of predictions by associating the loss for individual blocks to the joint distribution of succeeding discrete cosine transform coefficients. When the sample size grows, the prediction error is asymptotically upper bounded by the training error under the decomposable loss function. As an internal step, we optimize the underlying Markov network structure to find states that achieve the maximal energy using expectation propagation. For validation, we integrate the proposed model into HEVC for optimal mode selection on rate-distortion optimization. The proposed prediction model obtains up to 2.85% bit rate reduction and achieves better visual quality in comparison to the HEVC intra coding. PMID:25505829
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Elevated depressive symptoms enhance reflexive but not reflective auditory category learning.
Maddox, W Todd; Chandrasekaran, Bharath; Smayda, Kirsten; Yi, Han-Gyol; Koslov, Seth; Beevers, Christopher G
2014-09-01
In vision an extensive literature supports the existence of competitive dual-processing systems of category learning that are grounded in neuroscience and are partially-dissociable. The reflective system is prefrontally-mediated and uses working memory and executive attention to develop and test rules for classifying in an explicit fashion. The reflexive system is striatally-mediated and operates by implicitly associating perception with actions that lead to reinforcement. Although categorization is fundamental to auditory processing, little is known about the learning systems that mediate auditory categorization and even less is known about the effects of individual difference in the relative efficiency of the two learning systems. Previous studies have shown that individuals with elevated depressive symptoms show deficits in reflective processing. We exploit this finding to test critical predictions of the dual-learning systems model in audition. Specifically, we examine the extent to which the two systems are dissociable and competitive. We predicted that elevated depressive symptoms would lead to reflective-optimal learning deficits but reflexive-optimal learning advantages. Because natural speech category learning is reflexive in nature, we made the prediction that elevated depressive symptoms would lead to superior speech learning. In support of our predictions, individuals with elevated depressive symptoms showed a deficit in reflective-optimal auditory category learning, but an advantage in reflexive-optimal auditory category learning. In addition, individuals with elevated depressive symptoms showed an advantage in learning a non-native speech category structure. Computational modeling suggested that the elevated depressive symptom advantage was due to faster, more accurate, and more frequent use of reflexive category learning strategies in individuals with elevated depressive symptoms. The implications of this work for dual-process approach to auditory learning and depression are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Elevated Depressive Symptoms Enhance Reflexive but not Reflective Auditory Category Learning
Maddox, W. Todd; Chandrasekaran, Bharath; Smayda, Kirsten; Yi, Han-Gyol; Koslov, Seth; Beevers, Christopher G.
2014-01-01
In vision an extensive literature supports the existence of competitive dual-processing systems of category learning that are grounded in neuroscience and are partially-dissociable. The reflective system is prefrontally-mediated and uses working memory and executive attention to develop and test rules for classifying in an explicit fashion. The reflexive system is striatally-mediated and operates by implicitly associating perception with actions that lead to reinforcement. Although categorization is fundamental to auditory processing, little is known about the learning systems that mediate auditory categorization and even less is known about the effects of individual difference in the relative efficiency of the two learning systems. Previous studies have shown that individuals with elevated depressive symptoms show deficits in reflective processing. We exploit this finding to test critical predictions of the dual-learning systems model in audition. Specifically, we examine the extent to which the two systems are dissociable and competitive. We predicted that elevated depressive symptoms would lead to reflective-optimal learning deficits but reflexive-optimal learning advantages. Because natural speech category learning is reflexive in nature, we made the prediction that elevated depressive symptoms would lead to superior speech learning. In support of our predictions, individuals with elevated depressive symptoms showed a deficit in reflective-optimal auditory category learning, but an advantage in reflexive-optimal auditory category learning. In addition, individuals with elevated depressive symptoms showed an advantage in learning a non-native speech category structure. Computational modeling suggested that the elevated depressive symptom advantage was due to faster, more accurate, and more frequent use of reflexive category learning strategies in individuals with elevated depressive symptoms. The implications of this work for dual-process approach to auditory learning and depression are discussed. PMID:25041936
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Poorolajal, Jalal; Akbari, Mohammad Esmaeil; Ziaee, Fatane; Karami, Manoochehr; Ghoncheh, Mahshid
2017-05-15
The breast cancer screening (BCS) chart is suggested as a basic and preliminary tool to improve efficiency of screening mammography. We conducted this case-control study in 2016 and enrolled 1422 women aged 30-75 years, including 506 women with breast cancer (cases) and 916 women without breast cancer (controls). We developed the BCS chart using a multiple logistic regression analysis. We combined the risks of breast cancer to predict the individual risk of breast cancer. Then, we stratified and colored the predicted risk probabilities as follows: <05% (green), 05-09% (yellow), 10-14% (orange), 15-19% (red), 20-24% (brown) and ≥25% (black). The BCS chart provides the risk probability of breast cancer, based on age, body mass index, late menopause, having a benign breast disease and a positive family history of breast cancer among the first-degree or the second/third-degree relatives. According to this chart, an individual can be classified in a category of low risk (green), medium risk (yellow and orange), high risk (red and brown) and very high risk (black) for breast cancer. This chart is a flexible and easy to use tool that can detect high-risk subjects and make the screening program more efficient and productive. © The Author 2017. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
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Fitting neuron models to spike trains.
Rossant, Cyrille; Goodman, Dan F M; Fontaine, Bertrand; Platkiewicz, Jonathan; Magnusson, Anna K; Brette, Romain
2011-01-01
Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input-output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model.
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Visuoperceptual repetition priming and progression of parkinsonian signs in aging
Fleischman, Debra A.; Buchman, Aron S.; Bienias, Julia L.; Bennett, David A.
2009-01-01
Parkinsonian signs in older persons are associated with numerous adverse health outcomes, however there is limited information about factors which predict progression of these signs. Using generalized linear models, we examined the association between efficiency in visuoperceptual and conceptual processing, measured by repetition priming, and rate of change in parkinsonian signs in a large sample of older persons without cognitive impairment or Parkinson’s disease. Subjects with better visuoperceptual priming, measured by threshold word-identification and word-stem completion, at study baseline, progressed more slowly during follow-up of up to 11 years. Conceptual priming was not associated with change in parkinsonian signs. The findings demonstrate that individual differences in visuoperceptual efficiency, measured by repetition priming, occur in older persons without cognitive impairment and predict important changes in motor function. Reduced visuoperceptual priming in aging may be an early signal of vulnerability in a corticostrial circuit that contributes to sensorimotor integration. PMID:17709154
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Color vision predicts processing modes of goal activation during action cascading.
Jongkees, Bryant J; Steenbergen, Laura; Colzato, Lorenza S
2017-09-01
One of the most important functions of cognitive control is action cascading: the ability to cope with multiple response options when confronted with various task goals. A recent study implicates a key role for dopamine (DA) in this process, suggesting higher D1 efficiency shifts the action cascading strategy toward a more serial processing mode, whereas higher D2 efficiency promotes a shift in the opposite direction by inducing a more parallel processing mode (Stock, Arning, Epplen, & Beste, 2014). Given that DA is found in high concentration in the retina and modulation of retinal DA release displays characteristics of D2-receptors (Peters, Schweibold, Przuntek, & Müller, 2000), color vision discrimination might serve as an index of D2 efficiency. We used color discrimination, assessed with the Lanthony Desaturated Panel D-15 test, to predict individual differences (N = 85) in a stop-change paradigm that provides a well-established measure of action cascading. In this task it is possible to calculate an individual slope value for each participant that estimates the degree of overlap in task goal activation. When the stopping process of a previous task goal has not finished at the time the change process toward a new task goal is initiated (parallel processing), the slope value becomes steeper. In case of less overlap (more serial processing), the slope value becomes flatter. As expected, participants showing better color vision were more prone to activate goals in a parallel manner as indicated by a steeper slope. Our findings suggest that color vision might represent a predictor of D2 efficiency and the predisposed processing mode of goal activation during action cascading. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Pravosudov, Vladimir V; Mendoza, Sally P; Clayton, Nicola S
2003-08-01
It has been hypothesized that in avian social groups subordinate individuals should maintain more energy reserves than dominants, as an insurance against increased perceived risk of starvation. Subordinates might also have elevated baseline corticosterone levels because corticosterone is known to facilitate fattening in birds. Recent experiments showed that moderately elevated corticosterone levels resulting from unpredictable food supply are correlated with enhanced cache retrieval efficiency and more accurate performance on a spatial memory task. Given the correlation between corticosterone and memory, a further prediction is that subordinates might be more efficient at cache retrieval and show more accurate performance on spatial memory tasks. We tested these predictions in dominant-subordinate pairs of mountain chickadees (Poecile gambeli). Each pair was housed in the same cage but caching behavior was tested individually in an adjacent aviary to avoid the confounding effects of small spaces in which birds could unnaturally and directly influence each other's behavior. In sharp contrast to our hypothesis, we found that subordinate chickadees cached less food, showed less efficient cache retrieval, and performed significantly worse on the spatial memory task than dominants. Although the behavioral differences could have resulted from social stress of subordination, and dominant birds reached significantly higher levels of corticosterone during their response to acute stress compared to subordinates, there were no significant differences between dominants and subordinates in baseline levels or in the pattern of adrenocortical stress response. We find no evidence, therefore, to support the hypothesis that subordinate mountain chickadees maintain elevated baseline corticosterone levels whereas lower caching rates and inferior cache retrieval efficiency might contribute to reduced survival of subordinates commonly found in food-caching parids.
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An experimental validation of genomic selection in octoploid strawberry
Gezan, Salvador A; Osorio, Luis F; Verma, Sujeet; Whitaker, Vance M
2017-01-01
The primary goal of genomic selection is to increase genetic gains for complex traits by predicting performance of individuals for which phenotypic data are not available. The objective of this study was to experimentally evaluate the potential of genomic selection in strawberry breeding and to define a strategy for its implementation. Four clonally replicated field trials, two in each of 2 years comprised of a total of 1628 individuals, were established in 2013–2014 and 2014–2015. Five complex yield and fruit quality traits with moderate to low heritability were assessed in each trial. High-density genotyping was performed with the Affymetrix Axiom IStraw90 single-nucleotide polymorphism array, and 17 479 polymorphic markers were chosen for analysis. Several methods were compared, including Genomic BLUP, Bayes B, Bayes C, Bayesian LASSO Regression, Bayesian Ridge Regression and Reproducing Kernel Hilbert Spaces. Cross-validation within training populations resulted in higher values than for true validations across trials. For true validations, Bayes B gave the highest predictive abilities on average and also the highest selection efficiencies, particularly for yield traits that were the lowest heritability traits. Selection efficiencies using Bayes B for parent selection ranged from 74% for average fruit weight to 34% for early marketable yield. A breeding strategy is proposed in which advanced selection trials are utilized as training populations and in which genomic selection can reduce the breeding cycle from 3 to 2 years for a subset of untested parents based on their predicted genomic breeding values. PMID:28090334
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NASA Technical Reports Server (NTRS)
Whitney, W. J.; Behning, F. P.; Moffitt, T. P.; Hotz, G. M.
1980-01-01
The stage group performance of a 4 1/2 stage turbine with an average stage loading factor of 4.66 and high specific work output was determined in cold air at design equivalent speed. The four stage turbine configuration produced design equivalent work output with an efficiency of 0.856; a barely discernible difference from the 0.855 obtained for the complete 4 1/2 stage turbine in a previous investigation. The turbine was designed and the procedure embodied the following design features: (1) controlled vortex flow, (2) tailored radial work distribution, and (3) control of the location of the boundary-layer transition point on the airfoil suction surface. The efficiency forecast for the 4 1/2 stage turbine was 0.886, and the value predicted using a reference method was 0.862. The stage group performance results were used to determine the individual stage efficiencies for the condition at which design 4 1/2 stage work output was obtained. The efficiencies of stages one and four were about 0.020 lower than the predicted value, that of stage two was 0.014 lower, and that of stage three was about equal to the predicted value. Thus all the stages operated reasonably close to their expected performance levels, and the overall (4 1/2 stage) performance was not degraded by any particularly inefficient component.
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Johannesdottir, Fjola; Allaire, Brett; Bouxsein, Mary L
2018-05-30
This review critiques the ability of CT-based methods to predict incident hip and vertebral fractures. CT-based techniques with concurrent calibration all show strong associations with incident hip and vertebral fracture, predicting hip and vertebral fractures as well as, and sometimes better than, dual-energy X-ray absorptiometry areal biomass density (DXA aBMD). There is growing evidence for use of routine CT scans for bone health assessment. CT-based techniques provide a robust approach for osteoporosis diagnosis and fracture prediction. It remains to be seen if further technical advances will improve fracture prediction compared to DXA aBMD. Future work should include more standardization in CT analyses, establishment of treatment intervention thresholds, and more studies to determine whether routine CT scans can be efficiently used to expand the number of individuals who undergo evaluation for fracture risk.
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Variable context Markov chains for HIV protease cleavage site prediction.
Oğul, Hasan
2009-06-01
Deciphering the knowledge of HIV protease specificity and developing computational tools for detecting its cleavage sites in protein polypeptide chain are very desirable for designing efficient and specific chemical inhibitors to prevent acquired immunodeficiency syndrome. In this study, we developed a generative model based on a generalization of variable order Markov chains (VOMC) for peptide sequences and adapted the model for prediction of their cleavability by certain proteases. The new method, called variable context Markov chains (VCMC), attempts to identify the context equivalence based on the evolutionary similarities between individual amino acids. It was applied for HIV-1 protease cleavage site prediction problem and shown to outperform existing methods in terms of prediction accuracy on a common dataset. In general, the method is a promising tool for prediction of cleavage sites of all proteases and encouraged to be used for any kind of peptide classification problem as well.
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Supekar, Kaustubh; Swigart, Anna G.; Tenison, Caitlin; Jolles, Dietsje D.; Rosenberg-Lee, Miriam; Fuchs, Lynn; Menon, Vinod
2013-01-01
Now, more than ever, the ability to acquire mathematical skills efficiently is critical for academic and professional success, yet little is known about the behavioral and neural mechanisms that drive some children to acquire these skills faster than others. Here we investigate the behavioral and neural predictors of individual differences in arithmetic skill acquisition in response to 8-wk of one-to-one math tutoring. Twenty-four children in grade 3 (ages 8–9 y), a critical period for acquisition of basic mathematical skills, underwent structural and resting-state functional MRI scans pretutoring. A significant shift in arithmetic problem-solving strategies from counting to fact retrieval was observed with tutoring. Notably, the speed and accuracy of arithmetic problem solving increased with tutoring, with some children improving significantly more than others. Next, we examined whether pretutoring behavioral and brain measures could predict individual differences in arithmetic performance improvements with tutoring. No behavioral measures, including intelligence quotient, working memory, or mathematical abilities, predicted performance improvements. In contrast, pretutoring hippocampal volume predicted performance improvements. Furthermore, pretutoring intrinsic functional connectivity of the hippocampus with dorsolateral and ventrolateral prefrontal cortices and the basal ganglia also predicted performance improvements. Our findings provide evidence that individual differences in morphometry and connectivity of brain regions associated with learning and memory, and not regions typically involved in arithmetic processing, are strong predictors of responsiveness to math tutoring in children. More generally, our study suggests that quantitative measures of brain structure and intrinsic brain organization can provide a more sensitive marker of skill acquisition than behavioral measures. PMID:23630286
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Supekar, Kaustubh; Swigart, Anna G; Tenison, Caitlin; Jolles, Dietsje D; Rosenberg-Lee, Miriam; Fuchs, Lynn; Menon, Vinod
2013-05-14
Now, more than ever, the ability to acquire mathematical skills efficiently is critical for academic and professional success, yet little is known about the behavioral and neural mechanisms that drive some children to acquire these skills faster than others. Here we investigate the behavioral and neural predictors of individual differences in arithmetic skill acquisition in response to 8-wk of one-to-one math tutoring. Twenty-four children in grade 3 (ages 8-9 y), a critical period for acquisition of basic mathematical skills, underwent structural and resting-state functional MRI scans pretutoring. A significant shift in arithmetic problem-solving strategies from counting to fact retrieval was observed with tutoring. Notably, the speed and accuracy of arithmetic problem solving increased with tutoring, with some children improving significantly more than others. Next, we examined whether pretutoring behavioral and brain measures could predict individual differences in arithmetic performance improvements with tutoring. No behavioral measures, including intelligence quotient, working memory, or mathematical abilities, predicted performance improvements. In contrast, pretutoring hippocampal volume predicted performance improvements. Furthermore, pretutoring intrinsic functional connectivity of the hippocampus with dorsolateral and ventrolateral prefrontal cortices and the basal ganglia also predicted performance improvements. Our findings provide evidence that individual differences in morphometry and connectivity of brain regions associated with learning and memory, and not regions typically involved in arithmetic processing, are strong predictors of responsiveness to math tutoring in children. More generally, our study suggests that quantitative measures of brain structure and intrinsic brain organization can provide a more sensitive marker of skill acquisition than behavioral measures.
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Lee, Jeongmi; Geng, Joy J
2017-02-01
The efficiency of finding an object in a crowded environment depends largely on the similarity of nontargets to the search target. Models of attention theorize that the similarity is determined by representations stored within an "attentional template" held in working memory. However, the degree to which the contents of the attentional template are individually unique and where those idiosyncratic representations are encoded in the brain are unknown. We investigated this problem using representational similarity analysis of human fMRI data to measure the common and idiosyncratic representations of famous face morphs during an identity categorization task; data from the categorization task were then used to predict performance on a separate identity search task. We hypothesized that the idiosyncratic categorical representations of the continuous face morphs would predict their distractability when searching for each target identity. The results identified that patterns of activation in the lateral prefrontal cortex (LPFC) as well as in face-selective areas in the ventral temporal cortex were highly correlated with the patterns of behavioral categorization of face morphs and search performance that were common across subjects. However, the individually unique components of the categorization behavior were reliably decoded only in right LPFC. Moreover, the neural pattern in right LPFC successfully predicted idiosyncratic variability in search performance, such that reaction times were longer when distractors had a higher probability of being categorized as the target identity. These results suggest that the prefrontal cortex encodes individually unique components of categorical representations that are also present in attentional templates for target search. Everyone's perception of the world is uniquely shaped by personal experiences and preferences. Using functional MRI, we show that individual differences in the categorization of face morphs between two identities could be decoded from the prefrontal cortex and the ventral temporal cortex. Moreover, the individually unique representations in prefrontal cortex predicted idiosyncratic variability in attentional performance when looking for each identity in the "crowd" of another morphed face in a separate search task. Our results reveal that the representation of task-related information in prefrontal cortex is individually unique and preserved across categorization and search performance. This demonstrates the possibility of predicting individual behaviors across tasks with patterns of brain activity. Copyright © 2017 the authors 0270-6474/17/371257-12$15.00/0.
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Steffensen, Jon Lund; Dufault-Thompson, Keith; Zhang, Ying
2018-01-01
The metabolism of individual organisms and biological communities can be viewed as a network of metabolites connected to each other through chemical reactions. In metabolic networks, chemical reactions transform reactants into products, thereby transferring elements between these metabolites. Knowledge of how elements are transferred through reactant/product pairs allows for the identification of primary compound connections through a metabolic network. However, such information is not readily available and is often challenging to obtain for large reaction databases or genome-scale metabolic models. In this study, a new algorithm was developed for automatically predicting the element-transferring reactant/product pairs using the limited information available in the standard representation of metabolic networks. The algorithm demonstrated high efficiency in analyzing large datasets and provided accurate predictions when benchmarked with manually curated data. Applying the algorithm to the visualization of metabolic networks highlighted pathways of primary reactant/product connections and provided an organized view of element-transferring biochemical transformations. The algorithm was implemented as a new function in the open source software package PSAMM in the release v0.30 (https://zhanglab.github.io/psamm/).
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Assessing Predictive Properties of Genome-Wide Selection in Soybeans
Xavier, Alencar; Muir, William M.; Rainey, Katy Martin
2016-01-01
Many economically important traits in plant breeding have low heritability or are difficult to measure. For these traits, genomic selection has attractive features and may boost genetic gains. Our goal was to evaluate alternative scenarios to implement genomic selection for yield components in soybean (Glycine max L. merr). We used a nested association panel with cross validation to evaluate the impacts of training population size, genotyping density, and prediction model on the accuracy of genomic prediction. Our results indicate that training population size was the factor most relevant to improvement in genome-wide prediction, with greatest improvement observed in training sets up to 2000 individuals. We discuss assumptions that influence the choice of the prediction model. Although alternative models had minor impacts on prediction accuracy, the most robust prediction model was the combination of reproducing kernel Hilbert space regression and BayesB. Higher genotyping density marginally improved accuracy. Our study finds that breeding programs seeking efficient genomic selection in soybeans would best allocate resources by investing in a representative training set. PMID:27317786
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Poisson Mixture Regression Models for Heart Disease Prediction.
Mufudza, Chipo; Erol, Hamza
2016-01-01
Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.
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Poisson Mixture Regression Models for Heart Disease Prediction
Erol, Hamza
2016-01-01
Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611
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Nonuniversal star formation efficiency in turbulent ISM
Semenov, Vadim A.; Kravtsov, Andrey V.; Gnedin, Nickolay Y.
2016-07-29
Here, we present a study of a star formation prescription in which star formation efficiency depends on local gas density and turbulent velocity dispersion, as suggested by direct simulations of SF in turbulent giant molecular clouds (GMCs). We test the model using a simulation of an isolated Milky Way-sized galaxy with a self-consistent treatment of turbulence on unresolved scales. We show that this prescription predicts a wide variation of local star formation efficiency per free-fall time,more » $$\\epsilon_{\\rm ff} \\sim 0.1 - 10\\%$$, and gas depletion time, $$t_{\\rm dep} \\sim 0.1 - 10$$ Gyr. In addition, it predicts an effective density threshold for star formation due to suppression of $$\\epsilon_{\\rm ff}$$ in warm diffuse gas stabilized by thermal pressure. We show that the model predicts star formation rates in agreement with observations from the scales of individual star-forming regions to the kiloparsec scales. This agreement is non-trivial, as the model was not tuned in any way and the predicted star formation rates on all scales are determined by the distribution of the GMC-scale densities and turbulent velocities $$\\sigma$$ in the cold gas within the galaxy, which is shaped by galactic dynamics. The broad agreement of the star formation prescription calibrated in the GMC-scale simulations with observations, both gives credence to such simulations and promises to put star formation modeling in galaxy formation simulations on a much firmer theoretical footing.« less
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Prediction of human adaptation and performance in underwater environments.
Colodro Plaza, Joaquín; Garcés de los Fayos Ruiz, Enrique J; López García, Juan J; Colodro Conde, Lucía
2014-01-01
Environmental stressors require the professional diver to undergo a complex process of psychophysiological adaptation in order to overcome the demands of an extreme environment and carry out effective and efficient work under water. The influence of cognitive and personality traits in predicting underwater performance and adaptation has been a common concern for diving psychology, and definitive conclusions have not been reached. In this ex post facto study, psychological and academic data were analyzed from a large sample of personnel participating in scuba diving courses carried out in the Spanish Navy Diving Center. In order to verify the relevance of individual differences in adaptation to a hostile environment, we evaluated the predictive validity of general mental ability and personality traits with regression techniques. The data indicated the existence of psychological variables that can predict the performance ( R² = .30, p <.001) and adaptation ( R²(N) = .51, p <.001) of divers in underwater environment. These findings support the hypothesis that individual differences are related to the probability of successful adaptation and effective performance in professional diving. These results also verify that dispositional traits play a decisive role in diving training and are significant factors in divers' psychological fitness.
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Pathway index models for construction of patient-specific risk profiles.
Eng, Kevin H; Wang, Sijian; Bradley, William H; Rader, Janet S; Kendziorski, Christina
2013-04-30
Statistical methods for variable selection, prediction, and classification have proven extremely useful in moving personalized genomics medicine forward, in particular, leading to a number of genomic-based assays now in clinical use for predicting cancer recurrence. Although invaluable in individual cases, the information provided by these assays is limited. Most often, a patient is classified into one of very few groups (e.g., recur or not), limiting the potential for truly personalized treatment. Furthermore, although these assays provide information on which individuals are at most risk (e.g., those for which recurrence is predicted), they provide no information on the aberrant biological pathways that give rise to the increased risk. We have developed an approach to address these limitations. The approach models a time-to-event outcome as a function of known biological pathways, identifies important genomic aberrations, and provides pathway-based patient-specific assessments of risk. As we demonstrate in a study of ovarian cancer from The Cancer Genome Atlas project, the patient-specific risk profiles are powerful and efficient characterizations useful in addressing a number of questions related to identifying informative patient subtypes and predicting survival. Copyright © 2012 John Wiley & Sons, Ltd.
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Pu, Xia; Ye, Yuanqing; Wu, Xifeng
2014-01-01
Despite the advances made in cancer management over the past few decades, improvements in cancer diagnosis and prognosis are still poor, highlighting the need for individualized strategies. Toward this goal, risk prediction models and molecular diagnostic tools have been developed, tailoring each step of risk assessment from diagnosis to treatment and clinical outcomes based on the individual's clinical, epidemiological, and molecular profiles. These approaches hold increasing promise for delivering a new paradigm to maximize the efficiency of cancer surveillance and efficacy of treatment. However, they require stringent study design, methodology development, comprehensive assessment of biomarkers and risk factors, and extensive validation to ensure their overall usefulness for clinical translation. In the current study, the authors conducted a systematic review using breast cancer as an example and provide general guidelines for risk prediction models and molecular diagnostic tools, including development, assessment, and validation. © 2013 American Cancer Society.
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Real-time individualization of the unified model of performance.
Liu, Jianbo; Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Balkin, Thomas J; Reifman, Jaques
2017-12-01
Existing mathematical models for predicting neurobehavioural performance are not suited for mobile computing platforms because they cannot adapt model parameters automatically in real time to reflect individual differences in the effects of sleep loss. We used an extended Kalman filter to develop a computationally efficient algorithm that continually adapts the parameters of the recently developed Unified Model of Performance (UMP) to an individual. The algorithm accomplishes this in real time as new performance data for the individual become available. We assessed the algorithm's performance by simulating real-time model individualization for 18 subjects subjected to 64 h of total sleep deprivation (TSD) and 7 days of chronic sleep restriction (CSR) with 3 h of time in bed per night, using psychomotor vigilance task (PVT) data collected every 2 h during wakefulness. This UMP individualization process produced parameter estimates that progressively approached the solution produced by a post-hoc fitting of model parameters using all data. The minimum number of PVT measurements needed to individualize the model parameters depended upon the type of sleep-loss challenge, with ~30 required for TSD and ~70 for CSR. However, model individualization depended upon the overall duration of data collection, yielding increasingly accurate model parameters with greater number of days. Interestingly, reducing the PVT sampling frequency by a factor of two did not notably hamper model individualization. The proposed algorithm facilitates real-time learning of an individual's trait-like responses to sleep loss and enables the development of individualized performance prediction models for use in a mobile computing platform. © 2017 European Sleep Research Society.
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Mall, Jonathan T; Morey, Candice C; Wolff, Michael J; Lehnert, Franziska
2014-10-01
Selective attention and working memory capacity (WMC) are related constructs, but debate about the manner in which they are related remains active. One elegant explanation of variance in WMC is that the efficiency of filtering irrelevant information is the crucial determining factor, rather than differences in capacity per se. We examined this hypothesis by relating WMC (as measured by complex span tasks) to accuracy and eye movements during visual change detection tasks with different degrees of attentional filtering and allocation requirements. Our results did not indicate strong filtering differences between high- and low-WMC groups, and where differences were observed, they were counter to those predicted by the strongest attentional filtering hypothesis. Bayes factors indicated evidence favoring positive or null relationships between WMC and correct responses to unemphasized information, as well as between WMC and the time spent looking at unemphasized information. These findings are consistent with the hypothesis that individual differences in storage capacity, not only filtering efficiency, underlie individual differences in working memory.
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Body size, performance and fitness in galapagos marine iguanas.
Wikelski, Martin; Romero, L Michael
2003-07-01
Complex organismal traits such as body size are influenced by innumerable selective pressures, making the prediction of evolutionary trajectories for those traits difficult. A potentially powerful way to predict fitness in natural systems is to study the composite response of individuals in terms of performance measures, such as foraging or reproductive performance. Once key performance measures are identified in this top-down approach, we can determine the underlying physiological mechanisms and gain predictive power over long-term evolutionary processes. Here we use marine iguanas as a model system where body size differs by more than one order of magnitude between island populations. We identified foraging efficiency as the main performance measure that constrains body size. Mechanistically, foraging performance is determined by food pasture height and the thermal environment, influencing intake and digestion. Stress hormones may be a flexible way of influencing an individual's response to low-food situations that may be caused by high population density, famines, or anthropogenic disturbances like oil spills. Reproductive performance, on the other hand, increases with body size and is mediated by higher survival of larger hatchlings from larger females and increased mating success of larger males. Reproductive performance of males may be adjusted via plastic hormonal feedback mechanisms that allow individuals to assess their social rank annually within the current population size structure. When integrated, these data suggest that reproductive performance favors increased body size (influenced by reproductive hormones), with an overall limit imposed by foraging performance (influenced by stress hormones). Based on our mechanistic understanding of individual performances we predicted an evolutionary increase in maximum body size caused by global warming trends. We support this prediction using specimens collected during 1905. We also show in a common-garden experiment that body size may have a genetic component in iguanids. This 'performance paradigm' allows predictions about adaptive evolution in natural populations.
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Jawdy, Sara S.; Gunter, Lee E.; Engle, Nancy L.; ...
2016-04-26
Here, the biological function of the plant-microbiome system is the result of contributions from the host plant and microbiome members. In this work we study the function of a simplified community consisting of Pseudomonas and Burkholderia bacterial strains isolated from Populus hosts and inoculated on axenic Populus cutting in controlled laboratory conditions. Inoculation individually with either bacterial isolate increased root growth relative to uninoculated controls. Root area, photosynthetic efficiency, gene expression and metabolite expression data in individual and dual inoculated treatments indicate that the effects of these bacteria are unique and additive, suggesting that the function of a microbiome communitymore » may be predicted from the additive functions of the individual members.« less
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Granovsky, Yelena; Yarnitsky, David
2013-01-01
Experimental pain stimuli can be used to simulate patients’ pain experience. We review recent developments in psychophysical pain testing, focusing on the application of the dynamic tests—conditioned pain modulation (CPM) and temporal summation (TS). Typically, patients with clinical pain of various types express either less efficient CPM or enhanced TS, or both. These tests can be used in prediction of incidence of acquiring pain and of its intensity, as well as in assisting the correct choice of analgesic agents for individual patients. This can help to shorten the commonly occurring long and frustrating process of adjusting analgesic agents to the individual patients. We propose that evaluating pain modulation can serve as a step forward in individualizing pain medicine. PMID:24228167
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Granovsky, Yelena; Yarnitsky, David
2013-01-01
Experimental pain stimuli can be used to simulate patients' pain experience. We review recent developments in psychophysical pain testing, focusing on the application of the dynamic tests-conditioned pain modulation (CPM) and temporal summation (TS). Typically, patients with clinical pain of various types express either less efficient CPM or enhanced TS, or both. These tests can be used in prediction of incidence of acquiring pain and of its intensity, as well as in assisting the correct choice of analgesic agents for individual patients. This can help to shorten the commonly occurring long and frustrating process of adjusting analgesic agents to the individual patients. We propose that evaluating pain modulation can serve as a step forward in individualizing pain medicine.
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Matrix description of the complete topology of three-dimensional cells
Xue, Weihua; Wang, Hao; Liu, Guoquan; Meng, Li; Xiang, Song; Ma, Guang; Li, Wenwen
2016-01-01
A new, efficient method based on a series of matrices is introduced to completely describe the detailed topology of individual domains and their topology evolution in three-dimensional cellular structures. With this approach, we found a lot of new topological grain forms which are never reported before, i.e., there are total 8 and 32 topological forms for 7- and 8-faced grains respectively, other than the reported 7 and 27. This method is proved to be a practical tool to predict all possible grain forms efficiently. Moreover, a connectivity index of grain forms serves as a new convenient differentiator of different multicellular structures. PMID:27160500
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Forecasting influenza in Hong Kong with Google search queries and statistical model fusion.
Xu, Qinneng; Gel, Yulia R; Ramirez Ramirez, L Leticia; Nezafati, Kusha; Zhang, Qingpeng; Tsui, Kwok-Leung
2017-01-01
The objective of this study is to investigate predictive utility of online social media and web search queries, particularly, Google search data, to forecast new cases of influenza-like-illness (ILI) in general outpatient clinics (GOPC) in Hong Kong. To mitigate the impact of sensitivity to self-excitement (i.e., fickle media interest) and other artifacts of online social media data, in our approach we fuse multiple offline and online data sources. Four individual models: generalized linear model (GLM), least absolute shrinkage and selection operator (LASSO), autoregressive integrated moving average (ARIMA), and deep learning (DL) with Feedforward Neural Networks (FNN) are employed to forecast ILI-GOPC both one week and two weeks in advance. The covariates include Google search queries, meteorological data, and previously recorded offline ILI. To our knowledge, this is the first study that introduces deep learning methodology into surveillance of infectious diseases and investigates its predictive utility. Furthermore, to exploit the strength from each individual forecasting models, we use statistical model fusion, using Bayesian model averaging (BMA), which allows a systematic integration of multiple forecast scenarios. For each model, an adaptive approach is used to capture the recent relationship between ILI and covariates. DL with FNN appears to deliver the most competitive predictive performance among the four considered individual models. Combing all four models in a comprehensive BMA framework allows to further improve such predictive evaluation metrics as root mean squared error (RMSE) and mean absolute predictive error (MAPE). Nevertheless, DL with FNN remains the preferred method for predicting locations of influenza peaks. The proposed approach can be viewed a feasible alternative to forecast ILI in Hong Kong or other countries where ILI has no constant seasonal trend and influenza data resources are limited. The proposed methodology is easily tractable and computationally efficient.
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Efficiency turns the table on neural encoding, decoding and noise.
Deneve, Sophie; Chalk, Matthew
2016-04-01
Sensory neurons are usually described with an encoding model, for example, a function that predicts their response from the sensory stimulus using a receptive field (RF) or a tuning curve. However, central to theories of sensory processing is the notion of 'efficient coding'. We argue here that efficient coding implies a completely different neural coding strategy. Instead of a fixed encoding model, neural populations would be described by a fixed decoding model (i.e. a model reconstructing the stimulus from the neural responses). Because the population solves a global optimization problem, individual neurons are variable, but not noisy, and have no truly invariant tuning curve or receptive field. We review recent experimental evidence and implications for neural noise correlations, robustness and adaptation. Copyright © 2016. Published by Elsevier Ltd.
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Dávila-Romero, C; Hernández-Mocholí, M A; García-Hermoso, A
2015-03-01
This study is divided into three sequential stages: identification of fitness and game performance profiles (individual player performance), an assessment of the relationship between these profiles, and an assessment of the relationship between individual player profiles and team performance during play (in championship performance). The overall study sample comprised 525 (19 teams) female volleyball players aged 12-16 years and a subsample (N.=43) used to examine study aims one and two was selected from overall sample. Anthropometric, fitness and individual player performance (actual game) data were collected in the subsample. These data were analyzed through clustering methods, ANOVA and independence chi-square test. Then, we investigated whether the proportion of players with the highest individual player performance profile might predict a team's results in the championship. Cluster analysis identified three volleyball fitness profiles (high, medium, and low) and two individual player performance profiles (high and low). The results showed a relationship between both types of profile (fitness and individual player performance). Then, linear regression revealed a moderate relationship between the number of players with a high volleyball fitness profile and a team's results in the championship (R2=0.23). The current study findings may enable coaches and trainers to manage training programs more efficiently in order to obtain tailor-made training, identify volleyball-specific physical fitness training requirements and reach better results during competitions.
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Predicting Stroop Effect from Spontaneous Neuronal Activity: A Study of Regional Homogeneity
Liu, Congcong; Chen, Zhencai; Wang, Ting; Tang, Dandan; Hitchman, Glenn; Sun, Jiangzhou; Zhao, Xiaoyue; Wang, Lijun; Chen, Antao
2015-01-01
The Stroop effect is one of the most robust and well-studied phenomena in cognitive psychology and cognitive neuroscience. However, little is known about the relationship between intrinsic brain activity and the individual differences of this effect. In the present study, we explored this issue by examining whether resting-state functional magnetic resonance imaging (rs-fMRI) signals could predict individual differences in the Stroop effect of healthy individuals. A partial correlation analysis was calculated to examine the relationship between regional homogeneity (ReHo) and Stroop effect size, while controlling for age, sex, and framewise displacement (FD). The results showed positive correlations in the left inferior frontal gyrus (LIFG), the left insula, the ventral anterior cingulate cortex (vACC), and the medial frontal gyrus (MFG), and negative correlation in the left precentral gyrus (LPG). These results indicate the possible influences of the LIFG, the left insula, and the LPG on the efficiency of cognitive control, and demonstrate that the key nodes of default mode network (DMN) may be important in goal-directed behavior and/or mental effort during cognitive control tasks. PMID:25938442
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Resende, R T; Resende, M D V; Silva, F F; Azevedo, C F; Takahashi, E K; Silva-Junior, O B; Grattapaglia, D
2017-10-01
We report a genomic selection (GS) study of growth and wood quality traits in an outbred F 2 hybrid Eucalyptus population (n=768) using high-density single-nucleotide polymorphism (SNP) genotyping. Going beyond previous reports in forest trees, models were developed for different selection targets, namely, families, individuals within families and individuals across the entire population using a genomic model including dominance. To provide a more breeder-intelligible assessment of the performance of GS we calculated the expected response as the percentage gain over the population average expected genetic value (EGV) for different proportions of genomically selected individuals, using a rigorous cross-validation (CV) scheme that removed relatedness between training and validation sets. Predictive abilities (PAs) were 0.40-0.57 for individual selection and 0.56-0.75 for family selection. PAs under an additive+dominance model improved predictions by 5 to 14% for growth depending on the selection target, but no improvement was seen for wood traits. The good performance of GS with no relatedness in CV suggested that our average SNP density (~25 kb) captured some short-range linkage disequilibrium. Truncation GS successfully selected individuals with an average EGV significantly higher than the population average. Response to GS on a per year basis was ~100% more efficient than by phenotypic selection and more so with higher selection intensities. These results contribute further experimental data supporting the positive prospects of GS in forest trees. Because generation times are long, traits are complex and costs of DNA genotyping are plummeting, genomic prediction has good perspectives of adoption in tree breeding practice.
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Personalized Vehicle Energy Efficiency & Range Predictor/MyGreenCar
DOE Office of Scientific and Technical Information (OSTI.GOV)
SAXENA, SAMVEG
MyGreenCar provides users with the ability to predict the range capabilities, fuel economy, and operating costs for any vehicle for their individual driving patterns. Users launce the MyGreeCar mobile app on their smartphones to collect their driving patterns over any duration (e.g. serval days, weeks, months, etc) using a phones's locational capabilities. Using vehicle powertrain models for any user-specified vehicle type, MyGreenCar, calculates the component-level energy and power interactions for the chosen vehicle to predict several important quantities, including: 1. For Evs: Alleviating range anxiety 2. Comparing fuel economy, operating costs, and payback time across models and types.
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Experimental design and efficient parameter estimation in preclinical pharmacokinetic studies.
Ette, E I; Howie, C A; Kelman, A W; Whiting, B
1995-05-01
Monte Carlo simulation technique used to evaluate the effect of the arrangement of concentrations on the efficiency of estimation of population pharmacokinetic parameters in the preclinical setting is described. Although the simulations were restricted to the one compartment model with intravenous bolus input, they provide the basis of discussing some structural aspects involved in designing a destructive ("quantic") preclinical population pharmacokinetic study with a fixed sample size as is usually the case in such studies. The efficiency of parameter estimation obtained with sampling strategies based on the three and four time point designs were evaluated in terms of the percent prediction error, design number, individual and joint confidence intervals coverage for parameter estimates approaches, and correlation analysis. The data sets contained random terms for both inter- and residual intra-animal variability. The results showed that the typical population parameter estimates for clearance and volume were efficiently (accurately and precisely) estimated for both designs, while interanimal variability (the only random effect parameter that could be estimated) was inefficiently (inaccurately and imprecisely) estimated with most sampling schedules of the two designs. The exact location of the third and fourth time point for the three and four time point designs, respectively, was not critical to the efficiency of overall estimation of all population parameters of the model. However, some individual population pharmacokinetic parameters were sensitive to the location of these times.
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Early prediction of student goals and affect in narrative-centered learning environments
NASA Astrophysics Data System (ADS)
Lee, Sunyoung
Recent years have seen a growing recognition of the role of goal and affect recognition in intelligent tutoring systems. Goal recognition is the task of inferring users' goals from a sequence of observations of their actions. Because of the uncertainty inherent in every facet of human computer interaction, goal recognition is challenging, particularly in contexts in which users can perform many actions in any order, as is the case with intelligent tutoring systems. Affect recognition is the task of identifying the emotional state of a user from a variety of physical cues, which are produced in response to affective changes in the individual. Accurately recognizing student goals and affect states could contribute to more effective and motivating interactions in intelligent tutoring systems. By exploiting knowledge of student goals and affect states, intelligent tutoring systems can dynamically modify their behavior to better support individual students. To create effective interactions in intelligent tutoring systems, goal and affect recognition models should satisfy two key requirements. First, because incorrectly predicted goals and affect states could significantly diminish the effectiveness of interactive systems, goal and affect recognition models should provide accurate predictions of user goals and affect states. When observations of users' activities become available, recognizers should make accurate early" predictions. Second, goal and affect recognition models should be highly efficient so they can operate in real time. To address key issues, we present an inductive approach to recognizing student goals and affect states in intelligent tutoring systems by learning goals and affect recognition models. Our work focuses on goal and affect recognition in an important new class of intelligent tutoring systems, narrative-centered learning environments. We report the results of empirical studies of induced recognition models from observations of students' interactions in narrative-centered learning environments. Experimental results suggest that induced models can make accurate early predictions of student goals and affect states, and they are sufficiently efficient to meet the real-time performance requirements of interactive learning environments.
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Di Domenico, Stefano I; Rodrigo, Achala H; Ayaz, Hasan; Fournier, Marc A; Ruocco, Anthony C
2015-04-01
Research on the neural efficiency hypothesis of intelligence (NEH) has revealed that the brains of more intelligent individuals consume less energy when performing easy cognitive tasks but more energy when engaged in difficult mental operations. However, previous studies testing the NEH have relied on cognitive tasks that closely resemble psychometric tests of intelligence, potentially confounding efficiency during intelligence-test performance with neural efficiency per se. The present study sought to provide a novel test of the NEH by examining patterns of prefrontal activity while participants completed an experimental paradigm that is qualitatively distinct from the contents of psychometric tests of intelligence. Specifically, participants completed a personal decision-making task (e.g., which occupation would you prefer, dancer or chemist?) in which they made a series of forced choices according to their subjective preferences. The degree of decisional conflict (i.e., choice difficulty) between the available response options was manipulated on the basis of participants' unique preference ratings for the target stimuli, which were obtained prior to scanning. Evoked oxygenation of the prefrontal cortex was measured using 16-channel continuous-wave functional near-infrared spectroscopy. Consistent with the NEH, intelligence predicted decreased activation of the right inferior frontal gyrus (IFG) during low-conflict situations and increased activation of the right-IFG during high-conflict situations. This pattern of right-IFG activity among more intelligent individuals was complemented by faster reaction times in high-conflict situations. These results provide new support for the NEH and suggest that the neural efficiency of more intelligent individuals generalizes to the performance of cognitive tasks that are distinct from intelligence tests. Copyright © 2015 Elsevier Inc. All rights reserved.
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Dopamine Modulates Adaptive Prediction Error Coding in the Human Midbrain and Striatum.
Diederen, Kelly M J; Ziauddeen, Hisham; Vestergaard, Martin D; Spencer, Tom; Schultz, Wolfram; Fletcher, Paul C
2017-02-15
Learning to optimally predict rewards requires agents to account for fluctuations in reward value. Recent work suggests that individuals can efficiently learn about variable rewards through adaptation of the learning rate, and coding of prediction errors relative to reward variability. Such adaptive coding has been linked to midbrain dopamine neurons in nonhuman primates, and evidence in support for a similar role of the dopaminergic system in humans is emerging from fMRI data. Here, we sought to investigate the effect of dopaminergic perturbations on adaptive prediction error coding in humans, using a between-subject, placebo-controlled pharmacological fMRI study with a dopaminergic agonist (bromocriptine) and antagonist (sulpiride). Participants performed a previously validated task in which they predicted the magnitude of upcoming rewards drawn from distributions with varying SDs. After each prediction, participants received a reward, yielding trial-by-trial prediction errors. Under placebo, we replicated previous observations of adaptive coding in the midbrain and ventral striatum. Treatment with sulpiride attenuated adaptive coding in both midbrain and ventral striatum, and was associated with a decrease in performance, whereas bromocriptine did not have a significant impact. Although we observed no differential effect of SD on performance between the groups, computational modeling suggested decreased behavioral adaptation in the sulpiride group. These results suggest that normal dopaminergic function is critical for adaptive prediction error coding, a key property of the brain thought to facilitate efficient learning in variable environments. Crucially, these results also offer potential insights for understanding the impact of disrupted dopamine function in mental illness. SIGNIFICANCE STATEMENT To choose optimally, we have to learn what to expect. Humans dampen learning when there is a great deal of variability in reward outcome, and two brain regions that are modulated by the brain chemical dopamine are sensitive to reward variability. Here, we aimed to directly relate dopamine to learning about variable rewards, and the neural encoding of associated teaching signals. We perturbed dopamine in healthy individuals using dopaminergic medication and asked them to predict variable rewards while we made brain scans. Dopamine perturbations impaired learning and the neural encoding of reward variability, thus establishing a direct link between dopamine and adaptation to reward variability. These results aid our understanding of clinical conditions associated with dopaminergic dysfunction, such as psychosis. Copyright © 2017 Diederen et al.
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Age-Related Differences in Lexical Access Relate to Speech Recognition in Noise
Carroll, Rebecca; Warzybok, Anna; Kollmeier, Birger; Ruigendijk, Esther
2016-01-01
Vocabulary size has been suggested as a useful measure of “verbal abilities” that correlates with speech recognition scores. Knowing more words is linked to better speech recognition. How vocabulary knowledge translates to general speech recognition mechanisms, how these mechanisms relate to offline speech recognition scores, and how they may be modulated by acoustical distortion or age, is less clear. Age-related differences in linguistic measures may predict age-related differences in speech recognition in noise performance. We hypothesized that speech recognition performance can be predicted by the efficiency of lexical access, which refers to the speed with which a given word can be searched and accessed relative to the size of the mental lexicon. We tested speech recognition in a clinical German sentence-in-noise test at two signal-to-noise ratios (SNRs), in 22 younger (18–35 years) and 22 older (60–78 years) listeners with normal hearing. We also assessed receptive vocabulary, lexical access time, verbal working memory, and hearing thresholds as measures of individual differences. Age group, SNR level, vocabulary size, and lexical access time were significant predictors of individual speech recognition scores, but working memory and hearing threshold were not. Interestingly, longer accessing times were correlated with better speech recognition scores. Hierarchical regression models for each subset of age group and SNR showed very similar patterns: the combination of vocabulary size and lexical access time contributed most to speech recognition performance; only for the younger group at the better SNR (yielding about 85% correct speech recognition) did vocabulary size alone predict performance. Our data suggest that successful speech recognition in noise is mainly modulated by the efficiency of lexical access. This suggests that older adults’ poorer performance in the speech recognition task may have arisen from reduced efficiency in lexical access; with an average vocabulary size similar to that of younger adults, they were still slower in lexical access. PMID:27458400
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Age-Related Differences in Lexical Access Relate to Speech Recognition in Noise.
Carroll, Rebecca; Warzybok, Anna; Kollmeier, Birger; Ruigendijk, Esther
2016-01-01
Vocabulary size has been suggested as a useful measure of "verbal abilities" that correlates with speech recognition scores. Knowing more words is linked to better speech recognition. How vocabulary knowledge translates to general speech recognition mechanisms, how these mechanisms relate to offline speech recognition scores, and how they may be modulated by acoustical distortion or age, is less clear. Age-related differences in linguistic measures may predict age-related differences in speech recognition in noise performance. We hypothesized that speech recognition performance can be predicted by the efficiency of lexical access, which refers to the speed with which a given word can be searched and accessed relative to the size of the mental lexicon. We tested speech recognition in a clinical German sentence-in-noise test at two signal-to-noise ratios (SNRs), in 22 younger (18-35 years) and 22 older (60-78 years) listeners with normal hearing. We also assessed receptive vocabulary, lexical access time, verbal working memory, and hearing thresholds as measures of individual differences. Age group, SNR level, vocabulary size, and lexical access time were significant predictors of individual speech recognition scores, but working memory and hearing threshold were not. Interestingly, longer accessing times were correlated with better speech recognition scores. Hierarchical regression models for each subset of age group and SNR showed very similar patterns: the combination of vocabulary size and lexical access time contributed most to speech recognition performance; only for the younger group at the better SNR (yielding about 85% correct speech recognition) did vocabulary size alone predict performance. Our data suggest that successful speech recognition in noise is mainly modulated by the efficiency of lexical access. This suggests that older adults' poorer performance in the speech recognition task may have arisen from reduced efficiency in lexical access; with an average vocabulary size similar to that of younger adults, they were still slower in lexical access.
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Fischer, A; Friggens, N C; Berry, D P; Faverdin, P
2018-07-01
The ability to properly assess and accurately phenotype true differences in feed efficiency among dairy cows is key to the development of breeding programs for improving feed efficiency. The variability among individuals in feed efficiency is commonly characterised by the residual intake approach. Residual feed intake is represented by the residuals of a linear regression of intake on the corresponding quantities of the biological functions that consume (or release) energy. However, the residuals include both, model fitting and measurement errors as well as any variability in cow efficiency. The objective of this study was to isolate the individual animal variability in feed efficiency from the residual component. Two separate models were fitted, in one the standard residual energy intake (REI) was calculated as the residual of a multiple linear regression of lactation average net energy intake (NEI) on lactation average milk energy output, average metabolic BW, as well as lactation loss and gain of body condition score. In the other, a linear mixed model was used to simultaneously fit fixed linear regressions and random cow levels on the biological traits and intercept using fortnight repeated measures for the variables. This method split the predicted NEI in two parts: one quantifying the population mean intercept and coefficients, and one quantifying cow-specific deviations in the intercept and coefficients. The cow-specific part of predicted NEI was assumed to isolate true differences in feed efficiency among cows. NEI and associated energy expenditure phenotypes were available for the first 17 fortnights of lactation from 119 Holstein cows; all fed a constant energy-rich diet. Mixed models fitting cow-specific intercept and coefficients to different combinations of the aforementioned energy expenditure traits, calculated on a fortnightly basis, were compared. The variance of REI estimated with the lactation average model represented only 8% of the variance of measured NEI. Among all compared mixed models, the variance of the cow-specific part of predicted NEI represented between 53% and 59% of the variance of REI estimated from the lactation average model or between 4% and 5% of the variance of measured NEI. The remaining 41% to 47% of the variance of REI estimated with the lactation average model may therefore reflect model fitting errors or measurement errors. In conclusion, the use of a mixed model framework with cow-specific random regressions seems to be a promising method to isolate the cow-specific component of REI in dairy cows.
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USDA-ARS?s Scientific Manuscript database
Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its ef...
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Watson, A K; Klopfenstein, T J; Erickson, G E; MacDonald, J C; Wilkerson, V A
2017-07-01
Data from 16 trials were compiled to calculate microbial CP (MCP) production and MP requirements of growing cattle on high-forage diets. All cattle were individually fed diets with 28% to 72% corn cobs in addition to either alfalfa, corn silage, or sorghum silage at 18% to 60% of the diet (DM basis). The remainder of the diet consisted of protein supplement. Source of protein within the supplement varied and included urea, blood meal, corn gluten meal, dry distillers grains, feather meal, meat and bone meal, poultry by-product meal, soybean meal, and wet distillers grains. All trials included a urea-only treatment. Intake of all cattle within an experiment was held constant, as a percentage of BW, established by the urea-supplemented group. In each trial the base diet (forage and urea supplement) was MP deficient. Treatments consisted of increasing amounts of test protein replacing the urea supplement. As protein in the diet increased, ADG plateaued. Among experiments, ADG ranged from 0.11 to 0.73 kg. Three methods of calculating microbial efficiency were used to determine MP supply. Gain was then regressed against calculated MP supply to determine MP requirement for maintenance and gain. Method 1 (based on a constant 13% microbial efficiency as used by the beef NRC model) predicted an MP maintenance requirement of 3.8 g/kg BW and 385 g MP/kg gain. Method 2 calculated microbial efficiency using low-quality forage diets and predicted MP requirements of 3.2 g/kg BW for maintenance and 448 g/kg for gain. Method 3 (based on an equation predicting MCP yield from TDN intake, proposed by the Beef Cattle Nutrient Requirements Model [BCNRM]) predicted MP requirements of 3.1 g/kg BW for maintenance and 342 g/kg for gain. The factorial method of calculating MP maintenance requirements accounts for scurf, endogenous urinary, and metabolic fecal protein losses and averaged 4.2 g/kg BW. Cattle performance data demonstrate formulating diets to meet the beef NRC model recommended MP maintenance requirement (3.8 g/kg S) works well when using 13% microbial efficiency. Therefore, a change in how microbial efficiency is calculated necessitates a change in the proposed MP maintenance requirement to not oversupply or undersupply RUP. Using the 2016 BCNRM to predict MCP production and formulate diets to meet MP requirements also requires changing the MP maintenance requirement to 3.1 g/kg BW.
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NASA Astrophysics Data System (ADS)
Tayubi, Y. R.; Suhandi, A.; Samsudin, A.; Arifin, P.; Supriyatman
2018-05-01
Different approaches have been made in order to reach higher solar cells efficiencies. Concepts for multilayer solar cells have been developed. This can be realised if multiple individual single junction solar cells with different suitably chosen band gaps are connected in series in multi-junction solar cells. In our work, we have simulated and optimized solar cells based on the system mechanically stacked using computer simulation and predict their maximum performance. The structures of solar cells are based on the single junction GaAs, GaAs0.5Sb0.5 and GaSb cells. We have simulated each cell individually and extracted their optimal parameters (layer thickness, carrier concentration, the recombination velocity, etc), also, we calculated the efficiency of each cells optimized by separation of the solar spectrum in bands where the cell is sensible for the absorption. The optimal values of conversion efficiency have obtained for the three individual solar cells and the GaAs/GaAs0.5Sb0.5/GaSb tandem solar cells, that are: η = 19,76% for GaAs solar cell, η = 8,42% for GaAs0,5Sb0,5 solar cell, η = 4, 84% for GaSb solar cell and η = 33,02% for GaAs/GaAs0.5Sb0.5/GaSb tandem solar cell.
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Spatially explicit shallow landslide susceptibility mapping over large areas
Bellugi, Dino; Dietrich, William E.; Stock, Jonathan D.; McKean, Jim; Kazian, Brian; Hargrove, Paul
2011-01-01
Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so it has generated downscaled precipitation maps for the storm. To predict the corresponding pattern of shallow landslide susceptibility across the state, we have used the model Shalstab (a coupled steady state runoff and infinite slope stability model) which susceptibility spatially explicit estimates of relative potential instability. Such slope stability models that include the effects of subsurface runoff on potentially destabilizing pore pressure evolution require water routing and hence the definition of upslope drainage area to each potential cell. To calculate drainage area efficiently over a large area we developed a parallel framework to scale-up Shalstab and specifically introduce a new efficient parallel drainage area algorithm which produces seamless results. The single seamless shallow landslide susceptibility map for all of California was accomplished in a short run time, and indicates that much larger areas can be efficiently modelled. As landslide maps generally over predict the extent of instability for any given storm. Local empirical data on the fraction of predicted unstable cells that failed for observed rainfall intensity can be used to specify the likely extent of hazard for a given storm. This suggests that campaigns to collect local precipitation data and detailed shallow landslide location maps after major storms could be used to calibrate models and improve their use in hazard assessment for individual storms.
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NASA Astrophysics Data System (ADS)
Zhang, Y.; Chen, W.; Li, J.
2013-12-01
Climate change may alter the spatial distribution, composition, structure, and functions of plant communities. Transitional zones between biomes, or ecotones, are particularly sensitive to climate change. Ecotones are usually heterogeneous with sparse trees. The dynamics of ecotones are mainly determined by the growth and competition of individual plants in the communities. Therefore it is necessary to calculate solar radiation absorbed by individual plants for understanding and predicting their responses to climate change. In this study, we developed an individual plant radiation model, IPR (version 1.0), to calculate solar radiation absorbed by individual plants in sparse heterogeneous woody plant communities. The model is developed based on geometrical optical relationships assuming crowns of woody plants are rectangular boxes with uniform leaf area density. The model calculates the fractions of sunlit and shaded leaf classes and the solar radiation absorbed by each class, including direct radiation from the sun, diffuse radiation from the sky, and scattered radiation from the plant community. The solar radiation received on the ground is also calculated. We tested the model by comparing with the analytical solutions of random distributions of plants. The tests show that the model results are very close to the averages of the random distributions. This model is efficient in computation, and is suitable for ecological models to simulate long-term transient responses of plant communities to climate change.
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Efficient differentially private learning improves drug sensitivity prediction.
Honkela, Antti; Das, Mrinal; Nieminen, Arttu; Dikmen, Onur; Kaski, Samuel
2018-02-06
Users of a personalised recommendation system face a dilemma: recommendations can be improved by learning from data, but only if other users are willing to share their private information. Good personalised predictions are vitally important in precision medicine, but genomic information on which the predictions are based is also particularly sensitive, as it directly identifies the patients and hence cannot easily be anonymised. Differential privacy has emerged as a potentially promising solution: privacy is considered sufficient if presence of individual patients cannot be distinguished. However, differentially private learning with current methods does not improve predictions with feasible data sizes and dimensionalities. We show that useful predictors can be learned under powerful differential privacy guarantees, and even from moderately-sized data sets, by demonstrating significant improvements in the accuracy of private drug sensitivity prediction with a new robust private regression method. Our method matches the predictive accuracy of the state-of-the-art non-private lasso regression using only 4x more samples under relatively strong differential privacy guarantees. Good performance with limited data is achieved by limiting the sharing of private information by decreasing the dimensionality and by projecting outliers to fit tighter bounds, therefore needing to add less noise for equal privacy. The proposed differentially private regression method combines theoretical appeal and asymptotic efficiency with good prediction accuracy even with moderate-sized data. As already the simple-to-implement method shows promise on the challenging genomic data, we anticipate rapid progress towards practical applications in many fields. This article was reviewed by Zoltan Gaspari and David Kreil.
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Genome wide selection in Citrus breeding.
Gois, I B; Borém, A; Cristofani-Yaly, M; de Resende, M D V; Azevedo, C F; Bastianel, M; Novelli, V M; Machado, M A
2016-10-17
Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seq TM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.
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Hoeber, Stefanie; Fransson, Petra; Prieto-Ruiz, Inés; Manzoni, Stefano; Weih, Martin
2017-01-01
Individual plant species or genotypes often differ in their demand for nutrients; to compete in a community they must be able to acquire more nutrients (i.e., uptake efficiency) and/or use them more efficiently for biomass production than their competitors. These two mechanisms are often complementary, as there are inherent trade-offs between them. In a mixed-stand, species with contrasting nutrient use patterns interact and may use their resources to increase productivity in different ways. Under contrasting nutrient availabilities, the competitive advantages conferred by either strategy may also shift, so that the interaction between resource use strategy and resource availability ultimately determines the performance of individual genotypes in mixtures. The aim was to investigate growth and nitrogen (N) use efficiency of two willow (Salix) genotypes grown in monoculture and mixture in a fertilizer contrast. We explored the hypotheses that (1) the biomass production of at least one of the involved genotypes should be greater when grown in mixture as compared to the corresponding monoculture when nutrients are the most growth-limiting factor; and (2) the N economy of individual genotypes differs when grown in mixture compared to the corresponding monoculture. The genotypes ‘Tora’ (Salix schwerinii ×S. viminalis) and ‘Loden’ (S. dasyclados), with contrasting phenology and functional traits, were grown from cuttings in a growth container experiment under two nutrient fertilization treatments (high and low) in mono- and mixed-culture for 17 weeks. Under low nutrient level, ‘Tora’ showed a higher biomass production (aboveground biomass, leaf area productivity) and N uptake efficiency in mixture than in monoculture, whereas ‘Loden’ showed the opposite pattern. In addition, ‘Loden’ showed higher leaf N productivity but lower N uptake efficiency than ‘Tora.’ The results demonstrated that the specific functional trait combinations of individual genotypes affect their response to mixture as compared to monoculture. Plants grown in mixture as opposed to monoculture may thus increase biomass and vary in their response of N use efficiency traits. However, young plants were investigated here, and as we cannot predict mixture response in mature stands, our results need to be validated at field scale. PMID:28270828
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Hoeber, Stefanie; Fransson, Petra; Prieto-Ruiz, Inés; Manzoni, Stefano; Weih, Martin
2017-01-01
Individual plant species or genotypes often differ in their demand for nutrients; to compete in a community they must be able to acquire more nutrients (i.e., uptake efficiency) and/or use them more efficiently for biomass production than their competitors. These two mechanisms are often complementary, as there are inherent trade-offs between them. In a mixed-stand, species with contrasting nutrient use patterns interact and may use their resources to increase productivity in different ways. Under contrasting nutrient availabilities, the competitive advantages conferred by either strategy may also shift, so that the interaction between resource use strategy and resource availability ultimately determines the performance of individual genotypes in mixtures. The aim was to investigate growth and nitrogen (N) use efficiency of two willow ( Salix ) genotypes grown in monoculture and mixture in a fertilizer contrast. We explored the hypotheses that (1) the biomass production of at least one of the involved genotypes should be greater when grown in mixture as compared to the corresponding monoculture when nutrients are the most growth-limiting factor; and (2) the N economy of individual genotypes differs when grown in mixture compared to the corresponding monoculture. The genotypes 'Tora' ( Salix schwerinii × S. viminalis ) and 'Loden' ( S. dasyclados ), with contrasting phenology and functional traits, were grown from cuttings in a growth container experiment under two nutrient fertilization treatments (high and low) in mono- and mixed-culture for 17 weeks. Under low nutrient level, 'Tora' showed a higher biomass production (aboveground biomass, leaf area productivity) and N uptake efficiency in mixture than in monoculture, whereas 'Loden' showed the opposite pattern. In addition, 'Loden' showed higher leaf N productivity but lower N uptake efficiency than 'Tora.' The results demonstrated that the specific functional trait combinations of individual genotypes affect their response to mixture as compared to monoculture. Plants grown in mixture as opposed to monoculture may thus increase biomass and vary in their response of N use efficiency traits. However, young plants were investigated here, and as we cannot predict mixture response in mature stands, our results need to be validated at field scale.
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Java web tools for PCR, in silico PCR, and oligonucleotide assembly and analysis.
Kalendar, Ruslan; Lee, David; Schulman, Alan H
2011-08-01
The polymerase chain reaction is fundamental to molecular biology and is the most important practical molecular technique for the research laboratory. We have developed and tested efficient tools for PCR primer and probe design, which also predict oligonucleotide properties based on experimental studies of PCR efficiency. The tools provide comprehensive facilities for designing primers for most PCR applications and their combinations, including standard, multiplex, long-distance, inverse, real-time, unique, group-specific, bisulphite modification assays, Overlap-Extension PCR Multi-Fragment Assembly, as well as a programme to design oligonucleotide sets for long sequence assembly by ligase chain reaction. The in silico PCR primer or probe search includes comprehensive analyses of individual primers and primer pairs. It calculates the melting temperature for standard and degenerate oligonucleotides including LNA and other modifications, provides analyses for a set of primers with prediction of oligonucleotide properties, dimer and G-quadruplex detection, linguistic complexity, and provides a dilution and resuspension calculator. Copyright © 2011 Elsevier Inc. All rights reserved.
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Fitting Neuron Models to Spike Trains
Rossant, Cyrille; Goodman, Dan F. M.; Fontaine, Bertrand; Platkiewicz, Jonathan; Magnusson, Anna K.; Brette, Romain
2011-01-01
Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input–output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model. PMID:21415925
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Application of a prediction model for work-related sensitisation in bakery workers.
Meijer, E; Suarthana, E; Rooijackers, J; Grobbee, D E; Jacobs, J H; Meijster, T; de Monchy, J G R; van Otterloo, E; van Rooy, F G B G J; Spithoven, J J G; Zaat, V A C; Heederik, D J J
2010-10-01
Identification of work-related allergy, particularly work-related asthma, in a (nationwide) medical surveillance programme among bakery workers requires an effective and efficient strategy. Bakers at high risk of having work-related allergy were indentified by use of a questionnaire-based prediction model for work-related sensitisation. The questionnaire was applied among 5,325 participating bakers. Sequential diagnostic investigations were performed only in those with an elevated risk. Performance of the model was evaluated in 674 randomly selected bakers who participated in the medical surveillance programme and the validation study. Clinical investigations were evaluated in the first 73 bakers referred at high risk. Overall 90% of bakers at risk of having asthma could be identified. Individuals at low risk showed 0.3-3.8% work-related respiratory symptoms, medication use or absenteeism. Predicting flour sensitisation by a simple questionnaire and score chart seems more effective at detecting work-related allergy than serology testing followed by clinical investigation in all immunoglobulin E class II-positive individuals. This prediction based stratification procedure appeared effective in detecting work-related allergy among bakers and can accurately be used for periodic examination, especially in small enterprises where delivery of adequate care is difficult. This approach may contribute to cost reduction.
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Racial bias shapes social reinforcement learning.
Lindström, Björn; Selbing, Ida; Molapour, Tanaz; Olsson, Andreas
2014-03-01
Both emotional facial expressions and markers of racial-group belonging are ubiquitous signals in social interaction, but little is known about how these signals together affect future behavior through learning. To address this issue, we investigated how emotional (threatening or friendly) in-group and out-group faces reinforced behavior in a reinforcement-learning task. We asked whether reinforcement learning would be modulated by intergroup attitudes (i.e., racial bias). The results showed that individual differences in racial bias critically modulated reinforcement learning. As predicted, racial bias was associated with more efficiently learned avoidance of threatening out-group individuals. We used computational modeling analysis to quantitatively delimit the underlying processes affected by social reinforcement. These analyses showed that racial bias modulates the rate at which exposure to threatening out-group individuals is transformed into future avoidance behavior. In concert, these results shed new light on the learning processes underlying social interaction with racial-in-group and out-group individuals.
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Swimming efficiency of bacterium Escherichia coli
Chattopadhyay, Suddhashil; Moldovan, Radu; Yeung, Chuck; Wu, X. L.
2006-01-01
We use measurements of swimming bacteria in an optical trap to determine fundamental properties of bacterial propulsion. In particular, we directly measure the force required to hold the bacterium in the optical trap and determine the propulsion matrix, which relates the translational and angular velocity of the flagellum to the torques and forces propelling the bacterium. From the propulsion matrix, dynamical properties such as torques, swimming speed, and power can be obtained by measuring the angular velocity of the motor. We find significant heterogeneities among different individuals even though all bacteria started from a single colony. The propulsive efficiency, defined as the ratio of the propulsive power output to the rotary power input provided by the motors, is found to be ≈2%, which is consistent with the efficiency predicted theoretically for a rigid helical coil. PMID:16954194
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Coupling of individual quantum emitters to channel plasmons.
Bermúdez-Ureña, Esteban; Gonzalez-Ballestero, Carlos; Geiselmann, Michael; Marty, Renaud; Radko, Ilya P; Holmgaard, Tobias; Alaverdyan, Yury; Moreno, Esteban; García-Vidal, Francisco J; Bozhevolnyi, Sergey I; Quidant, Romain
2015-08-07
Efficient light-matter interaction lies at the heart of many emerging technologies that seek on-chip integration of solid-state photonic systems. Plasmonic waveguides, which guide the radiation in the form of strongly confined surface plasmon-polariton modes, represent a promising solution to manipulate single photons in coplanar architectures with unprecedented small footprints. Here we demonstrate coupling of the emission from a single quantum emitter to the channel plasmon polaritons supported by a V-groove plasmonic waveguide. Extensive theoretical simulations enable us to determine the position and orientation of the quantum emitter for optimum coupling. Concomitantly with these predictions, we demonstrate experimentally that 42% of a single nitrogen-vacancy centre emission efficiently couples into the supported modes of the V-groove. This work paves the way towards practical realization of efficient and long distance transfer of energy for integrated solid-state quantum systems.
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Pedersen, Kristine Bondo; Kirkelund, Gunvor M; Ottosen, Lisbeth M; Jensen, Pernille E; Lejon, Tore
2015-01-01
Chemometrics was used to develop a multivariate model based on 46 previously reported electrodialytic remediation experiments (EDR) of five different harbour sediments. The model predicted final concentrations of Cd, Cu, Pb and Zn as a function of current density, remediation time, stirring rate, dry/wet sediment, cell set-up as well as sediment properties. Evaluation of the model showed that remediation time and current density had the highest comparative influence on the clean-up levels. Individual models for each heavy metal showed variance in the variable importance, indicating that the targeted heavy metals were bound to different sediment fractions. Based on the results, a PLS model was used to design five new EDR experiments of a sixth sediment to achieve specified clean-up levels of Cu and Pb. The removal efficiencies were up to 82% for Cu and 87% for Pb and the targeted clean-up levels were met in four out of five experiments. The clean-up levels were better than predicted by the model, which could hence be used for predicting an approximate remediation strategy; the modelling power will however improve with more data included. Copyright © 2014 Elsevier B.V. All rights reserved.
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Neuropsychological impairments predict the clinical course in schizophrenia.
Wölwer, Wolfgang; Brinkmeyer, Jürgen; Riesbeck, Mathias; Freimüller, Lena; Klimke, Ansgar; Wagner, Michael; Möller, Hans-Jürgen; Klingberg, Stefan; Gaebel, Wolfgang
2008-11-01
To add to the open question whether cognitive impairments predict clinical outcome in schizophrenia, a sample of 125 first episode patients was assessed at the onset and over one year of controlled long-term treatment within a study of the German Research Network on Schizophrenia. No relapse according to predefined criteria occurred within the first year, but a total of 29 patients fulfilled post-hoc criteria of "clinical deterioration". Impairments in cognitive functioning assessed by the Trail-Making Test B at the onset of long-term treatment differentiated between patients with vs. without later clinical deterioration and proved to be a significant predictor of the clinical course in a regression analysis outperforming initial clinical status as predictor. However, low sensitivity (72%) and specificity (51%) limit possibilities of a transfer to individual predictions. As a linear combination of neuropsychological and psychopathological variables obtained highest predictive validity, such a combination may improve the prediction of the course of schizophrenic disorders and may ultimately lead to a more efficient and comprehensive treatment planning.
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Nuutinen, Mikko; Leskelä, Riikka-Leena; Suojalehto, Ella; Tirronen, Anniina; Komssi, Vesa
2017-04-13
In previous years a substantial number of studies have identified statistically important predictors of nursing home admission (NHA). However, as far as we know, the analyses have been done at the population-level. No prior research has analysed the prediction accuracy of a NHA model for individuals. This study is an analysis of 3056 longer-term home care customers in the city of Tampere, Finland. Data were collected from the records of social and health service usage and RAI-HC (Resident Assessment Instrument - Home Care) assessment system during January 2011 and September 2015. The aim was to find out the most efficient variable subsets to predict NHA for individuals and validate the accuracy. The variable subsets of predicting NHA were searched by sequential forward selection (SFS) method, a variable ranking metric and the classifiers of logistic regression (LR), support vector machine (SVM) and Gaussian naive Bayes (GNB). The validation of the results was guaranteed using randomly balanced data sets and cross-validation. The primary performance metrics for the classifiers were the prediction accuracy and AUC (average area under the curve). The LR and GNB classifiers achieved 78% accuracy for predicting NHA. The most important variables were RAI MAPLE (Method for Assigning Priority Levels), functional impairment (RAI IADL, Activities of Daily Living), cognitive impairment (RAI CPS, Cognitive Performance Scale), memory disorders (diagnoses G30-G32 and F00-F03) and the use of community-based health-service and prior hospital use (emergency visits and periods of care). The accuracy of the classifier for individuals was high enough to convince the officials of the city of Tampere to integrate the predictive model based on the findings of this study as a part of home care information system. Further work need to be done to evaluate variables that are modifiable and responsive to interventions.
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The neural correlates of cognitive effort in anxiety: effects on processing efficiency.
Ansari, Tahereh L; Derakshan, Nazanin
2011-03-01
We investigated the neural correlates of cognitive effort/pre-target preparation (Contingent Negative Variation activity; CNV) in anxiety using a mixed antisaccade task that manipulated the interval between offset of instructional cue and onset of target (CTI). According to attentional control theory (Eysenck et al., 2007) we predicted that anxiety should result in increased levels of compensatory effort, as indicated by greater frontal CNV, to maintain comparable levels of performance under competing task demands. Our results showed that anxiety resulted in faster antisaccade latencies during medium compared with short and long CTIs. Accordingly, high-anxious individuals compared with low-anxious individuals showed greater levels of CNV activity at frontal sites during medium CTI suggesting that they exerted greater cognitive effort and invested more attentional resources in preparation for the task goal. Our results are the first to demonstrate the neural correlates of processing efficiency and compensatory effort in anxiety and are discussed within the framework of attentional control theory. Copyright © 2011 Elsevier B.V. All rights reserved.
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Chen, Yixi; Guzauskas, Gregory F; Gu, Chengming; Wang, Bruce C M; Furnback, Wesley E; Xie, Guotong; Dong, Peng; Garrison, Louis P
2016-11-02
The "big data" era represents an exciting opportunity to utilize powerful new sources of information to reduce clinical and health economic uncertainty on an individual patient level. In turn, health economic outcomes research (HEOR) practices will need to evolve to accommodate individual patient-level HEOR analyses. We propose the concept of "precision HEOR", which utilizes a combination of costs and outcomes derived from big data to inform healthcare decision-making that is tailored to highly specific patient clusters or individuals. To explore this concept, we discuss the current and future roles of HEOR in health sector decision-making, big data and predictive analytics, and several key HEOR contexts in which big data and predictive analytics might transform traditional HEOR into precision HEOR. The guidance document addresses issues related to the transition from traditional to precision HEOR practices, the evaluation of patient similarity analysis and its appropriateness for precision HEOR analysis, and future challenges to precision HEOR adoption. Precision HEOR should make precision medicine more realizable by aiding and adapting healthcare resource allocation. The combined hopes for precision medicine and precision HEOR are that individual patients receive the best possible medical care while overall healthcare costs remain manageable or become more cost-efficient.
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Chen, Yixi; Guzauskas, Gregory F.; Gu, Chengming; Wang, Bruce C. M.; Furnback, Wesley E.; Xie, Guotong; Dong, Peng; Garrison, Louis P.
2016-01-01
The “big data” era represents an exciting opportunity to utilize powerful new sources of information to reduce clinical and health economic uncertainty on an individual patient level. In turn, health economic outcomes research (HEOR) practices will need to evolve to accommodate individual patient–level HEOR analyses. We propose the concept of “precision HEOR”, which utilizes a combination of costs and outcomes derived from big data to inform healthcare decision-making that is tailored to highly specific patient clusters or individuals. To explore this concept, we discuss the current and future roles of HEOR in health sector decision-making, big data and predictive analytics, and several key HEOR contexts in which big data and predictive analytics might transform traditional HEOR into precision HEOR. The guidance document addresses issues related to the transition from traditional to precision HEOR practices, the evaluation of patient similarity analysis and its appropriateness for precision HEOR analysis, and future challenges to precision HEOR adoption. Precision HEOR should make precision medicine more realizable by aiding and adapting healthcare resource allocation. The combined hopes for precision medicine and precision HEOR are that individual patients receive the best possible medical care while overall healthcare costs remain manageable or become more cost-efficient. PMID:27827859
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Lian, J; Yuan, L; Wu, Q
Purpose: The quality and efficiency of radiotherapy treatment planning are highly planer dependent. Previously we have developed a statistical model to correlate anatomical features with dosimetry features of head and neck Tomotherapy treatment. The model enables us to predict the best achievable dosimetry for individual patient prior to treatment planning. The purpose of this work is to study if the prediction model can facilitate the treatment planning in both the efficiency and dosimetric quality. Methods: The anatomy-dosimetry correlation model was used to calculate the expected DVH for nine patients formerly treated. In Group A (3 patients), the model prediction agreedmore » with the clinic plan; in Group B (3 patients), the model predicted lower larynx mean dose than the clinic plan; in Group C (3 patients), the model suggested the brainstem could be further spared. Guided by the prior knowledge, we re-planned all 9 cases. The number of interactions during the optimization process and dosimetric endpoints between the original clinical plan and model-guided re-plan were compared. Results: For Group A, the difference of target coverage and organs-at-risk sparing is insignificant (p>0.05) between the replan and the clinical plan. For Group B, the clinical plan larynx median dose is 49.4±4.7 Gy, while the prediction suggesting 40.0±6.2 Gy (p<0.05). The re-plan achieved 41.5±6.6 Gy, with similar dose on other structures as clinical plan. For Group C, the clinical plan brainstem maximum dose is 44.7±5.5 Gy. The model predicted lower value 32.2±3.8 Gy (p<0.05). The re-plans reduced brainstem maximum dose to 31.8±4.1 Gy without affecting the dosimetry of other structures. In the replanning of the 9 cases, the times operator interacted with TPS are reduced on average about 50% compared to the clinical plan. Conclusion: We have demonstrated that the prior expert knowledge embedded model improved the efficiency and quality of Tomotherapy treatment planning.« less
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Computer modeling of a two-junction, monolithic cascade solar cell
NASA Technical Reports Server (NTRS)
Lamorte, M. F.; Abbott, D.
1979-01-01
The theory and design criteria for monolithic, two-junction cascade solar cells are described. The departure from the conventional solar cell analytical method and the reasons for using the integral form of the continuity equations are briefly discussed. The results of design optimization are presented. The energy conversion efficiency that is predicted for the optimized structure is greater than 30% at 300 K, AMO and one sun. The analytical method predicts device performance characteristics as a function of temperature. The range is restricted to 300 to 600 K. While the analysis is capable of determining most of the physical processes occurring in each of the individual layers, only the more significant device performance characteristics are presented.
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NASA Astrophysics Data System (ADS)
Beier, F.; de Vries, O.; Schreiber, T.; Eberhardt, R.; Tünnermann, A.; Bollig, C.; Hofmeister, P. G.; Schmidt, J.; Reuter, R.
2013-02-01
Scaling of the power yield of offshore wind farms relies on the capacity of the individual wind turbines. This results in a trend to very large rotor diameters, which are difficult to control. It is crucial to monitor the inhomogeneous wind field in front of the wind turbines at different distances to ensure reliable operation and a long lifetime at high output levels. In this contribution, we demonstrate an all-fiber ns-pulsed fiber amplifier based on cost-efficient commercially available components. The amplifier is a suitable source for coherent Doppler lidar pulses making a predictive control of the turbine operation feasible.
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NASA Technical Reports Server (NTRS)
Bifano, W. J.
1972-01-01
Test results are presented for a nine couple (3 x 3 array) thermoelectric panel of hybrid thermocouples. In the hybrid couple, a hollow cylinder of p-type Si-Ge is used to encapsulate a segmented PbTe/Si-Ge n-leg. The hybrid couple is predicted to offer a 10- to 15-percent improvement in performance relative to all Si-Ge couples. The efficiency, output power, and internal resistance of the panel as well as the resistances of the individual hybrid couples are presented as a function of test time covering a period of more than 2600 hours. Initial test results indicated hybrid couple performance consistent with design predictions. Extraneous resistance ranged from 20 to 25% of the hybrid couple thermoelectric resistance.
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Long, Chengjiang; Hua, Gang; Kapoor, Ashish
2015-01-01
We present a noise resilient probabilistic model for active learning of a Gaussian process classifier from crowds, i.e., a set of noisy labelers. It explicitly models both the overall label noise and the expertise level of each individual labeler with two levels of flip models. Expectation propagation is adopted for efficient approximate Bayesian inference of our probabilistic model for classification, based on which, a generalized EM algorithm is derived to estimate both the global label noise and the expertise of each individual labeler. The probabilistic nature of our model immediately allows the adoption of the prediction entropy for active selection of data samples to be labeled, and active selection of high quality labelers based on their estimated expertise to label the data. We apply the proposed model for four visual recognition tasks, i.e., object category recognition, multi-modal activity recognition, gender recognition, and fine-grained classification, on four datasets with real crowd-sourced labels from the Amazon Mechanical Turk. The experiments clearly demonstrate the efficacy of the proposed model. In addition, we extend the proposed model with the Predictive Active Set Selection Method to speed up the active learning system, whose efficacy is verified by conducting experiments on the first three datasets. The results show our extended model can not only preserve a higher accuracy, but also achieve a higher efficiency. PMID:26924892
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Jennings, Beth
2006-04-01
With the increasing corporate and governmental rationalisation of medical care, the mandate of efficiency has caused many to fear that concern for the individual patient will be replaced with impersonal, rule-governed allocation of medical resources. Largely ignored is the role of moral principles in medical decision-making. This analysis comes from an ethnographic study conducted from 1999-2001 in three US Intensive Care Units, two of which were using the computerised decision-support tool, APACHE III (Acute Physiological and Chronic Health Evaluation III), which notably predicts the probability that a patient will die. It was found that the use of APACHE presents a paradox regarding concern for the individual patient. To maintain jurisdiction over the care of patients, physicians share the data with the payers and regulators of care to prove they are using resources effectively and efficiently, yet they use the system in conjunction with moral principles to justify treating each patient as unique. Thus, concern for the individual patient is not lessened with the use of this system. However, physicians do not share the data with patients or surrogate decision-makers because they fear they will be viewed as more interested in profits than patients.
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Decisional style, mood and work communication: email diaries.
Shirren, S; Phillips, J G
2011-10-01
To understand the use of technology to support interpersonal interaction, a theory of decisional style was applied to email use within the workplace. Previous research has used self-report and rating scales to address employee email behaviours, but this falls short of management's capability to monitor the actual behaviour. Thirty-nine employed individuals completed a five-day communication diary recording their actual behaviour upon receiving personal and work-related emails as well as the Melbourne Decision Making Questionnaire and the Depression Anxiety Stress Scales. It was found that vigilant individuals were more likely to use email in an efficient manner by deleting personal email and being less likely to open email later. Procrastinators, buckpassers and people experiencing high levels of negative affect were all more likely to delay dealing with email, which could be viewed as dealing with email in a less efficient manner. STATEMENT OF RELEVANCE: This work offers insights as to how people receive and process emails and is thus relevant to the development and implementation of collaborative technologies. Whilst other studies use individual's self-reports, this study uses a more accurate communication diary. Decisional style can predict the monitoring and response to electronic communication.
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Toofanian Ross, Parnian; Padula, Claudia B; Nitch, Stephen R; Kinney, Dominique I
2015-01-01
Intact cognition is a foundational component of one's ability to be competent to stand trial. Given the cost of assessing and treating incompetence, it is recommended that clinicians develop efficient methods to identify individuals who are most likely to require intensive competence-related treatment interventions. This study sought to ascertain whether a brief cognitive screening instrument, the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), could predict the length of stay required to restore trial competency among 288 forensic psychiatric inpatients undergoing competency restoration treatment. Results indicated that incompetent defendants who were older or demonstrated poorer overall RBANS performance required longer hospitalizations to be deemed restored to trial competence. Interestingly, incompetent defendants scoring in the 51-60 range on the RBANS Total Scale Index were almost three times more likely to require hospitalization beyond the average length of stay. Findings support the use of the RBANS to identify individuals early in the treatment process who may require and benefit from intensive restoration treatment.
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Developing Personalized Sensorimotor Adaptability Countermeasures for Spaceflight
NASA Technical Reports Server (NTRS)
Mulavara, A. P.; Seidler, R. D.; Peters, B.; Cohen, H. S.; Wood, S.; Bloomberg, J. J.
2016-01-01
Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. In this paper we will be presenting results from our ground-based study that show how behavioral, brain imaging and genomic data may be used to predict individual differences in sensorimotor adaptability to novel sensorimotor environments. This approach will allow us to better design and implement sensorimotor adaptability training countermeasures against decrements in post-mission adaptive capability that are customized for each crewmember's sensory biases, adaptive capacity, brain structure, functional capacities, and genetic predispositions. The ability to customize adaptability training will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to ensure expected outcomes.
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Conditioned pain modulation: a predictor for development and treatment of neuropathic pain.
Granovsky, Yelena
2013-09-01
Psychophysical evaluation of endogenous pain inhibition via conditioned pain modulation (CPM) represents a new generation of laboratory tests for pain assessment. In this review we discuss recent findings on CPM in neuropathic pain and refer to psychophysical, neurophysiological, and methodological aspects of its clinical implications. Typically, chronic neuropathic pain patients express less efficient CPM, to the extent that incidence of acquiring neuropathic pain (e.g. post-surgery) and its intensity can be predicted by a pre-surgery CPM assessment. Moreover, pre-treatment CPM evaluation may assist in the correct choice of serotonin-noradrenalin reuptake inhibitor analgesic agents for individual patients. Evaluation of pain modulation capabilities can serve as a step forward in individualizing pain medicine.
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Artemov, Artem; Aliper, Alexander; Korzinkin, Michael; Lezhnina, Ksenia; Jellen, Leslie; Zhukov, Nikolay; Roumiantsev, Sergey; Gaifullin, Nurshat; Zhavoronkov, Alex; Borisov, Nicolas; Buzdin, Anton
2015-10-06
A new generation of anticancer therapeutics called target drugs has quickly developed in the 21st century. These drugs are tailored to inhibit cancer cell growth, proliferation, and viability by specific interactions with one or a few target proteins. However, despite formally known molecular targets for every "target" drug, patient response to treatment remains largely individual and unpredictable. Choosing the most effective personalized treatment remains a major challenge in oncology and is still largely trial and error. Here we present a novel approach for predicting target drug efficacy based on the gene expression signature of the individual tumor sample(s). The enclosed bioinformatic algorithm detects activation of intracellular regulatory pathways in the tumor in comparison to the corresponding normal tissues. According to the nature of the molecular targets of a drug, it predicts whether the drug can prevent cancer growth and survival in each individual case by blocking the abnormally activated tumor-promoting pathways or by reinforcing internal tumor suppressor cascades. To validate the method, we compared the distribution of predicted drug efficacy scores for five drugs (Sorafenib, Bevacizumab, Cetuximab, Sorafenib, Imatinib, Sunitinib) and seven cancer types (Clear Cell Renal Cell Carcinoma, Colon cancer, Lung adenocarcinoma, non-Hodgkin Lymphoma, Thyroid cancer and Sarcoma) with the available clinical trials data for the respective cancer types and drugs. The percent of responders to a drug treatment correlated significantly (Pearson's correlation 0.77 p = 0.023) with the percent of tumors showing high drug scores calculated with the current algorithm.
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Haist, Frank; Wazny, Jarnet H; Toomarian, Elizabeth; Adamo, Maha
2015-02-01
A central question in cognitive and educational neuroscience is whether brain operations supporting nonlinguistic intuitive number sense (numerosity) predict individual acquisition and academic achievement for symbolic or "formal" math knowledge. Here, we conducted a developmental functional magnetic resonance imaging (MRI) study of nonsymbolic numerosity task performance in 44 participants including 14 school age children (6-12 years old), 14 adolescents (13-17 years old), and 16 adults and compared a brain activity measure of numerosity precision to scores from the Woodcock-Johnson III Broad Math index of math academic achievement. Accuracy and reaction time from the numerosity task did not reliably predict formal math achievement. We found a significant positive developmental trend for improved numerosity precision in the parietal cortex and intraparietal sulcus specifically. Controlling for age and overall cognitive ability, we found a reliable positive relationship between individual math achievement scores and parietal lobe activity only in children. In addition, children showed robust positive relationships between math achievement and numerosity precision within ventral stream processing areas bilaterally. The pattern of results suggests a dynamic developmental trajectory for visual discrimination strategies that predict the acquisition of formal math knowledge. In adults, the efficiency of visual discrimination marked by numerosity acuity in ventral occipital-temporal cortex and hippocampus differentiated individuals with better or worse formal math achievement, respectively. Overall, these results suggest that two different brain systems for nonsymbolic numerosity acuity may contribute to individual differences in math achievement and that the contribution of these systems differs across development. © 2014 Wiley Periodicals, Inc.
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Haist, Frank; Wazny, Jarnet H.; Toomarian, Elizabeth; Adamo, Maha
2015-01-01
A central question in cognitive and educational neuroscience is whether brain operations supporting non-linguistic intuitive number sense (numerosity) predict individual acquisition and academic achievement for symbolic or “formal” math knowledge. Here, we conducted a developmental functional MRI study of nonsymbolic numerosity task performance in 44 participants including 14 school age children (6–12 years-old), 14 adolescents (13–17 years-old), and 16 adults and compared a brain activity measure of numerosity precision to scores from the Woodcock-Johnson III Broad Math index of math academic achievement. Accuracy and reaction time from the numerosity task did not reliably predict formal math achievement. We found a significant positive developmental trend for improved numerosity precision in the parietal cortex and intraparietal sulcus (IPS) specifically. Controlling for age and overall cognitive ability, we found a reliable positive relationship between individual math achievement scores and parietal lobe activity only in children. In addition, children showed robust positive relationships between math achievement and numerosity precision within ventral stream processing areas bilaterally. The pattern of results suggests a dynamic developmental trajectory for visual discrimination strategies that predict the acquisition of formal math knowledge. In adults, the efficiency of visual discrimination marked by numerosity acuity in ventral occipital-temporal cortex and hippocampus differentiated individuals with better or worse formal math achievement, respectively. Overall, these results suggest that two different brain systems for nonsymbolic numerosity acuity may contribute to individual differences in math achievement and that the contribution of these systems differs across development. PMID:25327879
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Weng, Ensheng; Farrior, Caroline E; Dybzinski, Ray; Pacala, Stephen W
2017-06-01
Earth system models are incorporating plant trait diversity into their land components to better predict vegetation dynamics in a changing climate. However, extant plant trait distributions will not allow extrapolations to novel community assemblages in future climates, which will require a mechanistic understanding of the trade-offs that determine trait diversity. In this study, we show how physiological trade-offs involving leaf mass per unit area (LMA), leaf lifespan, leaf nitrogen, and leaf respiration may explain the distribution patterns of evergreen and deciduous trees in the temperate and boreal zones based on (1) an evolutionary analysis of a simple mathematical model and (2) simulation experiments of an individual-based dynamic vegetation model (i.e., LM3-PPA). The evolutionary analysis shows that these leaf traits set up a trade-off between carbon- and nitrogen-use efficiency at the scale of individual trees and therefore determine competitively dominant leaf strategies. As soil nitrogen availability increases, the dominant leaf strategy switches from one that is high in nitrogen-use efficiency to one that is high in carbon-use efficiency or, equivalently, from high-LMA/long-lived leaves (i.e., evergreen) to low-LMA/short-lived leaves (i.e., deciduous). In a region of intermediate soil nitrogen availability, the dominant leaf strategy may be either deciduous or evergreen depending on the initial conditions of plant trait abundance (i.e., founder controlled) due to feedbacks of leaf traits on soil nitrogen mineralization through litter quality. Simulated successional patterns by LM3-PPA from the leaf physiological trade-offs are consistent with observed successional dynamics of evergreen and deciduous forests at three sites spanning the temperate to boreal zones. © 2016 John Wiley & Sons Ltd.
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[Waist-to-height ratio is an indicator of metabolic risk in children].
Valle-Leal, Jaime; Abundis-Castro, Leticia; Hernández-Escareño, Juan; Flores-Rubio, Salvador
2016-01-01
Abdominal fat, particularly visceral, is associated with a high risk of metabolic complications. The waist-height ratio (WHtR) is used to assess abdominal fat in individuals of all ages. To determine the ability of the waist-to-height ratio to detect metabolic risk in mexican schoolchildren. A study was conducted on children between 6 and 12 years. Obesity was diagnosed as a body mass index (BMI) ≥ 85th percentile, and an ICE ≥0.5 was considered abdominal obesity. Blood levels of glucose, cholesterol and triglycerides were measured. The sensitivity, specificity, positive predictive and negative value, area under curve, the positive likelihood ratio and negative likelihood ratio of the WHtR and BMI were calculated in order to identify metabolic alterations. WHtR and BMI were compared to determine which had the best diagnostic efficiency. Of the 223 children included in the study, 51 had hypertriglyceridaemia, 27 with hypercholesterolaemia, and 9 with hyperglycaemia. On comparing the diagnostic efficiency of WHtR with that of BMI, there was a sensitivity of 100% vs. 56% for hyperglycaemia, 93 vs. 70% for cholesterol, and 76 vs. 59% for hypertriglyceridaemia. The specificity, negative predictive value, positive predictive value, positive likelihood ratio, negative likelihood ratio, and area under curve were also higher for WHtR. The WHtR is a more efficient indicator than BMI in identifying metabolic risk in mexican school-age. Copyright © 2015 Sociedad Chilena de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.
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Prediction and validation of hemodialysis duration in acute methanol poisoning
Lachance, Philippe; Mac-Way, Fabrice; Desmeules, Simon; De Serres, Sacha A; Julien, Anne-Sophie; Douville, Pierre; Ghannoum, Marc; Agharazii, Mohsen
2015-01-01
The duration of hemodialysis (HD) in methanol poisoning (MP) is dependent on the methanol concentration, the operational parameters used during HD, and the presence and severity of metabolic acidosis. However, methanol assays are not easily available, potentially leading to undue extension or premature termination of treatment. Here we provide a prediction model for the duration of high-efficiency HD in MP. In a retrospective cohort study, we identified 71 episodes of MP in 55 individuals who were treated with alcohol dehydrogenase inhibition and HD. Four patients had residual visual abnormality at discharge and only one patient died. In 46 unique episodes of MP with high-efficiency HD the mean methanol elimination half-life (T1/2) during HD was 108 min in women, significantly different from the 129 min in men. In a training set of 28 patients with MP, using the 90th percentile of gender-specific elimination T1/2 (147 min in men and 141 min in women) and a target methanol concentration of 4 mmol/l allowed all cases to reach a safe methanol of under 6 mmol/l. The prediction model was confirmed in a validation set of 18 patients with MP. High-efficiency HD time in hours can be estimated using 3.390 × (Ln (MCi/4)) for women and 3.534 × (Ln (MCi/4)) for men, where MCi is the initial methanol concentration in mmol/l, provided that metabolic acidosis is corrected. PMID:26244924
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Chakravorty, Rajib; Rawlinson, David; Zhang, Alan; Markham, John; Dowling, Mark R; Wellard, Cameron; Zhou, Jie H S; Hodgkin, Philip D
2014-01-01
Interest in cell heterogeneity and differentiation has recently led to increased use of time-lapse microscopy. Previous studies have shown that cell fate may be determined well in advance of the event. We used a mixture of automation and manual review of time-lapse live cell imaging to track the positions, contours, divisions, deaths and lineage of 44 B-lymphocyte founders and their 631 progeny in vitro over a period of 108 hours. Using this data to train a Support Vector Machine classifier, we were retrospectively able to predict the fates of individual lymphocytes with more than 90% accuracy, using only time-lapse imaging captured prior to mitosis or death of 90% of all cells. The motivation for this paper is to explore the impact of labour-efficient assistive software tools that allow larger and more ambitious live-cell time-lapse microscopy studies. After training on this data, we show that machine learning methods can be used for realtime prediction of individual cell fates. These techniques could lead to realtime cell culture segregation for purposes such as phenotype screening. We were able to produce a large volume of data with less effort than previously reported, due to the image processing, computer vision, tracking and human-computer interaction tools used. We describe the workflow of the software-assisted experiments and the graphical interfaces that were needed. To validate our results we used our methods to reproduce a variety of published data about lymphocyte populations and behaviour. We also make all our data publicly available, including a large quantity of lymphocyte spatio-temporal dynamics and related lineage information.
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Herman, Shoshy; Zurgil, Naomi; Langevitz, Pnina; Ehrenfeld, Michael; Deutsch, Mordechai
2003-04-01
The objectives of this study were to test the in vitro response of healthy non-activated, activated, and rheumatoid arthritis (RA) lymphocytes to methotrexate (MTX), and design an in vitro model for predicting the efficiency of MTX treatment for RA patients. Considering the RA profile of clonal-expanded CD4(+) T cells, phytohemagglutinin-activated mononuclear cells taken from healthy donors were incubated with different concentrations of MTX. The MTX-immunosuppressive effect was tested by fluorescence intensity measurements, including PI assay and annexin V assay. For simple detection, we used the Individual Cell Scanner (IC-S), which enables the measurement of early events in individual cells. Healthy mononuclear cells (MNC), and MNC derived from RA patients, were tested by the IC-S while utilizing fluorescence polarization (FP) measurements of fluorescein diacetate (FDA) as an established marker of activation or suppression. In healthy activated MNC, we found that MTX, through its early incubation period, interferes with the activation signal obtained by PHA and exerts an apoptotic signal, which is noted by increases in the FP. Comparing our model to six long-standing RA patients and five newly-diagnosed patients revealed significant differences in the FP measurements, including fluorescence depolarization as an early established measurement of lymphocyte activation, and hyperpolarization as a measurement of an early immunosuppressive effect. We conclude that MTX, an effective therapy for RA patients, could easily be tested by fluorescence polarization measurements of FDA before (or during) clinical use in order to predict its efficiency on a specific RA patient. Moreover, the FP measurements can be used for the diagnosis, and making timing and dosage decisions.
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Relationship between efficiency and predictability in stock price change
NASA Astrophysics Data System (ADS)
Eom, Cheoljun; Oh, Gabjin; Jung, Woo-Sung
2008-09-01
In this study, we evaluate the relationship between efficiency and predictability in the stock market. The efficiency, which is the issue addressed by the weak-form efficient market hypothesis, is calculated using the Hurst exponent and the approximate entropy (ApEn). The predictability corresponds to the hit-rate; this is the rate of consistency between the direction of the actual price change and that of the predicted price change, as calculated via the nearest neighbor prediction method. We determine that the Hurst exponent and the ApEn value are negatively correlated. However, predictability is positively correlated with the Hurst exponent.
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Screening for Dyslexia Using Eye Tracking during Reading.
Nilsson Benfatto, Mattias; Öqvist Seimyr, Gustaf; Ygge, Jan; Pansell, Tony; Rydberg, Agneta; Jacobson, Christer
2016-01-01
Dyslexia is a neurodevelopmental reading disability estimated to affect 5-10% of the population. While there is yet no full understanding of the cause of dyslexia, or agreement on its precise definition, it is certain that many individuals suffer persistent problems in learning to read for no apparent reason. Although it is generally agreed that early intervention is the best form of support for children with dyslexia, there is still a lack of efficient and objective means to help identify those at risk during the early years of school. Here we show that it is possible to identify 9-10 year old individuals at risk of persistent reading difficulties by using eye tracking during reading to probe the processes that underlie reading ability. In contrast to current screening methods, which rely on oral or written tests, eye tracking does not depend on the subject to produce some overt verbal response and thus provides a natural means to objectively assess the reading process as it unfolds in real-time. Our study is based on a sample of 97 high-risk subjects with early identified word decoding difficulties and a control group of 88 low-risk subjects. These subjects were selected from a larger population of 2165 school children attending second grade. Using predictive modeling and statistical resampling techniques, we develop classification models from eye tracking records less than one minute in duration and show that the models are able to differentiate high-risk subjects from low-risk subjects with high accuracy. Although dyslexia is fundamentally a language-based learning disability, our results suggest that eye movements in reading can be highly predictive of individual reading ability and that eye tracking can be an efficient means to identify children at risk of long-term reading difficulties.
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Prototype for measuring pupil size changes
NASA Astrophysics Data System (ADS)
Ventura, Liliane; Pergoraro Silva, Fernando; Rossi, Giuliano; Riul, Cassius
2007-02-01
The neurological control of the visual process is extremely complex and the pupil movement plays an important role. It controls the intensity of light entering the eye, is responsible for focusing depth and avoiding undesired paracentral rays. As such factors vary along the day for each patient individually, allied to the individual answer to determined light stimulation, it is not possible to predict the pupilar size change along the day, leading to undetermined image quality of the patient for a pre-existent condition. Among the clinical and surgical procedures in order to enhance the quality of the visual system of the patient, wave-front based surgeries are performed and its efficiency is strongly dependent on the pupilar position as well as the area to be ablated. In order to predict the individual behavior of the pupil change during an ordinary routine of the patient we have been developing a system to provide means for the personal refractive surgery to be the most efficient as possible. This work presents a method for monitoring the dynamics of the pupil. The methodology presented in this work provides measurements of the patient's pupil sizes along an entire day with light intensity conditioned to the one that the patient is exposed. A prototype has been developed using an eyeglass frame, where a dichroic mirror (70% transmittance) is attached to the frame, as well as a CMOS camera and an infrared illumination system. The image of the pupil is acquired every 4 minutes, its transferring is done by wireless serial communication (RS-232) and saved in a flash memory. Image processing and pupil size determination are done later separately from monitoring. The system is under preliminary tests.
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Zhelyabovskaya, Olga B.; Berlin, Yuri A.; Birikh, Klara R.
2004-01-01
In bacterial expression systems, translation initiation is usually the rate limiting and the least predictable stage of protein synthesis. Efficiency of a translation initiation site can vary dramatically depending on the sequence context. This is why many standard expression vectors provide very poor expression levels of some genes. This notion persuaded us to develop an artificial genetic selection protocol, which allows one to find for a given target gene an individual efficient ribosome binding site from a random pool. In order to create Darwinian pressure necessary for the genetic selection, we designed a system based on translational coupling, in which microorganism survival in the presence of antibiotic depends on expression of the target gene, while putting no special requirements on this gene. Using this system we obtained superproducing constructs for the human protein RACK1 (receptor for activated C kinase). PMID:15034151
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Andreu, Glòria; Vidal, Teresa
2013-03-01
In this work, kenaf pulp was delignified by using laccase in combination with various redox mediators and the efficiency of the different laccase–mediator systems assessed in terms of the changes in pulp properties after bleaching. The oxidative ability of the individual mediators used (acetosyringone, syringaldehyde, p-coumaric acid, vanillin and actovanillone) and the laccase–mediator systems was determined by monitoring the oxidation–reduction potential (ORP) during process. The results confirmed the production of phenoxy radicals of variable reactivity and stressed the significant role of lignin structure in the enzymatic process. Although changes in ORP were correlated with the oxidative ability of the mediators, pulp properties as determined after the bleaching stage were also influenced by condensation and grafting reactions. As shown here, ORP measurements provide a first estimation of the delignification efficiency of a laccase–mediator system. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Jiao, Bingqing; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Li, Junchao; Cai, Yuxuan; Gao, Mengxia; Gao, Zhenni; Chang, Song; Huang, Ruiwang; Liu, Ming
2017-10-01
Previous studies have indicated a tight linkage between resting-state functional connectivity of the human brain and creative ability. This study aimed to further investigate the association between the topological organization of resting-state brain networks and creativity. Therefore, we acquired resting-state fMRI data from 22 high-creativity participants and 22 low-creativity participants (as determined by their Torrance Tests of Creative Thinking scores). We then constructed functional brain networks for each participant and assessed group differences in network topological properties before exploring the relationships between respective network topological properties and creative ability. We identified an optimized organization of intrinsic brain networks in both groups. However, compared with low-creativity participants, high-creativity participants exhibited increased global efficiency and substantially decreased path length, suggesting increased efficiency of information transmission across brain networks in creative individuals. Using a multiple linear regression model, we further demonstrated that regional functional integration properties (i.e., the betweenness centrality and global efficiency) of brain networks, particularly the default mode network (DMN) and sensorimotor network (SMN), significantly predicted the individual differences in creative ability. Furthermore, the associations between network regional properties and creative performance were creativity-level dependent, where the difference in the resource control component may be important in explaining individual difference in creative performance. These findings provide novel insights into the neural substrate of creativity and may facilitate objective identification of creative ability. Copyright © 2017 Elsevier B.V. All rights reserved.
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Forecasting influenza in Hong Kong with Google search queries and statistical model fusion
Ramirez Ramirez, L. Leticia; Nezafati, Kusha; Zhang, Qingpeng; Tsui, Kwok-Leung
2017-01-01
Background The objective of this study is to investigate predictive utility of online social media and web search queries, particularly, Google search data, to forecast new cases of influenza-like-illness (ILI) in general outpatient clinics (GOPC) in Hong Kong. To mitigate the impact of sensitivity to self-excitement (i.e., fickle media interest) and other artifacts of online social media data, in our approach we fuse multiple offline and online data sources. Methods Four individual models: generalized linear model (GLM), least absolute shrinkage and selection operator (LASSO), autoregressive integrated moving average (ARIMA), and deep learning (DL) with Feedforward Neural Networks (FNN) are employed to forecast ILI-GOPC both one week and two weeks in advance. The covariates include Google search queries, meteorological data, and previously recorded offline ILI. To our knowledge, this is the first study that introduces deep learning methodology into surveillance of infectious diseases and investigates its predictive utility. Furthermore, to exploit the strength from each individual forecasting models, we use statistical model fusion, using Bayesian model averaging (BMA), which allows a systematic integration of multiple forecast scenarios. For each model, an adaptive approach is used to capture the recent relationship between ILI and covariates. Results DL with FNN appears to deliver the most competitive predictive performance among the four considered individual models. Combing all four models in a comprehensive BMA framework allows to further improve such predictive evaluation metrics as root mean squared error (RMSE) and mean absolute predictive error (MAPE). Nevertheless, DL with FNN remains the preferred method for predicting locations of influenza peaks. Conclusions The proposed approach can be viewed a feasible alternative to forecast ILI in Hong Kong or other countries where ILI has no constant seasonal trend and influenza data resources are limited. The proposed methodology is easily tractable and computationally efficient. PMID:28464015
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NASA Astrophysics Data System (ADS)
Zhang, Y.; Chen, W.; Li, J.
2014-07-01
Climate change may alter the spatial distribution, composition, structure and functions of plant communities. Transitional zones between biomes, or ecotones, are particularly sensitive to climate change. Ecotones are usually heterogeneous with sparse trees. The dynamics of ecotones are mainly determined by the growth and competition of individual plants in the communities. Therefore it is necessary to calculate the solar radiation absorbed by individual plants in order to understand and predict their responses to climate change. In this study, we developed an individual plant radiation model, IPR (version 1.0), to calculate solar radiation absorbed by individual plants in sparse heterogeneous woody plant communities. The model is developed based on geometrical optical relationships assuming that crowns of woody plants are rectangular boxes with uniform leaf area density. The model calculates the fractions of sunlit and shaded leaf classes and the solar radiation absorbed by each class, including direct radiation from the sun, diffuse radiation from the sky, and scattered radiation from the plant community. The solar radiation received on the ground is also calculated. We tested the model by comparing with the results of random distribution of plants. The tests show that the model results are very close to the averages of the random distributions. This model is efficient in computation, and can be included in vegetation models to simulate long-term transient responses of plant communities to climate change. The code and a user's manual are provided as Supplement of the paper.
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Dai, Mingwei; Ming, Jingsi; Cai, Mingxuan; Liu, Jin; Yang, Can; Wan, Xiang; Xu, Zongben
2017-09-15
Results from genome-wide association studies (GWAS) suggest that a complex phenotype is often affected by many variants with small effects, known as 'polygenicity'. Tens of thousands of samples are often required to ensure statistical power of identifying these variants with small effects. However, it is often the case that a research group can only get approval for the access to individual-level genotype data with a limited sample size (e.g. a few hundreds or thousands). Meanwhile, summary statistics generated using single-variant-based analysis are becoming publicly available. The sample sizes associated with the summary statistics datasets are usually quite large. How to make the most efficient use of existing abundant data resources largely remains an open question. In this study, we propose a statistical approach, IGESS, to increasing statistical power of identifying risk variants and improving accuracy of risk prediction by i ntegrating individual level ge notype data and s ummary s tatistics. An efficient algorithm based on variational inference is developed to handle the genome-wide analysis. Through comprehensive simulation studies, we demonstrated the advantages of IGESS over the methods which take either individual-level data or summary statistics data as input. We applied IGESS to perform integrative analysis of Crohns Disease from WTCCC and summary statistics from other studies. IGESS was able to significantly increase the statistical power of identifying risk variants and improve the risk prediction accuracy from 63.2% ( ±0.4% ) to 69.4% ( ±0.1% ) using about 240 000 variants. The IGESS software is available at https://github.com/daviddaigithub/IGESS . zbxu@xjtu.edu.cn or xwan@comp.hkbu.edu.hk or eeyang@hkbu.edu.hk. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
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Single nanowire thermal conductivity measurements by Raman thermography.
Doerk, Gregory S; Carraro, Carlo; Maboudian, Roya
2010-08-24
A facile, rapid, and nondestructive technique for determining the thermal conductivity of individual nanowires based on Raman temperature mapping has been demonstrated. Using calculated absorption efficiencies, the thermal conductivities of single cantilevered Si nanowires grown by the vapor-liquid-solid method are measured and the results agree well with values predicted by diffuse phonon boundary scattering. As a measurement performed on the wire, thermal contact effects are avoided and ambient air convection is found to be negligible for the range of diameters measured. The method's versatility is further exemplified in the reverse measurement of a single nanowire absorption efficiency assuming diffuse phonon boundary scattering. The results presented here outline the broad utility that Raman thermography may have for future thermoelectric and photovoltaic characterization of nanostructures.
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Arriola Apelo, S I; Knapp, J R; Hanigan, M D
2014-07-01
In current dairy production systems, an average of 25% of dietary N is captured in milk, with the remainder being excreted in urine and feces. About 60% of total N losses occur postabsorption. Splanchnic tissues extract a fixed proportion of total inflow of each essential AA (EAA). Those EAA removed by splanchnic tissues and not incorporated into protein are subjected to catabolism, with the resulting N converted to urea. Splanchnic affinity varies among individual EAA, from several fold lower than mammary glands' affinity for the branched-chain AA to similar or higher affinity for Phe, Met, His, and Arg. On average, 85% of absorbed EAA appear in peripheral circulation, indicating that first-pass removal is not the main source of loss. Essential AA in excess of the needs of the mammary glands return to general circulation. High splanchnic blood flow dictates that a large proportion of EAA that return to general circulation flow through splanchnic tissues. In association with this constant recycling, EAA are removed and catabolized by splanchnic tissues. This results in splanchnic catabolism equaling or surpassing the use of many EAA for milk protein synthesis. Recent studies have demonstrated that EAA, energy substrates, and hormones activate signaling pathways that in turn regulate local blood flow, tissue extraction of EAA, and rates of milk protein synthesis. These recent findings would allow manipulation of dairy diets to maximize mammary uptake of EAA and reduce catabolism by splanchnic tissues. Dairy cattle nutrient requirement systems consider EAA requirements in aggregate as metabolizable protein (MP) and assume a fixed efficiency of MP use for milk protein. Lysine and Met sufficiency is only considered after MP requirements have been met. By doing so, requirement systems limit the scope of diet manipulation to achieve improved gross N efficiency. Therefore, this review focuses on understanding the dynamics of EAA metabolism in mammary and splanchnic tissues that would lead to improved requirement prediction systems. Inclusion of variable individual EAA efficiencies derived from splanchnic and mammary responses to nutrient and hormonal signals should help reduce dietary protein levels. Supplementing reduced crude protein diets with individual EAA should increase gross N efficiency to more than 30%, reducing N excretion by the US dairy industry by 92,000 t annually. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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NASA Astrophysics Data System (ADS)
Kandare, Kaja; Ørka, Hans Ole; Dalponte, Michele; Næsset, Erik; Gobakken, Terje
2017-08-01
Site productivity is essential information for sustainable forest management and site index (SI) is the most common quantitative measure of it. The SI is usually determined for individual tree species based on tree height and the age of the 100 largest trees per hectare according to stem diameter. The present study aimed to demonstrate and validate a methodology for the determination of SI using remotely sensed data, in particular fused airborne laser scanning (ALS) and airborne hyperspectral data in a forest site in Norway. The applied approach was based on individual tree crown (ITC) delineation: tree species, tree height, diameter at breast height (DBH), and age were modelled and predicted at ITC level using 10-fold cross validation. Four dominant ITCs per 400 m2 plot were selected as input to predict SI at plot level for Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.). We applied an experimental setup with different subsets of dominant ITCs with different combinations of attributes (predicted or field-derived) for SI predictions. The results revealed that the selection of the dominant ITCs based on the largest DBH independent of tree species, predicted the SI with similar accuracy as ITCs matched with field-derived dominant trees (RMSE: 27.6% vs 23.3%). The SI accuracies were at the same level when dominant species were determined from the remotely sensed or field data (RMSE: 27.6% vs 27.8%). However, when the predicted tree age was used the SI accuracy decreased compared to field-derived age (RMSE: 27.6% vs 7.6%). In general, SI was overpredicted for both tree species in the mature forest, while there was an underprediction in the young forest. In conclusion, the proposed approach for SI determination based on ITC delineation and a combination of ALS and hyperspectral data is an efficient and stable procedure, which has the potential to predict SI in forest areas at various spatial scales and additionally to improve existing SI maps in Norway.
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Hooper, Paul L; Demps, Kathryn; Gurven, Michael; Gerkey, Drew; Kaplan, Hillard S
2015-12-05
In foraging and other productive activities, individuals make choices regarding whether and with whom to cooperate, and in what capacities. The size and composition of cooperative groups can be understood as a self-organized outcome of these choices, which are made under local ecological and social constraints. This article describes a theoretical framework for explaining the size and composition of foraging groups based on three principles: (i) the sexual division of labour; (ii) the intergenerational division of labour; and (iii) economies of scale in production. We test predictions from the theory with data from two field contexts: Tsimane' game hunters of lowland Bolivia, and Jenu Kuruba honey collectors of South India. In each case, we estimate the impacts of group size and individual group members' effort on group success. We characterize differences in the skill requirements of different foraging activities and show that individuals participate more frequently in activities in which they are more efficient. We evaluate returns to scale across different resource types and observe higher returns at larger group sizes in foraging activities (such as hunting large game) that benefit from coordinated and complementary roles. These results inform us that the foraging group size and composition are guided by the motivated choice of individuals on the basis of relative efficiency, benefits of cooperation, opportunity costs and other social considerations. © 2015 The Author(s).
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Kaganovich, Natalya; Schumaker, Jennifer
2016-01-01
Sensitivity to the temporal relationship between auditory and visual stimuli is key to efficient audiovisual integration. However, even adults vary greatly in their ability to detect audiovisual temporal asynchrony. What underlies this variability is currently unknown. We recorded event-related potentials (ERPs) while participants performed a simultaneity judgment task on a range of audiovisual (AV) and visual-auditory (VA) stimulus onset asynchronies (SOAs) and compared ERP responses in good and poor performers to the 200 ms SOA, which showed the largest individual variability in the number of synchronous perceptions. Analysis of ERPs to the VA200 stimulus yielded no significant results. However, those individuals who were more sensitive to the AV200 SOA had significantly more positive voltage between 210 and 270 ms following the sound onset. In a follow-up analysis, we showed that the mean voltage within this window predicted approximately 36% of variability in sensitivity to AV temporal asynchrony in a larger group of participants. The relationship between the ERP measure in the 210-270 ms window and accuracy on the simultaneity judgment task also held for two other AV SOAs with significant individual variability - 100 and 300 ms. Because the identified window was time-locked to the onset of sound in the AV stimulus, we conclude that sensitivity to AV temporal asynchrony is shaped to a large extent by the efficiency in the neural encoding of sound onsets. PMID:27094850
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Performance of immunological response in predicting virological failure.
Ingole, Nayana; Mehta, Preeti; Pazare, Amar; Paranjpe, Supriya; Sarkate, Purva
2013-03-01
In HIV-infected individuals on antiretroviral therapy (ART), the decision on when to switch from first-line to second-line therapy is dictated by treatment failure, and this can be measured in three ways: clinically, immunologically, and virologically. While viral load (VL) decreases and CD4 cell increases typically occur together after starting ART, discordant responses may be seen. Hence the current study was designed to determine the immunological and virological response to ART and to evaluate the utility of immunological response to predict virological failure. All treatment-naive HIV-positive individuals aged >18 years who were eligible for ART were enrolled and assessed at baseline, 6 months, and 12 months clinically and by CD4 cell count and viral load estimations. The patients were categorized as showing concordant favorable (CF), immunological only (IO), virological only (VO), and concordant unfavorable responses (CU). The efficiency of immunological failure to predict virological failure was analyzed across various levels of virological failure (VL>50, >500, and >5,000 copies/ml). At 6 months, 87(79.81%), 7(5.5%), 13 (11.92%), and 2 (1.83%) patients and at 12 months 61(69.3%), 9(10.2%), 16 (18.2%), and 2 (2.3%) patients had CF, IO, VO, and CU responses, respectively. Immunological failure criteria had a very low sensitivity (11.1-40%) and positive predictive value (8.3-25%) to predict virological failure. Immunological criteria do not accurately predict virological failure resulting in significant misclassification of therapeutic responses. There is an urgent need for inclusion of viral load testing in the initiation and monitoring of ART.
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A High-Throughput Arabidopsis Reverse Genetics System
Sessions, Allen; Burke, Ellen; Presting, Gernot; Aux, George; McElver, John; Patton, David; Dietrich, Bob; Ho, Patrick; Bacwaden, Johana; Ko, Cynthia; Clarke, Joseph D.; Cotton, David; Bullis, David; Snell, Jennifer; Miguel, Trini; Hutchison, Don; Kimmerly, Bill; Mitzel, Theresa; Katagiri, Fumiaki; Glazebrook, Jane; Law, Marc; Goff, Stephen A.
2002-01-01
A collection of Arabidopsis lines with T-DNA insertions in known sites was generated to increase the efficiency of functional genomics. A high-throughput modified thermal asymetric interlaced (TAIL)-PCR protocol was developed and used to amplify DNA fragments flanking the T-DNA left borders from ∼100,000 transformed lines. A total of 85,108 TAIL-PCR products from 52,964 T-DNA lines were sequenced and compared with the Arabidopsis genome to determine the positions of T-DNAs in each line. Predicted T-DNA insertion sites, when mapped, showed a bias against predicted coding sequences. Predicted insertion mutations in genes of interest can be identified using Arabidopsis Gene Index name searches or by BLAST (Basic Local Alignment Search Tool) search. Insertions can be confirmed by simple PCR assays on individual lines. Predicted insertions were confirmed in 257 of 340 lines tested (76%). This resource has been named SAIL (Syngenta Arabidopsis Insertion Library) and is available to the scientific community at www.tmri.org. PMID:12468722
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Liu, Xiao-Ke; Chen, Zhan; Zheng, Cai-Jun; Liu, Chuan-Lin; Lee, Chun-Sing; Li, Fan; Ou, Xue-Mei; Zhang, Xiao-Hong
2015-04-08
High-efficiency, thermally activated delayed-fluorescence organic light-emitting diodes based on exciplex emitters are demonstrated. The best device, based on a TAPC:DPTPCz emitter, shows a high external quantum efficiency of 15.4%. Strategies for predicting and designing efficient exciplex emitters are also provided. This approach allow prediction and design of efficient exciplex emitters for achieving high-efficiency organic light-emitting diodes, for future use in displays and lighting applications. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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NASA Astrophysics Data System (ADS)
Magnuson, Brian
A proof-of-concept software-in-the-loop study is performed to assess the accuracy of predicted net and charge-gaining energy consumption for potential effective use in optimizing powertrain management of hybrid vehicles. With promising results of improving fuel efficiency of a thermostatic control strategy for a series, plug-ing, hybrid-electric vehicle by 8.24%, the route and speed prediction machine learning algorithms are redesigned and implemented for real- world testing in a stand-alone C++ code-base to ingest map data, learn and predict driver habits, and store driver data for fast startup and shutdown of the controller or computer used to execute the compiled algorithm. Speed prediction is performed using a multi-layer, multi-input, multi- output neural network using feed-forward prediction and gradient descent through back- propagation training. Route prediction utilizes a Hidden Markov Model with a recurrent forward algorithm for prediction and multi-dimensional hash maps to store state and state distribution constraining associations between atomic road segments and end destinations. Predicted energy is calculated using the predicted time-series speed and elevation profile over the predicted route and the road-load equation. Testing of the code-base is performed over a known road network spanning 24x35 blocks on the south hill of Spokane, Washington. A large set of training routes are traversed once to add randomness to the route prediction algorithm, and a subset of the training routes, testing routes, are traversed to assess the accuracy of the net and charge-gaining predicted energy consumption. Each test route is traveled a random number of times with varying speed conditions from traffic and pedestrians to add randomness to speed prediction. Prediction data is stored and analyzed in a post process Matlab script. The aggregated results and analysis of all traversals of all test routes reflect the performance of the Driver Prediction algorithm. The error of average energy gained through charge-gaining events is 31.3% and the error of average net energy consumed is 27.3%. The average delta and average standard deviation of the delta of predicted energy gained through charge-gaining events is 0.639 and 0.601 Wh respectively for individual time-series calculations. Similarly, the average delta and average standard deviation of the delta of the predicted net energy consumed is 0.567 and 0.580 Wh respectively for individual time-series calculations. The average delta and standard deviation of the delta of the predicted speed is 1.60 and 1.15 respectively also for the individual time-series measurements. The percentage of accuracy of route prediction is 91%. Overall, test routes are traversed 151 times for a total test distance of 276.4 km.
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ProTSAV: A protein tertiary structure analysis and validation server.
Singh, Ankita; Kaushik, Rahul; Mishra, Avinash; Shanker, Asheesh; Jayaram, B
2016-01-01
Quality assessment of predicted model structures of proteins is as important as the protein tertiary structure prediction. A highly efficient quality assessment of predicted model structures directs further research on function. Here we present a new server ProTSAV, capable of evaluating predicted model structures based on some popular online servers and standalone tools. ProTSAV furnishes the user with a single quality score in case of individual protein structure along with a graphical representation and ranking in case of multiple protein structure assessment. The server is validated on ~64,446 protein structures including experimental structures from RCSB and predicted model structures for CASP targets and from public decoy sets. ProTSAV succeeds in predicting quality of protein structures with a specificity of 100% and a sensitivity of 98% on experimentally solved structures and achieves a specificity of 88%and a sensitivity of 91% on predicted protein structures of CASP11 targets under 2Å.The server overcomes the limitations of any single server/method and is seen to be robust in helping in quality assessment. ProTSAV is freely available at http://www.scfbio-iitd.res.in/software/proteomics/protsav.jsp. Copyright © 2015 Elsevier B.V. All rights reserved.
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Kim, Scott Y H
2014-04-01
The Patient Preference Predictor (PPP) proposal places a high priority on the accuracy of predicting patients' preferences and finds the performance of surrogates inadequate. However, the quest to develop a highly accurate, individualized statistical model has significant obstacles. First, it will be impossible to validate the PPP beyond the limit imposed by 60%-80% reliability of people's preferences for future medical decisions--a figure no better than the known average accuracy of surrogates. Second, evidence supports the view that a sizable minority of persons may not even have preferences to predict. Third, many, perhaps most, people express their autonomy just as much by entrusting their loved ones to exercise their judgment than by desiring to specifically control future decisions. Surrogate decision making faces none of these issues and, in fact, it may be more efficient, accurate, and authoritative than is commonly assumed.
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Relationships among attention networks and physiological responding to threat.
Sarapas, Casey; Weinberg, Anna; Langenecker, Scott A; Shankman, Stewart A
2017-02-01
Although researchers have long hypothesized a relationship between attention and anxiety, theoretical and empirical accounts of this relationship have conflicted. We attempted to resolve these conflicts by examining relationships of attentional abilities with responding to predictable and unpredictable threat - related but distinct motivational process implicated in a number of anxiety disorders. Eighty-one individuals completed a behavioral task assessing efficiency of three components of attention - alerting, orienting, and executive control (Attention Network Test - Revised). We also assessed startle responding during anticipation of both predictable, imminent threat (of mild electric shock) and unpredictable contextual threat. Faster alerting and slower disengaging from non-emotional attention cues were related to heightened responding to unpredictable threat, whereas poorer executive control of attention was related to heightened responding to predictable threat. This double dissociation helps to integrate models of attention and anxiety and may be informative for treatment development. Copyright © 2016 Elsevier Inc. All rights reserved.
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Forecasting Construction Cost Index based on visibility graph: A network approach
NASA Astrophysics Data System (ADS)
Zhang, Rong; Ashuri, Baabak; Shyr, Yu; Deng, Yong
2018-03-01
Engineering News-Record (ENR), a professional magazine in the field of global construction engineering, publishes Construction Cost Index (CCI) every month. Cost estimators and contractors assess projects, arrange budgets and prepare bids by forecasting CCI. However, fluctuations and uncertainties of CCI cause irrational estimations now and then. This paper aims at achieving more accurate predictions of CCI based on a network approach in which time series is firstly converted into a visibility graph and future values are forecasted relied on link prediction. According to the experimental results, the proposed method shows satisfactory performance since the error measures are acceptable. Compared with other methods, the proposed method is easier to implement and is able to forecast CCI with less errors. It is convinced that the proposed method is efficient to provide considerably accurate CCI predictions, which will make contributions to the construction engineering by assisting individuals and organizations in reducing costs and making project schedules.
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Relationships Among Attention Networks and Physiological Responding to Threat
Sarapas, Casey; Weinberg, Anna; Langenecker, Scott A.
2016-01-01
Although researchers have long hypothesized a relationship between attention and anxiety, theoretical and empirical accounts of this relationship have conflicted. We attempted to resolve these conflicts by examining relationships of attentional abilities with responding to predictable and unpredictable threat, related but distinct motivational process implicated in a number of anxiety disorders. Eighty-one individuals completed a behavioral task assessing efficiency of three components of attention – alerting, orienting, and executive control (Attention Network Test - Revised). We also assessed startle responding during anticipation of both predictable, imminent threat (of mild electric shock) and unpredictable contextual threat. Faster alerting and slower disengaging from non-emotional attention cues were related to heightened responding to unpredictable threat, whereas poorer executive control of attention was related to heightened responding to predictable threat. This double dissociation helps to integrate models of attention and anxiety and may be informative for treatment development. PMID:27816781
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Nair, Sankaran N; Czaja, Sara J; Sharit, Joseph
2007-06-01
This article explores the role of age, cognitive abilities, prior experience, and knowledge in skill acquisition for a computer-based simulated customer service task. Fifty-two participants aged 50-80 performed the task over 4 consecutive days following training. They also completed a battery that assessed prior computer experience and cognitive abilities. The data indicated that overall quality and efficiency of performance improved with practice. The predictors of initial level of performance and rate of change in performance varied according to the performance parameter assessed. Age and fluid intelligence predicted initial level and rate of improvement in overall quality, whereas crystallized intelligence and age predicted initial e-mail processing time, and crystallized intelligence predicted rate of change in e-mail processing time over days. We discuss the implications of these findings for the design of intervention strategies.
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Empirical Evaluation of Hunk Metrics as Bug Predictors
NASA Astrophysics Data System (ADS)
Ferzund, Javed; Ahsan, Syed Nadeem; Wotawa, Franz
Reducing the number of bugs is a crucial issue during software development and maintenance. Software process and product metrics are good indicators of software complexity. These metrics have been used to build bug predictor models to help developers maintain the quality of software. In this paper we empirically evaluate the use of hunk metrics as predictor of bugs. We present a technique for bug prediction that works at smallest units of code change called hunks. We build bug prediction models using random forests, which is an efficient machine learning classifier. Hunk metrics are used to train the classifier and each hunk metric is evaluated for its bug prediction capabilities. Our classifier can classify individual hunks as buggy or bug-free with 86 % accuracy, 83 % buggy hunk precision and 77% buggy hunk recall. We find that history based and change level hunk metrics are better predictors of bugs than code level hunk metrics.
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Gunn, Jane; Wachtler, Caroline; Fletcher, Susan; Davidson, Sandra; Mihalopoulos, Cathrine; Palmer, Victoria; Hegarty, Kelsey; Coe, Amy; Murray, Elizabeth; Dowrick, Christopher; Andrews, Gavin; Chondros, Patty
2017-07-20
Depression is a highly prevalent and costly disorder. Effective treatments are available but are not always delivered to the right person at the right time, with both under- and over-treatment a problem. Up to half the patients presenting to general practice report symptoms of depression, but general practitioners have no systematic way of efficiently identifying level of need and allocating treatment accordingly. Therefore, our team developed a new clinical prediction tool (CPT) to assist with this task. The CPT predicts depressive symptom severity in three months' time and based on these scores classifies individuals into three groups (minimal/mild, moderate, severe), then provides a matched treatment recommendation. This study aims to test whether using the CPT reduces depressive symptoms at three months compared with usual care. The Target-D study is an individually randomized controlled trial. Participants will be 1320 general practice patients with depressive symptoms who will be approached in the practice waiting room by a research assistant and invited to complete eligibility screening on an iPad. Eligible patients will provide informed consent and complete the CPT on a purpose-built website. A computer-generated allocation sequence stratified by practice and depressive symptom severity group, will randomly assign participants to intervention (treatment recommendation matched to predicted depressive symptom severity group) or comparison (usual care plus Target-D attention control) arms. Follow-up assessments will be completed online at three and 12 months. The primary outcome is depressive symptom severity at three months. Secondary outcomes include anxiety, mental health self-efficacy, quality of life, and cost-effectiveness. Intention-to-treat analyses will test for differences in outcome means between study arms overall and by depressive symptom severity group. To our knowledge, this is the first depressive symptom stratification tool designed for primary care which takes a prognosis-based approach to provide a tailored treatment recommendation. If shown to be effective, this tool could be used to assist general practitioners to implement stepped mental-healthcare models and contribute to a more efficient and effective mental health system. Australian New Zealand Clinical Trials Registry (ANZCTR 12616000537459 ). Retrospectively registered on 27 April 2016. See Additional file 1 for trial registration data.
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Lehr, M E; Plisky, P J; Butler, R J; Fink, M L; Kiesel, K B; Underwood, F B
2013-08-01
In athletics, efficient screening tools are sought to curb the rising number of noncontact injuries and associated health care costs. The authors hypothesized that an injury prediction algorithm that incorporates movement screening performance, demographic information, and injury history can accurately categorize risk of noncontact lower extremity (LE) injury. One hundred eighty-three collegiate athletes were screened during the preseason. The test scores and demographic information were entered into an injury prediction algorithm that weighted the evidence-based risk factors. Athletes were then prospectively followed for noncontact LE injury. Subsequent analysis collapsed the groupings into two risk categories: Low (normal and slight) and High (moderate and substantial). Using these groups and noncontact LE injuries, relative risk (RR), sensitivity, specificity, and likelihood ratios were calculated. Forty-two subjects sustained a noncontact LE injury over the course of the study. Athletes identified as High Risk (n = 63) were at a greater risk of noncontact LE injury (27/63) during the season [RR: 3.4 95% confidence interval 2.0 to 6.0]. These results suggest that an injury prediction algorithm composed of performance on efficient, low-cost, field-ready tests can help identify individuals at elevated risk of noncontact LE injury. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
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Auer, Tibor; Schweizer, Renate; Frahm, Jens
2015-01-01
This study investigated the level of self-regulation of the somatomotor cortices (SMCs) attained by an extended functional magnetic resonance imaging (fMRI) neurofeedback training. Sixteen healthy subjects performed 12 real-time functional magnetic resonance imaging neurofeedback training sessions within 4 weeks, involving motor imagery of the dominant right as well as the non-dominant left hand. Target regions of interests in the SMC were individually localized prior to the training by overt finger movements. The feedback signal (FS) was defined as the difference between fMRI activation in the contra- and ipsilateral SMC and visually presented to the subjects. Training efficiency was determined by an off-line general linear model analysis determining the fMRI percent signal changes in the SMC target areas accomplished during the neurofeedback training. Transfer success was assessed by comparing the pre- and post-training transfer task, i.e., the neurofeedback paradigm without the presentation of the FS. Group results show a distinct increase in feedback performance (FP) in the transfer task for the trained group compared to a matched untrained control group, as well as an increase in the time course of the training, indicating an efficient training and a successful transfer. Individual analysis revealed that the training efficiency was not only highly correlated to the transfer success but also predictive. Trainings with at least 12 efficient training runs were associated with a successful transfer outcome. A group analysis of the hemispheric contributions to the FP showed that it is mainly driven by increased fMRI activation in the contralateral SMC, although some individuals relied on ipsilateral deactivation. Training and transfer results showed no difference between left- and right-hand imagery, with a slight indication of more ipsilateral deactivation in the early right-hand trainings. PMID:26500521
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Rosenthal, Sara Brin; Twomey, Colin R; Hartnett, Andrew T; Wu, Hai Shan; Couzin, Iain D
2015-04-14
Coordination among social animals requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the communication network. Establishing the decision-making circuits and networks that give rise to individual behavior has been a central goal of neuroscience. However, the analogous problem of determining the structure of the communication network among organisms that gives rise to coordinated collective behavior, such as is exhibited by schooling fish and flocking birds, has remained almost entirely neglected. Here, we study collective evasion maneuvers, manifested through rapid waves, or cascades, of behavioral change (a ubiquitous behavior among taxa) in schooling fish (Notemigonus crysoleucas). We automatically track the positions and body postures, calculate visual fields of all individuals in schools of ∼150 fish, and determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals use simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates throughout groups are complex, being weighted, directed, and heterogeneous. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion and establish that individuals with relatively few, but strongly connected, neighbors are both most socially influential and most susceptible to social influence. Furthermore, we demonstrate that we can predict complex cascades of behavioral change at their moment of initiation, before they actually occur. Consequently, despite the intrinsic stochasticity of individual behavior, establishing the hidden communication networks in large self-organized groups facilitates a quantitative understanding of behavioral contagion.
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Rosenthal, Sara Brin; Twomey, Colin R.; Hartnett, Andrew T.; Wu, Hai Shan; Couzin, Iain D.
2015-01-01
Coordination among social animals requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the communication network. Establishing the decision-making circuits and networks that give rise to individual behavior has been a central goal of neuroscience. However, the analogous problem of determining the structure of the communication network among organisms that gives rise to coordinated collective behavior, such as is exhibited by schooling fish and flocking birds, has remained almost entirely neglected. Here, we study collective evasion maneuvers, manifested through rapid waves, or cascades, of behavioral change (a ubiquitous behavior among taxa) in schooling fish (Notemigonus crysoleucas). We automatically track the positions and body postures, calculate visual fields of all individuals in schools of ∼150 fish, and determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals use simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates throughout groups are complex, being weighted, directed, and heterogeneous. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion and establish that individuals with relatively few, but strongly connected, neighbors are both most socially influential and most susceptible to social influence. Furthermore, we demonstrate that we can predict complex cascades of behavioral change at their moment of initiation, before they actually occur. Consequently, despite the intrinsic stochasticity of individual behavior, establishing the hidden communication networks in large self-organized groups facilitates a quantitative understanding of behavioral contagion. PMID:25825752
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Algorithms for selecting informative marker panels for population assignment.
Rosenberg, Noah A
2005-11-01
Given a set of potential source populations, genotypes of an individual of unknown origin at a collection of markers can be used to predict the correct source population of the individual. For improved efficiency, informative markers can be chosen from a larger set of markers to maximize the accuracy of this prediction. However, selecting the loci that are individually most informative does not necessarily produce the optimal panel. Here, using genotypes from eight species--carp, cat, chicken, dog, fly, grayling, human, and maize--this univariate accumulation procedure is compared to new multivariate "greedy" and "maximin" algorithms for choosing marker panels. The procedures generally suggest similar panels, although the greedy method often recommends inclusion of loci that are not chosen by the other algorithms. In seven of the eight species, when applied to five or more markers, all methods achieve at least 94% assignment accuracy on simulated individuals, with one species--dog--producing this level of accuracy with only three markers, and the eighth species--human--requiring approximately 13-16 markers. The new algorithms produce substantial improvements over use of randomly selected markers; where differences among the methods are noticeable, the greedy algorithm leads to slightly higher probabilities of correct assignment. Although none of the approaches necessarily chooses the panel with optimal performance, the algorithms all likely select panels with performance near enough to the maximum that they all are suitable for practical use.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Masanet, Eric; Therkelsen, Peter; Worrell, Ernst
The U.S. baking industry—defined in this Energy Guide as facilities engaged in the manufacture of commercial bakery products such as breads, rolls, frozen cakes, pies, pastries, and cookies and crackers—consumes over $800 million worth of purchased fuels and electricity per year. Energy efficiency improvement is an important way to reduce these costs and to increase predictable earnings, especially in times of high energy price volatility. There are a variety of opportunities available at individual plants to reduce energy consumption in a cost-effective manner. This Energy Guide discusses energy efficiency practices and energy-efficient technologies that can be implemented at the component,more » process, facility, and organizational levels. Many measure descriptions include expected savings in energy and energy-related costs, based on case study data from real-world applications in food processing facilities and related industries worldwide. Typical measure payback periods and references to further information in the technical literature are also provided, when available. A summary of basic, proven measures for improving plant-level water efficiency is also provided. The information in this Energy Guide is intended to help energy and plant managers in the U.S. baking industry reduce energy and water consumption in a cost-effective manner while maintaining the quality of products manufactured. Further research on the economics of all measures—as well as on their applicability to different production practices—is needed to assess their cost effectiveness at individual plants.« less
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Paul, Keryn I; Roxburgh, Stephen H; Chave, Jerome; England, Jacqueline R; Zerihun, Ayalsew; Specht, Alison; Lewis, Tom; Bennett, Lauren T; Baker, Thomas G; Adams, Mark A; Huxtable, Dan; Montagu, Kelvin D; Falster, Daniel S; Feller, Mike; Sochacki, Stan; Ritson, Peter; Bastin, Gary; Bartle, John; Wildy, Dan; Hobbs, Trevor; Larmour, John; Waterworth, Rob; Stewart, Hugh T L; Jonson, Justin; Forrester, David I; Applegate, Grahame; Mendham, Daniel; Bradford, Matt; O'Grady, Anthony; Green, Daryl; Sudmeyer, Rob; Rance, Stan J; Turner, John; Barton, Craig; Wenk, Elizabeth H; Grove, Tim; Attiwill, Peter M; Pinkard, Elizabeth; Butler, Don; Brooksbank, Kim; Spencer, Beren; Snowdon, Peter; O'Brien, Nick; Battaglia, Michael; Cameron, David M; Hamilton, Steve; McAuthur, Geoff; Sinclair, Jenny
2016-06-01
Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above-ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalization (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9-356 Mg ha(-1) ). Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species-specific models is only warranted when gains in accuracy of stand-based predictions are relatively high (e.g. high-value monocultures). © 2015 John Wiley & Sons Ltd.
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Fine-Scale Variation and Genetic Determinants of Alternative Splicing across Individuals
Coulombe-Huntington, Jasmin; Lam, Kevin C. L.; Dias, Christel; Majewski, Jacek
2009-01-01
Recently, thanks to the increasing throughput of new technologies, we have begun to explore the full extent of alternative pre–mRNA splicing (AS) in the human transcriptome. This is unveiling a vast layer of complexity in isoform-level expression differences between individuals. We used previously published splicing sensitive microarray data from lymphoblastoid cell lines to conduct an in-depth analysis on splicing efficiency of known and predicted exons. By combining publicly available AS annotation with a novel algorithm designed to search for AS, we show that many real AS events can be detected within the usually unexploited, speculative majority of the array and at significance levels much below standard multiple-testing thresholds, demonstrating that the extent of cis-regulated differential splicing between individuals is potentially far greater than previously reported. Specifically, many genes show subtle but significant genetically controlled differences in splice-site usage. PCR validation shows that 42 out of 58 (72%) candidate gene regions undergo detectable AS, amounting to the largest scale validation of isoform eQTLs to date. Targeted sequencing revealed a likely causative SNP in most validated cases. In all 17 incidences where a SNP affected a splice-site region, in silico splice-site strength modeling correctly predicted the direction of the micro-array and PCR results. In 13 other cases, we identified likely causative SNPs disrupting predicted splicing enhancers. Using Fst and REHH analysis, we uncovered significant evidence that 2 putative causative SNPs have undergone recent positive selection. We verified the effect of five SNPs using in vivo minigene assays. This study shows that splicing differences between individuals, including quantitative differences in isoform ratios, are frequent in human populations and that causative SNPs can be identified using in silico predictions. Several cases affected disease-relevant genes and it is likely some of these differences are involved in phenotypic diversity and susceptibility to complex diseases. PMID:20011102
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Design of Supersonic Transport Flap Systems for Thrust Recovery at Subsonic Speeds
NASA Technical Reports Server (NTRS)
Mann, Michael J.; Carlson, Harry W.; Domack, Christopher S.
1999-01-01
A study of the subsonic aerodynamics of hinged flap systems for supersonic cruise commercial aircraft has been conducted using linear attached-flow theory that has been modified to include an estimate of attainable leading edge thrust and an approximate representation of vortex forces. Comparisons of theoretical predictions with experimental results show that the theory gives a reasonably good and generally conservative estimate of the performance of an efficient flap system and provides a good estimate of the leading and trailing-edge deflection angles necessary for optimum performance. A substantial reduction in the area of the inboard region of the leading edge flap has only a minor effect on the performance and the optimum deflection angles. Changes in the size of the outboard leading-edge flap show that performance is greatest when this flap has a chord equal to approximately 30 percent of the wing chord. A study was also made of the performance of various combinations of individual leading and trailing-edge flaps, and the results show that aerodynamic efficiencies as high as 85 percent of full suction are predicted.
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Efficient hash tables for network applications.
Zink, Thomas; Waldvogel, Marcel
2015-01-01
Hashing has yet to be widely accepted as a component of hard real-time systems and hardware implementations, due to still existing prejudices concerning the unpredictability of space and time requirements resulting from collisions. While in theory perfect hashing can provide optimal mapping, in practice, finding a perfect hash function is too expensive, especially in the context of high-speed applications. The introduction of hashing with multiple choices, d-left hashing and probabilistic table summaries, has caused a shift towards deterministic DRAM access. However, high amounts of rare and expensive high-speed SRAM need to be traded off for predictability, which is infeasible for many applications. In this paper we show that previous suggestions suffer from the false precondition of full generality. Our approach exploits four individual degrees of freedom available in many practical applications, especially hardware and high-speed lookups. This reduces the requirement of on-chip memory up to an order of magnitude and guarantees constant lookup and update time at the cost of only minute amounts of additional hardware. Our design makes efficient hash table implementations cheaper, more predictable, and more practical.
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A New Method for Predicting Patient Survivorship Using Efficient Bayesian Network Learning
Jiang, Xia; Xue, Diyang; Brufsky, Adam; Khan, Seema; Neapolitan, Richard
2014-01-01
The purpose of this investigation is to develop and evaluate a new Bayesian network (BN)-based patient survivorship prediction method. The central hypothesis is that the method predicts patient survivorship well, while having the capability to handle high-dimensional data and be incorporated into a clinical decision support system (CDSS). We have developed EBMC_Survivorship (EBMC_S), which predicts survivorship for each year individually. EBMC_S is based on the EBMC BN algorithm, which has been shown to handle high-dimensional data. BNs have excellent architecture for decision support systems. In this study, we evaluate EBMC_S using the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset, which concerns breast tumors. A 5-fold cross-validation study indicates that EMBC_S performs better than the Cox proportional hazard model and is comparable to the random survival forest method. We show that EBMC_S provides additional information such as sensitivity analyses, which covariates predict each year, and yearly areas under the ROC curve (AUROCs). We conclude that our investigation supports the central hypothesis. PMID:24558297
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A new method for predicting patient survivorship using efficient bayesian network learning.
Jiang, Xia; Xue, Diyang; Brufsky, Adam; Khan, Seema; Neapolitan, Richard
2014-01-01
The purpose of this investigation is to develop and evaluate a new Bayesian network (BN)-based patient survivorship prediction method. The central hypothesis is that the method predicts patient survivorship well, while having the capability to handle high-dimensional data and be incorporated into a clinical decision support system (CDSS). We have developed EBMC_Survivorship (EBMC_S), which predicts survivorship for each year individually. EBMC_S is based on the EBMC BN algorithm, which has been shown to handle high-dimensional data. BNs have excellent architecture for decision support systems. In this study, we evaluate EBMC_S using the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset, which concerns breast tumors. A 5-fold cross-validation study indicates that EMBC_S performs better than the Cox proportional hazard model and is comparable to the random survival forest method. We show that EBMC_S provides additional information such as sensitivity analyses, which covariates predict each year, and yearly areas under the ROC curve (AUROCs). We conclude that our investigation supports the central hypothesis.
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Gorman Ng, Melanie; Semple, Sean; Cherrie, John W; Christopher, Yvette; Northage, Christine; Tielemans, Erik; Veroughstraete, Violaine; Van Tongeren, Martie
2012-11-01
Occupational inadvertent ingestion exposure is ingestion exposure due to contact between the mouth and contaminated hands or objects. Although individuals are typically oblivious to their exposure by this route, it is a potentially significant source of occupational exposure for some substances. Due to the continual flux of saliva through the oral cavity and the non-specificity of biological monitoring to routes of exposure, direct measurement of exposure by the inadvertent ingestion route is challenging; predictive models may be required to assess exposure. The work described in this manuscript has been carried out as part of a project to develop a predictive model for estimating inadvertent ingestion exposure in the workplace. As inadvertent ingestion exposure mainly arises from hand-to-mouth contact, it is closely linked to dermal exposure. We present a new integrated conceptual model for dermal and inadvertent ingestion exposure that should help to increase our understanding of ingestion exposure and our ability to simultaneously estimate exposure by the dermal and ingestion routes. The conceptual model consists of eight compartments (source, air, surface contaminant layer, outer clothing contaminant layer, inner clothing contaminant layer, hands and arms layer, perioral layer, and oral cavity) and nine mass transport processes (emission, deposition, resuspension or evaporation, transfer, removal, redistribution, decontamination, penetration and/or permeation, and swallowing) that describe event-based movement of substances between compartments (e.g. emission, deposition, etc.). This conceptual model is intended to guide the development of predictive exposure models that estimate exposure from both the dermal and the inadvertent ingestion pathways. For exposure by these pathways the efficiency of transfer of materials between compartments (for example from surfaces to hands, or from hands to the mouth) are important determinants of exposure. A database of transfer efficiency data relevant for dermal and inadvertent ingestion exposure was developed, containing 534 empirically measured transfer efficiencies measured between 1980 and 2010 and reported in the peer-reviewed and grey literature. The majority of the reported transfer efficiencies (84%) relate to transfer between surfaces and hands, but the database also includes efficiencies for other transfer scenarios, including surface-to-glove, hand-to-mouth, and skin-to-skin. While the conceptual model can provide a framework for a predictive exposure assessment model, the database provides detailed information on transfer efficiencies between the various compartments. Together, the conceptual model and the database provide a basis for the development of a quantitative tool to estimate inadvertent ingestion exposure in the workplace.
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Typical action perception and interpretation without motor simulation.
Vannuscorps, Gilles; Caramazza, Alfonso
2016-01-05
Every day, we interact with people synchronously, immediately understand what they are doing, and easily infer their mental state and the likely outcome of their actions from their kinematics. According to various motor simulation theories of perception, such efficient perceptual processing of others' actions cannot be achieved by visual analysis of the movements alone but requires a process of motor simulation--an unconscious, covert imitation of the observed movements. According to this hypothesis, individuals incapable of simulating observed movements in their motor system should have difficulty perceiving and interpreting observed actions. Contrary to this prediction, we found across eight sensitive experiments that individuals born with absent or severely shortened upper limbs (upper limb dysplasia), despite some variability, could perceive, anticipate, predict, comprehend, and memorize upper limb actions, which they cannot simulate, as efficiently as typically developed participants. We also found that, like the typically developed participants, the dysplasic participants systematically perceived the position of moving upper limbs slightly ahead of their real position but only when the anticipated position was not biomechanically awkward. Such anticipatory bias and its modulation by implicit knowledge of the body biomechanical constraints were previously considered as indexes of the crucial role of motor simulation in action perception. Our findings undermine this assumption and the theories that place the locus of action perception and comprehension in the motor system and invite a shift in the focus of future research to the question of how the visuo-perceptual system represents and processes observed body movements and actions.
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An accurate method for measuring triploidy of larval fish spawns
Jenkins, Jill A.; Draugelis-Dale, Rassa O.; Glennon, Robert; Kelly, Anita; Brown, Bonnie L.; Morrison, John
2017-01-01
A standard flow cytometric protocol was developed for estimating triploid induction in batches of larval fish. Polyploid induction treatments are not guaranteed to be 100% efficient, thus the ability to quantify the proportion of triploid larvae generated by a particular treatment helps managers to stock high-percentage spawns and researchers to select treatments for efficient triploid induction. At 3 d posthatch, individual Grass Carp Ctenopharyngodon idella were mechanically dissociated into single-cell suspensions; nuclear DNA was stained with propidium iodide then analyzed by flow cytometry. Following ploidy identification of individuals, aliquots of diploid and triploid cell suspensions were mixed to generate 15 levels (0–100%) of known triploidy (n = 10). Using either 20 or 50 larvae per level, the observed triploid percentages were lower than the known, actual values. Using nonlinear regression analyses, quadratic equations solved for triploid proportions in mixed samples and corresponding estimation reference plots allowed for predicting triploidy. Thus, an accurate prediction of the proportion of triploids in a spawn can be made by following a standard larval processing and analysis protocol with either 20 or 50 larvae from a single spawn, coupled with applying the quadratic equations or reference plots to observed flow cytometry results. Due to the universality of triploid DNA content being 1.5 times the diploid level and because triploid fish consist of fewer cells than diploids, this method should be applicable to other produced triploid fish species, and it may be adapted for use with bivalves or other species where batch analysis is appropriate.
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Typical action perception and interpretation without motor simulation
Vannuscorps, Gilles; Caramazza, Alfonso
2016-01-01
Every day, we interact with people synchronously, immediately understand what they are doing, and easily infer their mental state and the likely outcome of their actions from their kinematics. According to various motor simulation theories of perception, such efficient perceptual processing of others’ actions cannot be achieved by visual analysis of the movements alone but requires a process of motor simulation—an unconscious, covert imitation of the observed movements. According to this hypothesis, individuals incapable of simulating observed movements in their motor system should have difficulty perceiving and interpreting observed actions. Contrary to this prediction, we found across eight sensitive experiments that individuals born with absent or severely shortened upper limbs (upper limb dysplasia), despite some variability, could perceive, anticipate, predict, comprehend, and memorize upper limb actions, which they cannot simulate, as efficiently as typically developed participants. We also found that, like the typically developed participants, the dysplasic participants systematically perceived the position of moving upper limbs slightly ahead of their real position but only when the anticipated position was not biomechanically awkward. Such anticipatory bias and its modulation by implicit knowledge of the body biomechanical constraints were previously considered as indexes of the crucial role of motor simulation in action perception. Our findings undermine this assumption and the theories that place the locus of action perception and comprehension in the motor system and invite a shift in the focus of future research to the question of how the visuo-perceptual system represents and processes observed body movements and actions. PMID:26699468
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Sahni, A K; Nagendra, A; Roy, Partha; Patrikar, S
2014-07-01
Standard HIV testing is done using serum or plasma. FDA approved ELISA to screen urine for IgG antibodies to HIV-1 in 1996. It is a simple, noninvasive test and is appropriate for developing countries where health care personnel may not be professionally trained or where clean needles for drawing blood may not always be available. 436 individuals with high-risk behavior and strong clinical suspicion of HIV infection were screened for IgG antibodies to HIV-1 in urine by ELISA. Urine HIV testing was performed by enzyme immunoassay, at the ongoing Voluntary Confidential Counseling and Testing Center (VCCTC) at a large tertiary care microbiology lab. The individuals enrolled for the study had high-risk exposure to the virus and majorities were from a state with a high incidence of HIV infection. In all individuals, both serum and urine were tested for IgG antibodies to HIV-1. Overall, 135 individuals (30.96%) were HIV-positive, of whom 96 (71%) had never previously tested positive; 87% of those who tested positive received their results, and most were referred for medical care. Sensitivity, specificity and predictive values of HIV-1 urine ELISA test kit were determined. Sensitivity was found to be 89.6%; 95% CI [82.9-94.0], specificity 97.3%; 95% CI [94.6-98.8], positive predictive value 93.8%; 95% CI [87.8-97.1] and negative predictive value 95.4%; 95% CI [92.3-97.4]. Efficiency, sensitivity, and specificity of the urine-based screening for HIV-1 test kits were excellent as compared to the reference test.
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Prefrontal Cortex Structure Predicts Training-Induced Improvements in Multitasking Performance.
Verghese, Ashika; Garner, K G; Mattingley, Jason B; Dux, Paul E
2016-03-02
The ability to perform multiple, concurrent tasks efficiently is a much-desired cognitive skill, but one that remains elusive due to the brain's inherent information-processing limitations. Multitasking performance can, however, be greatly improved through cognitive training (Van Selst et al., 1999, Dux et al., 2009). Previous studies have examined how patterns of brain activity change following training (for review, see Kelly and Garavan, 2005). Here, in a large-scale human behavioral and imaging study of 100 healthy adults, we tested whether multitasking training benefits, assessed using a standard dual-task paradigm, are associated with variability in brain structure. We found that the volume of the rostral part of the left dorsolateral prefrontal cortex (DLPFC) predicted an individual's response to training. Critically, this association was observed exclusively in a task-specific training group, and not in an active-training control group. Our findings reveal a link between DLPFC structure and an individual's propensity to gain from training on a task that taps the limits of cognitive control. Cognitive "brain" training is a rapidly growing, multibillion dollar industry (Hayden, 2012) that has been touted as the panacea for a variety of disorders that result in cognitive decline. A key process targeted by such training is "cognitive control." Here, we combined an established cognitive control measure, multitasking ability, with structural brain imaging in a sample of 100 participants. Our goal was to determine whether individual differences in brain structure predict the extent to which people derive measurable benefits from a cognitive training regime. Ours is the first study to identify a structural brain marker-volume of left hemisphere dorsolateral prefrontal cortex-associated with the magnitude of multitasking performance benefits induced by training at an individual level. Copyright © 2016 the authors 0270-6474/16/362638-08$15.00/0.
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Development of a brain MRI-based hidden Markov model for dementia recognition.
Chen, Ying; Pham, Tuan D
2013-01-01
Dementia is an age-related cognitive decline which is indicated by an early degeneration of cortical and sub-cortical structures. Characterizing those morphological changes can help to understand the disease development and contribute to disease early prediction and prevention. But modeling that can best capture brain structural variability and can be valid in both disease classification and interpretation is extremely challenging. The current study aimed to establish a computational approach for modeling the magnetic resonance imaging (MRI)-based structural complexity of the brain using the framework of hidden Markov models (HMMs) for dementia recognition. Regularity dimension and semi-variogram were used to extract structural features of the brains, and vector quantization method was applied to convert extracted feature vectors to prototype vectors. The output VQ indices were then utilized to estimate parameters for HMMs. To validate its accuracy and robustness, experiments were carried out on individuals who were characterized as non-demented and mild Alzheimer's diseased. Four HMMs were constructed based on the cohort of non-demented young, middle-aged, elder and demented elder subjects separately. Classification was carried out using a data set including both non-demented and demented individuals with a wide age range. The proposed HMMs have succeeded in recognition of individual who has mild Alzheimer's disease and achieved a better classification accuracy compared to other related works using different classifiers. Results have shown the ability of the proposed modeling for recognition of early dementia. The findings from this research will allow individual classification to support the early diagnosis and prediction of dementia. By using the brain MRI-based HMMs developed in our proposed research, it will be more efficient, robust and can be easily used by clinicians as a computer-aid tool for validating imaging bio-markers for early prediction of dementia.
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Ferritin levels predict severe dengue.
Soundravally, R; Agieshkumar, B; Daisy, M; Sherin, J; Cleetus, C C
2015-02-01
Currently, no tests are available to monitor and predict severity and outcome of dengue. To find potential markers that predict dengue severity, the present study validated the serum level of three acute-phase proteins α-1 antitrypsin, ceruloplasmin and ferritin in a pool of severe dengue cases compared to non-severe forms and other febrile illness controls. A total of 96 patients were divided into two equal groups with group 'A' comprising dengue-infected cases and group 'B' with other febrile illness cases negative for dengue. Out of 48 dengue-infected cases, 13 had severe dengue and the remaining 35 were classified as non-severe dengue. Immunoassays were performed to evaluate the serum levels of acute-phase proteins both on the day of admission and on the day of defervescence. The efficiency of individual proteins in predicting the disease severity was assessed using receiver operating characteristic curve. The study did not find any significant difference in the levels of α-1 antitrypsin between the clinical groups. A significant increase in the levels of ceruloplasmin around defervescence in severe cases compared to non-severe and other febrile controls was observed and this is the first report describing the potential association of ceruloplasmin and dengue severity. Interestingly, a steady increase in the level of serum ferritin was recorded throughout the course of illness. Among all the three proteins, the elevated ferritin level could predict the disease severity with highest sensitivity and specificity of 76.9 and 83.3 %, respectively, on the day of admission and the same was found to be 90 and 91.6 % around defervescence. On the basis of this diagnostic efficiency, we propose that ferritin may serve as a potential biomarker for an early prediction of disease severity.
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Polarization resolved angular optical scattering of aerosol particles
NASA Astrophysics Data System (ADS)
Redding, B.; Pan, Y.; Wang, C.; Videen, G.; Cao, Hui
2014-05-01
Real-time detection and identification of bio-aerosol particles are crucial for the protection against chemical and biological agents. The strong elastic light scattering properties of airborne particles provides a natural means for rapid, non-invasive aerosol characterization. Recent theoretical predictions suggested that variations in the polarization dependent angular scattering cross section could provide an efficient means of classifying different airborne particles. In particular, the polarization dependent scattering cross section of aggregate particles is expected to depend on the shape of the primary particles. In order to experimentally validate this prediction, we built a high throughput, sampling system, capable of measuring the polarization resolved angular scattering cross section of individual aerosol particles flowing through an interrogating volume with a single shot of laser pulse. We calibrated the system by comparing the polarization dependent scattering cross section of individual polystyrene spheres with that predicted by Mie theory. We then used the system to study different particles types: Polystyrene aggregates composed 500 nm spheres and Bacillus subtilis (BG, Anthrax simulant) spores composed of elongated 500 nm × 1000 nm cylinder-line particles. We found that the polarization resolved scattering cross section depends on the shape of the constituent elements of the aggregates. This work indicates that the polarization resolved scattering cross section could be used for rapid discrimination between different bio-aerosol particles.
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Peters, N.E.; Freer, J.; Beven, K.
2003-01-01
Preliminary modelling results for a new version of the rainfall-runoff model TOPMODEL, dynamic TOPMODEL, are compared with those of the original TOPMODEL formulation for predicting streamflow at the Panola Mountain Research Watershed, Georgia. Dynamic TOPMODEL uses a kinematic wave routing of subsurface flow, which allows for dynamically variable upslope contributing areas, while retaining the concept of hydrological similarity to increase computational efficiency. Model performance in predicting discharge was assessed for the original TOPMODEL and for one landscape unit (LU) and three LU versions of the dynamic TOPMODEL (a bare rock area, hillslope with regolith <1 m, and a riparian zone with regolith ???5 m). All simulations used a 30 min time step for each of three water years. Each 1-LU model underpredicted the peak streamflow, and generally overpredicted recession streamflow during wet periods and underpredicted during dry periods. The difference between predicted recession streamflow generally was less for the dynamic TOPMODEL and smallest for the 3-LU model. Bayesian combination of results for different water years within the GLUE methodology left no behavioural original or 1-LU dynamic models and only 168 (of 96 000 sample parameter sets) for the 3-LU model. The efficiency for the streamflow prediction of the best 3-LU model was 0.83 for an individual year, but the results suggest that further improvements could be made. ?? 2003 John Wiley & Sons, Ltd.
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Can static foot posture measurements predict regional plantar surface area?
McPoil, Thomas G; Haager, Mathew; Hilt, John; Klapheke, John; Martinez, Ray; VanSteenwyk, Cory; Weber, Nicholas; Cornwall, Mark W; Bade, Michael
2014-12-01
The intent of this study was to determine if the use of a single or combination of static foot posture measurements can be used to predict rearfoot, midfoot, and forefoot plantar surface area in individuals with pronated or normal foot types. Twelve foot measurements were collected on 52 individuals (mean age 25.8 years) with the change in midfoot width used to place subjects in a pronated or normal foot mobility group. Dynamic plantar contact area was collected during walking with a pressure sensor platform. The 12 measures were entered into a stepwise regression analysis to determine the optimal set of measures associated with regional plantar surface area. A two variable model was found to describe the relationship between the foot measurements and forefoot plantar contact area (r(2)=0.79, p<0.0001). A four variable model was found to describe the relationship between the foot measurements and midfoot plantar contact area (r(2)=0.85, p<0.0001) in those individuals with a 1.26cm or greater change in midfoot width. The results indicate that clinicians can use a combination of simple, reliable and time efficient foot measures to explain 79% and 85% of the plantar surface area in the forefoot and midfoot, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Violent aggression predicted by multiple pre-adult environmental hits.
Mitjans, Marina; Seidel, Jan; Begemann, Martin; Bockhop, Fabian; Moya-Higueras, Jorge; Bansal, Vikas; Wesolowski, Janina; Seelbach, Anna; Ibáñez, Manuel Ignacio; Kovacevic, Fatka; Duvar, Oguzhan; Fañanás, Lourdes; Wolf, Hannah-Ulrike; Ortet, Generós; Zwanzger, Peter; Klein, Verena; Lange, Ina; Tänzer, Andreas; Dudeck, Manuela; Penke, Lars; van Elst, Ludger Tebartz; Bittner, Robert A; Schmidmeier, Richard; Freese, Roland; Müller-Isberner, Rüdiger; Wiltfang, Jens; Bliesener, Thomas; Bonn, Stefan; Poustka, Luise; Müller, Jürgen L; Arias, Bárbara; Ehrenreich, Hannelore
2018-05-24
Early exposure to negative environmental impact shapes individual behavior and potentially contributes to any mental disease. We reported previously that accumulated environmental risk markedly decreases age at schizophrenia onset. Follow-up of matched extreme group individuals (≤1 vs. ≥3 risks) unexpectedly revealed that high-risk subjects had >5 times greater probability of forensic hospitalization. In line with longstanding sociological theories, we hypothesized that risk accumulation before adulthood induces violent aggression and criminal conduct, independent of mental illness. We determined in 6 independent cohorts (4 schizophrenia and 2 general population samples) pre-adult risk exposure, comprising urbanicity, migration, physical and sexual abuse as primary, and cannabis or alcohol as secondary hits. All single hits by themselves were marginally associated with higher violent aggression. Most strikingly, however, their accumulation strongly predicted violent aggression (odds ratio 10.5). An epigenome-wide association scan to detect differential methylation of blood-derived DNA of selected extreme group individuals yielded overall negative results. Conversely, determination in peripheral blood mononuclear cells of histone-deacetylase1 mRNA as 'umbrella mediator' of epigenetic processes revealed an increase in the high-risk group, suggesting lasting epigenetic alterations. Together, we provide sound evidence of a disease-independent unfortunate relationship between well-defined pre-adult environmental hits and violent aggression, calling for more efficient prevention.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
None
Building simulations are increasingly used in various applications related to energy efficient buildings. For individual buildings, applications include: design of new buildings, prediction of retrofit savings, ratings, performance path code compliance and qualification for incentives. Beyond individual building applications, larger scale applications (across the stock of buildings at various scales: national, regional and state) include: codes and standards development, utility program design, regional/state planning, and technology assessments. For these sorts of applications, a set of representative buildings are typically simulated to predict performance of the entire population of buildings. Focusing on the U.S. single-family residential building stock, this paper willmore » describe how multiple data sources for building characteristics are combined into a highly-granular database that preserves the important interdependencies of the characteristics. We will present the sampling technique used to generate a representative set of thousands (up to hundreds of thousands) of building models. We will also present results of detailed calibrations against building stock consumption data.« less
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Wang, Zhiwei; Zeljic, Kristina; Jiang, Qinying; Gu, Yong; Wang, Wei; Wang, Zheng
2018-01-01
Ubiquitous variability between individuals in visual perception is difficult to standardize and has thus essentially been ignored. Here we construct a quantitative psychophysical measure of illusory rotary motion based on the Pinna-Brelstaff figure (PBF) in 73 healthy volunteers and investigate the neural circuit mechanisms underlying perceptual variation using functional magnetic resonance imaging (fMRI). We acquired fMRI data from a subset of 42 subjects during spontaneous and 3 stimulus conditions: expanding PBF, expanding modified-PBF (illusion-free) and expanding modified-PBF with physical rotation. Brain-wide graph analysis of stimulus-evoked functional connectivity patterns yielded a functionally segregated architecture containing 3 discrete hierarchical networks, commonly shared between rest and stimulation conditions. Strikingly, communication efficiency and strength between 2 networks predominantly located in visual areas robustly predicted individual perceptual differences solely in the illusory stimulus condition. These unprecedented findings demonstrate that stimulus-dependent, not spontaneous, dynamic functional integration between distributed brain networks contributes to perceptual variability in humans. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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The effects of climatic fluctuations and extreme events on running water ecosystems
Woodward, Guy; Bonada, Núria; Brown, Lee E.; Death, Russell G.; Durance, Isabelle; Gray, Clare; Hladyz, Sally; Ledger, Mark E.; Milner, Alexander M.; Ormerod, Steve J.; Thompson, Ross M.
2016-01-01
Most research on the effects of environmental change in freshwaters has focused on incremental changes in average conditions, rather than fluctuations or extreme events such as heatwaves, cold snaps, droughts, floods or wildfires, which may have even more profound consequences. Such events are commonly predicted to increase in frequency, intensity and duration with global climate change, with many systems being exposed to conditions with no recent historical precedent. We propose a mechanistic framework for predicting potential impacts of environmental fluctuations on running-water ecosystems by scaling up effects of fluctuations from individuals to entire ecosystems. This framework requires integration of four key components: effects of the environment on individual metabolism, metabolic and biomechanical constraints on fluctuating species interactions, assembly dynamics of local food webs, and mapping the dynamics of the meta-community onto ecosystem function. We illustrate the framework by developing a mathematical model of environmental fluctuations on dynamically assembling food webs. We highlight (currently limited) empirical evidence for emerging insights and theoretical predictions. For example, widely supported predictions about the effects of environmental fluctuations are: high vulnerability of species with high per capita metabolic demands such as large-bodied ones at the top of food webs; simplification of food web network structure and impaired energetic transfer efficiency; and reduced resilience and top-down relative to bottom-up regulation of food web and ecosystem processes. We conclude by identifying key questions and challenges that need to be addressed to develop more accurate and predictive bio-assessments of the effects of fluctuations, and implications of fluctuations for management practices in an increasingly uncertain world. PMID:27114576
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Brooks, M A; Harvey, R M; Johnson, N F; Kerley, M S
2012-12-01
We hypothesized that microbial efficiency and output from fermentation in the rumen would be optimized when peptide supply was balanced with peptide requirement of ruminal microflora. This study was conducted to measure response of varying rumen degradable peptide (RDPep) supply on ruminal fermentation characteristics and steer growth. A continuous culture experiment was conducted with diets formulated to achieve a predicted RDPep balance (RDPep supplied above RDPep required) of -0.30 to 1.45% CP with rumen degradable N (RDN) balance (RDN supplied above RDN required) above dietary ammonia-N requirement of microbes. Two additional treatments had RDPep balances of -0.30 and 0.78% CP with insufficient ammonia-N supply to meet microbial requirements. Single-flow fermenters (N = 24; n = 6) were inoculated with rumen fluid and maintained anaerobically at 39°C with a 0.06 h(-1) dilution rate. Inadequate RDN decreased OM digestion and microbial N flow, and increased rumen undegradable N (P < 0.01). Microbial efficiency decreased in RDN-deficient diets and was greatest when RDPep balance did not excessively exceed microbial requirement of RDPep predicted (P < 0.01). A growth study was conducted with 49 yearling, crossbred, Angus steers (initial BW 370 ± 34 kg). Animals were assigned to 1 of 4 treatment groups by BW and further divided into 3 pens with 4 steers per pen to achieve similar initial pen weights. Treatments consisted of 4 isonitrogenous diets balanced for RDN but varying in predicted RDPep balance (0.55%, -0.02%, -0.25%, and -0.65% CP). Animals were maintained on treatment for 70 d with individual BW taken on d 0, 1, 21, 42, 70, and 71. Final BW decreased linearly with decreasing RDPep (P = 0.05). Average daily gain and G:F displayed a quadratic effect with greater ADG and G:F at greater and lesser RDPep levels (P = 0.02). We concluded that balancing RDPep supply to predicted requirement improved fermentation efficiency and microbial output, which in turn improved animal performance.
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Genetic basis of between-individual and within-individual variance of docility.
Martin, J G A; Pirotta, E; Petelle, M B; Blumstein, D T
2017-04-01
Between-individual variation in phenotypes within a population is the basis of evolution. However, evolutionary and behavioural ecologists have mainly focused on estimating between-individual variance in mean trait and neglected variation in within-individual variance, or predictability of a trait. In fact, an important assumption of mixed-effects models used to estimate between-individual variance in mean traits is that within-individual residual variance (predictability) is identical across individuals. Individual heterogeneity in the predictability of behaviours is a potentially important effect but rarely estimated and accounted for. We used 11 389 measures of docility behaviour from 1576 yellow-bellied marmots (Marmota flaviventris) to estimate between-individual variation in both mean docility and its predictability. We then implemented a double hierarchical animal model to decompose the variances of both mean trait and predictability into their environmental and genetic components. We found that individuals differed both in their docility and in their predictability of docility with a negative phenotypic covariance. We also found significant genetic variance for both mean docility and its predictability but no genetic covariance between the two. This analysis is one of the first to estimate the genetic basis of both mean trait and within-individual variance in a wild population. Our results indicate that equal within-individual variance should not be assumed. We demonstrate the evolutionary importance of the variation in the predictability of docility and illustrate potential bias in models ignoring variation in predictability. We conclude that the variability in the predictability of a trait should not be ignored, and present a coherent approach for its quantification. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.
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Jiang, Xiaoqian; Aziz, Md Momin Al; Wang, Shuang; Mohammed, Noman
2018-01-01
Background Machine learning is an effective data-driven tool that is being widely used to extract valuable patterns and insights from data. Specifically, predictive machine learning models are very important in health care for clinical data analysis. The machine learning algorithms that generate predictive models often require pooling data from different sources to discover statistical patterns or correlations among different attributes of the input data. The primary challenge is to fulfill one major objective: preserving the privacy of individuals while discovering knowledge from data. Objective Our objective was to develop a hybrid cryptographic framework for performing regression analysis over distributed data in a secure and efficient way. Methods Existing secure computation schemes are not suitable for processing the large-scale data that are used in cutting-edge machine learning applications. We designed, developed, and evaluated a hybrid cryptographic framework, which can securely perform regression analysis, a fundamental machine learning algorithm using somewhat homomorphic encryption and a newly introduced secure hardware component of Intel Software Guard Extensions (Intel SGX) to ensure both privacy and efficiency at the same time. Results Experimental results demonstrate that our proposed method provides a better trade-off in terms of security and efficiency than solely secure hardware-based methods. Besides, there is no approximation error. Computed model parameters are exactly similar to plaintext results. Conclusions To the best of our knowledge, this kind of secure computation model using a hybrid cryptographic framework, which leverages both somewhat homomorphic encryption and Intel SGX, is not proposed or evaluated to this date. Our proposed framework ensures data security and computational efficiency at the same time. PMID:29506966
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Sadat, Md Nazmus; Jiang, Xiaoqian; Aziz, Md Momin Al; Wang, Shuang; Mohammed, Noman
2018-03-05
Machine learning is an effective data-driven tool that is being widely used to extract valuable patterns and insights from data. Specifically, predictive machine learning models are very important in health care for clinical data analysis. The machine learning algorithms that generate predictive models often require pooling data from different sources to discover statistical patterns or correlations among different attributes of the input data. The primary challenge is to fulfill one major objective: preserving the privacy of individuals while discovering knowledge from data. Our objective was to develop a hybrid cryptographic framework for performing regression analysis over distributed data in a secure and efficient way. Existing secure computation schemes are not suitable for processing the large-scale data that are used in cutting-edge machine learning applications. We designed, developed, and evaluated a hybrid cryptographic framework, which can securely perform regression analysis, a fundamental machine learning algorithm using somewhat homomorphic encryption and a newly introduced secure hardware component of Intel Software Guard Extensions (Intel SGX) to ensure both privacy and efficiency at the same time. Experimental results demonstrate that our proposed method provides a better trade-off in terms of security and efficiency than solely secure hardware-based methods. Besides, there is no approximation error. Computed model parameters are exactly similar to plaintext results. To the best of our knowledge, this kind of secure computation model using a hybrid cryptographic framework, which leverages both somewhat homomorphic encryption and Intel SGX, is not proposed or evaluated to this date. Our proposed framework ensures data security and computational efficiency at the same time. ©Md Nazmus Sadat, Xiaoqian Jiang, Md Momin Al Aziz, Shuang Wang, Noman Mohammed. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 05.03.2018.
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Social Communication and Vocal Recognition in Free-Ranging Rhesus Monkeys
NASA Astrophysics Data System (ADS)
Rendall, Christopher Andrew
Kinship and individual identity are key determinants of primate sociality, and the capacity for vocal recognition of individuals and kin is hypothesized to be an important adaptation facilitating intra-group social communication. Research was conducted on adult female rhesus monkeys on Cayo Santiago, Puerto Rico to test this hypothesis for three acoustically distinct calls characterized by varying selective pressures on communicating identity: coos (contact calls), grunts (close range social calls), and noisy screams (agonistic recruitment calls). Vocalization playback experiments confirmed a capacity for both individual and kin recognition of coos, but not screams (grunts were not tested). Acoustic analyses, using traditional spectrographic methods as well as linear predictive coding techniques, indicated that coos (but not grunts or screams) were highly distinctive, and that the effects of vocal tract filtering--formants --contributed more to statistical discriminations of both individuals and kin groups than did temporal or laryngeal source features. Formants were identified from very short (23 ms.) segments of coos and were stable within calls, indicating that formant cues to individual and kin identity were available throughout a call. This aspect of formant cues is predicted to be an especially important design feature for signaling identity efficiently in complex acoustic environments. Results of playback experiments involving manipulated coo stimuli provided preliminary perceptual support for the statistical inference that formant cues take precedence in facilitating vocal recognition. The similarity of formants among female kin suggested a mechanism for the development of matrilineal vocal signatures from the genetic and environmental determinants of vocal tract morphology shared among relatives. The fact that screams --calls strongly expected to communicate identity--were not individually distinctive nor recognized suggested the possibility that their acoustic structure and role in signaling identity might be constrained by functional or morphological design requirements associated with their role in signaling submission.
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Structural and functional correlates for language efficiency in auditory word processing.
Jung, JeYoung; Kim, Sunmi; Cho, Hyesuk; Nam, Kichun
2017-01-01
This study aims to provide convergent understanding of the neural basis of auditory word processing efficiency using a multimodal imaging. We investigated the structural and functional correlates of word processing efficiency in healthy individuals. We acquired two structural imaging (T1-weighted imaging and diffusion tensor imaging) and functional magnetic resonance imaging (fMRI) during auditory word processing (phonological and semantic tasks). Our results showed that better phonological performance was predicted by the greater thalamus activity. In contrary, better semantic performance was associated with the less activation in the left posterior middle temporal gyrus (pMTG), supporting the neural efficiency hypothesis that better task performance requires less brain activation. Furthermore, our network analysis revealed the semantic network including the left anterior temporal lobe (ATL), dorsolateral prefrontal cortex (DLPFC) and pMTG was correlated with the semantic efficiency. Especially, this network acted as a neural efficient manner during auditory word processing. Structurally, DLPFC and cingulum contributed to the word processing efficiency. Also, the parietal cortex showed a significate association with the word processing efficiency. Our results demonstrated that two features of word processing efficiency, phonology and semantics, can be supported in different brain regions and, importantly, the way serving it in each region was different according to the feature of word processing. Our findings suggest that word processing efficiency can be achieved by in collaboration of multiple brain regions involved in language and general cognitive function structurally and functionally.
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Structural and functional correlates for language efficiency in auditory word processing
Kim, Sunmi; Cho, Hyesuk; Nam, Kichun
2017-01-01
This study aims to provide convergent understanding of the neural basis of auditory word processing efficiency using a multimodal imaging. We investigated the structural and functional correlates of word processing efficiency in healthy individuals. We acquired two structural imaging (T1-weighted imaging and diffusion tensor imaging) and functional magnetic resonance imaging (fMRI) during auditory word processing (phonological and semantic tasks). Our results showed that better phonological performance was predicted by the greater thalamus activity. In contrary, better semantic performance was associated with the less activation in the left posterior middle temporal gyrus (pMTG), supporting the neural efficiency hypothesis that better task performance requires less brain activation. Furthermore, our network analysis revealed the semantic network including the left anterior temporal lobe (ATL), dorsolateral prefrontal cortex (DLPFC) and pMTG was correlated with the semantic efficiency. Especially, this network acted as a neural efficient manner during auditory word processing. Structurally, DLPFC and cingulum contributed to the word processing efficiency. Also, the parietal cortex showed a significate association with the word processing efficiency. Our results demonstrated that two features of word processing efficiency, phonology and semantics, can be supported in different brain regions and, importantly, the way serving it in each region was different according to the feature of word processing. Our findings suggest that word processing efficiency can be achieved by in collaboration of multiple brain regions involved in language and general cognitive function structurally and functionally. PMID:28892503
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Carrier transport and emission efficiency in InGaN quantum-dot based light-emitting diodes
NASA Astrophysics Data System (ADS)
Barettin, Daniele; Auf der Maur, Matthias; di Carlo, Aldo; Pecchia, Alessandro; Tsatsulnikov, Andrei F.; Lundin, Wsevolod V.; Sakharov, Alexei V.; Nikolaev, Andrei E.; Korytov, Maxim; Cherkashin, Nikolay; Hÿtch, Martin J.; Karpov, Sergey Yu
2017-07-01
We present a study of blue III-nitride light-emitting diodes (LEDs) with multiple quantum well (MQW) and quantum dot (QD) active regions (ARs), comparing experimental and theoretical results. The LED samples were grown by metalorganic vapor phase epitaxy, utilizing growth interruption in the hydrogen/nitrogen atmosphere and variable reactor pressure to control the AR microstructure. Realistic configuration of the QD AR implied in simulations was directly extracted from HRTEM characterization of the grown QD-based structures. Multi-scale 2D simulations of the carrier transport inside the multiple QD AR have revealed a non-trivial pathway for carrier injection into the dots. Electrons and holes are found to penetrate deep into the multi-layer AR through the gaps between individual QDs and get into the dots via their side edges rather than via top and bottom interfaces. This enables a more homogeneous carrier distribution among the dots situated in different layers than among the laterally uniform quantum well (QWs) in the MQW AR. As a result, a lower turn-on voltage is predicted for QD-based LEDs, as compared to MQW ones. Simulations did not show any remarkable difference in the efficiencies of the MQW and QD-based LEDs, if the same recombination coefficients are utilized, i.e. a similar crystal quality of both types of LED structures is assumed. Measurements of the current-voltage characteristics of LEDs with both kinds of the AR have shown their close similarity, in contrast to theoretical predictions. This implies the conventional assumption of laterally uniform QWs not to be likely an adequate approximation for the carrier transport in MQW LED structures. Optical characterization of MQW and QD-based LEDs has demonstrated that the later ones exhibit a higher efficiency, which could be attributed to better crystal quality of the grown QD-based structures. The difference in the crystal quality explains the recently observed correlation between the growth pressure of LED structures and their efficiency and should be taken into account while further comparing performances of MQW and QD-based LEDs. In contrast to experimental results, our simulations did not reveal any advantages of using QD-based ARs over the MQW ones, if the same recombination constants are assumed for both cases. This fact demonstrates importance of accounting for growth-dependent factors, like crystal quality, which may limit the device performance. Nevertheless, a more uniform carrier injection into multi-layer QD ARs predicted by modeling may serve as the basis for further improvement of LED efficiency by lowering carrier density in individual QDs and, hence, suppressing the Auger recombination losses.
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Carrier transport and emission efficiency in InGaN quantum-dot based light-emitting diodes.
Barettin, Daniele; Auf der Maur, Matthias; di Carlo, Aldo; Pecchia, Alessandro; Tsatsulnikov, Andrei F; Lundin, Wsevolod V; Sakharov, Alexei V; Nikolaev, Andrei E; Korytov, Maxim; Cherkashin, Nikolay; Hÿtch, Martin J; Karpov, Sergey Yu
2017-07-07
We present a study of blue III-nitride light-emitting diodes (LEDs) with multiple quantum well (MQW) and quantum dot (QD) active regions (ARs), comparing experimental and theoretical results. The LED samples were grown by metalorganic vapor phase epitaxy, utilizing growth interruption in the hydrogen/nitrogen atmosphere and variable reactor pressure to control the AR microstructure. Realistic configuration of the QD AR implied in simulations was directly extracted from HRTEM characterization of the grown QD-based structures. Multi-scale 2D simulations of the carrier transport inside the multiple QD AR have revealed a non-trivial pathway for carrier injection into the dots. Electrons and holes are found to penetrate deep into the multi-layer AR through the gaps between individual QDs and get into the dots via their side edges rather than via top and bottom interfaces. This enables a more homogeneous carrier distribution among the dots situated in different layers than among the laterally uniform quantum well (QWs) in the MQW AR. As a result, a lower turn-on voltage is predicted for QD-based LEDs, as compared to MQW ones. Simulations did not show any remarkable difference in the efficiencies of the MQW and QD-based LEDs, if the same recombination coefficients are utilized, i.e. a similar crystal quality of both types of LED structures is assumed. Measurements of the current-voltage characteristics of LEDs with both kinds of the AR have shown their close similarity, in contrast to theoretical predictions. This implies the conventional assumption of laterally uniform QWs not to be likely an adequate approximation for the carrier transport in MQW LED structures. Optical characterization of MQW and QD-based LEDs has demonstrated that the later ones exhibit a higher efficiency, which could be attributed to better crystal quality of the grown QD-based structures. The difference in the crystal quality explains the recently observed correlation between the growth pressure of LED structures and their efficiency and should be taken into account while further comparing performances of MQW and QD-based LEDs. In contrast to experimental results, our simulations did not reveal any advantages of using QD-based ARs over the MQW ones, if the same recombination constants are assumed for both cases. This fact demonstrates importance of accounting for growth-dependent factors, like crystal quality, which may limit the device performance. Nevertheless, a more uniform carrier injection into multi-layer QD ARs predicted by modeling may serve as the basis for further improvement of LED efficiency by lowering carrier density in individual QDs and, hence, suppressing the Auger recombination losses.
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Instrument for evaluation of sedentary lifestyle in patients with high blood pressure.
Lopes, Marcos Venícios de Oliveira; da Silva, Viviane Martins; de Araujo, Thelma Leite; Guedes, Nirla Gomes; Martins, Larissa Castelo Guedes; Teixeira, Iane Ximenes
2015-01-01
this article describes the diagnostic accuracy of the International Physical Activity Questionnaire to identify the nursing diagnosis of sedentary lifestyle. a diagnostic accuracy study was developed with 240 individuals with established high blood pressure. The analysis of diagnostic accuracy was based on measures of sensitivity, specificity, predictive values, likelihood ratios, efficiency, diagnostic odds ratio, Youden index, and area under the receiver-operating characteristic curve. statistical differences between genders were observed for activities of moderate intensity and for total physical activity. Age was negatively correlated with activities of moderate intensity and total physical activity. the analysis of area under the receiver-operating characteristic curve for moderate intensity activities, walking, and total physical activity showed that the International Physical Activity Questionnaire present moderate capacity to correctly classify individuals with and without sedentary lifestyle.
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Molecular profiling of single circulating tumor cells from lung cancer patients.
Park, Seung-Min; Wong, Dawson J; Ooi, Chin Chun; Kurtz, David M; Vermesh, Ophir; Aalipour, Amin; Suh, Susie; Pian, Kelsey L; Chabon, Jacob J; Lee, Sang Hun; Jamali, Mehran; Say, Carmen; Carter, Justin N; Lee, Luke P; Kuschner, Ware G; Schwartz, Erich J; Shrager, Joseph B; Neal, Joel W; Wakelee, Heather A; Diehn, Maximilian; Nair, Viswam S; Wang, Shan X; Gambhir, Sanjiv S
2016-12-27
Circulating tumor cells (CTCs) are established cancer biomarkers for the "liquid biopsy" of tumors. Molecular analysis of single CTCs, which recapitulate primary and metastatic tumor biology, remains challenging because current platforms have limited throughput, are expensive, and are not easily translatable to the clinic. Here, we report a massively parallel, multigene-profiling nanoplatform to compartmentalize and analyze hundreds of single CTCs. After high-efficiency magnetic collection of CTC from blood, a single-cell nanowell array performs CTC mutation profiling using modular gene panels. Using this approach, we demonstrated multigene expression profiling of individual CTCs from non-small-cell lung cancer (NSCLC) patients with remarkable sensitivity. Thus, we report a high-throughput, multiplexed strategy for single-cell mutation profiling of individual lung cancer CTCs toward minimally invasive cancer therapy prediction and disease monitoring.
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Cost-of-illness studies based on massive data: a prevalence-based, top-down regression approach.
Stollenwerk, Björn; Welchowski, Thomas; Vogl, Matthias; Stock, Stephanie
2016-04-01
Despite the increasing availability of routine data, no analysis method has yet been presented for cost-of-illness (COI) studies based on massive data. We aim, first, to present such a method and, second, to assess the relevance of the associated gain in numerical efficiency. We propose a prevalence-based, top-down regression approach consisting of five steps: aggregating the data; fitting a generalized additive model (GAM); predicting costs via the fitted GAM; comparing predicted costs between prevalent and non-prevalent subjects; and quantifying the stochastic uncertainty via error propagation. To demonstrate the method, it was applied to aggregated data in the context of chronic lung disease to German sickness funds data (from 1999), covering over 7.3 million insured. To assess the gain in numerical efficiency, the computational time of the innovative approach has been compared with corresponding GAMs applied to simulated individual-level data. Furthermore, the probability of model failure was modeled via logistic regression. Applying the innovative method was reasonably fast (19 min). In contrast, regarding patient-level data, computational time increased disproportionately by sample size. Furthermore, using patient-level data was accompanied by a substantial risk of model failure (about 80 % for 6 million subjects). The gain in computational efficiency of the innovative COI method seems to be of practical relevance. Furthermore, it may yield more precise cost estimates.
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Lesnik, Keaton Larson; Liu, Hong
2017-09-19
The complex interactions that occur in mixed-species bioelectrochemical reactors, like microbial fuel cells (MFCs), make accurate predictions of performance outcomes under untested conditions difficult. While direct correlations between any individual waste stream characteristic or microbial community structure and reactor performance have not been able to be directly established, the increase in sequencing data and readily available computational power enables the development of alternate approaches. In the current study, 33 MFCs were evaluated under a range of conditions including eight separate substrates and three different wastewaters. Artificial Neural Networks (ANNs) were used to establish mathematical relationships between wastewater/solution characteristics, biofilm communities, and reactor performance. ANN models that incorporated biotic interactions predicted reactor performance outcomes more accurately than those that did not. The average percent error of power density predictions was 16.01 ± 4.35%, while the average percent error of Coulombic efficiency and COD removal rate predictions were 1.77 ± 0.57% and 4.07 ± 1.06%, respectively. Predictions of power density improved to within 5.76 ± 3.16% percent error through classifying taxonomic data at the family versus class level. Results suggest that the microbial communities and performance of bioelectrochemical systems can be accurately predicted using data-mining, machine-learning techniques.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Geisz, John F.; France, Ryan M.; Steiner, Myles A.
Quantitative electroluminescence (EL) and luminescent coupling (LC) analysis, along with more conventional characterization techniques, are combined to completely characterize the subcell JV curves within a fourjunction (4J) inverted metamorphic solar cell (IMM). The 4J performance under arbitrary spectral conditions can be predicted from these subcell JV curves. The internal radiative efficiency (IRE) of each junction has been determined as a function of current density from the external radiative efficiency using optical modeling, but this required the accurate determination of the individual junction current densities during the EL measurement as affected by LC. These measurement and analysis techniques can be appliedmore » to any multijunction solar cell. The 4J IMM solar cell used to illustrate these techniques showed excellent junction quality as exhibited by high IRE and a one-sun AM1.5D efficiency of 36.3%. This device operates up to 1000 suns without limitations due to any of the three tunnel junctions.« less
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Using risk-adjustment models to identify high-cost risks.
Meenan, Richard T; Goodman, Michael J; Fishman, Paul A; Hornbrook, Mark C; O'Keeffe-Rosetti, Maureen C; Bachman, Donald J
2003-11-01
We examine the ability of various publicly available risk models to identify high-cost individuals and enrollee groups using multi-HMO administrative data. Five risk-adjustment models (the Global Risk-Adjustment Model [GRAM], Diagnostic Cost Groups [DCGs], Adjusted Clinical Groups [ACGs], RxRisk, and Prior-expense) were estimated on a multi-HMO administrative data set of 1.5 million individual-level observations for 1995-1996. Models produced distributions of individual-level annual expense forecasts for comparison to actual values. Prespecified "high-cost" thresholds were set within each distribution. The area under the receiver operating characteristic curve (AUC) for "high-cost" prevalences of 1% and 0.5% was calculated, as was the proportion of "high-cost" dollars correctly identified. Results are based on a separate 106,000-observation validation dataset. For "high-cost" prevalence targets of 1% and 0.5%, ACGs, DCGs, GRAM, and Prior-expense are very comparable in overall discrimination (AUCs, 0.83-0.86). Given a 0.5% prevalence target and a 0.5% prediction threshold, DCGs, GRAM, and Prior-expense captured $963,000 (approximately 3%) more "high-cost" sample dollars than other models. DCGs captured the most "high-cost" dollars among enrollees with asthma, diabetes, and depression; predictive performance among demographic groups (Medicaid members, members over 64, and children under 13) varied across models. Risk models can efficiently identify enrollees who are likely to generate future high costs and who could benefit from case management. The dollar value of improved prediction performance of the most accurate risk models should be meaningful to decision-makers and encourage their broader use for identifying high costs.
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Vanthournout, Bram; Greve, Michelle; Bruun, Anne; Bechsgaard, Jesper; Overgaard, Johannes; Bilde, Trine
2016-01-01
Group living carries a price: it inherently entails increased competition for resources and reproduction, and may also be associated with mating among relatives, which carries costs of inbreeding. Nonetheless, group living and sociality is found in many animals, and understanding the direct and indirect benefits of cooperation that override the inherent costs remains a challenge in evolutionary ecology. Individuals in groups may benefit from more efficient management of energy or water reserves, for example in the form of reduced water or heat loss from groups of animals huddling, or through reduced energy demands afforded by shared participation in tasks. We investigated the putative benefits of group living in the permanently social spider Stegodyphus dumicola by comparing the effect of group size on standard metabolic rate, lipid/protein content as a body condition measure, feeding efficiency, per capita web investment, and weight/water loss and survival during desiccation. Because energetic expenditure is temperature sensitive, some assays were performed under varying temperature conditions. We found that feeding efficiency increased with group size, and the rate of weight loss was higher in solitary individuals than in animals in groups of various sizes during desiccation. Interestingly, this was not translated into differences in survival or in standard metabolic rate. We did not detect any group size effects for other parameters, and group size effects did not co-vary with experimental temperature in a predictive manner. Both feeding efficiency and mass loss during desiccation are relevant ecological factors as the former results in lowered predator exposure time, and the latter benefits social spiders which occupy arid, hot environments. PMID:26869936
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NASA Technical Reports Server (NTRS)
English, Robert E; Cavicchi, Richard H
1951-01-01
Empirical methods of Ainley and Kochendorfer and Nettles were used to predict performances of nine turbine designs. Measured and predicted performances were compared. Appropriate values of blade-loss parameter were determined for the method of Kochendorfer and Nettles. The measured design-point efficiencies were lower than predicted by as much as 0.09 (Ainley and 0.07 (Kochendorfer and Nettles). For the method of Kochendorfer and Nettles, appropriate values of blade-loss parameter ranged from 0.63 to 0.87 and the off-design performance was accurately predicted.
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Models of social evolution: can we do better to predict 'who helps whom to achieve what'?
Rodrigues, António M M; Kokko, Hanna
2016-02-05
Models of social evolution and the evolution of helping have been classified in numerous ways. Two categorical differences have, however, escaped attention in the field. Models tend not to justify why they use a particular assumption structure about who helps whom: a large number of authors model peer-to-peer cooperation of essentially identical individuals, probably for reasons of mathematical convenience; others are inspired by particular cooperatively breeding species, and tend to assume unidirectional help where subordinates help a dominant breed more efficiently. Choices regarding what the help achieves (i.e. which life-history trait of the helped individual is improved) are similarly made without much comment: fecundity benefits are much more commonly modelled than survival enhancements, despite evidence that these may interact when the helped individual can perform life-history reallocations (load-lightening and related phenomena). We review our current theoretical understanding of effects revealed when explicitly asking 'who helps whom to achieve what', from models of mutual aid in partnerships to the very few models that explicitly contrast the strength of selection to help enhance another individual's fecundity or survival. As a result of idiosyncratic modelling choices in contemporary literature, including the varying degree to which demographic consequences are made explicit, there is surprisingly little agreement on what types of help are predicted to evolve most easily. We outline promising future directions to fill this gap. © 2016 The Author(s).
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Models of social evolution: can we do better to predict ‘who helps whom to achieve what’?
Rodrigues, António M. M.; Kokko, Hanna
2016-01-01
Models of social evolution and the evolution of helping have been classified in numerous ways. Two categorical differences have, however, escaped attention in the field. Models tend not to justify why they use a particular assumption structure about who helps whom: a large number of authors model peer-to-peer cooperation of essentially identical individuals, probably for reasons of mathematical convenience; others are inspired by particular cooperatively breeding species, and tend to assume unidirectional help where subordinates help a dominant breed more efficiently. Choices regarding what the help achieves (i.e. which life-history trait of the helped individual is improved) are similarly made without much comment: fecundity benefits are much more commonly modelled than survival enhancements, despite evidence that these may interact when the helped individual can perform life-history reallocations (load-lightening and related phenomena). We review our current theoretical understanding of effects revealed when explicitly asking ‘who helps whom to achieve what’, from models of mutual aid in partnerships to the very few models that explicitly contrast the strength of selection to help enhance another individual's fecundity or survival. As a result of idiosyncratic modelling choices in contemporary literature, including the varying degree to which demographic consequences are made explicit, there is surprisingly little agreement on what types of help are predicted to evolve most easily. We outline promising future directions to fill this gap. PMID:26729928
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Optimal Prediction in the Retina and Natural Motion Statistics
NASA Astrophysics Data System (ADS)
Salisbury, Jared M.; Palmer, Stephanie E.
2016-03-01
Almost all behaviors involve making predictions. Whether an organism is trying to catch prey, avoid predators, or simply move through a complex environment, the organism uses the data it collects through its senses to guide its actions by extracting from these data information about the future state of the world. A key aspect of the prediction problem is that not all features of the past sensory input have predictive power, and representing all features of the external sensory world is prohibitively costly both due to space and metabolic constraints. This leads to the hypothesis that neural systems are optimized for prediction. Here we describe theoretical and computational efforts to define and quantify the efficient representation of the predictive information by the brain. Another important feature of the prediction problem is that the physics of the world is diverse enough to contain a wide range of possible statistical ensembles, yet not all inputs are probable. Thus, the brain might not be a generalized predictive machine; it might have evolved to specifically solve the prediction problems most common in the natural environment. This paper summarizes recent results on predictive coding and optimal predictive information in the retina and suggests approaches for quantifying prediction in response to natural motion. Basic statistics of natural movies reveal that general patterns of spatiotemporal correlation are present across a wide range of scenes, though individual differences in motion type may be important for optimal processing of motion in a given ecological niche.
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NASA Astrophysics Data System (ADS)
Tsang, Sik-Ho; Chan, Yui-Lam; Siu, Wan-Chi
2017-01-01
Weighted prediction (WP) is an efficient video coding tool that was introduced since the establishment of the H.264/AVC video coding standard, for compensating the temporal illumination change in motion estimation and compensation. WP parameters, including a multiplicative weight and an additive offset for each reference frame, are required to be estimated and transmitted to the decoder by slice header. These parameters cause extra bits in the coded video bitstream. High efficiency video coding (HEVC) provides WP parameter prediction to reduce the overhead. Therefore, WP parameter prediction is crucial to research works or applications, which are related to WP. Prior art has been suggested to further improve the WP parameter prediction by implicit prediction of image characteristics and derivation of parameters. By exploiting both temporal and interlayer redundancies, we propose three WP parameter prediction algorithms, enhanced implicit WP parameter, enhanced direct WP parameter derivation, and interlayer WP parameter, to further improve the coding efficiency of HEVC. Results show that our proposed algorithms can achieve up to 5.83% and 5.23% bitrate reduction compared to the conventional scalable HEVC in the base layer for SNR scalability and 2× spatial scalability, respectively.
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RGAugury: a pipeline for genome-wide prediction of resistance gene analogs (RGAs) in plants.
Li, Pingchuan; Quan, Xiande; Jia, Gaofeng; Xiao, Jin; Cloutier, Sylvie; You, Frank M
2016-11-02
Resistance gene analogs (RGAs), such as NBS-encoding proteins, receptor-like protein kinases (RLKs) and receptor-like proteins (RLPs), are potential R-genes that contain specific conserved domains and motifs. Thus, RGAs can be predicted based on their conserved structural features using bioinformatics tools. Computer programs have been developed for the identification of individual domains and motifs from the protein sequences of RGAs but none offer a systematic assessment of the different types of RGAs. A user-friendly and efficient pipeline is needed for large-scale genome-wide RGA predictions of the growing number of sequenced plant genomes. An integrative pipeline, named RGAugury, was developed to automate RGA prediction. The pipeline first identifies RGA-related protein domains and motifs, namely nucleotide binding site (NB-ARC), leucine rich repeat (LRR), transmembrane (TM), serine/threonine and tyrosine kinase (STTK), lysin motif (LysM), coiled-coil (CC) and Toll/Interleukin-1 receptor (TIR). RGA candidates are identified and classified into four major families based on the presence of combinations of these RGA domains and motifs: NBS-encoding, TM-CC, and membrane associated RLP and RLK. All time-consuming analyses of the pipeline are paralleled to improve performance. The pipeline was evaluated using the well-annotated Arabidopsis genome. A total of 98.5, 85.2, and 100 % of the reported NBS-encoding genes, membrane associated RLPs and RLKs were validated, respectively. The pipeline was also successfully applied to predict RGAs for 50 sequenced plant genomes. A user-friendly web interface was implemented to ease command line operations, facilitate visualization and simplify result management for multiple datasets. RGAugury is an efficiently integrative bioinformatics tool for large scale genome-wide identification of RGAs. It is freely available at Bitbucket: https://bitbucket.org/yaanlpc/rgaugury .
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Riewe, E; Neubauer, E; Pfeifer, A C; Schiltenwolf, M
2016-01-01
10% of all individuals in Germany develop persistent symptoms due to nonspecific back pain (NSBP) causing up to 90% of direct and indirect expenses for health care systems. Evidence indicates a strong relationship between chronic nonspecific back pain and psychosocial risk factors. The Örebro Musculoskeletal Pain Screening Questionnaire (ÖMPSQ) and the German Heidelberger Kurzfragebogen Rückenschmerz (HKF-R 10) are deemed valid in prediction of persistent pain, functional loss or amount of sick leave. This study provides and discusses validity criteria for these questionnaires using ROC-curve analyses. Quality measurements included sensitivity and specificity, likelihood-ratio related test-efficiencies and clinical utility in regard to predictive values. 265 patients recruited from primary and secondary care units completed both questionnaires during the same timeframe. From the total, 133 patients returned a 6-month follow-up questionnaire to assess the validity criteria for outcomes of pain, function and sick leave. Based on heterogeneous cut-offs for the ÖMPSQ, sensitivity and specificity were moderate for outcome of pain (72%/75%). Very high sensitivity was observed for function (97%/57%) and high specificity for sick leave (63%/85%). The latter also applied to the HKF-R 10 (pain 50%/84%). Proportions between sensitivity and specificity were unbalanced except for the ÖMPSQ outcome of pain. Likelihood-ratios and positive predictive values ranged from low to moderate. Although the ÖMPSQ may be considered useful in identification of long-term functional loss or pain, over- and underestimation of patients at risk of chronic noncspecific back pain led to limited test-efficiencies and clinical utility for both questionnaires. Further studies are required to quantify the predictive validity of both questionnaires in Germany.
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Cheie, Lavinia; Veraksa, Aleksander; Zinchenko, Yuri; Gorovaya, Alexandra; Visu-Petra, Laura
2015-01-01
The current study focused on the early development of inhibitory control in 5- to 7-year-old children attending kindergarten in two Eastern-European countries, Romania and Russia. These two countries share many aspects of child-rearing and educational practices, previously documented to influence the development of inhibitory control. Using the Lurian-based developmental approach offered by the Developmental Neuropsychological Assessment battery, the study aimed to contribute to cross-cultural developmental neuropsychology by exploring (a) early interrelationships between subcomponents of inhibitory control (response suppression and attention control) and generative fluency (verbal and figural) in these two cultures, as well as (b) the predictive value of external factors (culture and maternal education) and individual differences (age, gender, nonverbal intelligence, trait anxiety) on inhibitory control and fluency outcomes in children from both countries. First, findings in both culture samples suggest that even at this young age, the construct of inhibitory control cannot be considered a unitary entity. Second, differences in maternal education were not predictive of either inhibitory control or fluency scores. However, children's attention control performance varied as a function of culture, and the direction of these cultural effects differed by whether the target outcome involved performance accuracy versus efficiency as an output. Findings also confirmed the previously documented intensive developmental improvement in preschoolers' inhibitory control during this period, influencing measures of response suppression and particularly attention control. Finally, the results further stress the importance of individual differences effects in trait anxiety on attention control efficiency across cultures.
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Data-driven forecasting algorithms for building energy consumption
NASA Astrophysics Data System (ADS)
Noh, Hae Young; Rajagopal, Ram
2013-04-01
This paper introduces two forecasting methods for building energy consumption data that are recorded from smart meters in high resolution. For utility companies, it is important to reliably forecast the aggregate consumption profile to determine energy supply for the next day and prevent any crisis. The proposed methods involve forecasting individual load on the basis of their measurement history and weather data without using complicated models of building system. The first method is most efficient for a very short-term prediction, such as the prediction period of one hour, and uses a simple adaptive time-series model. For a longer-term prediction, a nonparametric Gaussian process has been applied to forecast the load profiles and their uncertainty bounds to predict a day-ahead. These methods are computationally simple and adaptive and thus suitable for analyzing a large set of data whose pattern changes over the time. These forecasting methods are applied to several sets of building energy consumption data for lighting and heating-ventilation-air-conditioning (HVAC) systems collected from a campus building at Stanford University. The measurements are collected every minute, and corresponding weather data are provided hourly. The results show that the proposed algorithms can predict those energy consumption data with high accuracy.
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Effect of exit locations on ants escaping a two-exit room stressed with repellent
NASA Astrophysics Data System (ADS)
Wang, Shujie; Cao, Shuchao; Wang, Qiao; Lian, Liping; Song, Weiguo
2016-09-01
In order to investigate the effect of the distance between two exits on ant evacuation efficiency and the behavior of ants escaping from a two-exit room, we conducted ant egress experiments using Camponotus japonicus in multiple situations. We found that the ants demonstrated the phenomenon of "symmetry breaking" in this stress situation. It was also shown that different locations for the exits obviously affected the ants' egress efficiency by measuring the time intervals between individual egress and flow rate in eight repeated experiments, each of which contained five different distance between the two exits. In addition, it is demonstrated that there are differences between the predictions of Social Force Model of pedestrians and the behaviors of ants in stress conditions through comparing some important behavioral features, including position, trajectory, velocity, and density map.
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[Prediction of the efficiency of endoscopic lung volume reduction by valves in severe emphysema].
Bocquillon, V; Briault, A; Reymond, E; Arbib, F; Jankowski, A; Ferretti, G; Pison, C
2016-11-01
In severe emphysema, endoscopic lung volume reduction with valves is an alternative to surgery with less morbidity and mortality. In 2015, selection of patients who will respond to this technique is based on emphysema heterogeneity, a complete fissure visible on the CT-scan and absence of collateral ventilation between lobes. Our case report highlights that individualized prediction is possible. A 58-year-old woman had severe, disabling pulmonary emphysema. A high resolution thoracic computed tomography scan showed that the emphysema was heterogeneous, predominantly in the upper lobes, integrity of the left greater fissure and no collateral ventilation with the left lower lobe. A valve was inserted in the left upper lobe bronchus. At one year, clinical and functional benefits were significant with complete atelectasis of the treated lobe. The success of endoscopic lung volume reduction with a valve can be predicted, an example of personalized medicine. Copyright © 2016 SPLF. Published by Elsevier Masson SAS. All rights reserved.
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Accounting for receptor flexibility and enhanced sampling methods in computer-aided drug design.
Sinko, William; Lindert, Steffen; McCammon, J Andrew
2013-01-01
Protein flexibility plays a major role in biomolecular recognition. In many cases, it is not obvious how molecular structure will change upon association with other molecules. In proteins, these changes can be major, with large deviations in overall backbone structure, or they can be more subtle as in a side-chain rotation. Either way the algorithms that predict the favorability of biomolecular association require relatively accurate predictions of the bound structure to give an accurate assessment of the energy involved in association. Here, we review a number of techniques that have been proposed to accommodate receptor flexibility in the simulation of small molecules binding to protein receptors. We investigate modifications to standard rigid receptor docking algorithms and also explore enhanced sampling techniques, and the combination of free energy calculations and enhanced sampling techniques. The understanding and allowance for receptor flexibility are helping to make computer simulations of ligand protein binding more accurate. These developments may help improve the efficiency of drug discovery and development. Efficiency will be essential as we begin to see personalized medicine tailored to individual patients, which means specific drugs are needed for each patient's genetic makeup. © 2012 John Wiley & Sons A/S.
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Abdul-Razak, Suraya; Rahmat, Radzi; Mohd Kasim, Alicezah; Rahman, Thuhairah Abdul; Muid, Suhaila; Nasir, Nadzimah Mohd; Ibrahim, Zubin; Kasim, Sazzli; Ismail, Zaliha; Abdul Ghani, Rohana; Sanusi, Abdul Rais; Rosman, Azhari; Nawawi, Hapizah
2017-10-16
Familial hypercholesterolaemia (FH) is a genetic disorder with a high risk of developing premature coronary artery disease that should be diagnosed as early as possible. Several clinical diagnostic criteria for FH are available, with the Dutch Lipid Clinic Criteria (DLCC) being widely used. Information regarding diagnostic performances of the other criteria against the DLCC is scarce. We aimed to examine the diagnostic performance of the Simon-Broom (SB) Register criteria, the US Make Early Diagnosis to Prevent Early Deaths (US MEDPED) and the Japanese FH Management Criteria (JFHMC) compared to the DLCC. Seven hundered fifty five individuals from specialist clinics and community health screenings with LDL-c level ≥ 4.0 mmol/L were selected and diagnosed as FH using the DLCC, the SB Register criteria, the US MEDPED and the JFHMC. The sensitivity, specificity, efficiency, positive and negative predictive values of individuals screened with the SB register criteria, US MEDPED and JFHMC were assessed against the DLCC. We found the SB register criteria identified more individuals with FH compared to the US MEDPED and the JFHMC (212 vs. 105 vs. 195; p < 0.001) when assessed against the DLCC. The SB Register criteria, the US MEDPED and the JFHMC had low sensitivity (51.1% vs. 25.3% vs. 47.0% respectively). The SB Register criteria showed better diagnostic performance than the other criteria with 98.8% specificity, 28.6% efficiency value, 98.1% and 62.3% for positive and negative predictive values respectively. The SB Register criteria appears to be more useful in identifying positive cases leading to genetic testing compared to the JFHMC and US MEDPED in this Asian population. However, further research looking into a suitable diagnosis criterion with high likelihood of positive genetic findings is required in the Asian population including in Malaysia.
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The relations between sleep, time of physical activity, and time outdoors among adult women
Godbole, Suneeta; Natarajan, Loki; Full, Kelsie; Hipp, J. Aaron; Glanz, Karen; Mitchell, Jonathan; Laden, Francine; James, Peter; Quante, Mirja; Kerr, Jacqueline
2017-01-01
Physical activity and time spent outdoors may be important non-pharmacological approaches to improve sleep quality and duration (or sleep patterns) but there is little empirical research evaluating the two simultaneously. The current study assesses the role of physical activity and time outdoors in predicting sleep health by using objective measurement of the three variables. A convenience sample of 360 adult women (mean age = 55.38 ±9.89 years; mean body mass index = 27.74 ±6.12) was recruited from different regions of the U.S. Participants wore a Global Positioning System device and ActiGraph GT3X+ accelerometers on the hip for 7 days and on the wrist for 7 days and 7 nights to assess total time and time of day spent outdoors, total minutes in moderate-to-vigorous physical activity per day, and 4 measures of sleep health, respectively. A generalized mixed-effects model was used to assess temporal associations between moderate-to-vigorous physical activity, outdoor time, and sleep at the daily level (days = 1931) within individuals. There was a significant interaction (p = 0.04) between moderate-to-vigorous physical activity and time spent outdoors in predicting total sleep time but not for predicting sleep efficiency. Increasing time outdoors in the afternoon (versus morning) predicted lower sleep efficiency, but had no effect on total sleep time. Time spent outdoors and the time of day spent outdoors may be important moderators in assessing the relation between physical activity and sleep. More research is needed in larger populations using experimental designs. PMID:28877192
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The relations between sleep, time of physical activity, and time outdoors among adult women.
Murray, Kate; Godbole, Suneeta; Natarajan, Loki; Full, Kelsie; Hipp, J Aaron; Glanz, Karen; Mitchell, Jonathan; Laden, Francine; James, Peter; Quante, Mirja; Kerr, Jacqueline
2017-01-01
Physical activity and time spent outdoors may be important non-pharmacological approaches to improve sleep quality and duration (or sleep patterns) but there is little empirical research evaluating the two simultaneously. The current study assesses the role of physical activity and time outdoors in predicting sleep health by using objective measurement of the three variables. A convenience sample of 360 adult women (mean age = 55.38 ±9.89 years; mean body mass index = 27.74 ±6.12) was recruited from different regions of the U.S. Participants wore a Global Positioning System device and ActiGraph GT3X+ accelerometers on the hip for 7 days and on the wrist for 7 days and 7 nights to assess total time and time of day spent outdoors, total minutes in moderate-to-vigorous physical activity per day, and 4 measures of sleep health, respectively. A generalized mixed-effects model was used to assess temporal associations between moderate-to-vigorous physical activity, outdoor time, and sleep at the daily level (days = 1931) within individuals. There was a significant interaction (p = 0.04) between moderate-to-vigorous physical activity and time spent outdoors in predicting total sleep time but not for predicting sleep efficiency. Increasing time outdoors in the afternoon (versus morning) predicted lower sleep efficiency, but had no effect on total sleep time. Time spent outdoors and the time of day spent outdoors may be important moderators in assessing the relation between physical activity and sleep. More research is needed in larger populations using experimental designs.
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1/f neural noise and electrophysiological indices of contextual prediction in aging.
Dave, S; Brothers, T A; Swaab, T Y
2018-07-15
Prediction of upcoming words during reading has been suggested to enhance the efficiency of discourse processing. Emerging models have postulated that predictive mechanisms require synchronous firing of neural networks, but to date, this relationship has been investigated primarily through oscillatory activity in narrow frequency bands. A recently-developed measure proposed to reflect broadband neural activity - and thereby synchronous neuronal firing - is 1/f neural noise extracted from EEG spectral power. Previous research has indicated that this measure of 1/f neural noise changes across the lifespan, and these neural changes predict age-related behavioral impairments in visual working memory. Using a cross-sectional sample of young and older adults, we examined age-related changes in 1/f neural noise and whether this measure predicted ERP correlates of successful lexical prediction during discourse comprehension. 1/f neural noise across two different language tasks revealed high within-subject correlations, indicating that this measure can provide a reliable index of individualized patterns of neural activation. In addition to age, 1/f noise was a significant predictor of N400 effects of successful lexical prediction; however, noise did not mediate age-related declines in other ERP effects. We discuss broader implications of these findings for theories of predictive processing, as well as potential applications of 1/f noise across research populations. Copyright © 2018 Elsevier B.V. All rights reserved.
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Hurst exponent and prediction based on weak-form efficient market hypothesis of stock markets
NASA Astrophysics Data System (ADS)
Eom, Cheoljun; Choi, Sunghoon; Oh, Gabjin; Jung, Woo-Sung
2008-07-01
We empirically investigated the relationships between the degree of efficiency and the predictability in financial time-series data. The Hurst exponent was used as the measurement of the degree of efficiency, and the hit rate calculated from the nearest-neighbor prediction method was used for the prediction of the directions of future price changes. We used 60 market indexes of various countries. We empirically discovered that the relationship between the degree of efficiency (the Hurst exponent) and the predictability (the hit rate) is strongly positive. That is, a market index with a higher Hurst exponent tends to have a higher hit rate. These results suggested that the Hurst exponent is useful for predicting future price changes. Furthermore, we also discovered that the Hurst exponent and the hit rate are useful as standards that can distinguish emerging capital markets from mature capital markets.
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Connor, E E; Hutchison, J L; Norman, H D; Olson, K M; Van Tassell, C P; Leith, J M; Baldwin, R L
2013-08-01
Improved feed efficiency is a primary goal in dairy production to reduce feed costs and negative impacts of production on the environment. Estimates for efficiency of feed conversion to milk production based on residual feed intake (RFI) in dairy cattle are limited, primarily due to a lack of individual feed intake measurements for lactating cows. Feed intake was measured in Holstein cows during the first 90 d of lactation to estimate the heritability and repeatability of RFI, minimum test duration for evaluating RFI in early lactation, and its association with other production traits. Data were obtained from 453 lactations (214 heifers and 239 multiparous cows) from 292 individual cows from September 2007 to December 2011. Cows were housed in a free-stall barn and monitored for individual daily feed consumption using the GrowSafe 4000 System (GrowSafe Systems, Ltd., Airdrie, AB, Canada). Animals were fed a total mixed ration 3 times daily, milked twice daily, and weighed every 10 to 14 d. Milk yield was measured at each milking. Feed DM percentage was measured daily, and nutrient composition was analyzed from a weekly composite. Milk composition was analyzed weekly, alternating between morning and evening milking periods. Estimates of RFI were determined as the difference between actual energy intake and predicted intake based on a linear model with fixed effects of parity (1, 2, ≥ 3) and regressions on metabolic BW, ADG, and energy-corrected milk yield. Heritability was estimated to be moderate (0.36 ± 0.06), and repeatability was estimated at 0.56 across lactations. A test period through 53 d in milk (DIM) explained 81% of the variation provided by a test through 90 DIM. Multiple regression analysis indicated that high efficiency was associated with less time feeding per day and slower feeding rate, which may contribute to differences in RFI among cows. The heritability and repeatability of RFI suggest an opportunity to improve feed efficiency through genetic selection, which could reduce feed costs, manure output, and greenhouse gas emissions associated with dairy production.
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Fully Coupled Micro/Macro Deformation, Damage, and Failure Prediction for SiC/Ti-15-3 Laminates
NASA Technical Reports Server (NTRS)
Bednarcyk, Brett A.; Arnold, Steven M.; Lerch, Brad A.
2001-01-01
The deformation, failure, and low cycle fatigue life of SCS-6/Ti-15-3 composites are predicted using a coupled deformation and damage approach in the context of the analytical generalized method of cells (GMC) micromechanics model. The local effects of inelastic deformation, fiber breakage, fiber-matrix interfacial debonding, and fatigue damage are included as sub-models that operate on the micro scale for the individual composite phases. For the laminate analysis, lamination theory is employed as the global or structural scale model, while GMC is embedded to operate on the meso scale to simulate the behavior of the composite material within each laminate layer. While the analysis approach is quite complex and multifaceted, it is shown, through comparison with experimental data, to be quite accurate and realistic while remaining extremely efficient.
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Forecasting staffing needs for productivity management in hospital laboratories.
Pang, C Y; Swint, J M
1985-12-01
Daily and weekly prediction models are developed to help forecast hospital laboratory work load for the entire laboratory and individual sections of the laboratory. The models are tested using historical data obtained from hospital census and laboratory log books of a 90-bed southwestern hospital. The results indicate that the predictor variables account for 50%, 81%, 56%, and 82% of the daily work load variation for chemistry, hematology, and microbiology sections, and for the entire laboratory, respectively. Equivalent results for the weekly model are 53%, 72%, 12%, and 78% for the same respective sections. On the basis of the predicted work load, staffing assessment is made and a productivity monitoring system constructed. The purpose of such a system is to assist laboratory management in efforts to utilize laboratory manpower in a more efficient and cost-effective manner.
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Algorithms in the historical emergence of word senses.
Ramiro, Christian; Srinivasan, Mahesh; Malt, Barbara C; Xu, Yang
2018-03-06
Human language relies on a finite lexicon to express a potentially infinite set of ideas. A key result of this tension is that words acquire novel senses over time. However, the cognitive processes that underlie the historical emergence of new word senses are poorly understood. Here, we present a computational framework that formalizes competing views of how new senses of a word might emerge by attaching to existing senses of the word. We test the ability of the models to predict the temporal order in which the senses of individual words have emerged, using an historical lexicon of English spanning the past millennium. Our findings suggest that word senses emerge in predictable ways, following an historical path that reflects cognitive efficiency, predominantly through a process of nearest-neighbor chaining. Our work contributes a formal account of the generative processes that underlie lexical evolution.
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Goligher, Ewan C; Amato, Marcelo B P; Slutsky, Arthur S
2017-09-01
In clinical trials of therapies for acute respiratory distress syndrome (ARDS), the average treatment effect in the study population may be attenuated because individual patient responses vary widely. This inflates sample size requirements and increases the cost and difficulty of conducting successful clinical trials. One solution is to enrich the study population with patients most likely to benefit, based on predicted patient response to treatment (predictive enrichment). In this perspective, we apply the precision medicine paradigm to the emerging use of extracorporeal CO 2 removal (ECCO 2 R) for ultraprotective ventilation in ARDS. ECCO 2 R enables reductions in tidal volume and driving pressure, key determinants of ventilator-induced lung injury. Using basic physiological concepts, we demonstrate that dead space and static compliance determine the effect of ECCO 2 R on driving pressure and mechanical power. This framework might enable prediction of individual treatment responses to ECCO 2 R. Enriching clinical trials by selectively enrolling patients with a significant predicted treatment response can increase treatment effect size and statistical power more efficiently than conventional enrichment strategies that restrict enrollment according to the baseline risk of death. To support this claim, we simulated the predicted effect of ECCO 2 R on driving pressure and mortality in a preexisting cohort of patients with ARDS. Our computations suggest that restricting enrollment to patients in whom ECCO 2 R allows driving pressure to be decreased by 5 cm H 2 O or more can reduce sample size requirement by more than 50% without increasing the total number of patients to be screened. We discuss potential implications for trial design based on this framework.
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He, Liye; Tang, Jing; Andersson, Emma I; Timonen, Sanna; Koschmieder, Steffen; Wennerberg, Krister; Mustjoki, Satu; Aittokallio, Tero
2018-05-01
The molecular pathways that drive cancer progression and treatment resistance are highly redundant and variable between individual patients with the same cancer type. To tackle this complex rewiring of pathway cross-talk, personalized combination treatments targeting multiple cancer growth and survival pathways are required. Here we implemented a computational-experimental drug combination prediction and testing (DCPT) platform for efficient in silico prioritization and ex vivo testing in patient-derived samples to identify customized synergistic combinations for individual cancer patients. DCPT used drug-target interaction networks to traverse the massive combinatorial search spaces among 218 compounds (a total of 23,653 pairwise combinations) and identified cancer-selective synergies by using differential single-compound sensitivity profiles between patient cells and healthy controls, hence reducing the likelihood of toxic combination effects. A polypharmacology-based machine learning modeling and network visualization made use of baseline genomic and molecular profiles to guide patient-specific combination testing and clinical translation phases. Using T-cell prolymphocytic leukemia (T-PLL) as a first case study, we show how the DCPT platform successfully predicted distinct synergistic combinations for each of the three T-PLL patients, each presenting with different resistance patterns and synergy mechanisms. In total, 10 of 24 (42%) of selective combination predictions were experimentally confirmed to show synergy in patient-derived samples ex vivo The identified selective synergies among approved drugs, including tacrolimus and temsirolimus combined with BCL-2 inhibitor venetoclax, may offer novel drug repurposing opportunities for treating T-PLL. Significance: An integrated use of functional drug screening combined with genomic and molecular profiling enables patient-customized prediction and testing of drug combination synergies for T-PLL patients. Cancer Res; 78(9); 2407-18. ©2018 AACR . ©2018 American Association for Cancer Research.
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Tools for outcome prediction in patients with community acquired pneumonia.
Khan, Faheem; Owens, Mark B; Restrepo, Marcos; Povoa, Pedro; Martin-Loeches, Ignacio
2017-02-01
Community-acquired pneumonia (CAP) is one of the most common causes of mortality world-wide. The mortality rate of patients with CAP is influenced by the severity of the disease, treatment failure and the requirement for hospitalization and/or intensive care unit (ICU) management, all of which may be predicted by biomarkers and clinical scoring systems. Areas covered: We review the recent literature examining the efficacy of established and newly-developed clinical scores, biological and inflammatory markers such as C-Reactive protein (CRP), procalcitonin (PCT) and Interleukin-6 (IL-6), whether used alone or in conjunction with clinical severity scores to assess the severity of CAP, predict treatment failure, guide acute in-hospital or ICU admission and predict mortality. Expert commentary: The early prediction of treatment failure using clinical scores and biomarkers plays a developing role in improving survival of patients with CAP by identifying high-risk patients requiring hospitalization or ICU admission; and may enable more efficient allocation of resources. However, it is likely that combinations of scoring systems and biomarkers will be of greater use than individual markers. Further larger studies are needed to corroborate the additive value of these markers to clinical prediction scores to provide a safer and more effective assessment tool for clinicians.
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Departure Queue Prediction for Strategic and Tactical Surface Scheduler Integration
NASA Technical Reports Server (NTRS)
Zelinski, Shannon; Windhorst, Robert
2016-01-01
A departure metering concept to be demonstrated at Charlotte Douglas International Airport (CLT) will integrate strategic and tactical surface scheduling components to enable the respective collaborative decision making and improved efficiency benefits these two methods of scheduling provide. This study analyzes the effect of tactical scheduling on strategic scheduler predictability. Strategic queue predictions and target gate pushback times to achieve a desired queue length are compared between fast time simulations of CLT surface operations with and without tactical scheduling. The use of variable departure rates as a strategic scheduler input was shown to substantially improve queue predictions over static departure rates. With target queue length calibration, the strategic scheduler can be tuned to produce average delays within one minute of the tactical scheduler. However, root mean square differences between strategic and tactical delays were between 12 and 15 minutes due to the different methods the strategic and tactical schedulers use to predict takeoff times and generate gate pushback clearances. This demonstrates how difficult it is for the strategic scheduler to predict tactical scheduler assigned gate delays on an individual flight basis as the tactical scheduler adjusts departure sequence to accommodate arrival interactions. Strategic/tactical scheduler compatibility may be improved by providing more arrival information to the strategic scheduler and stabilizing tactical scheduler changes to runway sequence in response to arrivals.
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Queuing Time Prediction Using WiFi Positioning Data in an Indoor Scenario.
Shu, Hua; Song, Ci; Pei, Tao; Xu, Lianming; Ou, Yang; Zhang, Libin; Li, Tao
2016-11-22
Queuing is common in urban public places. Automatically monitoring and predicting queuing time can not only help individuals to reduce their wait time and alleviate anxiety but also help managers to allocate resources more efficiently and enhance their ability to address emergencies. This paper proposes a novel method to estimate and predict queuing time in indoor environments based on WiFi positioning data. First, we use a series of parameters to identify the trajectories that can be used as representatives of queuing time. Next, we divide the day into equal time slices and estimate individuals' average queuing time during specific time slices. Finally, we build a nonstandard autoregressive (NAR) model trained using the previous day's WiFi estimation results and actual queuing time to predict the queuing time in the upcoming time slice. A case study comparing two other time series analysis models shows that the NAR model has better precision. Random topological errors caused by the drift phenomenon of WiFi positioning technology (locations determined by a WiFi positioning system may drift accidently) and systematic topological errors caused by the positioning system are the main factors that affect the estimation precision. Therefore, we optimize the deployment strategy during the positioning system deployment phase and propose a drift ratio parameter pertaining to the trajectory screening phase to alleviate the impact of topological errors and improve estimates. The WiFi positioning data from an eight-day case study conducted at the T3-C entrance of Beijing Capital International Airport show that the mean absolute estimation error is 147 s, which is approximately 26.92% of the actual queuing time. For predictions using the NAR model, the proportion is approximately 27.49%. The theoretical predictions and the empirical case study indicate that the NAR model is an effective method to estimate and predict queuing time in indoor public areas.
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Caywood, Matthew S.; Roberts, Daniel M.; Colombe, Jeffrey B.; Greenwald, Hal S.; Weiland, Monica Z.
2017-01-01
There is increasing interest in real-time brain-computer interfaces (BCIs) for the passive monitoring of human cognitive state, including cognitive workload. Too often, however, effective BCIs based on machine learning techniques may function as “black boxes” that are difficult to analyze or interpret. In an effort toward more interpretable BCIs, we studied a family of N-back working memory tasks using a machine learning model, Gaussian Process Regression (GPR), which was both powerful and amenable to analysis. Participants performed the N-back task with three stimulus variants, auditory-verbal, visual-spatial, and visual-numeric, each at three working memory loads. GPR models were trained and tested on EEG data from all three task variants combined, in an effort to identify a model that could be predictive of mental workload demand regardless of stimulus modality. To provide a comparison for GPR performance, a model was additionally trained using multiple linear regression (MLR). The GPR model was effective when trained on individual participant EEG data, resulting in an average standardized mean squared error (sMSE) between true and predicted N-back levels of 0.44. In comparison, the MLR model using the same data resulted in an average sMSE of 0.55. We additionally demonstrate how GPR can be used to identify which EEG features are relevant for prediction of cognitive workload in an individual participant. A fraction of EEG features accounted for the majority of the model’s predictive power; using only the top 25% of features performed nearly as well as using 100% of features. Subsets of features identified by linear models (ANOVA) were not as efficient as subsets identified by GPR. This raises the possibility of BCIs that require fewer model features while capturing all of the information needed to achieve high predictive accuracy. PMID:28123359
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Assessing Similarity Among Individual Tumor Size Lesion Dynamics: The CICIL Methodology
Girard, Pascal; Ioannou, Konstantinos; Klinkhardt, Ute; Munafo, Alain
2018-01-01
Mathematical models of tumor dynamics generally omit information on individual target lesions (iTLs), and consider the most important variable to be the sum of tumor sizes (TS). However, differences in lesion dynamics might be predictive of tumor progression. To exploit this information, we have developed a novel and flexible approach for the non‐parametric analysis of iTLs, which integrates knowledge from signal processing and machine learning. We called this new methodology ClassIfication Clustering of Individual Lesions (CICIL). We used CICIL to assess similarities among the TS dynamics of 3,223 iTLs measured in 1,056 patients with metastatic colorectal cancer treated with cetuximab combined with irinotecan, in two phase II studies. We mainly observed similar dynamics among lesions within the same tumor site classification. In contrast, lesions in anatomic locations with different features showed different dynamics in about 35% of patients. The CICIL methodology has also been implemented in a user‐friendly and efficient Java‐based framework. PMID:29388396
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Dang, Hao Dan; Chen, Yu; Shi, Xiao Hua; Hou, Bo; Xing, Hai Qun; Zhang, Tao; Chen, Xing Ming; Zhang, Zhu Hua; Xue, Hua Dan; Jin, Zheng Yu
2018-04-28
Objective To evaluate the correlation of the positron emission tomography/magnetic resonance imaging (PET/MR) parameters with the pathological differentiation of head and neck squamous cell carcinoma(HNSCC) and the diagnostic efficiencies of PET/MR parameters. Methods Patients with clinical suspicion of HNSCC were included and underwent PET/MR scan. HNSCC was pathologically confirmed in all these patients. The PET/MR examination included PET and MR sequences of diffusion-weighted imaging (DWI) and T2-and T1-weighted imaging. The multiple parameters of PET/MR included the mean values of apparent diffusion coefficient(ADC mean ) and the maximum and mean values of standardized uptake value (SUV max and SUV mean ) were measured and estimated. The correlations of all the parameters and distribution between the different tumor differentiation groups were analyzed. Logistic regression was utilized to build the model as the PET/MR combined parameter for predicting the differentiation by multiple parameters of PET/MR. The receiver operating characteristic curve was calculated for each parameter and the combination. Results Totally 23 patients were included in this study:9 patients (9 males and 0 female) had well-differentiated tumor,with an average age of (61.0±6.8)years;14 cases had moderately-differentiated (n=10) or poorly-differentiated tumors (n=4),with an average age of (62.0±9.1) years. All the patients were males. There was statistical correlation between SUV mean and SUV max (P<0.001);however,ADC mean showed no statistical correlation with SUV max and with SUV mean (P=0.42,P=0.13). ADC mean and SUV mean showed significant difference between well-differentiated group and moderately-poorly-differentiated group (P=0.005,P=0.007). Compared with the individual parameters,the combination of PET/MR parameters with SUV mean and ADC mean had higher efficacy in predicting tumor differentiation,with an area under curve of 0.84. Conclusions The distributions of ADC mean ,SUV max and SUV mean differ among HNSCC with different pathological differentiation. Compared with the individual parameters,the combination of the PET/MR parameters has higher efficiency in predicting tumor differentiation.
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NASA Astrophysics Data System (ADS)
Morschhauser, Tamás; Rudolf, Kinga; Botta-Dukát, Zoltán; Oborny, Beáta
2009-09-01
We studied the establishment of new genets in a wild garlic population ( Allium ursinum L.) in the herb layer of an oak-hornbeam forest. We tested whether establishment could be successful in relatively small gaps (25 cm) surrounded by adult individuals. Furthermore, we asked whether more empty space in the neighborhood would increase the success. Newly germinated individuals were selected, and observed throughout the growth season. The success of establishment was characterized by the biomass of the bulb at the end of the season. The surrounding vegetation cover was recorded in a 25 cm resolution. We found that the success of establishment had a peak at intermediate neighborhood density. At higher densities, a significant, linear decline was found, indicating competition with the neighbors. At lower values, this trend did not continue, but a plateau was observed, indicating the effect of inverse density-dependence (an Allee effect). The results suggest that a rather broad radius (>25 cm) should be considered when predicting the establishment of new genets in A. ursinum, and beside competition, facilitative interactions should also be taken into consideration. This may explain the tendency of the species for maintaining high, often monodominant cover in the herb layer. Due to the observed efficiency of gap-filling and lateral spreading by sexual reproduction, we predict considerable genetic diversity even in high-cover A. ursinum patches.
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Wang, Xueyi; Davidson, Nicholas J.
2011-01-01
Ensemble methods have been widely used to improve prediction accuracy over individual classifiers. In this paper, we achieve a few results about the prediction accuracies of ensemble methods for binary classification that are missed or misinterpreted in previous literature. First we show the upper and lower bounds of the prediction accuracies (i.e. the best and worst possible prediction accuracies) of ensemble methods. Next we show that an ensemble method can achieve > 0.5 prediction accuracy, while individual classifiers have < 0.5 prediction accuracies. Furthermore, for individual classifiers with different prediction accuracies, the average of the individual accuracies determines the upper and lower bounds. We perform two experiments to verify the results and show that it is hard to achieve the upper and lower bounds accuracies by random individual classifiers and better algorithms need to be developed. PMID:21853162
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Brush, Adrian; Masanet, Eric; Worrell, Ernst
The U.S. dairy processing industry—defined in this Energy Guide as facilities engaged in the conversion of raw milk to consumable dairy products—consumes around $1.5 billion worth of purchased fuels and electricity per year. Energy efficiency improvement is an important way to reduce these costs and to increase predictable earnings, especially in times of high energy price volatility. There are a variety of opportunities available at individual plants in the U.S. dairy processing industry to reduce energy consumption and greenhouse gas emissions in a cost-effective manner. This Energy Guide discusses energy efficiency practices and energy-efficient technologies that can be implemented atmore » the component, process, facility, and organizational levels. A discussion of the trends, structure, and energy consumption characteristics of the U.S. dairy processing industry is provided along with a description of the major process technologies used within the industry. Next, a wide variety of energy efficiency measures applicable to dairy processing plants are described. Many measure descriptions include expected savings in energy and energy-related costs, based on case study data from real-world applications in dairy processing facilities and related industries worldwide. Typical measure payback periods and references to further information in the technical literature are also provided, when available. Given the importance of water in dairy processing, a summary of basic, proven measures for improving water efficiency are also provided. The information in this Energy Guide is intended to help energy and plant managers in the U.S. dairy processing industry reduce energy and water consumption in a cost-effective manner while maintaining the quality of products manufactured. Further research on the economics of all measures—as well as on their applicability to different production practices—is needed to assess their cost effectiveness at individual plants.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Masanet, Eric; Masanet, Eric; Worrell, Ernst
2008-01-01
The U.S. fruit and vegetable processing industry--defined in this Energy Guide as facilities engaged in the canning, freezing, and drying or dehydrating of fruits and vegetables--consumes over $800 million worth of purchased fuels and electricity per year. Energy efficiency improvement isan important way to reduce these costs and to increase predictable earnings, especially in times of high energy price volatility. There are a variety of opportunities available at individual plants in the U.S. fruit and vegetable processing industry to reduce energy consumption in a cost-effective manner. This Energy Guide discusses energy efficiency practices and energy-efficient technologies that can be implementedmore » at the component, process, facility, and organizational levels. A discussion of the trends, structure, and energy consumption characteristics of the U.S. fruit and vegetable processing industry is provided along with a description of the major process technologies used within the industry. Next, a wide variety of energy efficiency measures applicable to fruit and vegetable processing plants are described. Many measure descriptions include expected savings in energy and energy-related costs, based on case study data from real-world applications in fruit and vegetable processing facilities and related industries worldwide. Typical measure payback periods and references to further information in the technical literature are also provided, when available. Given the importance of water in fruit and vegetable processing, a summary of basic, proven measures for improving plant-level water efficiency are also provided. The information in this Energy Guide is intended to help energy and plant managers in the U.S. fruit and vegetable processing industry reduce energy and water consumption in a cost-effective manner while maintaining the quality of products manufactured. Further research on the economics of all measures--as well as on their applicability to different production practices--is needed to assess their cost effectiveness at individual plants.« less
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Is self-generated thought a means of social problem solving?
Ruby, Florence J. M.; Smallwood, Jonathan; Sackur, Jerome; Singer, Tania
2013-01-01
Appropriate social problem solving constitutes a critical skill for individuals and may rely on processes important for self-generated thought (SGT). The aim of the current study was to investigate the link between SGT and social problem solving. Using the Means-End Problem Solving task (MEPS), we assessed participants' abilities to resolve daily social problems in terms of overall efficiency and number of relevant means they provided to reach the given solution. Participants also performed a non-demanding choice reaction time task (CRT) and a moderately-demanding working memory task (WM) as a context in which to measure their SGT (assessed via thought sampling). We found that although overall SGT was associated with lower MEPS efficiency, it was also associated with higher relevant means, perhaps because both depend on the capacity to generate cognition that is independent from the hear and now. The specific content of SGT did not differentially predict individual differences in social problem solving, suggesting that the relationship may depend on SGT regardless of its content. In addition, we also found that performance at the WM but not the CRT was linked to overall better MEPS performance, suggesting that individuals good at social processing are also distinguished by their capacity to constrain attention to an external task. Our results provide novel evidence that the capacity for SGT is implicated in the process by which solutions to social problems are generated, although optimal problem solving may be achieved by individuals who display a suitable balance between SGT and cognition derived from perceptual input. PMID:24391621
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Social familiarity modulates group living and foraging behaviour of juvenile predatory mites
NASA Astrophysics Data System (ADS)
Strodl, Markus A.; Schausberger, Peter
2012-04-01
Environmental stressors during early life may have persistent consequences for phenotypic development and fitness. In group-living species, an important stressor during juvenile development is the presence and familiarity status of conspecific individuals. To alleviate intraspecific conflicts during juvenile development, many animals evolved the ability to discriminate familiar and unfamiliar individuals based on prior association and use this ability to preferentially associate with familiar individuals. Assuming that familiar neighbours require less attention than unfamiliar ones, as predicted by limited attention theory, assorting with familiar individuals should increase the efficiency in other tasks. We assessed the influence of social familiarity on within-group association behaviour, development and foraging of juvenile life stages of the group-living, plant-inhabiting predatory mite Phytoseiulus persimilis. The observed groups consisted either of mixed-age familiar and unfamiliar juvenile mites or of age-synchronized familiar or unfamiliar juvenile mites or of pairs of familiar or unfamiliar larvae. Overall, familiar mites preferentially grouped together and foraged more efficiently, i.e. needed less prey at similar developmental speed and body size at maturity, than unfamiliar mites. Preferential association of familiar mites was also apparent in the inter-exuviae distances. Social familiarity was established by imprinting in the larval stage, was not cancelled or overridden by later conspecific contacts and persisted into adulthood. Life stage had an effect on grouping with larvae being closer together than nymphal stages. Ultimately, optimized foraging during the developmental phase may relax within-group competition, enhance current and future food supply needed for optimal development and optimize patch exploitation and leaving under limited food.
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Systematic determination of absolute absorption cross-section of individual carbon nanotubes
Liu, Kaihui; Hong, Xiaoping; Choi, Sangkook; Jin, Chenhao; Capaz, Rodrigo B.; Kim, Jihoon; Wang, Wenlong; Bai, Xuedong; Louie, Steven G.; Wang, Enge; Wang, Feng
2014-01-01
Optical absorption is the most fundamental optical property characterizing light–matter interactions in materials and can be most readily compared with theoretical predictions. However, determination of optical absorption cross-section of individual nanostructures is experimentally challenging due to the small extinction signal using conventional transmission measurements. Recently, dramatic increase of optical contrast from individual carbon nanotubes has been successfully achieved with a polarization-based homodyne microscope, where the scattered light wave from the nanostructure interferes with the optimized reference signal (the reflected/transmitted light). Here we demonstrate high-sensitivity absorption spectroscopy for individual single-walled carbon nanotubes by combining the polarization-based homodyne technique with broadband supercontinuum excitation in transmission configuration. To our knowledge, this is the first time that high-throughput and quantitative determination of nanotube absorption cross-section over broad spectral range at the single-tube level was performed for more than 50 individual chirality-defined single-walled nanotubes. Our data reveal chirality-dependent behaviors of exciton resonances in carbon nanotubes, where the exciton oscillator strength exhibits a universal scaling law with the nanotube diameter and the transition order. The exciton linewidth (characterizing the exciton lifetime) varies strongly in different nanotubes, and on average it increases linearly with the transition energy. In addition, we establish an empirical formula by extrapolating our data to predict the absorption cross-section spectrum for any given nanotube. The quantitative information of absorption cross-section in a broad spectral range and all nanotube species not only provides new insight into the unique photophysics in one-dimensional carbon nanotubes, but also enables absolute determination of optical quantum efficiencies in important photoluminescence and photovoltaic processes. PMID:24821815
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Systematic determination of absolute absorption cross-section of individual carbon nanotubes.
Liu, Kaihui; Hong, Xiaoping; Choi, Sangkook; Jin, Chenhao; Capaz, Rodrigo B; Kim, Jihoon; Wang, Wenlong; Bai, Xuedong; Louie, Steven G; Wang, Enge; Wang, Feng
2014-05-27
Optical absorption is the most fundamental optical property characterizing light-matter interactions in materials and can be most readily compared with theoretical predictions. However, determination of optical absorption cross-section of individual nanostructures is experimentally challenging due to the small extinction signal using conventional transmission measurements. Recently, dramatic increase of optical contrast from individual carbon nanotubes has been successfully achieved with a polarization-based homodyne microscope, where the scattered light wave from the nanostructure interferes with the optimized reference signal (the reflected/transmitted light). Here we demonstrate high-sensitivity absorption spectroscopy for individual single-walled carbon nanotubes by combining the polarization-based homodyne technique with broadband supercontinuum excitation in transmission configuration. To our knowledge, this is the first time that high-throughput and quantitative determination of nanotube absorption cross-section over broad spectral range at the single-tube level was performed for more than 50 individual chirality-defined single-walled nanotubes. Our data reveal chirality-dependent behaviors of exciton resonances in carbon nanotubes, where the exciton oscillator strength exhibits a universal scaling law with the nanotube diameter and the transition order. The exciton linewidth (characterizing the exciton lifetime) varies strongly in different nanotubes, and on average it increases linearly with the transition energy. In addition, we establish an empirical formula by extrapolating our data to predict the absorption cross-section spectrum for any given nanotube. The quantitative information of absorption cross-section in a broad spectral range and all nanotube species not only provides new insight into the unique photophysics in one-dimensional carbon nanotubes, but also enables absolute determination of optical quantum efficiencies in important photoluminescence and photovoltaic processes.
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Evaluation and comparison of predictive individual-level general surrogates.
Gabriel, Erin E; Sachs, Michael C; Halloran, M Elizabeth
2018-07-01
An intermediate response measure that accurately predicts efficacy in a new setting at the individual level could be used both for prediction and personalized medical decisions. In this article, we define a predictive individual-level general surrogate (PIGS), which is an individual-level intermediate response that can be used to accurately predict individual efficacy in a new setting. While methods for evaluating trial-level general surrogates, which are predictors of trial-level efficacy, have been developed previously, few, if any, methods have been developed to evaluate individual-level general surrogates, and no methods have formalized the use of cross-validation to quantify the expected prediction error. Our proposed method uses existing methods of individual-level surrogate evaluation within a given clinical trial setting in combination with cross-validation over a set of clinical trials to evaluate surrogate quality and to estimate the absolute prediction error that is expected in a new trial setting when using a PIGS. Simulations show that our method performs well across a variety of scenarios. We use our method to evaluate and to compare candidate individual-level general surrogates over a set of multi-national trials of a pentavalent rotavirus vaccine.
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Can the theory of planned behaviour predict the physical activity behaviour of individuals?
Hobbs, Nicola; Dixon, Diane; Johnston, Marie; Howie, Kate
2013-01-01
The theory of planned behaviour (TPB) can identify cognitions that predict differences in behaviour between individuals. However, it is not clear whether the TPB can predict the behaviour of an individual person. This study employs a series of n-of-1 studies and time series analyses to examine the ability of the TPB to predict physical activity (PA) behaviours of six individuals. Six n-of-1 studies were conducted, in which TPB cognitions and up to three PA behaviours (walking, gym workout and a personally defined PA) were measured twice daily for six weeks. Walking was measured by pedometer step count, gym attendance by self-report with objective validation of gym entry and the personally defined PA behaviour by self-report. Intra-individual variability in TPB cognitions and PA behaviour was observed in all participants. The TPB showed variable predictive utility within individuals and across behaviours. The TPB predicted at least one PA behaviour for five participants but had no predictive utility for one participant. Thus, n-of-1 designs and time series analyses can be used to test theory in an individual.
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Chemical Risk Assessment: Traditional vs Public Health ...
Preventing adverse health impacts from exposures to environmental chemicals is fundamental to protecting individual and public health. When done efficiently and properly, chemical risk assessment enables risk management actions that minimize the incidence and impacts of environmentally-induced diseases related to chemical exposure. However, traditional chemical risk assessment is faced with multiple challenges with respect to predicting and preventing disease in human populations, and epidemiological studies increasingly report observations of adverse health effects at exposure levels predicted from animal studies to be safe for humans. This discordance reinforces concerns about the adequacy of contemporary risk assessment practices (Birnbaum, Burke, & Jones, 2016) for protecting public health. It is becoming clear that to protect public health more effectively, future risk assessments will need to use the full range of available data, draw on innovative methods to integrate diverse data streams, and consider health endpoints that also reflect the range of subtle effects and morbidities observed in human populations. Given these factors, there is a need to reframe chemical risk assessment to be more clearly aligned with the public health goal of minimizing environmental exposures associated with disease. Preventing adverse health impacts from exposures to environmental chemicals is fundamental to protecting individual and public health. Chemical risk assessments
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Pursuit of communal values in an agentic manner: a way to happiness?
Abele, Andrea E
2014-01-01
The present research studies the association between traits, values, and life satisfaction. While values should influence the direction of an individual's goals and behavior, his/her traits impact effort-expenditure, efficiency, and persistence in goal-pursuit. We apply the framework of the "Big Two" of agency and communion (Bakan, 1966) for distinguishing the content of values and traits. While agentic content refers to qualities relevant for goal-attainment, such as assertiveness, competence or persistence, communal content refers to qualities relevant for the establishment and maintenance of social relationships, such as being friendly, helpful, or fair. We predict that high scores on communal values and high scores on agentic traits are associated with life satisfaction. We test these predictions in two studies conducted in different countries (Germany and Russia) with different cultural background. The findings support our reasoning: across both countries we find positive associations of communal values and agentic traits with life satisfaction; and individuals high in communal values and high in agentic traits are most satisfied with their lives. In Russia, the association of communal values with life satisfaction is moderated by agentic traits; in Germany, however, there is a main effect of communal values.
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Large-scale Cortical Network Properties Predict Future Sound-to-Word Learning Success
Sheppard, John Patrick; Wang, Ji-Ping; Wong, Patrick C. M.
2013-01-01
The human brain possesses a remarkable capacity to interpret and recall novel sounds as spoken language. These linguistic abilities arise from complex processing spanning a widely distributed cortical network and are characterized by marked individual variation. Recently, graph theoretical analysis has facilitated the exploration of how such aspects of large-scale brain functional organization may underlie cognitive performance. Brain functional networks are known to possess small-world topologies characterized by efficient global and local information transfer, but whether these properties relate to language learning abilities remains unknown. Here we applied graph theory to construct large-scale cortical functional networks from cerebral hemodynamic (fMRI) responses acquired during an auditory pitch discrimination task and found that such network properties were associated with participants’ future success in learning words of an artificial spoken language. Successful learners possessed networks with reduced local efficiency but increased global efficiency relative to less successful learners and had a more cost-efficient network organization. Regionally, successful and less successful learners exhibited differences in these network properties spanning bilateral prefrontal, parietal, and right temporal cortex, overlapping a core network of auditory language areas. These results suggest that efficient cortical network organization is associated with sound-to-word learning abilities among healthy, younger adults. PMID:22360625
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A CFD Study on the Prediction of Cyclone Collection Efficiency
NASA Astrophysics Data System (ADS)
Gimbun, Jolius; Chuah, T. G.; Choong, Thomas S. Y.; Fakhru'L-Razi, A.
2005-09-01
This work presents a Computational Fluid Dynamics calculation to predict and to evaluate the effects of temperature, operating pressure and inlet velocity on the collection efficiency of gas cyclones. The numerical solutions were carried out using spreadsheet and commercial CFD code FLUENT 6.0. This paper also reviews four empirical models for the prediction of cyclone collection efficiency, namely Lapple [1], Koch and Licht [2], Li and Wang [3], and Iozia and Leith [4]. All the predictions proved to be satisfactory when compared with the presented experimental data. The CFD simulations predict the cyclone cut-off size for all operating conditions with a deviation of 3.7% from the experimental data. Specifically, results obtained from the computer modelling exercise have demonstrated that CFD model is the best method of modelling the cyclones collection efficiency.
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Stevens, Alexander A.; Tappon, Sarah C.; Garg, Arun; Fair, Damien A.
2012-01-01
Background Cognitive abilities, such as working memory, differ among people; however, individuals also vary in their own day-to-day cognitive performance. One potential source of cognitive variability may be fluctuations in the functional organization of neural systems. The degree to which the organization of these functional networks is optimized may relate to the effective cognitive functioning of the individual. Here we specifically examine how changes in the organization of large-scale networks measured via resting state functional connectivity MRI and graph theory track changes in working memory capacity. Methodology/Principal Findings Twenty-two participants performed a test of working memory capacity and then underwent resting-state fMRI. Seventeen subjects repeated the protocol three weeks later. We applied graph theoretic techniques to measure network organization on 34 brain regions of interest (ROI). Network modularity, which measures the level of integration and segregation across sub-networks, and small-worldness, which measures global network connection efficiency, both predicted individual differences in memory capacity; however, only modularity predicted intra-individual variation across the two sessions. Partial correlations controlling for the component of working memory that was stable across sessions revealed that modularity was almost entirely associated with the variability of working memory at each session. Analyses of specific sub-networks and individual circuits were unable to consistently account for working memory capacity variability. Conclusions/Significance The results suggest that the intrinsic functional organization of an a priori defined cognitive control network measured at rest provides substantial information about actual cognitive performance. The association of network modularity to the variability in an individual's working memory capacity suggests that the organization of this network into high connectivity within modules and sparse connections between modules may reflect effective signaling across brain regions, perhaps through the modulation of signal or the suppression of the propagation of noise. PMID:22276205
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Development of a brain MRI-based hidden Markov model for dementia recognition
2013-01-01
Background Dementia is an age-related cognitive decline which is indicated by an early degeneration of cortical and sub-cortical structures. Characterizing those morphological changes can help to understand the disease development and contribute to disease early prediction and prevention. But modeling that can best capture brain structural variability and can be valid in both disease classification and interpretation is extremely challenging. The current study aimed to establish a computational approach for modeling the magnetic resonance imaging (MRI)-based structural complexity of the brain using the framework of hidden Markov models (HMMs) for dementia recognition. Methods Regularity dimension and semi-variogram were used to extract structural features of the brains, and vector quantization method was applied to convert extracted feature vectors to prototype vectors. The output VQ indices were then utilized to estimate parameters for HMMs. To validate its accuracy and robustness, experiments were carried out on individuals who were characterized as non-demented and mild Alzheimer's diseased. Four HMMs were constructed based on the cohort of non-demented young, middle-aged, elder and demented elder subjects separately. Classification was carried out using a data set including both non-demented and demented individuals with a wide age range. Results The proposed HMMs have succeeded in recognition of individual who has mild Alzheimer's disease and achieved a better classification accuracy compared to other related works using different classifiers. Results have shown the ability of the proposed modeling for recognition of early dementia. Conclusion The findings from this research will allow individual classification to support the early diagnosis and prediction of dementia. By using the brain MRI-based HMMs developed in our proposed research, it will be more efficient, robust and can be easily used by clinicians as a computer-aid tool for validating imaging bio-markers for early prediction of dementia. PMID:24564961
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Collins, Á B; Grant, J; Barrett, D; Doherty, M L; Hallinan, A; Mee, J F
2017-08-01
Schmallenberg virus (SBV) is transmitted by Culicoides spp. biting midges and can cause abortions and congenital malformations in ruminants and milk drop in dairy cattle. Estimating true within-herd seroprevalence is an essential component of efficient and cost-effective SBV surveillance programs. The objectives of this study were: (1) determine the correlation between bulk-tank milk (BTM)-ELISA results and within-herd seroprevalence, (2) evaluate the ability of BTM-ELISA results to predict within-herd seroprevalence and (3) explore the distributions of individual animal serology results using novel statistical methodology. BTM samples (n=24) and blood samples (n=4019) collected from all lactating cows contributing to the BTM in 26 Irish dairy herds (58-444 cows/herd) in 2014 located in a region exposed to SBV in 2012/2013, were analysed for SBV-specific antibodies using IDVet ® ELISA kits. The correlation between BTM-ELISA results and within-herd seroprevalence was determined by calculating Pearson's correlation coefficient. Linear regression models were used to assess the ability of BTM-ELISA results to predict within-herd seroprevalence. The distributions of individual animal serology results were explored by determining the empirical distribution functions (EDF) of the individual animal serum ELISA results in each herd. EDFs were compared pairwise across herds, using the Kolmogorov-Smirnov statistical test. Herds with similar BTM-ELISA results, herds with similar within-herd seroprevalence and herds with similar mean-herd serology ELISA results were stratified in order to explore their respective paired-herd EDF comparisons. Statistical significance was set at p<0.05. Twenty-two herds were BTM-ELISA-positive (within-herd seroprevalence 30.6-100%) and two herds were BTM-ELISA-negative (within-herd seroprevalence 10.7 and 16.2%) indicating BTM-ELISA-negative herds can have seropositive animals present. BTM-ELISA results were highly correlated (r=0.807, p<0.0001) with, and predictive of (R 2 =0.832, p<0.0001) of within-herd seroprevalence. Predictions were most accurate for upper-range BTM-ELISA antibody titres, while they were less accurate at higher and lower antibody titres. This is likely a result of the overall high within-herd seroprevalence. In herds with similar BTM-ELISA results 82% of the paired-herd EDF comparisons were significantly different. In herds with similar within-herd seroprevalence and in herds with similar mean-herd serology ELISA results, 46% and 47% of the paired-herd EDF comparisons were significantly different, respectively. These results demonstrate that BTM antibody titres are highly predictive of within-herd seroprevalence in an SBV exposed region. Furthermore, exploring the serum EDFs revealed that the variation observed in the predicted within-herd seroprevalence in the regression models is likely a result of individual animal variation in serum antibody titres in these herds. Copyright © 2017 Elsevier B.V. All rights reserved.
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Exploring the effect of depressive symptoms and ageing on metamemory in an Italian adult sample.
Fastame, Maria Chiara
2014-01-01
The current study aimed to investigate the effect of depression and age-related factors on metamemory measures in an Italian adult sample. Fifty-eight healthy participants were recruited in Northern Italy and were, respectively, assigned to the following groups: Young (20-30 years old), old (60-70 years old), and Very Old (71-84 years old). Participants were administered a battery of tests, including a word recall task, self-referent mnestic efficiency scales, general beliefs about memory, and depression measures. General beliefs about memory, self-efficacy, and beliefs about the control of personal memory were predicted by age, education, depression, and mnestic and cognitive efficiency. Finally, age-related differences were found in metamemory measures: the accuracy of mnestic control processes is thought to be lower by very old adults than by old and young individuals.
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Energy and fuels from electrochemical interfaces
NASA Astrophysics Data System (ADS)
Stamenkovic, Vojislav R.; Strmcnik, Dusan; Lopes, Pietro P.; Markovic, Nenad M.
2017-01-01
Advances in electrocatalysis at solid-liquid interfaces are vital for driving the technological innovations that are needed to deliver reliable, affordable and environmentally friendly energy. Here, we highlight the key achievements in the development of new materials for efficient hydrogen and oxygen production in electrolysers and, in reverse, their use in fuel cells. A key issue addressed here is the degree to which the fundamental understanding of the synergy between covalent and non-covalent interactions can form the basis for any predictive ability in tailor-making real-world catalysts. Common descriptors such as the substrate-hydroxide binding energy and the interactions in the double layer between hydroxide-oxides and H---OH are found to control individual parts of the hydrogen and oxygen electrochemistry that govern the efficiency of water-based energy conversion and storage systems. Links between aqueous- and organic-based environments are also established, encouraging the 'fuel cell' and 'battery' communities to move forward together.
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Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits.
Ujfalussy, Balázs B; Makara, Judit K; Branco, Tiago; Lengyel, Máté
2015-12-24
Cortical neurons integrate thousands of synaptic inputs in their dendrites in highly nonlinear ways. It is unknown how these dendritic nonlinearities in individual cells contribute to computations at the level of neural circuits. Here, we show that dendritic nonlinearities are critical for the efficient integration of synaptic inputs in circuits performing analog computations with spiking neurons. We developed a theory that formalizes how a neuron's dendritic nonlinearity that is optimal for integrating synaptic inputs depends on the statistics of its presynaptic activity patterns. Based on their in vivo preynaptic population statistics (firing rates, membrane potential fluctuations, and correlations due to ensemble dynamics), our theory accurately predicted the responses of two different types of cortical pyramidal cells to patterned stimulation by two-photon glutamate uncaging. These results reveal a new computational principle underlying dendritic integration in cortical neurons by suggesting a functional link between cellular and systems--level properties of cortical circuits.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Heo, Yeonsook; Augenbroe, Godfried; Graziano, Diane
2015-05-01
The increasing interest in retrofitting of existing buildings is motivated by the need to make a major contribution to enhancing building energy efficiency and reducing energy consumption and CO2 emission by the built environment. This paper examines the relevance of calibration in model-based analysis to support decision-making for energy and carbon efficiency retrofits of individual buildings and portfolios of buildings. The authors formulate a set of real retrofit decision-making situations and evaluate the role of calibration by using a case study that compares predictions and decisions from an uncalibrated model with those of a calibrated model. The case study illustratesmore » both the mechanics and outcomes of a practical alternative to the expert- and time-intense application of dynamic energy simulation models for large-scale retrofit decision-making under uncertainty.« less
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Behavioral flexibility and problem solving in an invasive bird.
Logan, Corina J
2016-01-01
Behavioral flexibility is considered an important trait for adapting to environmental change, but it is unclear what it is, how it works, and whether it is a problem solving ability. I investigated behavioral flexibility and problem solving experimentally in great-tailed grackles, an invasive bird species and thus a likely candidate for possessing behavioral flexibility. Grackles demonstrated behavioral flexibility in two contexts, the Aesop's Fable paradigm and a color association test. Contrary to predictions, behavioral flexibility did not correlate across contexts. Four out of 6 grackles exhibited efficient problem solving abilities, but problem solving efficiency did not appear to be directly linked with behavioral flexibility. Problem solving speed also did not significantly correlate with reversal learning scores, indicating that faster learners were not the most flexible. These results reveal how little we know about behavioral flexibility, and provide an immense opportunity for future research to explore how individuals and species can use behavior to react to changing environments.
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Noise and the statistical mechanics of distributed transport in a colony of interacting agents
NASA Astrophysics Data System (ADS)
Katifori, Eleni; Graewer, Johannes; Ronellenfitsch, Henrik; Mazza, Marco G.
Inspired by the process of liquid food distribution between individuals in an ant colony, in this work we consider the statistical mechanics of resource dissemination between interacting agents with finite carrying capacity. The agents move inside a confined space (nest), pick up the food at the entrance of the nest and share it with other agents that they encounter. We calculate analytically and via a series of simulations the global food intake rate for the whole colony as well as observables describing how uniformly the food is distributed within the nest. Our model and predictions provide a useful benchmark to assess which strategies can lead to efficient food distribution within the nest and also to what level the observed food uptake rates and efficiency in food distribution are due to stochastic fluctuations or specific food exchange strategies by an actual ant colony.
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Group-regularized individual prediction: theory and application to pain.
Lindquist, Martin A; Krishnan, Anjali; López-Solà, Marina; Jepma, Marieke; Woo, Choong-Wan; Koban, Leonie; Roy, Mathieu; Atlas, Lauren Y; Schmidt, Liane; Chang, Luke J; Reynolds Losin, Elizabeth A; Eisenbarth, Hedwig; Ashar, Yoni K; Delk, Elizabeth; Wager, Tor D
2017-01-15
Multivariate pattern analysis (MVPA) has become an important tool for identifying brain representations of psychological processes and clinical outcomes using fMRI and related methods. Such methods can be used to predict or 'decode' psychological states in individual subjects. Single-subject MVPA approaches, however, are limited by the amount and quality of individual-subject data. In spite of higher spatial resolution, predictive accuracy from single-subject data often does not exceed what can be accomplished using coarser, group-level maps, because single-subject patterns are trained on limited amounts of often-noisy data. Here, we present a method that combines population-level priors, in the form of biomarker patterns developed on prior samples, with single-subject MVPA maps to improve single-subject prediction. Theoretical results and simulations motivate a weighting based on the relative variances of biomarker-based prediction-based on population-level predictive maps from prior groups-and individual-subject, cross-validated prediction. Empirical results predicting pain using brain activity on a trial-by-trial basis (single-trial prediction) across 6 studies (N=180 participants) confirm the theoretical predictions. Regularization based on a population-level biomarker-in this case, the Neurologic Pain Signature (NPS)-improved single-subject prediction accuracy compared with idiographic maps based on the individuals' data alone. The regularization scheme that we propose, which we term group-regularized individual prediction (GRIP), can be applied broadly to within-person MVPA-based prediction. We also show how GRIP can be used to evaluate data quality and provide benchmarks for the appropriateness of population-level maps like the NPS for a given individual or study. Copyright © 2015 Elsevier Inc. All rights reserved.
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NASA Technical Reports Server (NTRS)
Daigle, Matthew John; Goebel, Kai Frank
2010-01-01
Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.
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Tomei, M Concetta; Mosca Angelucci, Domenica; Ademollo, Nicoletta; Daugulis, Andrew J
2015-03-01
Solid phase extraction performed with commercial polymer beads to treat soil contaminated by chlorophenols (4-chlorophenol, 2,4-dichlorophenol and pentachlorophenol) as single compounds and in a mixture has been investigated in this study. Soil-water-polymer partition tests were conducted to determine the relative affinities of single compounds in soil-water and polymer-water pairs. Subsequent soil extraction tests were performed with Hytrel 8206, the polymer showing the highest affinity for the tested chlorophenols. Factors that were examined were polymer type, moisture content, and contamination level. Increased moisture content (up to 100%) improved the extraction efficiency for all three compounds. Extraction tests at this upper level of moisture content showed removal efficiencies ≥70% for all the compounds and their ternary mixture, for 24 h of contact time, which is in contrast to the weeks and months, normally required for conventional ex situ remediation processes. A dynamic model characterizing the rate and extent of decontamination was also formulated, calibrated and validated with the experimental data. The proposed model, based on the simplified approach of "lumped parameters" for the mass transfer coefficients, provided very good predictions of the experimental data for the absorptive removal of contaminants from soil at different individual solute levels. Parameters evaluated from calibration by fitting of single compound data, have been successfully applied to predict mixture data, with differences between experimental and predicted data in all cases being ≤3%. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Hunter-gatherer residential mobility and the marginal value of rainforest patches.
Venkataraman, Vivek V; Kraft, Thomas S; Dominy, Nathaniel J; Endicott, Kirk M
2017-03-21
The residential mobility patterns of modern hunter-gatherers broadly reflect local resource availability, but the proximate ecological and social forces that determine the timing of camp movements are poorly known. We tested the hypothesis that the timing of such moves maximizes foraging efficiency as hunter-gatherers move across the landscape. The marginal value theorem predicts when a group should depart a camp and its associated foraging area and move to another based on declining marginal return rates. This influential model has yet to be directly applied in a population of hunter-gatherers, primarily because the shape of gain curves (cumulative resource acquisition through time) and travel times between patches have been difficult to estimate in ethnographic settings. We tested the predictions of the marginal value theorem in the context of hunter-gatherer residential mobility using historical foraging data from nomadic, socially egalitarian Batek hunter-gatherers ( n = 93 d across 11 residential camps) living in the tropical rainforests of Peninsular Malaysia. We characterized the gain functions for all resources acquired by the Batek at daily timescales and examined how patterns of individual foraging related to the emergent property of residential movements. Patterns of camp residence times conformed well with the predictions of the marginal value theorem, indicating that communal perceptions of resource depletion are closely linked to collective movement decisions. Despite (and perhaps because of) a protracted process of deliberation and argument about when to depart camps, Batek residential mobility seems to maximize group-level foraging efficiency.
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Hunter-gatherer residential mobility and the marginal value of rainforest patches
Venkataraman, Vivek V.; Kraft, Thomas S.; Endicott, Kirk M.
2017-01-01
The residential mobility patterns of modern hunter-gatherers broadly reflect local resource availability, but the proximate ecological and social forces that determine the timing of camp movements are poorly known. We tested the hypothesis that the timing of such moves maximizes foraging efficiency as hunter-gatherers move across the landscape. The marginal value theorem predicts when a group should depart a camp and its associated foraging area and move to another based on declining marginal return rates. This influential model has yet to be directly applied in a population of hunter-gatherers, primarily because the shape of gain curves (cumulative resource acquisition through time) and travel times between patches have been difficult to estimate in ethnographic settings. We tested the predictions of the marginal value theorem in the context of hunter-gatherer residential mobility using historical foraging data from nomadic, socially egalitarian Batek hunter-gatherers (n = 93 d across 11 residential camps) living in the tropical rainforests of Peninsular Malaysia. We characterized the gain functions for all resources acquired by the Batek at daily timescales and examined how patterns of individual foraging related to the emergent property of residential movements. Patterns of camp residence times conformed well with the predictions of the marginal value theorem, indicating that communal perceptions of resource depletion are closely linked to collective movement decisions. Despite (and perhaps because of) a protracted process of deliberation and argument about when to depart camps, Batek residential mobility seems to maximize group-level foraging efficiency. PMID:28265058
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Iliuta, Ioan-Andrei; Lachance, Philippe; Ghannoum, Marc; Bégin, Yannick; Mac-Way, Fabrice; Desmeules, Simon; De Serres, Sacha A; Julien, Anne-Sophie; Douville, Pierre; Agharazii, Mohsen
2017-08-01
The duration of hemodialysis (HD) sessions for the treatment of acute ethylene glycol poisoning is dependent on concentration, the operational parameters used during HD, and the presence and severity of metabolic acidosis. Ethylene glycol assays are not readily available, potentially leading to undue extension or premature termination of HD. We report a prediction model for the duration of high-efficiency HD sessions based retrospectively on a cohort study of 26 cases of acute ethylene glycol poisoning in 24 individuals treated by alcohol dehydrogenase competitive inhibitors, cofactors and HD. Two patients required HD for more than 14 days, and two died. In 19 cases, the mean ethylene glycol elimination half-life during high-efficiency HD was 165 minutes (95% confidence interval of 151-180 minutes). In a training set of 12 patients with acute ethylene glycol poisoning, using the 90th percentile half-life (195 minutes) and a target ethylene glycol concentration of 2 mmol/l (12.4 mg/dl) allowed all cases to reach a safe ethylene glycol under 3 mmol/l (18.6 mg/dl). The prediction model was then validated in a set of seven acute ethylene glycol poisonings. Thus, the HD session time in hours can be estimated using 4.7 x (Ln [the initial ethylene glycol concentration (mmol/l)/2]), provided that metabolic acidosis is corrected. Copyright © 2017 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Hodgson, Alfred T.; Sullivan, Douglas P.; Fisk, William J.
2005-10-31
An innovative Ultra-Violet Photocatalytic Oxidation (UVPCO) air cleaning technology employing a semitransparent catalyst coated on a semitransparent polymer substrate was evaluated to determine its effectiveness for treating mixtures of volatile organic compounds (VOCs) representative of indoor environments at low, indoor-relevant concentration levels. The experimental UVPCO contained four 30 by 30-cm honeycomb monoliths irradiated with nine UVA lamps arranged in three banks. A parametric evaluation of the effects of monolith thickness, air flow rate through the device, UV power, and reactant concentrations in inlet air was conducted for the purpose of suggesting design improvements. The UVPCO was challenged with three mixturesmore » of VOCs. A synthetic office mixture contained 27 VOCs commonly measured in office buildings. A building product mixture was created by combining sources including painted wallboard, composite wood products, carpet systems, and vinyl flooring. The third mixture contained formaldehyde and acetaldehyde. Steady state concentrations were produced in a classroom laboratory or a 20-m{sup 3} chamber. Air was drawn through the UVPCO, and single-pass conversion efficiencies were measured from replicate samples collected upstream and downstream of the reactor. Thirteen experiments were conducted in total. In this UVPCO employing a semitransparent monolith design, an increase in monolith thickness is expected to result in general increases in both reaction efficiencies and absolute reaction rates for VOCs oxidized by photocatalysis. The thickness of individual monolith panels was varied between 1.2 and 5 cm (5 to 20 cm total thickness) in experiments with the office mixture. VOC reaction efficiencies and rates increased with monolith thickness. However, the analysis of the relationship was confounded by high reaction efficiencies in all configurations for a number of compounds. These reaction efficiencies approached or exceeded 90% for alcohols, glycol ethers, and other individual compounds including d-limonene, 1,2,4-trimethylbenzene, and decamethylcyclopentasiloxane. This result implies a reaction efficiency of about 30% per irradiated monolith face, which is in agreement with the maximum efficiency for the system predicted with a simulation model. In these and other experiments, the performance of the system for highly reactive VOCs appeared to be limited by mass transport of reactants to the catalyst surface rather than by photocatalytic activity. Increasing the air flow rate through the UVPCO device decreases the residence time of the air in the monoliths and improves mass transfer to the catalyst surface. The effect of gas velocity was examined in four pairs of experiments in which the air flow rate was varied from approximately 175 m{sup 3}/h to either 300 or 600 m{sup 3}/h. Increased gas velocity caused a decrease in reaction efficiency for nearly all reactive VOCs. For all of the more reactive VOCs, the decrease in performance was less, and often substantially less, than predicted based solely on residence time, again likely due to mass transfer limitations at the low flow rate. The results demonstrate that the UVPCO is capable of achieving high conversion efficiencies for reactive VOCs at air flow rates above the base experimental rate of 175 m{sup 3}/h. The effect of UV power was examined in a series of experiments with the building product mixture in which the number of lamps was varied between nine and three. For the most reactive VOCs in the mixture, the effects of UV power were surprisingly small. Thus, even with only one lamp in each section, there appears to be sufficient photocatalytic activity to decompose most of the mass of reactive VOCs that reach the catalyst surface. For some less reactive VOCs, the trend of decreasing efficiency with decreasing UV intensity was in general agreement with simulation model predictions.« less
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Rapid simulation of spatial epidemics: a spectral method.
Brand, Samuel P C; Tildesley, Michael J; Keeling, Matthew J
2015-04-07
Spatial structure and hence the spatial position of host populations plays a vital role in the spread of infection. In the majority of situations, it is only possible to predict the spatial spread of infection using simulation models, which can be computationally demanding especially for large population sizes. Here we develop an approximation method that vastly reduces this computational burden. We assume that the transmission rates between individuals or sub-populations are determined by a spatial transmission kernel. This kernel is assumed to be isotropic, such that the transmission rate is simply a function of the distance between susceptible and infectious individuals; as such this provides the ideal mechanism for modelling localised transmission in a spatial environment. We show that the spatial force of infection acting on all susceptibles can be represented as a spatial convolution between the transmission kernel and a spatially extended 'image' of the infection state. This representation allows the rapid calculation of stochastic rates of infection using fast-Fourier transform (FFT) routines, which greatly improves the computational efficiency of spatial simulations. We demonstrate the efficiency and accuracy of this fast spectral rate recalculation (FSR) method with two examples: an idealised scenario simulating an SIR-type epidemic outbreak amongst N habitats distributed across a two-dimensional plane; the spread of infection between US cattle farms, illustrating that the FSR method makes continental-scale outbreak forecasting feasible with desktop processing power. The latter model demonstrates which areas of the US are at consistently high risk for cattle-infections, although predictions of epidemic size are highly dependent on assumptions about the tail of the transmission kernel. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Vanos, J K; Warland, J S; Gillespie, T J; Kenny, N A
2012-11-01
The purpose of this paper is to implement current and novel research techniques in human energy budget estimations to give more accurate and efficient application of models by a variety of users. Using the COMFA model, the conditioning level of an individual is incorporated into overall energy budget predictions, giving more realistic estimations of the metabolism experienced at various fitness levels. Through the use of VO(2) reserve estimates, errors are found when an elite athlete is modelled as an unconditioned or a conditioned individual, giving budgets underpredicted significantly by -173 and -123 W m(-2), respectively. Such underprediction can result in critical errors regarding heat stress, particularly in highly motivated individuals; thus this revision is critical for athletic individuals. A further improvement in the COMFA model involves improved adaptation of clothing insulation (I (cl)), as well clothing non-uniformity, with changing air temperature (T (a)) and metabolic activity (M (act)). Equivalent T (a) values (for I (cl) estimation) are calculated in order to lower the I (cl) value with increasing M (act) at equal T (a). Furthermore, threshold T (a) values are calculated to predict the point at which an individual will change from a uniform I (cl) to a segmented I (cl) (full ensemble to shorts and a T-shirt). Lastly, improved relative velocity (v (r)) estimates were found with a refined equation accounting for the degree angle of wind to body movement. Differences between the original and improved v (r) equations increased with higher wind and activity speeds, and as the wind to body angle moved away from 90°. Under moderate microclimate conditions, and wind from behind a person, the convective heat loss and skin temperature estimates were 47 W m(-2) and 1.7°C higher when using the improved v (r) equation. These model revisions improve the applicability and usability of the COMFA energy budget model for subjects performing physical activity in outdoor environments. Application is possible for other similar energy budget models, and within various urban and rural environments.
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NASA Astrophysics Data System (ADS)
Vanos, J. K.; Warland, J. S.; Gillespie, T. J.; Kenny, N. A.
2012-11-01
The purpose of this paper is to implement current and novel research techniques in human energy budget estimations to give more accurate and efficient application of models by a variety of users. Using the COMFA model, the conditioning level of an individual is incorporated into overall energy budget predictions, giving more realistic estimations of the metabolism experienced at various fitness levels. Through the use of VO2 reserve estimates, errors are found when an elite athlete is modelled as an unconditioned or a conditioned individual, giving budgets underpredicted significantly by -173 and -123 W m-2, respectively. Such underprediction can result in critical errors regarding heat stress, particularly in highly motivated individuals; thus this revision is critical for athletic individuals. A further improvement in the COMFA model involves improved adaptation of clothing insulation ( I cl), as well clothing non-uniformity, with changing air temperature ( T a) and metabolic activity ( M act). Equivalent T a values (for I cl estimation) are calculated in order to lower the I cl value with increasing M act at equal T a. Furthermore, threshold T a values are calculated to predict the point at which an individual will change from a uniform I cl to a segmented I cl (full ensemble to shorts and a T-shirt). Lastly, improved relative velocity ( v r) estimates were found with a refined equation accounting for the degree angle of wind to body movement. Differences between the original and improved v r equations increased with higher wind and activity speeds, and as the wind to body angle moved away from 90°. Under moderate microclimate conditions, and wind from behind a person, the convective heat loss and skin temperature estimates were 47 W m-2 and 1.7°C higher when using the improved v r equation. These model revisions improve the applicability and usability of the COMFA energy budget model for subjects performing physical activity in outdoor environments. Application is possible for other similar energy budget models, and within various urban and rural environments.
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Efficient hybrid metrology for focus, CD, and overlay
NASA Astrophysics Data System (ADS)
Tel, W. T.; Segers, B.; Anunciado, R.; Zhang, Y.; Wong, P.; Hasan, T.; Prentice, C.
2017-03-01
In the advent of multiple patterning techniques in semiconductor industry, metrology has progressively become a burden. With multiple patterning techniques such as Litho-Etch-Litho-Etch and Sidewall Assisted Double Patterning, the number of processing step have increased significantly and therefore, so as the amount of metrology steps needed for both control and yield monitoring. The amount of metrology needed is increasing in each and every node as more layers needed multiple patterning steps, and more patterning steps per layer. In addition to this, there is that need for guided defect inspection, which in itself requires substantially denser focus, overlay, and CD metrology as before. Metrology efficiency will therefore be cruicial to the next semiconductor nodes. ASML's emulated wafer concept offers a highly efficient method for hybrid metrology for focus, CD, and overlay. In this concept metrology is combined with scanner's sensor data in order to predict the on-product performance. The principle underlying the method is to isolate and estimate individual root-causes which are then combined to compute the on-product performance. The goal is to use all the information available to avoid ever increasing amounts of metrology.
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PDF-based heterogeneous multiscale filtration model.
Gong, Jian; Rutland, Christopher J
2015-04-21
Motivated by modeling of gasoline particulate filters (GPFs), a probability density function (PDF) based heterogeneous multiscale filtration (HMF) model is developed to calculate filtration efficiency of clean particulate filters. A new methodology based on statistical theory and classic filtration theory is developed in the HMF model. Based on the analysis of experimental porosimetry data, a pore size probability density function is introduced to represent heterogeneity and multiscale characteristics of the porous wall. The filtration efficiency of a filter can be calculated as the sum of the contributions of individual collectors. The resulting HMF model overcomes the limitations of classic mean filtration models which rely on tuning of the mean collector size. Sensitivity analysis shows that the HMF model recovers the classical mean model when the pore size variance is very small. The HMF model is validated by fundamental filtration experimental data from different scales of filter samples. The model shows a good agreement with experimental data at various operating conditions. The effects of the microstructure of filters on filtration efficiency as well as the most penetrating particle size are correctly predicted by the model.
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Persistent and transient cost efficiency—an application to the Swiss hydropower sector
Filippini, Massimo; Geissmann, Thomas; Greene, William H.
2017-11-27
Electricity prices on the European market have decreased significantly over the past few years, resulting in a deterioration of Swiss hydropower firms’ competitiveness and profitability. One option to improve the sector’s competitiveness is to increase cost efficiency. The goal of this study is to quantify the level of persistent and transient cost efficiency of individual firms by applying the generalized true random effects (GTRE) model introduced by Colombi et al. (Journal of Productivity Analysis 42(2): 123–136, 2014) and Filippini and Greene (Journal of Productivity Analysis 45(2): 187–196, 2016). Applying this newly developed GTRE model to a total cost function, themore » level of cost efficiency of 65 Swiss hydropower firms is analyzed for the period between 2000 and 2013. A true random effects specification is estimated as a benchmark for the transient level of cost efficiency. The results show the presence of both transient as well as persistent cost inefficiencies. The GTREM predicts the aggregate level of cost inefficiency to amount to 21.8% (8.0% transient, 13.8% persistent) on average between 2000 and 2013. These two components differ in interpretation and implication. From an individual firm’s perspective, the two types of cost inefficiencies might require a firm’s management to respond with different improvement strategies. The existing level of persistent inefficiency could prevent the hydropower firms from adjusting their production processes to new market environments. From a regulatory point of view, the results of this study could be used in the scope and determination of the amount of financial support given to struggling firms.« less
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Persistent and transient cost efficiency—an application to the Swiss hydropower sector
DOE Office of Scientific and Technical Information (OSTI.GOV)
Filippini, Massimo; Geissmann, Thomas; Greene, William H.
Electricity prices on the European market have decreased significantly over the past few years, resulting in a deterioration of Swiss hydropower firms’ competitiveness and profitability. One option to improve the sector’s competitiveness is to increase cost efficiency. The goal of this study is to quantify the level of persistent and transient cost efficiency of individual firms by applying the generalized true random effects (GTRE) model introduced by Colombi et al. (Journal of Productivity Analysis 42(2): 123–136, 2014) and Filippini and Greene (Journal of Productivity Analysis 45(2): 187–196, 2016). Applying this newly developed GTRE model to a total cost function, themore » level of cost efficiency of 65 Swiss hydropower firms is analyzed for the period between 2000 and 2013. A true random effects specification is estimated as a benchmark for the transient level of cost efficiency. The results show the presence of both transient as well as persistent cost inefficiencies. The GTREM predicts the aggregate level of cost inefficiency to amount to 21.8% (8.0% transient, 13.8% persistent) on average between 2000 and 2013. These two components differ in interpretation and implication. From an individual firm’s perspective, the two types of cost inefficiencies might require a firm’s management to respond with different improvement strategies. The existing level of persistent inefficiency could prevent the hydropower firms from adjusting their production processes to new market environments. From a regulatory point of view, the results of this study could be used in the scope and determination of the amount of financial support given to struggling firms.« less
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Top-Down Network Effective Connectivity in Abstinent Substance Dependent Individuals
Regner, Michael F.; Saenz, Naomi; Maharajh, Keeran; Yamamoto, Dorothy J.; Mohl, Brianne; Wylie, Korey; Tregellas, Jason; Tanabe, Jody
2016-01-01
Objective We hypothesized that compared to healthy controls, long-term abstinent substance dependent individuals (SDI) will differ in their effective connectivity between large-scale brain networks and demonstrate increased directional information from executive control to interoception-, reward-, and habit-related networks. In addition, using graph theory to compare network efficiencies we predicted decreased small-worldness in SDI compared to controls. Methods 50 SDI and 50 controls of similar sex and age completed psychological surveys and resting state fMRI. fMRI results were analyzed using group independent component analysis; 14 networks-of-interest (NOI) were selected using template matching to a canonical set of resting state networks. The number, direction, and strength of connections between NOI were analyzed with Granger Causality. Within-group thresholds were p<0.005 using a bootstrap permutation. Between group thresholds were p<0.05, FDR-corrected for multiple comparisons. NOI were correlated with behavioral measures, and group-level graph theory measures were compared. Results Compared to controls, SDI showed significantly greater Granger causal connectivity from right executive control network (RECN) to dorsal default mode network (dDMN) and from dDMN to basal ganglia network (BGN). RECN was negatively correlated with impulsivity, behavioral approach, and negative affect; dDMN was positively correlated with impulsivity. Among the 14 NOI, SDI showed greater bidirectional connectivity; controls showed more unidirectional connectivity. SDI demonstrated greater global efficiency and lower local efficiency. Conclusions Increased effective connectivity in long-term abstinent drug users may reflect improved cognitive control over habit and reward processes. Higher global and lower local efficiency across all networks in SDI compared to controls may reflect connectivity changes associated with drug dependence or remission and requires future, longitudinal studies to confirm. PMID:27776135
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[The truth and present uncertainty about mad cow disease].
Suárez Fernández, G
2001-01-01
A historical review is made about Spongiform Encephalopathies which affect both animals and man. This is the base for an epidemiological and predictive analysis of these type of diseases, especially Bovine Spongiform Encephalopathy (BSE) as a present health problem. The scientific certainties or truths, such as the prion theory (PrPc-PrPsc), the low natural infectivity of these group of diseases, the high dose of prions necessary to produce the experimental disease, the species barrier or specificity, the individual susceptibility due to genetic traits, and the low transmission efficiency by the oral route, compared to the parenteral route, agree with the epidemiological observations of human cases of the variant of the Creutzfeldt-Jakob disease (vCJD), which is 0.1 cases per million inhabitants and year. The present and future prediction of BSE should not be alarmist, taking into account the certainties that we know.
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Assessing fitness to stand trial: the utility of the Fitness Interview Test (revised edition).
Zapf, P A; Roesch, R; Viljoen, J L
2001-06-01
In Canada most evaluations of fitness to stand trial are conducted on an inpatient basis. This costs time and money, and deprives those defendants remanded for evaluation of liberty. This research assessed the predictive efficiency of the Fitness Interview Test, revised edition (FIT) as a screening instrument for fitness to stand trial. We compared decisions about fitness to stand trial, based on the FIT, with the results of institution-based evaluations for 2 samples of men remanded for inpatient fitness assessments. The FIT demonstrates excellent utility as a screening instrument. The FIT shows good sensitivity and negative predictive power, which suggests that it can reliably screen those individuals who are clearly fit to stand trial, before they are remanded to an inpatient facility for a fitness assessment. We discuss the implications for evaluating fitness to stand trial, particularly in terms of the need for community-based alternatives to traditional forensic assessments.
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Numerical methods for engine-airframe integration
DOE Office of Scientific and Technical Information (OSTI.GOV)
Murthy, S.N.B.; Paynter, G.C.
1986-01-01
Various papers on numerical methods for engine-airframe integration are presented. The individual topics considered include: scientific computing environment for the 1980s, overview of prediction of complex turbulent flows, numerical solutions of the compressible Navier-Stokes equations, elements of computational engine/airframe integrations, computational requirements for efficient engine installation, application of CAE and CFD techniques to complete tactical missile design, CFD applications to engine/airframe integration, and application of a second-generation low-order panel methods to powerplant installation studies. Also addressed are: three-dimensional flow analysis of turboprop inlet and nacelle configurations, application of computational methods to the design of large turbofan engine nacelles, comparison ofmore » full potential and Euler solution algorithms for aeropropulsive flow field computations, subsonic/transonic, supersonic nozzle flows and nozzle integration, subsonic/transonic prediction capabilities for nozzle/afterbody configurations, three-dimensional viscous design methodology of supersonic inlet systems for advanced technology aircraft, and a user's technology assessment.« less
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Do institutional logics predict interpretation of contract rules at the dental chair-side?
Harris, Rebecca; Brown, Stephen; Holt, Robin; Perkins, Elizabeth
2014-01-01
In quasi-markets, contracts find purchasers influencing health care providers, although problems exist where providers use personal bias and heuristics to respond to written agreements, tending towards the moral hazard of opportunism. Previous research on quasi-market contracts typically understands opportunism as fully rational, individual responses selecting maximally efficient outcomes from a set of possibilities. We take a more emotive and collective view of contracting, exploring the influence of institutional logics in relation to the opportunistic behaviour of dentists. Following earlier qualitative work where we identified four institutional logics in English general dental practice, and six dental contract areas where there was scope for opportunism; in 2013 we surveyed 924 dentists to investigate these logics and whether they had predictive purchase over dentists' chair-side behaviour. Factor analysis involving 300 responses identified four logics entwined in (often technical) behaviour: entrepreneurial commercialism, duty to staff and patients, managerialism, public good. PMID:25441320
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NASA Astrophysics Data System (ADS)
Peri, Claudio; Gori, Alessandro; Gagni, Paola; Sola, Laura; Girelli, Daniela; Sottotetti, Samantha; Cariani, Lisa; Chiari, Marcella; Cretich, Marina; Colombo, Giorgio
2016-09-01
Efficient diagnosis of emerging and novel bacterial infections is fundamental to guide decisions on therapeutic treatments. Here, we engineered a novel rational strategy to design peptide microarray platforms, which combines structural and genomic analyses to predict the binding interfaces between diverse protein antigens and antibodies against Burkholderia cepacia complex infections present in the sera of Cystic Fibrosis (CF) patients. The predicted binding interfaces on the antigens are synthesized in the form of isolated peptides and chemically optimized for controlled orientation on the surface. Our platform displays multiple Burkholderia-related epitopes and is shown to diagnose infected individuals even in presence of superinfections caused by other prevalent CF pathogens, with limited cost and time requirements. Moreover, our data point out that the specific patterns determined by combined probe responses might provide a characterization of Burkholderia infections even at the subtype level (genomovars). The method is general and immediately applicable to other bacteria.
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Chu, Chi Meng; Thomas, Stuart D M; Ogloff, James R P; Daffern, Michael
2013-04-01
Although violence risk assessment knowledge and practice has advanced over the past few decades, it remains practically difficult to decide which measures clinicians should use to assess and make decisions about the violence potential of individuals on an ongoing basis, particularly in the short to medium term. Within this context, this study sought to compare the predictive accuracy of dynamic risk assessment measures for violence with static risk assessment measures over the short term (up to 1 month) and medium term (up to 6 months) in a forensic psychiatric inpatient setting. Results showed that dynamic measures were generally more accurate than static measures for short- to medium-term predictions of inpatient aggression. These findings highlight the necessity of using risk assessment measures that are sensitive to important clinical risk state variables to improve the short- to medium-term prediction of aggression within the forensic inpatient setting. Such knowledge can assist with the development of more accurate and efficient risk assessment procedures, including the selection of appropriate risk assessment instruments to manage and prevent the violence of offenders with mental illnesses during inpatient treatment.
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Kirschner, Andreas; Frishman, Dmitrij
2008-10-01
Prediction of beta-turns from amino acid sequences has long been recognized as an important problem in structural bioinformatics due to their frequent occurrence as well as their structural and functional significance. Because various structural features of proteins are intercorrelated, secondary structure information has been often employed as an additional input for machine learning algorithms while predicting beta-turns. Here we present a novel bidirectional Elman-type recurrent neural network with multiple output layers (MOLEBRNN) capable of predicting multiple mutually dependent structural motifs and demonstrate its efficiency in recognizing three aspects of protein structure: beta-turns, beta-turn types, and secondary structure. The advantage of our method compared to other predictors is that it does not require any external input except for sequence profiles because interdependencies between different structural features are taken into account implicitly during the learning process. In a sevenfold cross-validation experiment on a standard test dataset our method exhibits the total prediction accuracy of 77.9% and the Mathew's Correlation Coefficient of 0.45, the highest performance reported so far. It also outperforms other known methods in delineating individual turn types. We demonstrate how simultaneous prediction of multiple targets influences prediction performance on single targets. The MOLEBRNN presented here is a generic method applicable in a variety of research fields where multiple mutually depending target classes need to be predicted. http://webclu.bio.wzw.tum.de/predator-web/.
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The influence of mixed tree plantations on the nutrition of individual species: a review.
Richards, Anna E; Forrester, David I; Bauhus, Jürgen; Scherer-Lorenzen, Michael
2010-09-01
Productivity of tree plantations is a function of the supply, capture and efficiency of use of resources, as outlined in the Production Ecology Equation. Species interactions in mixed-species stands can influence each of these variables. The importance of resource-use efficiency in determining forest productivity has been clearly demonstrated in monocultures; however, substantial knowledge gaps remain for mixtures. This review examines how the physiology and morphology of a given species can vary depending on whether it grows in a mixture or monoculture. We outline how physiological and morphological shifts within species, resulting from interactions in mixtures, may influence the three variables of the Production Ecology Equation, with an emphasis on nutrient resources [nitrogen (N) and phosphorus (P)]. These include (i) resource availability, including soil nutrient mineralization, N₂ fixation and litter decomposition; (ii) proportion of resources captured, resulting from shifts in spatial, temporal and chemical patterns of root dynamics; (iii) resource-use efficiency. We found that more than 50% of mixed-species studies report a shift to greater above-ground nutrient content of species grown in mixtures compared to monocultures, indicating an increase in the proportion of resources captured from a site. Secondly, a meta-analysis showed that foliar N concentrations significantly increased for a given species in a mixture containing N₂-fixing species, compared to a monoculture, suggesting higher rates of photosynthesis and greater resource-use efficiency. Significant shifts in N- and P-use efficiencies of a given species, when grown in a mixture compared to a monoculture, occurred in over 65% of studies where resource-use efficiency could be calculated. Such shifts can result from changes in canopy photosynthetic capacities, changes in carbon allocation or changes to foliar nutrient residence times of species in a mixture. We recommend that future research focus on individual species' changes, particularly with respect to resource-use efficiency (including nutrients, water and light), when trees are grown in mixtures compared to monocultures. A better understanding of processes responsible for changes to tree productivity in mixed-species tree plantations can improve species, and within-species, selection so that the long-term outcome of mixtures is more predictable.
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Sparse RNA folding revisited: space-efficient minimum free energy structure prediction.
Will, Sebastian; Jabbari, Hosna
2016-01-01
RNA secondary structure prediction by energy minimization is the central computational tool for the analysis of structural non-coding RNAs and their interactions. Sparsification has been successfully applied to improve the time efficiency of various structure prediction algorithms while guaranteeing the same result; however, for many such folding problems, space efficiency is of even greater concern, particularly for long RNA sequences. So far, space-efficient sparsified RNA folding with fold reconstruction was solved only for simple base-pair-based pseudo-energy models. Here, we revisit the problem of space-efficient free energy minimization. Whereas the space-efficient minimization of the free energy has been sketched before, the reconstruction of the optimum structure has not even been discussed. We show that this reconstruction is not possible in trivial extension of the method for simple energy models. Then, we present the time- and space-efficient sparsified free energy minimization algorithm SparseMFEFold that guarantees MFE structure prediction. In particular, this novel algorithm provides efficient fold reconstruction based on dynamically garbage-collected trace arrows. The complexity of our algorithm depends on two parameters, the number of candidates Z and the number of trace arrows T; both are bounded by [Formula: see text], but are typically much smaller. The time complexity of RNA folding is reduced from [Formula: see text] to [Formula: see text]; the space complexity, from [Formula: see text] to [Formula: see text]. Our empirical results show more than 80 % space savings over RNAfold [Vienna RNA package] on the long RNAs from the RNA STRAND database (≥2500 bases). The presented technique is intentionally generalizable to complex prediction algorithms; due to their high space demands, algorithms like pseudoknot prediction and RNA-RNA-interaction prediction are expected to profit even stronger than "standard" MFE folding. SparseMFEFold is free software, available at http://www.bioinf.uni-leipzig.de/~will/Software/SparseMFEFold.
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Tan, Y M; Flynn, M R
2000-10-01
The transfer efficiency of a spray-painting gun is defined as the amount of coating applied to the workpiece divided by the amount sprayed. Characterizing this transfer process allows for accurate estimation of the overspray generation rate, which is important for determining a spray painter's exposure to airborne contaminants. This study presents an experimental evaluation of a mathematical model for predicting the transfer efficiency of a high volume-low pressure spray gun. The effects of gun-to-surface distance and nozzle pressure on the agreement between the transfer efficiency measurement and prediction were examined. Wind tunnel studies and non-volatile vacuum pump oil in place of commercial paint were used to determine transfer efficiency at nine gun-to-surface distances and four nozzle pressure levels. The mathematical model successfully predicts transfer efficiency within the uncertainty limits. The least squares regression between measured and predicted transfer efficiency has a slope of 0.83 and an intercept of 0.12 (R2 = 0.98). Two correction factors were determined to improve the mathematical model. At higher nozzle pressure settings, 6.5 psig and 5.5 psig, the correction factor is a function of both gun-to-surface distance and nozzle pressure level. At lower nozzle pressures, 4 psig and 2.75 psig, gun-to-surface distance slightly influences the correction factor, while nozzle pressure has no discernible effect.
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Molinaro, Nicola; Giannelli, Francesco; Caffarra, Sendy; Martin, Clara
2017-07-01
Language comprehension is largely supported by predictive mechanisms that account for the ease and speed with which communication unfolds. Both native and proficient non-native speakers can efficiently handle contextual cues to generate reliable linguistic expectations. However, the link between the variability of the linguistic background of the speaker and the hierarchical format of the representations predicted is still not clear. We here investigate whether native language exposure to typologically highly diverse languages (Spanish and Basque) affects the way early balanced bilingual speakers carry out language predictions. During Spanish sentence comprehension, participants developed predictions of words the form of which (noun ending) could be either diagnostic of grammatical gender values (transparent) or totally ambiguous (opaque). We measured electrophysiological prediction effects time-locked both to the target word and to its determiner, with the former being expected or unexpected. Event-related (N200-N400) and oscillatory activity in the low beta-band (15-17Hz) frequency channel showed that both Spanish and Basque natives optimally carry out lexical predictions independently of word transparency. Crucially, in contrast to Spanish natives, Basque natives displayed visual word form predictions for transparent words, in consistency with the relevance that noun endings (post-nominal suffixes) play in their native language. We conclude that early language exposure largely shapes prediction mechanisms, so that bilinguals reading in their second language rely on the distributional regularities that are highly relevant in their first language. More importantly, we show that individual linguistic experience hierarchically modulates the format of the predicted representation. Copyright © 2017 Elsevier B.V. All rights reserved.
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Tomasik, M
1982-01-01
Glucose utilization by the erythrocytes, lactic acid concentration in the blood and erythrocytes, and haematocrit value were determined before exercise and during one hour rest following maximal exercise in 97 individuals of either sex differing in physical efficiency. In the investigations reported by the author individuals with strikingly high physical fitness performed maximal work one-third greater than that performed by individuals with medium fitness. The serum concentration of lactic acid was in all individuals above the resting value still after 60 minutes of rest. On the other hand, this concentration returned to the normal level in the erythrocytes but only in individuals with strikingly high efficiency. Glucose utilization by the erythrocytes during the restitution period was highest immediately after the exercise in all studied individuals and showed a tendency for more rapid return to resting values again in individuals with highest efficiency. The investigation of very efficient individuals repeated twice demonstrated greater utilization of glucose by the erythrocytes at the time of greater maximal exercise. This was associated with greater lactic acid concentration in the serum and erythrocytes throughout the whole one-hour rest period. The observed facts suggest an active participation of erythrocytes in the process of adaptation of the organism to exercise.
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Spiral Form of the Human Cochlea Results from Spatial Constraints.
Pietsch, M; Aguirre Dávila, L; Erfurt, P; Avci, E; Lenarz, T; Kral, A
2017-08-08
The human inner ear has an intricate spiral shape often compared to shells of mollusks, particularly to the nautilus shell. It has inspired many functional hearing theories. The reasons for this complex geometry remain unresolved. We digitized 138 human cochleae at microscopic resolution and observed an astonishing interindividual variability in the shape. A 3D analytical cochlear model was developed that fits the analyzed data with high precision. The cochlear geometry neither matched a proposed function, namely sound focusing similar to a whispering gallery, nor did it have the form of a nautilus. Instead, the innate cochlear blueprint and its actual ontogenetic variants were determined by spatial constraints and resulted from an efficient packing of the cochlear duct within the petrous bone. The analytical model predicts well the individual 3D cochlear geometry from few clinical measures and represents a clinical tool for an individualized approach to neurosensory restoration with cochlear implants.
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The non-random walk of stock prices: the long-term correlation between signs and sizes
NASA Astrophysics Data System (ADS)
La Spada, G.; Farmer, J. D.; Lillo, F.
2008-08-01
We investigate the random walk of prices by developing a simple model relating the properties of the signs and absolute values of individual price changes to the diffusion rate (volatility) of prices at longer time scales. We show that this benchmark model is unable to reproduce the diffusion properties of real prices. Specifically, we find that for one hour intervals this model consistently over-predicts the volatility of real price series by about 70%, and that this effect becomes stronger as the length of the intervals increases. By selectively shuffling some components of the data while preserving others we are able to show that this discrepancy is caused by a subtle but long-range non-contemporaneous correlation between the signs and sizes of individual returns. We conjecture that this is related to the long-memory of transaction signs and the need to enforce market efficiency.
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Architecture and functional ecology of the human gastrocnemius muscle-tendon unit.
Butler, Erin E; Dominy, Nathaniel J
2016-04-01
The gastrocnemius muscle-tendon unit (MTU) is central to human locomotion. Structural variation in the human gastrocnemius MTU is predicted to affect the efficiency of locomotion, a concept most often explored in the context of performance activities. For example, stiffness of the Achilles tendon varies among individuals with different histories of competitive running. Such a finding highlights the functional variation of individuals and raises the possibility of similar variation between populations, perhaps in response to specific ecological or environmental demands. Researchers often assume minimal variation in human populations, or that industrialized populations represent the human species as well as any other. Yet rainforest hunter-gatherers, which often express the human pygmy phenotype, contradict such assumptions. Indeed, the human pygmy phenotype is a potential model system for exploring the range of ecomorphological variation in the architecture of human hindlimb muscles, a concept we review here. © 2015 Anatomical Society.
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Goodsman, Devin W.; Aukema, Brian H.; McDowell, Nate G.; ...
2017-11-26
Phenology models are becoming increasingly important tools to accurately predict how climate change will impact the life histories of organisms. We propose a class of integral projection phenology models derived from stochastic individual-based models of insect development and demography. Our derivation, which is based on the rate summation concept, produces integral projection models that capture the effect of phenotypic rate variability on insect phenology, but which are typically more computationally frugal than equivalent individual-based phenology models. We demonstrate our approach using a temperature-dependent model of the demography of the mountain pine beetle (Dendroctonus ponderosae Hopkins), an insect that kills maturemore » pine trees. This work illustrates how a wide range of stochastic phenology models can be reformulated as integral projection models. Due to their computational efficiency, these integral projection models are suitable for deployment in large-scale simulations, such as studies of altered pest distributions under climate change.« less
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Schmader, Toni; Forbes, Chad E; Zhang, Shen; Mendes, Wendy Berry
2009-05-01
Three studies tested the hypothesis that negative metacognitive interpretations of anxious arousal under stereotype threat create cognitive deficits in intellectually threatening environments. Study 1 showed that among minority and White undergraduates, anxiety about an intelligence test predicted lower working memory when participants were primed with doubt as compared to confidence. Study 2 replicated this pattern with women and showed it to be unique to intellectually threatening environments. Study 3 used emotional reappraisal as an individual difference measure of the tendency to metacognitively reinterpret negative emotions and found that when sympathetic activation was high (indexed by salivary alpha-amylase), women who tended to reappraise negative feelings performed better in math and felt less self-doubt than those low in reappraisal. Overall, findings highlight how metacognitive interpretations of affect can undermine cognitive efficiency under stereotype threat and offer implications for the situational and individual difference variables that buffer people from these effects.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Goodsman, Devin W.; Aukema, Brian H.; McDowell, Nate G.
Phenology models are becoming increasingly important tools to accurately predict how climate change will impact the life histories of organisms. We propose a class of integral projection phenology models derived from stochastic individual-based models of insect development and demography. Our derivation, which is based on the rate summation concept, produces integral projection models that capture the effect of phenotypic rate variability on insect phenology, but which are typically more computationally frugal than equivalent individual-based phenology models. We demonstrate our approach using a temperature-dependent model of the demography of the mountain pine beetle (Dendroctonus ponderosae Hopkins), an insect that kills maturemore » pine trees. This work illustrates how a wide range of stochastic phenology models can be reformulated as integral projection models. Due to their computational efficiency, these integral projection models are suitable for deployment in large-scale simulations, such as studies of altered pest distributions under climate change.« less
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Howell, Bryan; Lad, Shivanand P.; Grill, Warren M.
2014-01-01
Spinal cord stimulation (SCS) is an alternative or adjunct therapy to treat chronic pain, a prevalent and clinically challenging condition. Although SCS has substantial clinical success, the therapy is still prone to failures, including lead breakage, lead migration, and poor pain relief. The goal of this study was to develop a computational model of SCS and use the model to compare activation of neural elements during intradural and extradural electrode placement. We constructed five patient-specific models of SCS. Stimulation thresholds predicted by the model were compared to stimulation thresholds measured intraoperatively, and we used these models to quantify the efficiency and selectivity of intradural and extradural SCS. Intradural placement dramatically increased stimulation efficiency and reduced the power required to stimulate the dorsal columns by more than 90%. Intradural placement also increased selectivity, allowing activation of a greater proportion of dorsal column fibers before spread of activation to dorsal root fibers, as well as more selective activation of individual dermatomes at different lateral deviations from the midline. Further, the results suggest that current electrode designs used for extradural SCS are not optimal for intradural SCS, and a novel azimuthal tripolar design increased stimulation selectivity, even beyond that achieved with an intradural paddle array. Increased stimulation efficiency is expected to increase the battery life of implantable pulse generators, increase the recharge interval of rechargeable implantable pulse generators, and potentially reduce stimulator volume. The greater selectivity of intradural stimulation may improve the success rate of SCS by mitigating the sensitivity of pain relief to malpositioning of the electrode. The outcome of this effort is a better quantitative understanding of how intradural electrode placement can potentially increase the selectivity and efficiency of SCS, which, in turn, provides predictions that can be tested in future clinical studies assessing the potential therapeutic benefits of intradural SCS. PMID:25536035
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Ihne, Jessica L; Gallagher, Natalie M; Sullivan, Marie; Callicott, Joseph H; Green, Adam E
2016-01-01
Perhaps the most widely studied effect to emerge from the combination of neuroimaging and human genetics is the association of the COMT-Val(108/158)Met polymorphism with prefrontal activity during working memory. COMT-Val is a putative risk factor in schizophrenia, which is characterized by disordered prefrontal function. Work in healthy populations has sought to characterize mechanisms by which the valine (Val) allele may lead to disadvantaged prefrontal cognition. Lower activity in methionine (Met) carriers has been interpreted as advantageous neural efficiency. Notably, however, studies reporting COMT effects on neural efficiency have generally not reported working memory performance effects. Those studies have employed relatively low/easy working memory loads. Higher loads are known to elicit individual differences in working memory performance that are not visible at lower loads. If COMT-Met confers greater neural efficiency when working memory is easy, a reasonable prediction is that Met carriers will be better able to cope with increasing demand for neural resources when working memory becomes difficult. To our knowledge, this prediction has thus far gone untested. Here, we tested performance on three working memory tasks. Performance on each task was measured at multiple levels of load/difficulty, including loads more demanding than those used in prior studies. We found no genotype-by-load interactions or main effects of COMT genotype on accuracy or reaction time. Indeed, even testing for performance differences at each load of each task failed to find a single significant effect of COMT genotype. Thus, even if COMT genotype has the effects on prefrontal efficiency that prior work has suggested, such effects may not directly impact high-load working memory ability. The present findings accord with previous evidence that behavioral effects of COMT are small or nonexistent and, more broadly, with a growing consensus that substantial effects on phenotype will not emerge from candidate gene studies. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Political ideology affects energy-efficiency attitudes and choices
Gromet, Dena M.; Kunreuther, Howard; Larrick, Richard P.
2013-01-01
This research demonstrates how promoting the environment can negatively affect adoption of energy efficiency in the United States because of the political polarization surrounding environmental issues. Study 1 demonstrated that more politically conservative individuals were less in favor of investment in energy-efficient technology than were those who were more politically liberal. This finding was driven primarily by the lessened psychological value that more conservative individuals placed on reducing carbon emissions. Study 2 showed that this difference has consequences: In a real-choice context, more conservative individuals were less likely to purchase a more expensive energy-efficient light bulb when it was labeled with an environmental message than when it was unlabeled. These results highlight the importance of taking into account psychological value-based considerations in the individual adoption of energy-efficient technology in the United States and beyond. PMID:23630266
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Political ideology affects energy-efficiency attitudes and choices.
Gromet, Dena M; Kunreuther, Howard; Larrick, Richard P
2013-06-04
This research demonstrates how promoting the environment can negatively affect adoption of energy efficiency in the United States because of the political polarization surrounding environmental issues. Study 1 demonstrated that more politically conservative individuals were less in favor of investment in energy-efficient technology than were those who were more politically liberal. This finding was driven primarily by the lessened psychological value that more conservative individuals placed on reducing carbon emissions. Study 2 showed that this difference has consequences: In a real-choice context, more conservative individuals were less likely to purchase a more expensive energy-efficient light bulb when it was labeled with an environmental message than when it was unlabeled. These results highlight the importance of taking into account psychological value-based considerations in the individual adoption of energy-efficient technology in the United States and beyond.
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ERIC Educational Resources Information Center
Hill, Anita; And Others
1985-01-01
To test ways of predicting how efficiently visually impaired children learn travel skills, a criteria checklist of spatial skills was developed for close-body space, local space, and geographical/travel space. Comparison was made between predictors of efficient learning including subjective ratings of teachers, personal qualities and factors of…
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Urinary Biomarkers and Obstructive Sleep Apnea in Patients with Down Syndrome
Elsharkawi, Ibrahim; Gozal, David; Macklin, Eric A.; Voelz, Lauren; Weintraub, Gil; Skotko, Brian G.
2017-01-01
Study Objectives The study aim was to compare urinary biomarkers in individuals with Down syndrome (DS) with and without obstructive sleep apnea (OSA) to those of age- and sex-matched neurotypically developing healthy controls (HC). We further investigated whether we could predict OSA in individuals with DS using these biomarkers. Methods Urine samples were collected from 58 individuals with DS the night before or the morning after their scheduled overnight polysomnogram or both, of whom 47 could be age- and sex-matched to a sample of 43 HC. Concentrations of 12 neurotransmitters were determined by enzyme-linked immunosorbent assay. Log-transformed creatinine-corrected assay levels were normalized. Normalized z-scores were compared between individuals with DS vs. HC, between individuals with DS with vs. without OSA, and to derive composite models to predict OSA. Results Most night-sampled urinary biomarkers were elevated among individuals with DS relative to matched HC. No urinary biomarker levels differed between individuals with DS with vs. without OSA. A combination of four urinary biomarkers predicted AHI > 1 with a positive predictive value of 90% and a negative predictive value of 68%. Conclusions Having DS, even in the absence of concurrent OSA, is associated with a different urinary biomarker profile when compared to HC. Therefore, while urinary biomarkers may be predictive of OSA in the general pediatric population, a different approach is needed in interpreting urinary biomarker assays in individuals with DS. Certain biomarkers also seem promising to be predictive of OSA in individuals with DS. PMID:28522103
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Yeo, Ronald A; Ryman, Sephira G; van den Heuvel, Martijn P; de Reus, Marcel A; Jung, Rex E; Pommy, Jessica; Mayer, Andrew R; Ehrlich, Stefan; Schulz, S Charles; Morrow, Eric M; Manoach, Dara; Ho, Beng-Choon; Sponheim, Scott R; Calhoun, Vince D
2016-02-01
One of the most prominent features of schizophrenia is relatively lower general cognitive ability (GCA). An emerging approach to understanding the roots of variation in GCA relies on network properties of the brain. In this multi-center study, we determined global characteristics of brain networks using graph theory and related these to GCA in healthy controls and individuals with schizophrenia. Participants (N=116 controls, 80 patients with schizophrenia) were recruited from four sites. GCA was represented by the first principal component of a large battery of neurocognitive tests. Graph metrics were derived from diffusion-weighted imaging. The global metrics of longer characteristic path length and reduced overall connectivity predicted lower GCA across groups, and group differences were noted for both variables. Measures of clustering, efficiency, and modularity did not differ across groups or predict GCA. Follow-up analyses investigated three topological types of connectivity--connections among high degree "rich club" nodes, "feeder" connections to these rich club nodes, and "local" connections not involving the rich club. Rich club and local connectivity predicted performance across groups. In a subsample (N=101 controls, 56 patients), a genetic measure reflecting mutation load, based on rare copy number deletions, was associated with longer characteristic path length. Results highlight the importance of characteristic path lengths and rich club connectivity for GCA and provide no evidence for group differences in the relationships between graph metrics and GCA.
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Hu, Xiao Hua; Sun, X.; Hector, Jr., L. G.; ...
2017-04-21
Here, microstructure-based constitutive models for multiphase steels require accurate constitutive properties of the individual phases for component forming and performance simulations. We address this requirement with a combined experimental/theoretical methodology which determines the critical resolved shear stresses and hardening parameters of the constituent phases in QP980, a TRIP assisted steel subject to a two-step quenching and partitioning heat treatment. High energy X-Ray diffraction (HEXRD) from a synchrotron source provided the average lattice strains of the ferrite, martensite, and austenite phases from the measured volume during in situ tensile deformation. The HEXRD data was then input to a computationally efficient, elastic-plasticmore » self-consistent (EPSC) crystal plasticity model which estimated the constitutive parameters of different slip systems for the three phases via a trial-and-error approach. The EPSC-estimated parameters are then input to a finite element crystal plasticity (CPFE) model representing the QP980 tensile sample. The predicted lattice strains and global stress versus strain curves are found to be 8% lower that the EPSC model predicted values and from the HEXRD measurements, respectively. This discrepancy, which is attributed to the stiff secant assumption in the EPSC formulation, is resolved with a second step in which CPFE is used to iteratively refine the EPSC-estimated parameters. Remarkably close agreement is obtained between the theoretically-predicted and experimentally derived flow curve for the QP980 material.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Hu, X. H.; Sun, X.; Hector, L. G.
2017-06-01
Microstructure-based constitutive models for multiphase steels require accurate constitutive properties of the individual phases for component forming and performance simulations. We address this requirement with a combined experimental/theoretical methodology which determines the critical resolved shear stresses and hardening parameters of the constituent phases in QP980, a TRIP assisted steel subject to a two-step quenching and partitioning heat treatment. High energy X-Ray diffraction (HEXRD) from a synchrotron source provided the average lattice strains of the ferrite, martensite, and austenite phases from the measured volume during in situ tensile deformation. The HEXRD data was then input to a computationally efficient, elastic-plastic self-consistentmore » (EPSC) crystal plasticity model which estimated the constitutive parameters of different slip systems for the three phases via a trial-and-error approach. The EPSC-estimated parameters are then input to a finite element crystal plasticity (CPFE) model representing the QP980 tensile sample. The predicted lattice strains and global stress versus strain curves are found to be 8% lower that the EPSC model predicted values and from the HEXRD measurements, respectively. This discrepancy, which is attributed to the stiff secant assumption in the EPSC formulation, is resolved with a second step in which CPFE is used to iteratively refine the EPSC-estimated parameters. Remarkably close agreement is obtained between the theoretically-predicted and experimentally derived flow curve for the QP980 material.« less
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Perry, Sara Jansen; Rubino, Cristina; Witt, L A
2011-04-01
In an integrated test of the job demands-resources model and trait activation theory, we predicted that the general job performance of employees who also hold supervisory roles may act as a demand to subordinates, depending on levels of subordinate conscientiousness. In a sample of 313 customer service call centre employees, we found that high-conscientiousness individuals were more likely to experience emotional exhaustion, and low-conscientiousness individuals were less likely as the general job performance of their supervisor improved. The results were curvilinear, such that high-conscientiousness individuals' exhaustion levelled off with very high supervisor performance (two standard deviations above the mean), and low-conscientiousness individuals' exhaustion levelled off as supervisor performance improved from moderate to high. These findings suggest high-conscientiousness employees may efficiently handle demands presented by a low-performing coworker who is their boss, but when performance expectations are high (i.e. high-performing boss), these achievement-oriented employees may direct their resources (i.e. energy and time) towards performance-related efforts at the expense of their well-being. Conversely, low-conscientiousness employees suffer when paired with a low-performing boss, but benefit from a supervisor who demonstrates at least moderate job performance.
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NASA Astrophysics Data System (ADS)
da Silva, Thaísa Leal; Agostini, Luciano Volcan; da Silva Cruz, Luis A.
2014-05-01
Intra prediction is a very important tool in current video coding standards. High-efficiency video coding (HEVC) intra prediction presents relevant gains in encoding efficiency when compared to previous standards, but with a very important increase in the computational complexity since 33 directional angular modes must be evaluated. Motivated by this high complexity, this article presents a complexity reduction algorithm developed to reduce the HEVC intra mode decision complexity targeting multiview videos. The proposed algorithm presents an efficient fast intra prediction compliant with singleview and multiview video encoding. This fast solution defines a reduced subset of intra directions according to the video texture and it exploits the relationship between prediction units (PUs) of neighbor depth levels of the coding tree. This fast intra coding procedure is used to develop an inter-view prediction method, which exploits the relationship between the intra mode directions of adjacent views to further accelerate the intra prediction process in multiview video encoding applications. When compared to HEVC simulcast, our method achieves a complexity reduction of up to 47.77%, at the cost of an average BD-PSNR loss of 0.08 dB.
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Eijkemans, Marinus J C; Polinder, Suzanne; Mulders, Annemarie G M G J; Laven, Joop S E; Habbema, J Dik F; Fauser, Bart C J M
2005-10-01
Conventional treatment in normogonadotrophic anovulatory infertility (WHO 2) consists of clomiphene citrate (CC), followed by exogenous gonadotrophins (FSH) and IVF. Response to these treatments may be predicted on the basis of individual patient characteristics. We aimed to devise a patient-tailored, cost-effective treatment algorithm involving the above-mentioned treatment modalities, based on individual patient characteristics. Sixteen prognostic groups are defined, according to the presence or absence of: age >30 years, amenorrhea, elevated androgen levels and obesity. The chances of response with each of the three treatments were calculated using prediction models. Treatment costs were based on the data of 240 patients visiting a specialist academic fertility unit. Outcome was an ongoing pregnancy within 12 months after initiation of treatment. The costs per pregnancy of three different strategies were compared, with a threshold for cost-effectiveness of 10 000. The strategy CC + FSH + IVF compared with FSH + IVF generated more pregnancies against lower costs. Compared with CC + IVF, it also produced more pregnancies, but at higher costs. For <30 years of age with normal androgen levels, costs per pregnancy were less than 10 000. For women >30 years old, costs per pregnancy were 25 000 and over 200 000, when presenting with normal or elevated androgen levels, respectively. The conventional treatment protocol is efficient for women aged <30 years with normal androgen levels. For women >30 years old with elevated androgen levels, FSH may be skipped.
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Obstructive sleep apnea alters sleep stage transition dynamics.
Bianchi, Matt T; Cash, Sydney S; Mietus, Joseph; Peng, Chung-Kang; Thomas, Robert
2010-06-28
Enhanced characterization of sleep architecture, compared with routine polysomnographic metrics such as stage percentages and sleep efficiency, may improve the predictive phenotyping of fragmented sleep. One approach involves using stage transition analysis to characterize sleep continuity. We analyzed hypnograms from Sleep Heart Health Study (SHHS) participants using the following stage designations: wake after sleep onset (WASO), non-rapid eye movement (NREM) sleep, and REM sleep. We show that individual patient hypnograms contain insufficient number of bouts to adequately describe the transition kinetics, necessitating pooling of data. We compared a control group of individuals free of medications, obstructive sleep apnea (OSA), medical co-morbidities, or sleepiness (n = 374) with mild (n = 496) or severe OSA (n = 338). WASO, REM sleep, and NREM sleep bout durations exhibited multi-exponential temporal dynamics. The presence of OSA accelerated the "decay" rate of NREM and REM sleep bouts, resulting in instability manifesting as shorter bouts and increased number of stage transitions. For WASO bouts, previously attributed to a power law process, a multi-exponential decay described the data well. Simulations demonstrated that a multi-exponential process can mimic a power law distribution. OSA alters sleep architecture dynamics by decreasing the temporal stability of NREM and REM sleep bouts. Multi-exponential fitting is superior to routine mono-exponential fitting, and may thus provide improved predictive metrics of sleep continuity. However, because a single night of sleep contains insufficient transitions to characterize these dynamics, extended monitoring of sleep, probably at home, would be necessary for individualized clinical application.
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Optimizing complex phenotypes through model-guided multiplex genome engineering
Kuznetsov, Gleb; Goodman, Daniel B.; Filsinger, Gabriel T.; ...
2017-05-25
Here, we present a method for identifying genomic modifications that optimize a complex phenotype through multiplex genome engineering and predictive modeling. We apply our method to identify six single nucleotide mutations that recover 59% of the fitness defect exhibited by the 63-codon E. coli strain C321.ΔA. By introducing targeted combinations of changes in multiplex we generate rich genotypic and phenotypic diversity and characterize clones using whole-genome sequencing and doubling time measurements. Regularized multivariate linear regression accurately quantifies individual allelic effects and overcomes bias from hitchhiking mutations and context-dependence of genome editing efficiency that would confound other strategies.
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Optimizing complex phenotypes through model-guided multiplex genome engineering
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kuznetsov, Gleb; Goodman, Daniel B.; Filsinger, Gabriel T.
Here, we present a method for identifying genomic modifications that optimize a complex phenotype through multiplex genome engineering and predictive modeling. We apply our method to identify six single nucleotide mutations that recover 59% of the fitness defect exhibited by the 63-codon E. coli strain C321.ΔA. By introducing targeted combinations of changes in multiplex we generate rich genotypic and phenotypic diversity and characterize clones using whole-genome sequencing and doubling time measurements. Regularized multivariate linear regression accurately quantifies individual allelic effects and overcomes bias from hitchhiking mutations and context-dependence of genome editing efficiency that would confound other strategies.
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Mukunthan, B; Nagaveni, N
2014-01-01
In genetic engineering, conventional techniques and algorithms employed by forensic scientists to assist in identification of individuals on the basis of their respective DNA profiles involves more complex computational steps and mathematical formulae, also the identification of location of mutation in a genomic sequence in laboratories is still an exigent task. This novel approach provides ability to solve the problems that do not have an algorithmic solution and the available solutions are also too complex to be found. The perfect blend made of bioinformatics and neural networks technique results in efficient DNA pattern analysis algorithm with utmost prediction accuracy.
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Economic networks: the new challenges.
Schweitzer, Frank; Fagiolo, Giorgio; Sornette, Didier; Vega-Redondo, Fernando; Vespignani, Alessandro; White, Douglas R
2009-07-24
The current economic crisis illustrates a critical need for new and fundamental understanding of the structure and dynamics of economic networks. Economic systems are increasingly built on interdependencies, implemented through trans-national credit and investment networks, trade relations, or supply chains that have proven difficult to predict and control. We need, therefore, an approach that stresses the systemic complexity of economic networks and that can be used to revise and extend established paradigms in economic theory. This will facilitate the design of policies that reduce conflicts between individual interests and global efficiency, as well as reduce the risk of global failure by making economic networks more robust.
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Schrag, Tobias A; Westhues, Matthias; Schipprack, Wolfgang; Seifert, Felix; Thiemann, Alexander; Scholten, Stefan; Melchinger, Albrecht E
2018-04-01
The ability to predict the agronomic performance of single-crosses with high precision is essential for selecting superior candidates for hybrid breeding. With recent technological advances, thousands of new parent lines, and, consequently, millions of new hybrid combinations are possible in each breeding cycle, yet only a few hundred can be produced and phenotyped in multi-environment yield trials. Well established prediction approaches such as best linear unbiased prediction (BLUP) using pedigree data and whole-genome prediction using genomic data are limited in capturing epistasis and interactions occurring within and among downstream biological strata such as transcriptome and metabolome. Because mRNA and small RNA (sRNA) sequences are involved in transcriptional, translational and post-translational processes, we expect them to provide information influencing several biological strata. However, using sRNA data of parent lines to predict hybrid performance has not yet been addressed. Here, we gathered genomic, transcriptomic (mRNA and sRNA) and metabolomic data of parent lines to evaluate the ability of the data to predict the performance of untested hybrids for important agronomic traits in grain maize. We found a considerable interaction for predictive ability between predictor and trait, with mRNA data being a superior predictor for grain yield and genomic data for grain dry matter content, while sRNA performed relatively poorly for both traits. Combining mRNA and genomic data as predictors resulted in high predictive abilities across both traits and combining other predictors improved prediction over that of the individual predictors alone. We conclude that downstream "omics" can complement genomics for hybrid prediction, and, thereby, contribute to more efficient selection of hybrid candidates. Copyright © 2018 by the Genetics Society of America.
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A nucleobase-centered coarse-grained representation for structure prediction of RNA motifs.
Poblete, Simón; Bottaro, Sandro; Bussi, Giovanni
2018-02-28
We introduce the SPlit-and-conQueR (SPQR) model, a coarse-grained (CG) representation of RNA designed for structure prediction and refinement. In our approach, the representation of a nucleotide consists of a point particle for the phosphate group and an anisotropic particle for the nucleoside. The interactions are, in principle, knowledge-based potentials inspired by the $\\mathcal {E}$SCORE function, a base-centered scoring function. However, a special treatment is given to base-pairing interactions and certain geometrical conformations which are lost in a raw knowledge-based model. This results in a representation able to describe planar canonical and non-canonical base pairs and base-phosphate interactions and to distinguish sugar puckers and glycosidic torsion conformations. The model is applied to the folding of several structures, including duplexes with internal loops of non-canonical base pairs, tetraloops, junctions and a pseudoknot. For the majority of these systems, experimental structures are correctly predicted at the level of individual contacts. We also propose a method for efficiently reintroducing atomistic detail from the CG representation.
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Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches.
Rawassizadeh, Reza; Tomitsch, Martin; Nourizadeh, Manouchehr; Momeni, Elaheh; Peery, Aaron; Ulanova, Liudmila; Pazzani, Michael
2015-09-08
As the availability and use of wearables increases, they are becoming a promising platform for context sensing and context analysis. Smartwatches are a particularly interesting platform for this purpose, as they offer salient advantages, such as their proximity to the human body. However, they also have limitations associated with their small form factor, such as processing power and battery life, which makes it difficult to simply transfer smartphone-based context sensing and prediction models to smartwatches. In this paper, we introduce an energy-efficient, generic, integrated framework for continuous context sensing and prediction on smartwatches. Our work extends previous approaches for context sensing and prediction on wrist-mounted wearables that perform predictive analytics outside the device. We offer a generic sensing module and a novel energy-efficient, on-device prediction module that is based on a semantic abstraction approach to convert sensor data into meaningful information objects, similar to human perception of a behavior. Through six evaluations, we analyze the energy efficiency of our framework modules, identify the optimal file structure for data access and demonstrate an increase in accuracy of prediction through our semantic abstraction method. The proposed framework is hardware independent and can serve as a reference model for implementing context sensing and prediction on small wearable devices beyond smartwatches, such as body-mounted cameras.
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Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches
Rawassizadeh, Reza; Tomitsch, Martin; Nourizadeh, Manouchehr; Momeni, Elaheh; Peery, Aaron; Ulanova, Liudmila; Pazzani, Michael
2015-01-01
As the availability and use of wearables increases, they are becoming a promising platform for context sensing and context analysis. Smartwatches are a particularly interesting platform for this purpose, as they offer salient advantages, such as their proximity to the human body. However, they also have limitations associated with their small form factor, such as processing power and battery life, which makes it difficult to simply transfer smartphone-based context sensing and prediction models to smartwatches. In this paper, we introduce an energy-efficient, generic, integrated framework for continuous context sensing and prediction on smartwatches. Our work extends previous approaches for context sensing and prediction on wrist-mounted wearables that perform predictive analytics outside the device. We offer a generic sensing module and a novel energy-efficient, on-device prediction module that is based on a semantic abstraction approach to convert sensor data into meaningful information objects, similar to human perception of a behavior. Through six evaluations, we analyze the energy efficiency of our framework modules, identify the optimal file structure for data access and demonstrate an increase in accuracy of prediction through our semantic abstraction method. The proposed framework is hardware independent and can serve as a reference model for implementing context sensing and prediction on small wearable devices beyond smartwatches, such as body-mounted cameras. PMID:26370997
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Dana, Alexandra; Tuller, Tamir
2014-12-01
Gene translation modeling and prediction is a fundamental problem that has numerous biomedical implementations. In this work we present a novel, user-friendly tool/index for calculating the mean of the typical decoding rates that enables predicting translation elongation efficiency of protein coding genes for different tissue types, developmental stages, and experimental conditions. The suggested translation efficiency index is based on the analysis of the organism's ribosome profiling data. This index could be used for example to predict changes in translation elongation efficiency of lowly expressed genes that usually have relatively low and/or biased ribosomal densities and protein levels measurements, or can be used for example for predicting translation efficiency of new genetically engineered genes. We demonstrate the usability of this index via the analysis of six organisms in different tissues and developmental stages. Distributable cross platform application and guideline are available for download at: http://www.cs.tau.ac.il/~tamirtul/MTDR/MTDR_Install.html. Copyright © 2015 Dana and Tuller.
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Wilhelm, Frank H.; Boger, Sabrina; Georgii, Claudio; Klimesch, Wolfgang; Blechert, Jens
2017-01-01
Abstract Today’s stressors largely arise from social interactions rather than from physical threat. However, the dominant laboratory model of emotional learning relies on physical stimuli (e.g. electric shock) whereas adequate models of social conditioning are missing, possibly due to more subtle and multilayered biobehavioral responses to such stimuli. To fill this gap, we acquired a broad set of measures during conditioning to negative social unconditioned stimuli, also taking into account long-term maintenance of conditioning and inter-individual differences. Fifty-nine healthy participants underwent a classical conditioning task with videos of actors expressing disapproving (US-neg) or neutral (US-neu) statements. Static images of the corresponding actors with a neutral facial expression served as CS+ and CS−, predicting US-neg and US-neu, respectively. Autonomic and facial-muscular measures confirmed differential unconditioned responding whereas experiential CS ratings, event-related potentials, and evoked theta oscillations confirmed differential conditioned responding. Conditioning was maintained at 1 month and 1 year follow-ups on experiential ratings, especially in individuals with elevated anxiety and depressive symptoms, documenting the efficiency of social conditioning and its clinical relevance. This novel, ecologically improved conditioning paradigm uncovered a remarkably efficient multi-layered social learning mechanism that may represent a risk factor for anxiety and depression. PMID:27614767
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Brady, Timothy F; Konkle, Talia; Alvarez, George A
2009-11-01
The information that individuals can hold in working memory is quite limited, but researchers have typically studied this capacity using simple objects or letter strings with no associations between them. However, in the real world there are strong associations and regularities in the input. In an information theoretic sense, regularities introduce redundancies that make the input more compressible. The current study shows that observers can take advantage of these redundancies, enabling them to remember more items in working memory. In 2 experiments, covariance was introduced between colors in a display so that over trials some color pairs were more likely to appear than other color pairs. Observers remembered more items from these displays than from displays where the colors were paired randomly. The improved memory performance cannot be explained by simply guessing the high-probability color pair, suggesting that observers formed more efficient representations to remember more items. Further, as observers learned the regularities, their working memory performance improved in a way that is quantitatively predicted by a Bayesian learning model and optimal encoding scheme. These results suggest that the underlying capacity of the individuals' working memory is unchanged, but the information they have to remember can be encoded in a more compressed fashion. Copyright 2009 APA
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Schwenke, Michael; Strehlow, Jan; Demedts, Daniel; Haase, Sabrina; Barrios Romero, Diego; Rothlübbers, Sven; von Dresky, Caroline; Zidowitz, Stephan; Georgii, Joachim; Mihcin, Senay; Bezzi, Mario; Tanner, Christine; Sat, Giora; Levy, Yoav; Jenne, Jürgen; Günther, Matthias; Melzer, Andreas; Preusser, Tobias
2017-01-01
Focused ultrasound (FUS) is entering clinical routine as a treatment option. Currently, no clinically available FUS treatment system features automated respiratory motion compensation. The required quality standards make developing such a system challenging. A novel FUS treatment system with motion compensation is described, developed with the goal of clinical use. The system comprises a clinically available MR device and FUS transducer system. The controller is very generic and could use any suitable MR or FUS device. MR image sequences (echo planar imaging) are acquired for both motion observation and thermometry. Based on anatomical feature tracking, motion predictions are estimated to compensate for processing delays. FUS control parameters are computed repeatedly and sent to the hardware to steer the focus to the (estimated) target position. All involved calculations produce individually known errors, yet their impact on therapy outcome is unclear. This is solved by defining an intuitive quality measure that compares the achieved temperature to the static scenario, resulting in an overall efficiency with respect to temperature rise. To allow for extensive testing of the system over wide ranges of parameters and algorithmic choices, we replace the actual MR and FUS devices by a virtual system. It emulates the hardware and, using numerical simulations of FUS during motion, predicts the local temperature rise in the tissue resulting from the controls it receives. With a clinically available monitoring image rate of 6.67 Hz and 20 FUS control updates per second, normal respiratory motion is estimated to be compensable with an estimated efficiency of 80%. This reduces to about 70% for motion scaled by 1.5. Extensive testing (6347 simulated sonications) over wide ranges of parameters shows that the main source of error is the temporal motion prediction. A history-based motion prediction method performs better than a simple linear extrapolator. The estimated efficiency of the new treatment system is already suited for clinical applications. The simulation-based in-silico testing as a first-stage validation reduces the efforts of real-world testing. Due to the extensible modular design, the described approach might lead to faster translations from research to clinical practice.
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Kischkel, Frank Christian; Meyer, Carina; Eich, Julia; Nassir, Mani; Mentze, Monika; Braicu, Ioana; Kopp-Schneider, Annette; Sehouli, Jalid
2017-10-27
In order to validate if the test result of the Chemotherapy Resistance Test (CTR-Test) is able to predict the resistances or sensitivities of tumors in ovarian cancer patients to drugs, the CTR-Test result and the corresponding clinical response of individual patients were correlated retrospectively. Results were compared to previous recorded correlations. The CTR-Test was performed on tumor samples from 52 ovarian cancer patients for specific chemotherapeutic drugs. Patients were treated with monotherapies or drug combinations. Resistances were classified as extreme (ER), medium (MR) or slight (SR) resistance in the CTR-Test. Combination treatment resistances were transformed by a scoring system into these classifications. Accurate sensitivity prediction was accomplished in 79% of the cases and accurate prediction of resistance in 100% of the cases in the total data set. The data set of single agent treatment and drug combination treatment were analyzed individually. Single agent treatment lead to an accurate sensitivity in 44% of the cases and the drug combination to 95% accuracy. The detection of resistances was in both cases to 100% correct. ROC curve analysis indicates that the CTR-Test result correlates with the clinical response, at least for the combination chemotherapy. Those values are similar or better than the values from a publication from 1990. Chemotherapy resistance testing in vitro via the CTR-Test is able to accurately detect resistances in ovarian cancer patients. These numbers confirm and even exceed results published in 1990. Better sensitivity detection might be caused by a higher percentage of drug combinations tested in 2012 compared to 1990. Our study confirms the functionality of the CTR-Test to plan an efficient chemotherapeutic treatment for ovarian cancer patients.
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Improving effectiveness of systematic conservation planning with density data.
Veloz, Samuel; Salas, Leonardo; Altman, Bob; Alexander, John; Jongsomjit, Dennis; Elliott, Nathan; Ballard, Grant
2015-08-01
Systematic conservation planning aims to design networks of protected areas that meet conservation goals across large landscapes. The optimal design of these conservation networks is most frequently based on the modeled habitat suitability or probability of occurrence of species, despite evidence that model predictions may not be highly correlated with species density. We hypothesized that conservation networks designed using species density distributions more efficiently conserve populations of all species considered than networks designed using probability of occurrence models. To test this hypothesis, we used the Zonation conservation prioritization algorithm to evaluate conservation network designs based on probability of occurrence versus density models for 26 land bird species in the U.S. Pacific Northwest. We assessed the efficacy of each conservation network based on predicted species densities and predicted species diversity. High-density model Zonation rankings protected more individuals per species when networks protected the highest priority 10-40% of the landscape. Compared with density-based models, the occurrence-based models protected more individuals in the lowest 50% priority areas of the landscape. The 2 approaches conserved species diversity in similar ways: predicted diversity was higher in higher priority locations in both conservation networks. We conclude that both density and probability of occurrence models can be useful for setting conservation priorities but that density-based models are best suited for identifying the highest priority areas. Developing methods to aggregate species count data from unrelated monitoring efforts and making these data widely available through ecoinformatics portals such as the Avian Knowledge Network will enable species count data to be more widely incorporated into systematic conservation planning efforts. © 2015, Society for Conservation Biology.
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Measuring the operational efficiency of individual theme park attractions.
Kim, Changhee; Kim, Soowook
2016-01-01
This study assesses the operation efficiency of theme park attractions using the data envelopment analysis, utilizing actual data on 15 attractions at Samsung Everland located in Yongin-si, Republic of Korea. In particular, this study identifies crowding and waiting time as one of the main causes of visitor's satisfaction, and analyzes the efficiency of individual attractions in terms of waiting time. The installation area, installation cost, and annual repair cost are set as input factors and the number of annual users and customer satisfaction as output factors. The results show that the roller coaster-type attractions were less efficient than other types of attractions while rotating-type attractions were relatively more efficient. However, an importance performance analysis on individual attraction's efficiency and satisfaction showed that operational efficiency should not be the sole consideration in attraction installation. In addition, the projection points for input factors for efficient use of attractions and the appropriate reference set for benchmarking are provided as guideline for attraction efficiency management.
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Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R
2015-02-01
Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.
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Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R.
2015-01-01
Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline. PMID:25689273
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Hot topic: Definition and implementation of a breeding value for feed efficiency in dairy cows.
Pryce, J E; Gonzalez-Recio, O; Nieuwhof, G; Wales, W J; Coffey, M P; Hayes, B J; Goddard, M E
2015-10-01
A new breeding value that combines the amount of feed saved through improved metabolic efficiency with predicted maintenance requirements is described. The breeding value includes a genomic component for residual feed intake (RFI) combined with maintenance requirements calculated from either a genomic or pedigree estimated breeding value (EBV) for body weight (BW) predicted using conformation traits. Residual feed intake is only available for genotyped Holsteins; however, BW is available for all breeds. The RFI component of the "feed saved" EBV has 2 parts: Australian calf RFI and Australian lactating cow RFI. Genomic breeding values for RFI were estimated from a reference population of 2,036 individuals in a multi-trait analysis including Australian calf RFI (n=843), Australian lactating cow RFI (n=234), and UK and Dutch lactating cow RFI (n=958). In all cases, the RFI phenotypes were deviations from a mean of 0, calculated by correcting dry matter intake for BW, growth, and milk yield (in the case of lactating cows). Single nucleotide polymorphism effects were calculated from the output of genomic BLUP and used to predict breeding values of 4,106 Holstein sires that were genotyped but did not have RFI phenotypes themselves. These bulls already had BW breeding values calculated from type traits, from which maintenance requirements in kilograms of feed per year were inferred. Finally, RFI and the feed required for maintenance (through BW) were used to calculate a feed saved breeding value and expressed as the predicted amount of feed saved per year. Animals that were 1 standard deviation above the mean were predicted to eat 66 kg dry matter less per year at the same level of milk production. In a data set of genotyped Holstein sires, the mean reliability of the feed saved breeding value was 0.37. For Holsteins that are not genotyped and for breeds other than Holsteins, feed saved is calculated using BW only. From April 2015, feed saved has been included as part of the Australian national selection index, the Balanced Performance Index (BPI). Selection on the BPI is expected to lead to modest gains in feed efficiency. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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Federal Register 2010, 2011, 2012, 2013, 2014
2010-12-22
... Commission, adopts a point-to-point predictive model for determining the ability of individual locations to... predictive model for reliably and presumptively determining the ability of individual locations, through the... adopted a point-to-point predictive model for determining the ability of individual locations to receive...
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Predicting genotypes environmental range from genome-environment associations.
Manel, Stéphanie; Andrello, Marco; Henry, Karine; Verdelet, Daphné; Darracq, Aude; Guerin, Pierre-Edouard; Desprez, Bruno; Devaux, Pierre
2018-05-17
Genome-environment association methods aim to detect genetic markers associated with environmental variables. The detected associations are usually analysed separately to identify the genomic regions involved in local adaptation. However, a recent study suggests that single-locus associations can be combined and used in a predictive way to estimate environmental variables for new individuals on the basis of their genotypes. Here, we introduce an original approach to predict the environmental range (values and upper and lower limits) of species genotypes from the genetic markers significantly associated with those environmental variables in an independent set of individuals. We illustrate this approach to predict aridity in a database constituted of 950 individuals of wild beets and 299 individuals of cultivated beets genotyped at 14,409 random Single Nucleotide Polymorphisms (SNPs). We detected 66 alleles associated with aridity and used them to calculate the fraction (I) of aridity-associated alleles in each individual. The fraction I correctly predicted the values of aridity in an independent validation set of wild individuals and was then used to predict aridity in the 299 cultivated individuals. Wild individuals had higher median values and a wider range of values of aridity than the cultivated individuals, suggesting that wild individuals have higher ability to resist to stress-aridity conditions and could be used to improve the resistance of cultivated varieties to aridity. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
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Swann, William B; Kwan, Virginia S Y; Polzer, Jeffrey T; Milton, Laurie P
2003-11-01
A longitudinal study examined the interplay of identity negotiation processes and diversity in small groups of master's of business administration (MBA) students. When perceivers formed relatively positive impressions of other group members, higher diversity predicted more individuation of targets. When perceivers formed relatively neutral impressions of other group members, however, higher diversity predicted less individuation of targets. Individuation at the outset of the semester predicted self-verification effects several weeks later, and self-verification, in turn, predicted group identification and creative task performance. The authors conclude that contrary to self-categorization theory, fostering individuation and self-verification in diverse groups may maximize group identification and productivity.
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NATO IST 124 Experimentation Instructions
2016-11-10
more reliable and predictable network performance through adaptive and efficient control schemes . This report provides guidance and instructions for...tactical heterogeneous networks for more reliable and predictable network performance through adaptive and efficient control schemes . This report
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NASA Astrophysics Data System (ADS)
Helbing, Dirk; Schönhof, Martin; Kern, Daniel
2002-06-01
The coordinated and efficient distribution of limited resources by individual decisions is a fundamental, unsolved problem. When individuals compete for road capacities, time, space, money, goods, etc, they normally make decisions based on aggregate rather than complete information, such as TV news or stock market indices. In related experiments, we have observed a volatile decision dynamics and far-from-optimal payoff distributions. We have also identified methods of information presentation that can considerably improve the overall performance of the system. In order to determine optimal strategies of decision guidance by means of user-specific recommendations, a stochastic behavioural description is developed. These strategies manage to increase the adaptibility to changing conditions and to reduce the deviation from the time-dependent user equilibrium, thereby enhancing the average and individual payoffs. Hence, our guidance strategies can increase the performance of all users by reducing overreaction and stabilizing the decision dynamics. These results are highly significant for predicting decision behaviour, for reaching optimal behavioural distributions by decision support systems and for information service providers. One of the promising fields of application is traffic optimization.
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Bruder, Martin; Haffke, Peter; Neave, Nick; Nouripanah, Nina; Imhoff, Roland
2013-01-01
Conspiracy theories are ubiquitous when it comes to explaining political events and societal phenomena. Individuals differ not only in the degree to which they believe in specific conspiracy theories, but also in their general susceptibility to explanations based on such theories, that is, their conspiracy mentality. We present the Conspiracy Mentality Questionnaire (CMQ), an instrument designed to efficiently assess differences in the generic tendency to engage in conspiracist ideation within and across cultures. The CMQ is available in English, German, and Turkish. In four studies, we examined the CMQ’s factorial structure, reliability, measurement equivalence across cultures, and its convergent, discriminant, and predictive validity. Analyses based on a cross-cultural sample (Study 1a; N = 7,766) supported the conceptualization of conspiracy mentality as a one-dimensional construct across the three language versions of the CMQ that is stable across time (Study 1b; N = 141). Multi-group confirmatory factor analysis demonstrated cross-cultural measurement equivalence of the CMQ items. The instrument could therefore be used to examine differences in conspiracy mentality between European, North American, and Middle Eastern cultures. In Studies 2–4 (total N = 476), we report (re-)analyses of three datasets demonstrating the validity of the CMQ in student and working population samples in the UK and Germany. First, attesting to its convergent validity, the CMQ was highly correlated with another measure of generic conspiracy belief. Second, the CMQ showed patterns of meaningful associations with personality measures (e.g., Big Five dimensions, schizotypy), other generalized political attitudes (e.g., social dominance orientation and right-wing authoritarianism), and further individual differences (e.g., paranormal belief, lack of socio-political control). Finally, the CMQ predicted beliefs in specific conspiracy theories over and above other individual difference measures. PMID:23641227
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Cheng, Guo; Firmato de Almeida, Manoel; So, Man-Ting; Sham, Pak-Chung; Cherny, Stacey S.; Tam, Paul Kwong-Hang; Garcia-Barceló, Maria-Mercè
2013-01-01
We present the genetic analyses conducted on a three-generation family (14 individuals) with three members affected with isolated-Hirschsprung disease (HSCR) and one with HSCR and heterochromia iridum (syndromic-HSCR), a phenotype reminiscent of Waardenburg-Shah syndrome (WS4). WS4 is characterized by pigmentary abnormalities of the skin, eyes and/or hair, sensorineural deafness and HSCR. None of the members had sensorineural deafness. The family was screened for copy number variations (CNVs) using Illumina-HumanOmni2.5-Beadchip and for coding sequence mutations in WS4 genes (EDN3, EDNRB, or SOX10) and in the main HSCR gene (RET). Confocal microscopy and immunoblotting were used to assess the functional impact of the mutations. A heterozygous A/G transition in EDNRB was identified in 4 affected and 3 unaffected individuals. While in EDNRB isoforms 1 and 2 (cellular receptor) the transition results in the abolishment of translation initiation (M1V), in isoform 3 (only in the cytosol) the replacement occurs at Met91 (M91V) and is predicted benign. Another heterozygous transition (c.-248G/A; -predicted to affect translation efficiency-) in the 5′-untranslated region of EDN3 (EDNRB ligand) was detected in all affected individuals but not in healthy carriers of the EDNRB mutation. Also, a de novo CNVs encompassing DACH1 was identified in the patient with heterochromia iridum and HSCR Since the EDNRB and EDN3 variants only coexist in affected individuals, HSCR could be due to the joint effect of mutations in genes of the same pathway. Iris heterochromia could be due to an independent genetic event and would account for the additional phenotype within the family. PMID:23840513
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High-accuracy direct ZT and intrinsic properties measurement of thermoelectric couple devices.
Kraemer, D; Chen, G
2014-04-01
Advances in thermoelectric materials in recent years have led to significant improvements in thermoelectric device performance and thus, give rise to many new potential applications. In order to optimize a thermoelectric device for specific applications and to accurately predict its performance ideally the material's figure of merit ZT as well as the individual intrinsic properties (Seebeck coefficient, electrical resistivity, and thermal conductivity) should be known with high accuracy. For that matter, we developed two experimental methods in which the first directly obtains the ZT and the second directly measures the individual intrinsic leg properties of the same p/n-type thermoelectric couple device. This has the advantage that all material properties are measured in the same sample direction after the thermoelectric legs have been mounted in the final device. Therefore, possible effects from crystal anisotropy and from the device fabrication process are accounted for. The Seebeck coefficients, electrical resistivities, and thermal conductivities are measured with differential methods to minimize measurement uncertainties to below 3%. The thermoelectric couple ZT is directly measured with a differential Harman method which is in excellent agreement with the calculated ZT from the individual leg properties. The errors in both the directly measured and calculated thermoelectric couple ZT are below 5% which is significantly lower than typical uncertainties using commercial methods. Thus, the developed technique is ideal for characterizing assembled couple devices and individual thermoelectric materials and enables accurate device optimization and performance predictions. We demonstrate the methods by measuring a p/n-type thermoelectric couple device assembled from commercial bulk thermoelectric Bi2Te3 elements in the temperature range of 30 °C-150 °C and discuss the performance of the couple thermoelectric generator in terms of its efficiency and materials' self-compatibility.
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NASA Astrophysics Data System (ADS)
Castilla, Antonio R.; Alonso, Conchita; Herrera, Carlos M.
2011-05-01
Biogeographic models predict that marginal populations should be more geographically isolated and smaller than central populations, linked to more stressful conditions and likely also to a reduction in density of individuals, individual growth, survival and reproductive output. This variation in population features could have important consequences for different aspects of plant ecology such as individual reproductive success, population genetic structure or plant-animal interactions. In this study, we analyze if individuals of the evergreen shrub Daphne laureola at disjunt populations in a local border of its distribution area in southern Iberian Peninsula differ in individual size, shoot growth, reproductive output and the pollination environment from central continuous populations within the area. Plants of central continuous populations were larger and produced more flowers and fruits than plants of marginal disjunct populations suggesting more optimal conditions, although they had lower annual shoot growth. In contrast, fruit set was higher in plants at the local border, suggesting a more efficient pollinator service in these populations where the main pollinator in central continuous populations, the pollen beetle Meligethes elongatus, was not present. Our results do not support strong differences in the ecological stress between marginal disjunct and central continuous populations of D. laureola in the south of the Iberian Peninsula but indicate some changes in plant-pollinator interactions that could be relevant for the sexual polymorphism in this gynodioecious species.
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Modeling of venturi scrubber efficiency
NASA Astrophysics Data System (ADS)
Crowder, Jerry W.; Noll, Kenneth E.; Davis, Wayne T.
The parameters affecting venturi scrubber performance have been rationally examined and modifications to the current modeling theory have been developed. The modified model has been validated with available experimental data for a range of throat gas velocities, liquid-to-gas ratios and particle diameters and is used to study the effect of some design parameters on collection efficiency. Most striking among the observations is the prediction of a new design parameter termed the minimum contactor length. Also noted is the prediction of little effect on collection efficiency with increasing liquid-to-gas ratio above about 2ℓ m-3. Indeed, for some cases a decrease in collection efficiency is predicted for liquid rates above this value.
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Grilo, C M; Skodol, A E; Gunderson, J G; Sanislow, C A; Stout, R L; Shea, M T; Morey, L C; Zanarini, M C; Bender, D S; Yen, S; McGlashan, T H
2004-07-01
To examine the longitudinal diagnostic efficiency of the DSM-IV criteria for obsessive-compulsive personality disorder (OCPD). At baseline, criteria and diagnoses were determined using diagnostic interviews, and blinded assessments were performed 24 months later with 550 participants. Diagnostic efficiency indices (conditional probabilities, total predictive power, and kappa) were calculated for each criterion determined at baseline, using the independent OCPD diagnosis at follow-up as the standard. Longitudinal diagnostic efficiencies for the OCPD criteria varied; findings suggested the overall predictive utility of 'preoccupied with details', 'rigid and stubborn', and 'reluctant to delegate'. These findings suggest the predictive validity of three cognitive-interpersonal OCPD criteria.
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NASA Astrophysics Data System (ADS)
Pandey, Rahul; Chaujar, Rishu
2017-04-01
A 29.5% efficient perovskite/SiC passivated interdigitated back contact silicon heterojunction (IBC-SiHJ) mechanically stacked tandem solar cell device has been designed and simulated. This is a substantial improvement of 40% and 15%, respectively, compared to the transparent perovskite solar cell (21.1%) and Si solar cell (25.6%) operated individually. The perovskite solar cell has been used as a top subcell, whereas 250- and 25-μm-thick IBC-SiHJ solar cells have been used as bottom subcells. The realistic technology computer aided design analysis has been performed to understand the physical processes in the device and to make reliable predictions of the behavior. The performance of the top subcell has been obtained for different acceptor densities and hole mobility in Spiro-MeOTAD along with the impact of counter electrode work function. To incorporate the effect of material quality, the influence of carrier lifetimes has also been studied for perovskite top and IBC-SiHJ bottom subcells. The optical and electrical behavior of the devices has been obtained for both standalone as well as tandem configuration. Results reported in this study reveal that the proposed four-terminal tandem device may open a new door for cost-effective and energy-efficient applications.
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NASA Technical Reports Server (NTRS)
Mulavara, A. P.; Peters, B.; De Dios, Y. E.; Gadd, N. E.; Caldwell, E. E.; Batson, C. D.; Goel, R.; Oddsson, L.; Kreutzberg, G.; Zanello, S.;
2017-01-01
Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. These alterations may disrupt crewmembers' ability to perform mission critical functional tasks requiring ambulation, manual control and gaze stability. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts are affected will improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. For such an approach to succeed, we must develop predictive measures of sensorimotor adaptability that will allow us to foresee, before actual spaceflight, which crewmembers are likely to experience greater challenges to their adaptive capacities. The goals of this project are to identify and characterize this set of predictive measures. Our approach includes: 1) behavioral tests to assess sensory bias and adaptability quantified using both strategic and plastic-adaptive responses; 2) imaging to determine individual brain morphological and functional features, using structural magnetic resonance imaging (MRI), diffusion tensor imaging, resting state functional connectivity MRI, and sensorimotor adaptation task-related functional brain activation; and 3) assessment of genetic polymorphisms in the catechol-O-methyl transferase, dopamine receptor D2, and brain-derived neurotrophic factor genes and genetic polymorphisms of alpha2-adrenergic receptors that play a role in the neural pathways underlying sensorimotor adaptation. We anticipate that these predictive measures will be significantly correlated with individual differences in sensorimotor adaptability after long-duration spaceflight and exposure to an analog bed rest environment. We will be conducting a retrospective study, leveraging data already collected from relevant ongoing or completed bed rest and spaceflight studies. This data will be combined with predictor metrics that will be collected prospectively (as described for behavioral, brain imaging and genomic measures) from these returning subjects to build models for predicting post spaceflight and bed rest adaptive capability. In this presentation we will discuss the optimized set of tests for predictive metrics to be used for evaluating post mission adaptive capability as manifested in their outcome measures. Comparisons of model performance will allow us to better design and implement sensorimotor adaptability training countermeasures against decrements in post-mission adaptive capability that are customized for each crewmember's sensory biases, adaptive ability, brain structure, brain function, and genetic predispositions. The ability to customize adaptability training will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to mitigate the deleterious effects of spaceflight.
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Social networks in primates: smart and tolerant species have more efficient networks.
Pasquaretta, Cristian; Levé, Marine; Claidière, Nicolas; van de Waal, Erica; Whiten, Andrew; MacIntosh, Andrew J J; Pelé, Marie; Bergstrom, Mackenzie L; Borgeaud, Christèle; Brosnan, Sarah F; Crofoot, Margaret C; Fedigan, Linda M; Fichtel, Claudia; Hopper, Lydia M; Mareno, Mary Catherine; Petit, Odile; Schnoell, Anna Viktoria; di Sorrentino, Eugenia Polizzi; Thierry, Bernard; Tiddi, Barbara; Sueur, Cédric
2014-12-23
Network optimality has been described in genes, proteins and human communicative networks. In the latter, optimality leads to the efficient transmission of information with a minimum number of connections. Whilst studies show that differences in centrality exist in animal networks with central individuals having higher fitness, network efficiency has never been studied in animal groups. Here we studied 78 groups of primates (24 species). We found that group size and neocortex ratio were correlated with network efficiency. Centralisation (whether several individuals are central in the group) and modularity (how a group is clustered) had opposing effects on network efficiency, showing that tolerant species have more efficient networks. Such network properties affecting individual fitness could be shaped by natural selection. Our results are in accordance with the social brain and cultural intelligence hypotheses, which suggest that the importance of network efficiency and information flow through social learning relates to cognitive abilities.
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Social networks in primates: smart and tolerant species have more efficient networks
Pasquaretta, Cristian; Levé, Marine; Claidière, Nicolas; van de Waal, Erica; Whiten, Andrew; MacIntosh, Andrew J. J.; Pelé, Marie; Bergstrom, Mackenzie L.; Borgeaud, Christèle; Brosnan, Sarah F.; Crofoot, Margaret C.; Fedigan, Linda M.; Fichtel, Claudia; Hopper, Lydia M.; Mareno, Mary Catherine; Petit, Odile; Schnoell, Anna Viktoria; di Sorrentino, Eugenia Polizzi; Thierry, Bernard; Tiddi, Barbara; Sueur, Cédric
2014-01-01
Network optimality has been described in genes, proteins and human communicative networks. In the latter, optimality leads to the efficient transmission of information with a minimum number of connections. Whilst studies show that differences in centrality exist in animal networks with central individuals having higher fitness, network efficiency has never been studied in animal groups. Here we studied 78 groups of primates (24 species). We found that group size and neocortex ratio were correlated with network efficiency. Centralisation (whether several individuals are central in the group) and modularity (how a group is clustered) had opposing effects on network efficiency, showing that tolerant species have more efficient networks. Such network properties affecting individual fitness could be shaped by natural selection. Our results are in accordance with the social brain and cultural intelligence hypotheses, which suggest that the importance of network efficiency and information flow through social learning relates to cognitive abilities. PMID:25534964
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Lower group productivity under kin-selected reproductive altruism.
Teyssèdre, Anne; Couvet, Denis; Nunney, Leonard
2006-10-01
Hamilton's rule provides the foundation for understanding the genetic evolution of social behavior, showing that altruism is favored by increased relatedness and increased productivity of altruists. But how likely is it that a new altruistic mutation will satisfy Hamilton's rule by increasing the reproductive efficiency of the group? Altruism per se does not improve efficiency, and hence we would not expect a typical altruistic mutation to increase the mean productivity of the population. We examined the conditions under which a mutation causing reproductive altruism can spread when it does not increase productivity. We considered a population divided into temporary groups of genetically similar individuals (typically family groups). We show that the spread of altruism requires a pleiotropic link between altruism and enhanced productivity in diploid organisms, but not in haplodiploid organisms such as Hymenoptera. This result provides a novel biological understanding of the barrier to the spread of reproductive altruism in diploids. In haplodiploid organisms, altruism within families that lowers productivity may spread, provided daughters sacrifice their own reproduction to raise full-sisters. We verified our results using three single-locus genetic models that explore a range of the possible reproductive costs of helping. The advantage of female-to-female altruism in haplodiploids is a well-known prediction of Hamilton's rule, but its importance in relaxing the linkage between altruism and efficiency has not been explored. We discuss the possible role of such unproductive altruism in the origins of sociality. We also note that each model predicts a large region of parameter space were polymorphism between altruism and selfishness is maintained, a pattern independent of dominance.
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Sparano, Joseph A; Hortobagyi, Gabriel N; Gralow, Julie R; Perez, Edith A; Comis, Robert L
2010-02-01
Over 9,000 women with breast cancer are enrolled annually on clinical trials sponsored by the National Cancer Institute (NCI), accounting for about one-third of all patients enrolled on NCI-sponsored trials. Thousands are also enrolled on pharmaceutical-sponsored studies. Although breast cancer mortality rates have recently declined for the first time in part due to systemic therapeutic advances, coordinated efforts will be necessary to maintain this trend. The Coalition of Cancer Cooperative Groups convened the Scientific Leadership Council in breast cancer (BC), an expert panel, to identify priorities for future research and current trials with greatest practice-changing potential. Panelists formed a consensus on research priorities for chemoprevention, development and application of molecular markers for predicting therapeutic benefit and toxicity, intermediate markers predictive of therapeutic effect, pathogenesis-based therapeutic approaches, utilization of adaptive designs requiring fewer patients to achieve objectives, special and minority populations, and effects of BC and treatment on patients and families. Panelists identified 13 ongoing studies as High Priority and identified gaps in the current trial portfolio. We propose priorities for current and future clinical breast cancer research evaluating systemic therapies that may serve to improve the efficiency of clinical trials, identify individuals most likely to derive therapeutic benefit, and prioritize therapeutic strategies.
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Zhang, L; Price, R; Aweeka, F; Bellibas, S E; Sheiner, L B
2001-02-01
A small-scale clinical investigation was done to quantify the penetration of stavudine (D4T) into cerebrospinal fluid (CSF). A model-based analysis estimates the steady-state ratio of AUCs of CSF and plasma concentrations (R(AUC)) to be 0.270, and the mean residence time of drug in the CSF to be 7.04 h. The analysis illustrates the advantages of a causal (scientific, predictive) model-based approach to analysis over a noncausal (empirical, descriptive) approach when the data, as here, demonstrate certain problematic features commonly encountered in clinical data, namely (i) few subjects, (ii) sparse sampling, (iii) repeated measures, (iv) imbalance, and (v) individual design variation. These features generally require special attention in data analysis. The causal-model-based analysis deals with features (i) and (ii), both of which reduce efficiency, by combining data from different studies and adding subject-matter prior information. It deals with features (iii)--(v), all of which prevent 'averaging' individual data points directly, first, by adjusting in the model for interindividual data differences due to design differences, secondly, by explicitly differentiating between interpatient, interoccasion, and measurement error variation, and lastly, by defining a scientifically meaningful estimand (R(AUC)) that is independent of design.
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Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rossi, R; Gallagher, B; Neville, J
Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied ourmore » model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.« less
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Pearson, Dean E; Ortega, Yvette K; Villarreal, Diego; Lekberg, Ylva; Cock, Marina C; Eren, Özkan; Hierro, José L
2018-06-01
Invasibility is a key indicator of community susceptibility to changes in structure and function. The fluctuating resource hypothesis (FRH) postulates that invasibility is an emergent community property, a manifestation of multiple processes that cannot be reliably predicted by individual community attributes like diversity or productivity. Yet, research has emphasized the role of these individual attributes, with the expectation that diversity should deter invasibility and productivity enhance it. In an effort to explore how these and other factors may influence invasibility, we evaluated the relationship between invasibility and species richness, productivity, resource availability, and resilience in experiments crossing disturbance with exotic seed addition in 1-m 2 plots replicated over large expanses of grasslands in Montana, USA and La Pampa, Argentina. Disturbance increased invasibility as predicted by FRH, but grasslands were more invasible in Montana than La Pampa whether disturbed or not, despite Montana's higher species richness and lower productivity. Moreover, invasibility correlated positively with nitrogen availability and negatively with native plant cover. These patterns suggested that resource availability and the ability of the community to recover from disturbance (resilience) better predicted invasibility than either species richness or productivity, consistent with predictions from FRH. However, in ambient, unseeded plots in Montana, disturbance reduced native cover by >50% while increasing exotic cover >200%. This provenance bias could not be explained by FRH, which predicts that colonization processes act on species' traits independent of origins. The high invasibility of Montana grasslands following disturbance was associated with a strong shift from perennial to annual species, as predicted by succession theory. However, this shift was driven primarily by exotic annuals, which were more strongly represented than perennials in local exotic vs. native species pools. We attribute this provenance bias to extrinsic biogeographic factors such as disparate evolutionary histories and/or introduction filters selecting for traits that favor exotics following disturbance. Our results suggest that (1) invasibility is an emergent property best explained by a community's efficiency in utilizing resources, as predicted by FRH but (2) understanding provenance biases in biological invasions requires moving beyond FRH to incorporate extrinsic biogeographic factors that may favor exotics in community assembly. © 2018 by the Ecological Society of America.
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Lack of predictive power of trait fear and anxiety for conditioned pain modulation (CPM).
Horn-Hofmann, Claudia; Priebe, Janosch A; Schaller, Jörg; Görlitz, Rüdiger; Lautenbacher, Stefan
2016-12-01
In recent years the association of conditioned pain modulation (CPM) with trait fear and anxiety has become a hot topic in pain research due to the assumption that such variables may explain the low CPM efficiency in some individuals. However, empirical evidence concerning this association is still equivocal. Our study is the first to investigate the predictive power of fear and anxiety for CPM by using a well-established psycho-physiological measure of trait fear, i.e. startle potentiation, in addition to two self-report measures of pain-related trait anxiety. Forty healthy, pain-free participants (female: N = 20; age: M = 23.62 years) underwent two experimental blocks in counter-balanced order: (1) a startle paradigm with affective picture presentation and (2) a CPM procedure with hot water as conditioning stimulus (CS) and contact heat as test stimulus (TS). At the end of the experimental session, pain catastrophizing (PCS) and pain anxiety (PASS) were assessed. PCS score, PASS score and startle potentiation to threatening pictures were entered as predictors in a linear regression model with CPM magnitude as criterion. We were able to show an inhibitory CPM effect in our sample: pain ratings of the heat stimuli were significantly reduced during hot water immersion. However, CPM was neither predicted by self-report of pain-related anxiety nor by startle potentiation as psycho-physiological measure of trait fear. These results corroborate previous negative findings concerning the association between trait fear/anxiety and CPM efficiency and suggest that shifting the focus from trait to state measures might be promising.
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A new condition for assessing the clinical efficiency of a diagnostic test.
Bokhari, Ehsan; Hubert, Lawrence
2015-09-01
When prediction using a diagnostic test outperforms simple prediction using base rates, the test is said to be "clinically efficient," a term first introduced into the literature by Meehl and Rosen (1955) in Psychological Bulletin. This article provides three equivalent conditions for determining the clinical efficiency of a diagnostic test: (a) Meehl-Rosen (Meehl & Rosen, 1955); (b) Dawes (Dawes, 1962); and (c) the Bokhari-Hubert condition, introduced here for the first time. Clinical efficiency is then generalized to situations where misclassification costs are considered unequal (for example, false negatives are more costly than false positives). As an illustration, the clinical efficiency of an actuarial device for predicting violent and dangerous behavior is examined that was developed as part of the MacArthur Violence Risk Assessment Study. (c) 2015 APA, all rights reserved.
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Application of biological simulation models in estimating feed efficiency of finishing steers.
Williams, C B
2010-07-01
Data on individual daily feed intake, BW at 28-d intervals, and carcass composition were obtained on 1,212 crossbred steers. Within-animal regressions of cumulative feed intake and BW on linear and quadratic days on feed were used to quantify initial and ending BW, average daily observed feed intake (OFI), and ADG over a 120-d finishing period. Feed intake was predicted (PFI) with 3 biological simulation models (BSM): a) Decision Evaluator for the Cattle Industry, b) Cornell Value Discovery System, and c) NRC update 2000, using observed growth and carcass data as input. Residual feed intake (RFI) was estimated using OFI (RFI(EL)) in a linear statistical model (LSM), and feed conversion ratio (FCR) was estimated as OFI/ADG (FCR(E)). Output from the BSM was used to estimate RFI by using PFI in place of OFI with the same LSM, and FCR was estimated as PFI/ADG. These estimates were evaluated against RFI(EL) and FCR(E). In a second analysis, estimates of RFI were obtained for the 3 BSM as the difference between OFI and PFI, and these estimates were evaluated against RFI(EL). The residual variation was extremely small when PFI was used in the LSM to estimate RFI, and this was mainly due to the fact that the same input variables (initial BW, days on feed, and ADG) were used in the BSM and LSM. Hence, the use of PFI obtained with BSM as a replacement for OFI in a LSM to characterize individual animals for RFI was not feasible. This conclusion was also supported by weak correlations (<0.4) between RFI(EL) and RFI obtained with PFI in the LSM, and very weak correlations (<0.13) between RFI(EL) and FCR obtained with PFI. In the second analysis, correlations (>0.89) for RFI(EL) with the other RFI estimates suggest little difference between RFI(EL) and any of these RFI estimates. In addition, results suggest that the RFI estimates calculated with PFI would be better able to identify animals with low OFI and small ADG as inefficient compared with RFI(EL). These results may be due to the fact that computer models predict performance on an individual-animal basis in contrast to a LSM, which estimates a fixed relationship for all animals; hence, the BSM may provide RFI estimates that are closer to the true biological efficiency of animals. In addition, BSM may facilitate comparisons across different data sets and provide more accurate estimates of efficiency in small data sets where errors would be greater with a LSM.
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Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor
NASA Technical Reports Server (NTRS)
Wilson, Scott D.; Reid, Terry; Schifer, Nicholas; Briggs, Maxwell
2011-01-01
Past methods of predicting net heat input needed to be validated. Validation effort pursued with several paths including improving model inputs, using test hardware to provide validation data, and validating high fidelity models. Validation test hardware provided direct measurement of net heat input for comparison to predicted values. Predicted value of net heat input was 1.7 percent less than measured value and initial calculations of measurement uncertainty were 2.1 percent (under review). Lessons learned during validation effort were incorporated into convertor modeling approach which improved predictions of convertor efficiency.
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A Simple Model Predicting Individual Weight Change in Humans
Thomas, Diana M.; Martin, Corby K.; Heymsfield, Steven; Redman, Leanne M.; Schoeller, Dale A.; Levine, James A.
2010-01-01
Excessive weight in adults is a national concern with over 2/3 of the US population deemed overweight. Because being overweight has been correlated to numerous diseases such as heart disease and type 2 diabetes, there is a need to understand mechanisms and predict outcomes of weight change and weight maintenance. A simple mathematical model that accurately predicts individual weight change offers opportunities to understand how individuals lose and gain weight and can be used to foster patient adherence to diets in clinical settings. For this purpose, we developed a one dimensional differential equation model of weight change based on the energy balance equation is paired to an algebraic relationship between fat free mass and fat mass derived from a large nationally representative sample of recently released data collected by the Centers for Disease Control. We validate the model's ability to predict individual participants’ weight change by comparing model estimates of final weight data from two recent underfeeding studies and one overfeeding study. Mean absolute error and standard deviation between model predictions and observed measurements of final weights are less than 1.8 ± 1.3 kg for the underfeeding studies and 2.5 ± 1.6 kg for the overfeeding study. Comparison of the model predictions to other one dimensional models of weight change shows improvement in mean absolute error, standard deviation of mean absolute error, and group mean predictions. The maximum absolute individual error decreased by approximately 60% substantiating reliability in individual weight change predictions. The model provides a viable method for estimating individual weight change as a result of changes in intake and determining individual dietary adherence during weight change studies. PMID:24707319
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Genomic prediction using phenotypes from pedigreed lines with no marker data
USDA-ARS?s Scientific Manuscript database
Until now genomic prediction in plant breeding has only used information from individuals that have been genotyped. In practice, information from non-genotyped relatives of genotyped individuals can be used to improve the genomic prediction accuracy. Single-step genomic prediction integrates all the...
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DOT National Transportation Integrated Search
2011-06-14
This paper presents a novel analytical approach to and techniques for translating characteristics of uncertainty in predicting sector entry times and times in sector for individual flights into characteristics of uncertainty in predicting one-minute ...
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Hartman, Jessica H.; Cothren, Steven D.; Park, Sun-Ha; Yun, Chul-Ho; Darsey, Jerry A.; Miller, Grover P.
2013-01-01
Cytochromes P450 (CYP for isoforms) play a central role in biological processes especially metabolism of chiral molecules; thus, development of computational methods to predict parameters for chiral reactions is important for advancing this field. In this study, we identified the most optimal artificial neural networks using conformation-independent chirality codes to predict CYP2C19 catalytic parameters for enantioselective reactions. Optimization of the neural networks required identifying the most suitable representation of structure among a diverse array of training substrates, normalizing distribution of the corresponding catalytic parameters (kcat, Km, and kcat/Km), and determining the best topology for networks to make predictions. Among different structural descriptors, the use of partial atomic charges according to the CHelpG scheme and inclusion of hydrogens yielded the most optimal artificial neural networks. Their training also required resolution of poorly distributed output catalytic parameters using a Box-Cox transformation. End point leave-one-out cross correlations of the best neural networks revealed that predictions for individual catalytic parameters (kcat and Km) were more consistent with experimental values than those for catalytic efficiency (kcat/Km). Lastly, neural networks predicted correctly enantioselectivity and comparable catalytic parameters measured in this study for previously uncharacterized CYP2C19 substrates, R- and S-propranolol. Taken together, these seminal computational studies for CYP2C19 are the first to predict all catalytic parameters for enantioselective reactions using artificial neural networks and thus provide a foundation for expanding the prediction of cytochrome P450 reactions to chiral drugs, pollutants, and other biologically active compounds. PMID:23673224
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Iannetta, Danilo; Fontana, Federico Y; Maturana, Felipe Mattioni; Inglis, Erin Calaine; Pogliaghi, Silvia; Keir, Daniel A; Murias, Juan M
2018-05-23
The maximal lactate steady state (MLSS) represents the highest exercise intensity at which an elevated blood lactate concentration ([Lac] b ) is stabilized above resting values. MLSS quantifies the boundary between the heavy-to-very-heavy intensity domains but its determination is not widely performed due to the number of trials required. This study aimed to: (i) develop a mathematical equation capable of predicting MLSS using variables measured during a single ramp-incremental cycling test and (ii) test the accuracy of the optimized mathematical equation. The predictive MLSS equation was determined by stepwise backward regression analysis of twelve independent variables measured in sixty individuals who had previously performed ramp-incremental exercise and in whom MLSS was known (MLSS obs ). Next, twenty-nine different individuals were prospectively recruited to test the accuracy of the equation. These participants performed ramp-incremental exercise to exhaustion and two-to-three 30-min constant-power output cycling bouts with [Lac] b sampled at regular intervals for determination of MLSS obs . Predicted MLSS (MLSS pred ) and MLSS obs in both phases of the study were compared by paired t-test, major-axis regression and Bland-Altman analysis. The predictor variables of MLSS were: respiratory compensation point (Wkg -1 ), peak oxygen uptake (V˙O 2peak ) (mlkg -1 min -1 ) and body mass (kg). MLSS pred was highly correlated with MLSS obs (r=0.93; p<0.01). When this equation was tested on the independent group, MLSS pred was not different from MLSS obs (234±43 vs. 234±44W; SEE 4.8W; r=0.99; p<0.01). These data support the validity of the predictive MLSS equation. We advocate its use as a time-efficient alternative to traditional MLSS testing in cycling. Copyright © 2018 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
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Li, Linling; Huang, Gan; Lin, Qianqian; Liu, Jia; Zhang, Shengli; Zhang, Zhiguo
2018-01-01
The level of pain perception is correlated with the magnitude of pain-evoked brain responses, such as laser-evoked potentials (LEP), across trials. The positive LEP-pain relationship lays the foundation for pain prediction based on single-trial LEP, but cross-individual pain prediction does not have a good performance because the LEP-pain relationship exhibits substantial cross-individual difference. In this study, we aim to explain the cross-individual difference in the LEP-pain relationship using inter-stimulus EEG (isEEG) features. The isEEG features (root mean square as magnitude and mean square successive difference as temporal variability) were estimated from isEEG data (at full band and five frequency bands) recorded between painful stimuli. A linear model was fitted to investigate the relationship between pain ratings and LEP response for fast-pain trials on a trial-by-trial basis. Then the correlation between isEEG features and the parameters of LEP-pain model (slope and intercept) was evaluated. We found that the magnitude and temporal variability of isEEG could modulate the parameters of an individual's linear LEP-pain model for fast-pain trials. Based on this, we further developed a new individualized fast-pain prediction scheme, which only used training individuals with similar isEEG features as the test individual to train the fast-pain prediction model, and obtained improved accuracy in cross-individual fast-pain prediction. The findings could help elucidate the neural mechanism of cross-individual difference in pain experience and the proposed fast-pain prediction scheme could be potentially used as a practical and feasible pain prediction method in clinical practice. PMID:29904336
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Optimal Predictions in Everyday Cognition: The Wisdom of Individuals or Crowds?
ERIC Educational Resources Information Center
Mozer, Michael C.; Pashler, Harold; Homaei, Hadjar
2008-01-01
Griffiths and Tenenbaum (2006) asked individuals to make predictions about the duration or extent of everyday events (e.g., cake baking times), and reported that predictions were optimal, employing Bayesian inference based on veridical prior distributions. Although the predictions conformed strikingly to statistics of the world, they reflect…
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Efficient biprediction decision scheme for fast high efficiency video coding encoding
NASA Astrophysics Data System (ADS)
Park, Sang-hyo; Lee, Seung-ho; Jang, Euee S.; Jun, Dongsan; Kang, Jung-Won
2016-11-01
An efficient biprediction decision scheme of high efficiency video coding (HEVC) is proposed for fast-encoding applications. For low-delay video applications, bidirectional prediction can be used to increase compression performance efficiently with previous reference frames. However, at the same time, the computational complexity of the HEVC encoder is significantly increased due to the additional biprediction search. Although a some research has attempted to reduce this complexity, whether the prediction is strongly related to both motion complexity and prediction modes in a coding unit has not yet been investigated. A method that avoids most compression-inefficient search points is proposed so that the computational complexity of the motion estimation process can be dramatically decreased. To determine if biprediction is critical, the proposed method exploits the stochastic correlation of the context of prediction units (PUs): the direction of a PU and the accuracy of a motion vector. Through experimental results, the proposed method showed that the time complexity of biprediction can be reduced to 30% on average, outperforming existing methods in view of encoding time, number of function calls, and memory access.
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Predicting individual brain functional connectivity using a Bayesian hierarchical model.
Dai, Tian; Guo, Ying
2017-02-15
Network-oriented analysis of functional magnetic resonance imaging (fMRI), especially resting-state fMRI, has revealed important association between abnormal connectivity and brain disorders such as schizophrenia, major depression and Alzheimer's disease. Imaging-based brain connectivity measures have become a useful tool for investigating the pathophysiology, progression and treatment response of psychiatric disorders and neurodegenerative diseases. Recent studies have started to explore the possibility of using functional neuroimaging to help predict disease progression and guide treatment selection for individual patients. These studies provide the impetus to develop statistical methodology that would help provide predictive information on disease progression-related or treatment-related changes in neural connectivity. To this end, we propose a prediction method based on Bayesian hierarchical model that uses individual's baseline fMRI scans, coupled with relevant subject characteristics, to predict the individual's future functional connectivity. A key advantage of the proposed method is that it can improve the accuracy of individualized prediction of connectivity by combining information from both group-level connectivity patterns that are common to subjects with similar characteristics as well as individual-level connectivity features that are particular to the specific subject. Furthermore, our method also offers statistical inference tools such as predictive intervals that help quantify the uncertainty or variability of the predicted outcomes. The proposed prediction method could be a useful approach to predict the changes in individual patient's brain connectivity with the progression of a disease. It can also be used to predict a patient's post-treatment brain connectivity after a specified treatment regimen. Another utility of the proposed method is that it can be applied to test-retest imaging data to develop a more reliable estimator for individual functional connectivity. We show there exists a nice connection between our proposed estimator and a recently developed shrinkage estimator of connectivity measures in the neuroimaging community. We develop an expectation-maximization (EM) algorithm for estimation of the proposed Bayesian hierarchical model. Simulations studies are performed to evaluate the accuracy of our proposed prediction methods. We illustrate the application of the methods with two data examples: the longitudinal resting-state fMRI from ADNI2 study and the test-retest fMRI data from Kirby21 study. In both the simulation studies and the fMRI data applications, we demonstrate that the proposed methods provide more accurate prediction and more reliable estimation of individual functional connectivity as compared with alternative methods. Copyright © 2017 Elsevier Inc. All rights reserved.
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Savage, V. M.; Bentley, L. P.; Enquist, B. J.; Sperry, J. S.; Smith, D. D.; Reich, P. B.; von Allmen, E. I.
2010-01-01
Plant vascular networks are central to botanical form, function, and diversity. Here, we develop a theory for plant network scaling that is based on optimal space filling by the vascular system along with trade-offs between hydraulic safety and efficiency. Including these evolutionary drivers leads to predictions for sap flow, the taper of the radii of xylem conduits from trunk to terminal twig, and how the frequency of xylem conduits varies with conduit radius. To test our predictions, we use comprehensive empirical measurements of maple, oak, and pine trees and complementary literature data that we obtained for a wide range of tree species. This robust intra- and interspecific assessment of our botanical network model indicates that the central tendency of observed scaling properties supports our predictions much better than the West, Brown, and Enquist (WBE) or pipe models. Consequently, our model is a more accurate description of vascular architecture than what is given by existing network models and should be used as a baseline to understand and to predict the scaling of individual plants to whole forests. In addition, our model is flexible enough to allow the quantification of species variation around rules for network design. These results suggest that the evolutionary drivers that we propose have been fundamental in determining how physiological processes scale within and across plant species. PMID:21149696
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Savage, V M; Bentley, L P; Enquist, B J; Sperry, J S; Smith, D D; Reich, P B; von Allmen, E I
2010-12-28
Plant vascular networks are central to botanical form, function, and diversity. Here, we develop a theory for plant network scaling that is based on optimal space filling by the vascular system along with trade-offs between hydraulic safety and efficiency. Including these evolutionary drivers leads to predictions for sap flow, the taper of the radii of xylem conduits from trunk to terminal twig, and how the frequency of xylem conduits varies with conduit radius. To test our predictions, we use comprehensive empirical measurements of maple, oak, and pine trees and complementary literature data that we obtained for a wide range of tree species. This robust intra- and interspecific assessment of our botanical network model indicates that the central tendency of observed scaling properties supports our predictions much better than the West, Brown, and Enquist (WBE) or pipe models. Consequently, our model is a more accurate description of vascular architecture than what is given by existing network models and should be used as a baseline to understand and to predict the scaling of individual plants to whole forests. In addition, our model is flexible enough to allow the quantification of species variation around rules for network design. These results suggest that the evolutionary drivers that we propose have been fundamental in determining how physiological processes scale within and across plant species.
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NASA Technical Reports Server (NTRS)
Goldberg, Robert K.
2012-01-01
In order to practically utilize ceramic matrix composites in aircraft engine components, robust analysis tools are required that can simulate the material response in a computationally efficient manner. The MAC/GMC software developed at NASA Glenn Research Center, based on the Generalized Method of Cells micromechanics method, has the potential to meet this need. Utilizing MAC/GMC, the effective stiffness properties, proportional limit stress and ultimate strength can be predicted based on the properties and response of the individual constituents. In this paper, the effective stiffness and strength properties for a representative laminated ceramic matrix composite with a large diameter fiber are predicted for a variety of fiber orientation angles and laminate orientations. As part of the analytical study, methods to determine the in-situ stiffness and strength properties of the constituents required to appropriately simulate the effective composite response are developed. The stiffness properties of the representative composite have been adequately predicted for all of the fiber orientations and laminate configurations examined in this study. The proportional limit stresses and strains and ultimate stresses and strains were predicted with varying levels of accuracy, depending on the laminate orientation. However, for the cases where the predictions did not have the desired level of accuracy, the specific issues related to the micromechanics theory were identified which could lead to difficulties that were encountered that could be addressed in future work.
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NASA Astrophysics Data System (ADS)
Chouaib, Wafa; Alila, Younes; Caldwell, Peter V.
2018-05-01
The need for predictions of flow time-series persists at ungauged catchments, motivating the research goals of our study. By means of the Sacramento model, this paper explores the use of parameter transfer within homogeneous regions of similar climate and flow characteristics and makes comparisons with predictions from a priori parameters. We assessed the performance using the Nash-Sutcliffe (NS), bias, mean monthly hydrograph and flow duration curve (FDC). The study was conducted on a large dataset of 73 catchments within the eastern US. Two approaches to the parameter transferability were developed and evaluated; (i) the within homogeneous region parameter transfer using one donor catchment specific to each region, (ii) the parameter transfer disregarding the geographical limits of homogeneous regions, where one donor catchment was common to all regions. Comparisons between both parameter transfers enabled to assess the gain in performance from the parameter regionalization and its respective constraints and limitations. The parameter transfer within homogeneous regions outperformed the a priori parameters and led to a decrease in bias and increase in efficiency reaching a median NS of 0.77 and a NS of 0.85 at individual catchments. The use of FDC revealed the effect of bias on the inaccuracy of prediction from parameter transfer. In one specific region, of mountainous and forested catchments, the prediction accuracy of the parameter transfer was less satisfactory and equivalent to a priori parameters. In this region, the parameter transfer from the outsider catchment provided the best performance; less-biased with smaller uncertainty in medium flow percentiles (40%-60%). The large disparity of energy conditions explained the lack of performance from parameter transfer in this region. Besides, the subsurface stormflow is predominant and there is a likelihood of lateral preferential flow, which according to its specific properties further explained the reduced efficiency. Testing the parameter transferability using criteria of similar climate and flow characteristics at ungauged catchments and comparisons with predictions from a priori parameters are a novelty. The ultimate limitations of both approaches are recognized and recommendations are made for future research.
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NASA Astrophysics Data System (ADS)
Wright, David; Thyer, Mark; Westra, Seth
2015-04-01
Highly influential data points are those that have a disproportionately large impact on model performance, parameters and predictions. However, in current hydrological modelling practice the relative influence of individual data points on hydrological model calibration is not commonly evaluated. This presentation illustrates and evaluates several influence diagnostics tools that hydrological modellers can use to assess the relative influence of data. The feasibility and importance of including influence detection diagnostics as a standard tool in hydrological model calibration is discussed. Two classes of influence diagnostics are evaluated: (1) computationally demanding numerical "case deletion" diagnostics; and (2) computationally efficient analytical diagnostics, based on Cook's distance. These diagnostics are compared against hydrologically orientated diagnostics that describe changes in the model parameters (measured through the Mahalanobis distance), performance (objective function displacement) and predictions (mean and maximum streamflow). These influence diagnostics are applied to two case studies: a stage/discharge rating curve model, and a conceptual rainfall-runoff model (GR4J). Removing a single data point from the calibration resulted in differences to mean flow predictions of up to 6% for the rating curve model, and differences to mean and maximum flow predictions of up to 10% and 17%, respectively, for the hydrological model. When using the Nash-Sutcliffe efficiency in calibration, the computationally cheaper Cook's distance metrics produce similar results to the case-deletion metrics at a fraction of the computational cost. However, Cooks distance is adapted from linear regression with inherit assumptions on the data and is therefore less flexible than case deletion. Influential point detection diagnostics show great potential to improve current hydrological modelling practices by identifying highly influential data points. The findings of this study establish the feasibility and importance of including influential point detection diagnostics as a standard tool in hydrological model calibration. They provide the hydrologist with important information on whether model calibration is susceptible to a small number of highly influent data points. This enables the hydrologist to make a more informed decision of whether to (1) remove/retain the calibration data; (2) adjust the calibration strategy and/or hydrological model to reduce the susceptibility of model predictions to a small number of influential observations.
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Vu, Tuong-Van; Finkenauer, Catrin; Huizinga, Mariette; Novin, Sheida; Krabbendam, Lydia
2017-01-01
This study investigated whether individualism and collectivism (IC) at country, individual, and situational level influence how quickly and accurately people can infer mental states (i.e. theory of mind, or ToM), indexed by accuracy and reaction time in a ToM task. We hypothesized that collectivism (having an interdependent self and valuing group concerns), compared to individualism (having an independent self and valuing personal concerns), is associated with greater accuracy and speed in recognizing and understanding the thoughts and feelings of others. Students (N = 207) from individualism-representative (the Netherlands) and collectivism-representative (Vietnam) countries (Country IC) answered an individualism-collectivism questionnaire (Individual IC) and were randomly assigned to an individualism-primed, collectivism-primed, or no-prime task (Situational IC) before performing a ToM task. The data showed vast differences between the Dutch and Vietnamese groups that might not be attributable to experimental manipulation. Therefore, we analyzed the data for the groups separately and found that Individual IC did not predict ToM accuracy or reaction time performance. Regarding Situational IC, when primed with individualism, the accuracy performance of Vietnamese participants in affective ToM trials decreased compared to when primed with collectivism and when no prime was used. However, an interesting pattern emerged: Dutch participants were least accurate in affective ToM trials, while Vietnamese participants were quickest in affective ToM trials. Our research also highlights a dilemma faced by cross-cultural researchers who use hard-to-reach populations but face the challenge of disentangling experimental effects from biases that might emerge due to an interaction between cultural differences and experimental settings. We propose suggestions for overcoming such challenges.
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Finkenauer, Catrin; Huizinga, Mariette; Novin, Sheida; Krabbendam, Lydia
2017-01-01
This study investigated whether individualism and collectivism (IC) at country, individual, and situational level influence how quickly and accurately people can infer mental states (i.e. theory of mind, or ToM), indexed by accuracy and reaction time in a ToM task. We hypothesized that collectivism (having an interdependent self and valuing group concerns), compared to individualism (having an independent self and valuing personal concerns), is associated with greater accuracy and speed in recognizing and understanding the thoughts and feelings of others. Students (N = 207) from individualism-representative (the Netherlands) and collectivism-representative (Vietnam) countries (Country IC) answered an individualism-collectivism questionnaire (Individual IC) and were randomly assigned to an individualism-primed, collectivism-primed, or no-prime task (Situational IC) before performing a ToM task. The data showed vast differences between the Dutch and Vietnamese groups that might not be attributable to experimental manipulation. Therefore, we analyzed the data for the groups separately and found that Individual IC did not predict ToM accuracy or reaction time performance. Regarding Situational IC, when primed with individualism, the accuracy performance of Vietnamese participants in affective ToM trials decreased compared to when primed with collectivism and when no prime was used. However, an interesting pattern emerged: Dutch participants were least accurate in affective ToM trials, while Vietnamese participants were quickest in affective ToM trials. Our research also highlights a dilemma faced by cross-cultural researchers who use hard-to-reach populations but face the challenge of disentangling experimental effects from biases that might emerge due to an interaction between cultural differences and experimental settings. We propose suggestions for overcoming such challenges. PMID:28832602
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NASA Technical Reports Server (NTRS)
Briggs, Maxwell; Schifer, Nicholas
2011-01-01
Test hardware used to validate net heat prediction models. Problem: Net Heat Input cannot be measured directly during operation. Net heat input is a key parameter needed in prediction of efficiency for convertor performance. Efficiency = Electrical Power Output (Measured) divided by Net Heat Input (Calculated). Efficiency is used to compare convertor designs and trade technology advantages for mission planning.
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Salience and Default Mode Network Coupling Predicts Cognition in Aging and Parkinson's Disease.
Putcha, Deepti; Ross, Robert S; Cronin-Golomb, Alice; Janes, Amy C; Stern, Chantal E
2016-02-01
Cognitive impairment is common in Parkinson's disease (PD). Three neurocognitive networks support efficient cognition: the salience network, the default mode network, and the central executive network. The salience network is thought to switch between activating and deactivating the default mode and central executive networks. Anti-correlated interactions between the salience and default mode networks in particular are necessary for efficient cognition. Our previous work demonstrated altered functional coupling between the neurocognitive networks in non-demented individuals with PD compared to age-matched control participants. Here, we aim to identify associations between cognition and functional coupling between these neurocognitive networks in the same group of participants. We investigated the extent to which intrinsic functional coupling among these neurocognitive networks is related to cognitive performance across three neuropsychological domains: executive functioning, psychomotor speed, and verbal memory. Twenty-four non-demented individuals with mild to moderate PD and 20 control participants were scanned at rest and evaluated on three neuropsychological domains. PD participants were impaired on tests from all three domains compared to control participants. Our imaging results demonstrated that successful cognition across healthy aging and Parkinson's disease participants was related to anti-correlated coupling between the salience and default mode networks. Individuals with poorer performance scores across groups demonstrated more positive salience network/default-mode network coupling. Successful cognition relies on healthy coupling between the salience and default mode networks, which may become dysfunctional in PD. These results can help inform non-pharmacological interventions (repetitive transcranial magnetic stimulation) targeting these specific networks before they become vulnerable in early stages of Parkinson's disease.
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Production efficiency in small mammal populations.
Grodziński, Władysław; French, Norman R
1983-01-01
Data from 102 populations of small mammals from 9 ecosystem types in Europe and in North and Central America were analyzed to define the relationship between productivity and respiration in insectivore and rodent populations. Productivity includes addition of new tissue in the form of growth of individual members of the population and new individuals added by reproduction. All data were recalculated to kilojoules per hectare per year. Linear regression was performed on logarithmic transformation of the data to determine the allometric form of the equation relating production to respiration. The relationship for rodents was determined to be: P=0.026 R 1.008 The relationship for shrews was significantly different both in slope and intercept from that for rodents, and was determined to be: P=0.543 R 0.628 The data were also divided according to functional group or trophic level, in addition to taxonomic grouping. Significant differences were found between herbivores and granivores but not among taxonomic divisions other than the Insectivora. Thus, ecological energetics of small mammals is correlated with trophic position but not with taxonomic position.These equations can be used for prediction of production in rodent and shrew populations where the biomass or respiration is known, thereby aiding the evaluation of trophic relationships in terrestrial communities.Production efficiency is lowest for insectivores (0.7%), and is higher for granivores (2.3%), omnivores (2.6%), and for herbivores (3.4%). The three parameters of respiration, production and assimilation define the conditions for existence of individual mammal populations. Population growth characteristics and species strategies are correlated with energetics and moderated through diet selection by the environment.
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Liu, X. Sherry; Wang, Ji; Zhou, Bin; Stein, Emily; Shi, Xiutao; Adams, Mark; Shane, Elizabeth; Guo, X. Edward
2013-01-01
While high-resolution peripheral quantitative computed tomography (HR-pQCT) has advanced clinical assessment of trabecular bone microstructure, nonlinear microstructural finite element (μFE) prediction of yield strength by HR-pQCT voxel model is impractical for clinical use due to its prohibitively high computational costs. The goal of this study was to develop an efficient HR-pQCT-based plate and rod (PR) modeling technique to fill the unmet clinical need for fast bone strength estimation. By using individual trabecula segmentation (ITS) technique to segment the trabecular structure into individual plates and rods, a patient-specific PR model was implemented by modeling each trabecular plate with multiple shell elements and each rod with a beam element. To validate this modeling technique, predictions by HR-pQCT PR model were compared with those of the registered high resolution μCT voxel model of 19 trabecular sub-volumes from human cadaveric tibiae samples. Both Young’s modulus and yield strength of HR-pQCT PR models strongly correlated with those of μCT voxel models (r2=0.91 and 0.86). Notably, the HR-pQCT PR models achieved major reductions in element number (>40-fold) and CPU time (>1,200-fold). Then, we applied PR model μFE analysis to HR-pQCT images of 60 postmenopausal women with (n=30) and without (n=30) a history of vertebral fracture. HR-pQCT PR model revealed significantly lower Young’s modulus and yield strength at the radius and tibia in fracture subjects compared to controls. Moreover, these mechanical measurements remained significantly lower in fracture subjects at both sites after adjustment for aBMD T-score at the ultradistal radius or total hip. In conclusion, we validated a novel HR-pQCT PR model of human trabecular bone against μCT voxel models and demonstrated its ability to discriminate vertebral fracture status in postmenopausal women. This accurate nonlinear μFE prediction of HR-pQCT PR model, which requires only seconds of desktop computer time, has tremendous promise for clinical assessment of bone strength. PMID:23456922
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Svensson, Fredrik; Aniceto, Natalia; Norinder, Ulf; Cortes-Ciriano, Isidro; Spjuth, Ola; Carlsson, Lars; Bender, Andreas
2018-05-29
Making predictions with an associated confidence is highly desirable as it facilitates decision making and resource prioritization. Conformal regression is a machine learning framework that allows the user to define the required confidence and delivers predictions that are guaranteed to be correct to the selected extent. In this study, we apply conformal regression to model molecular properties and bioactivity values and investigate different ways to scale the resultant prediction intervals to create as efficient (i.e., narrow) regressors as possible. Different algorithms to estimate the prediction uncertainty were used to normalize the prediction ranges, and the different approaches were evaluated on 29 publicly available data sets. Our results show that the most efficient conformal regressors are obtained when using the natural exponential of the ensemble standard deviation from the underlying random forest to scale the prediction intervals, but other approaches were almost as efficient. This approach afforded an average prediction range of 1.65 pIC50 units at the 80% confidence level when applied to bioactivity modeling. The choice of nonconformity function has a pronounced impact on the average prediction range with a difference of close to one log unit in bioactivity between the tightest and widest prediction range. Overall, conformal regression is a robust approach to generate bioactivity predictions with associated confidence.
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Schädler, Marc René; Warzybok, Anna; Meyer, Bernd T.; Brand, Thomas
2016-01-01
To characterize the individual patient’s hearing impairment as obtained with the matrix sentence recognition test, a simulation Framework for Auditory Discrimination Experiments (FADE) is extended here using the Attenuation and Distortion (A+D) approach by Plomp as a blueprint for setting the individual processing parameters. FADE has been shown to predict the outcome of both speech recognition tests and psychoacoustic experiments based on simulations using an automatic speech recognition system requiring only few assumptions. It builds on the closed-set matrix sentence recognition test which is advantageous for testing individual speech recognition in a way comparable across languages. Individual predictions of speech recognition thresholds in stationary and in fluctuating noise were derived using the audiogram and an estimate of the internal level uncertainty for modeling the individual Plomp curves fitted to the data with the Attenuation (A-) and Distortion (D-) parameters of the Plomp approach. The “typical” audiogram shapes from Bisgaard et al with or without a “typical” level uncertainty and the individual data were used for individual predictions. As a result, the individualization of the level uncertainty was found to be more important than the exact shape of the individual audiogram to accurately model the outcome of the German Matrix test in stationary or fluctuating noise for listeners with hearing impairment. The prediction accuracy of the individualized approach also outperforms the (modified) Speech Intelligibility Index approach which is based on the individual threshold data only. PMID:27604782
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Zhao, Chun; Liu, Xiaoguang; Shi, Zhonghua; Zhang, Jing; Zhang, Junqiang; Jia, Xuemei; Ling, Xiufeng
2015-01-01
Polycystic ovarian syndrome (PCOS) causes a significantly increased risk of ovarian hyperstimulation syndrome (OHSS). Here, we focused on the altered expression of serum miRNAs and their predictive value for OHSS in PCOS patients. We used the TaqMan low density array followed by individual quantitative reverse transcription-polymerase chain reaction to identify and validate the expression of serum miRNAs in PCOS patients likely to develop severe OHSS. The miR-16 and miR-223 expression levels were significantly reduced in the patients who were likely to develop severe OHSS than in the control subjects who were likely to develop mild or no OHSS. The sensitivity and specificity of the basal LH, basal LH/FSH, and body mass index (BMI) as OHSS predictors were also evaluated. miR-16 was the most efficient for OHSS prediction as it yielded the highest AUC. Logistic binary regression analyses revealed a positive association of miR-223 and BMI. Serum miRNAs are differentially expressed in PCOS patients likely to suffer from severe OHSS. We identified and validated two serum miRNAs that have potential for use as novel noninvasive biomarkers to accurately predict OHSS before controlled ovarian hyperstimulation (COH) for PCOS patients. © 2015 S. Karger AG, Basel.
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Weibull-Based Design Methodology for Rotating Aircraft Engine Structures
NASA Technical Reports Server (NTRS)
Zaretsky, Erwin; Hendricks, Robert C.; Soditus, Sherry
2002-01-01
The NASA Energy Efficient Engine (E(sup 3)-Engine) is used as the basis of a Weibull-based life and reliability analysis. Each component's life and thus the engine's life is defined by high-cycle fatigue (HCF) or low-cycle fatigue (LCF). Knowing the cumulative life distribution of each of the components making up the engine as represented by a Weibull slope is a prerequisite to predicting the life and reliability of the entire engine. As the engine Weibull slope increases, the predicted lives decrease. The predicted engine lives L(sub 5) (95 % probability of survival) of approximately 17,000 and 32,000 hr do correlate with current engine maintenance practices without and with refurbishment. respectively. The individual high pressure turbine (HPT) blade lives necessary to obtain a blade system life L(sub 0.1) (99.9 % probability of survival) of 9000 hr for Weibull slopes of 3, 6 and 9, are 47,391 and 20,652 and 15,658 hr, respectively. For a design life of the HPT disks having probable points of failure equal to or greater than 36,000 hr at a probability of survival of 99.9 %, the predicted disk system life L(sub 0.1) can vary from 9,408 to 24,911 hr.
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Huang, Jui-Hua; Huang, Shu-Ling; Li, Ren-Hau; Wang, Ling-Hui; Chen, Yu-Ling; Tang, Feng-Cheng
2014-04-29
Workplace health promotion programs should be tailored according to individual needs and efficient intervention. This study aimed to determine the effects of nutrition and exercise health behaviors on predicted risk for cardiovascular disease (CVD) when body mass index (BMI) is considered. In total, 3350 Taiwanese workers were included in this cross-sectional study. A self-reported questionnaire was used to measure their nutrition and exercise behaviors. Data on anthropometric values, biochemical blood determinations, and predicted CVD risk (using the Framingham risk score) were collected. In multiple regression analyses, the nutrition behavior score was independently and negatively associated with CVD risk. Exercise was not significantly associated with the risk. However, the interactive effect of exercise and BMI on CVD risk was evident. When stratified by BMI levels, associations between exercise and CVD risk were statistically significant for ideal weight and overweight subgroups. In conclusion, nutrition behavior plays an important role in predicting the CVD risk. Exercise behavior is also a significant predictor for ideal weight and overweight workers. Notably, for underweight or obese workers, maintaining health-promoting exercise seems insufficient to prevent the CVD. In order to improve workers' cardiovascular health, more specific health-promoting strategies should be developed to suit the different BMI levels.
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Mani, Nivedita; Huettig, Falk
2014-10-01
Despite the efficiency with which language users typically process spoken language, a growing body of research finds substantial individual differences in both the speed and accuracy of spoken language processing potentially attributable to participants' literacy skills. Against this background, the current study took a look at the role of word reading skill in listeners' anticipation of upcoming spoken language input in children at the cusp of learning to read; if reading skills affect predictive language processing, then children at this stage of literacy acquisition should be most susceptible to the effects of reading skills on spoken language processing. We tested 8-year-olds on their prediction of upcoming spoken language input in an eye-tracking task. Although children, like in previous studies to date, were successfully able to anticipate upcoming spoken language input, there was a strong positive correlation between children's word reading skills (but not their pseudo-word reading and meta-phonological awareness or their spoken word recognition skills) and their prediction skills. We suggest that these findings are most compatible with the notion that the process of learning orthographic representations during reading acquisition sharpens pre-existing lexical representations, which in turn also supports anticipation of upcoming spoken words. Copyright © 2014 Elsevier Inc. All rights reserved.
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Rapid measurement and prediction of bacterial contamination in milk using an oxygen electrode.
Numthuam, Sonthaya; Suzuki, Hiroaki; Fukuda, Junji; Phunsiri, Suthiluk; Rungchang, Saowaluk; Satake, Takaaki
2009-03-01
An oxygen electrode was used to measure oxygen consumption to determine bacterial contamination in milk. Dissolved oxygen (DO) measured at 10-35 degrees C for 2 hours provided a reasonable prediction efficiency (r > or = 0.90) of the amount of bacteria between 1.9 and 7.3 log (CFU/mL). A temperature-dependent predictive model was developed that has the same prediction accuracy like the normal predictive model. The analysis performed with and without stirring provided the same prediction efficiency, with correlation coefficient of 0.90. The measurement of DO is a simple and rapid method for the determination of bacteria in milk.
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Rapid race perception despite individuation and accuracy goals.
Kubota, Jennifer T; Ito, Tiffany
2017-08-01
Perceivers rapidly process social category information and form stereotypic impressions of unfamiliar others. However, a goal to individuate a target or to accurately predict their behavior can result in individuated impressions. It is unknown how the combination of both accuracy and individuation goals affects perceptual category processing. To explore this, participants were given both the goal to individuate targets and accurately predict behavior. We then recorded event-related brain potentials while participants viewed photos of black and white males along with four pieces of individuating information in the form of descriptions of past behavior. Even with explicit individuation and accuracy task goals, participants rapidly differentiated targets by race within 200 ms. Importantly, this rapid categorical processing did not influence behavioral outcomes as participants made individuated predictions. These findings indicate that individuals engage in category processing even when provided with individuation and accuracy goals, but that this processing does not necessarily result in category-based judgments.
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Mathematical model for prediction of efficiency indicators of educational activity in high school
NASA Astrophysics Data System (ADS)
Tikhonova, O. M.; Kushnikov, V. A.; Fominykh, D. S.; Rezchikov, A. F.; Ivashchenko, V. A.; Bogomolov, A. S.; Filimonyuk, L. Yu; Dolinina, O. N.; Kushnikov, O. V.; Shulga, T. E.; Tverdokhlebov, V. A.
2018-05-01
The quality of high school is a current problem all over the world. The paper presents the system dedicated to predicting the accreditation indicators of technical universities based on J. Forrester mechanism of system dynamics. The mathematical model is developed for prediction of efficiency indicators of the educational activity and is based on the apparatus of nonlinear differential equations.
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Ordinary kriging as a tool to estimate historical daily streamflow records
Farmer, William H.
2016-01-01
Efficient and responsible management of water resources relies on accurate streamflow records. However, many watersheds are ungaged, limiting the ability to assess and understand local hydrology. Several tools have been developed to alleviate this data scarcity, but few provide continuous daily streamflow records at individual streamgages within an entire region. Building on the history of hydrologic mapping, ordinary kriging was extended to predict daily streamflow time series on a regional basis. Pooling parameters to estimate a single, time-invariant characterization of spatial semivariance structure is shown to produce accurate reproduction of streamflow. This approach is contrasted with a time-varying series of variograms, representing the temporal evolution and behavior of the spatial semivariance structure. Furthermore, the ordinary kriging approach is shown to produce more accurate time series than more common, single-index hydrologic transfers. A comparison between topological kriging and ordinary kriging is less definitive, showing the ordinary kriging approach to be significantly inferior in terms of Nash–Sutcliffe model efficiencies while maintaining significantly superior performance measured by root mean squared errors. Given the similarity of performance and the computational efficiency of ordinary kriging, it is concluded that ordinary kriging is useful for first-order approximation of daily streamflow time series in ungaged watersheds.
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Multiscale musculoskeletal modelling, data–model fusion and electromyography-informed modelling
Zhang, J.; Heidlauf, T.; Sartori, M.; Besier, T.; Röhrle, O.; Lloyd, D.
2016-01-01
This paper proposes methods and technologies that advance the state of the art for modelling the musculoskeletal system across the spatial and temporal scales; and storing these using efficient ontologies and tools. We present population-based modelling as an efficient method to rapidly generate individual morphology from only a few measurements and to learn from the ever-increasing supply of imaging data available. We present multiscale methods for continuum muscle and bone models; and efficient mechanostatistical methods, both continuum and particle-based, to bridge the scales. Finally, we examine both the importance that muscles play in bone remodelling stimuli and the latest muscle force prediction methods that use electromyography-assisted modelling techniques to compute musculoskeletal forces that best reflect the underlying neuromuscular activity. Our proposal is that, in order to have a clinically relevant virtual physiological human, (i) bone and muscle mechanics must be considered together; (ii) models should be trained on population data to permit rapid generation and use underlying principal modes that describe both muscle patterns and morphology; and (iii) these tools need to be available in an open-source repository so that the scientific community may use, personalize and contribute to the database of models. PMID:27051510
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Statistical modeling of an integrated boiler for coal fired thermal power plant.
Chandrasekharan, Sreepradha; Panda, Rames Chandra; Swaminathan, Bhuvaneswari Natrajan
2017-06-01
The coal fired thermal power plants plays major role in the power production in the world as they are available in abundance. Many of the existing power plants are based on the subcritical technology which can produce power with the efficiency of around 33%. But the newer plants are built on either supercritical or ultra-supercritical technology whose efficiency can be up to 50%. Main objective of the work is to enhance the efficiency of the existing subcritical power plants to compensate for the increasing demand. For achieving the objective, the statistical modeling of the boiler units such as economizer, drum and the superheater are initially carried out. The effectiveness of the developed models is tested using analysis methods like R 2 analysis and ANOVA (Analysis of Variance). The dependability of the process variable (temperature) on different manipulated variables is analyzed in the paper. Validations of the model are provided with their error analysis. Response surface methodology (RSM) supported by DOE (design of experiments) are implemented to optimize the operating parameters. Individual models along with the integrated model are used to study and design the predictive control of the coal-fired thermal power plant.
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Pathak, Rajesh Kumar; Gupta, Sanjay Mohan; Gaur, Vikram Singh; Pandey, Dinesh
2015-01-01
Abstract In recent years, rapid developments in several omics platforms and next generation sequencing technology have generated a huge amount of biological data about plants. Systems biology aims to develop and use well-organized and efficient algorithms, data structure, visualization, and communication tools for the integration of these biological data with the goal of computational modeling and simulation. It studies crop plant systems by systematically perturbing them, checking the gene, protein, and informational pathway responses; integrating these data; and finally, formulating mathematical models that describe the structure of system and its response to individual perturbations. Consequently, systems biology approaches, such as integrative and predictive ones, hold immense potential in understanding of molecular mechanism of agriculturally important complex traits linked to agricultural productivity. This has led to identification of some key genes and proteins involved in networks of pathways involved in input use efficiency, biotic and abiotic stress resistance, photosynthesis efficiency, root, stem and leaf architecture, and nutrient mobilization. The developments in the above fields have made it possible to design smart crops with superior agronomic traits through genetic manipulation of key candidate genes. PMID:26484978
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NASA Astrophysics Data System (ADS)
Eric, L.; Vrugt, J. A.
2010-12-01
Spatially distributed hydrologic models potentially contain hundreds of parameters that need to be derived by calibration against a historical record of input-output data. The quality of this calibration strongly determines the predictive capability of the model and thus its usefulness for science-based decision making and forecasting. Unfortunately, high-dimensional optimization problems are typically difficult to solve. Here we present our recent developments to the Differential Evolution Adaptive Metropolis (DREAM) algorithm (Vrugt et al., 2009) to warrant efficient solution of high-dimensional parameter estimation problems. The algorithm samples from an archive of past states (Ter Braak and Vrugt, 2008), and uses multiple-try Metropolis sampling (Liu et al., 2000) to decrease the required burn-in time for each individual chain and increase efficiency of posterior sampling. This approach is hereafter referred to as MT-DREAM. We present results for 2 synthetic mathematical case studies, and 2 real-world examples involving from 10 to 240 parameters. Results for those cases show that our multiple-try sampler, MT-DREAM, can consistently find better solutions than other Bayesian MCMC methods. Moreover, MT-DREAM is admirably suited to be implemented and ran on a parallel machine and is therefore a powerful method for posterior inference.
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NASA Astrophysics Data System (ADS)
Gosses, M. J.; Wöhling, Th.; Moore, C. R.; Dann, R.; Scott, D. M.; Close, M.
2012-04-01
Groundwater resources worldwide are increasingly under pressure. Demands from different local stakeholders add to the challenge of managing this resource. In response, groundwater models have become popular to make predictions about the impact of different management strategies and to estimate possible impacts of changes in climatic conditions. These models can assist to find optimal management strategies that comply with the various stakeholder needs. Observations of the states of the groundwater system are essential for the calibration and evaluation of groundwater flow models, particularly when they are used to guide the decision making process. On the other hand, installation and maintenance of observation networks are costly. Therefore it is important to design monitoring networks carefully and cost-efficiently. In this study, we analyse the Central Plains groundwater aquifer (~ 4000 km2) between the Rakaia and Waimakariri rivers on the Eastern side of the Southern Alps in New Zealand. The large sedimentary groundwater aquifer is fed by the two alpine rivers and by recharge from the land surface. The area is mainly under agricultural land use and large areas of the land are irrigated. The other major water use is the drinking water supply for the city of Christchurch. The local authority in the region, Environment Canterbury, maintains an extensive groundwater quantity and quality monitoring programme to monitor the effects of land use and discharges on groundwater quality, and the suitability of the groundwater for various uses, especially drinking-water supply. Current and projected irrigation water demand has raised concerns about possible impacts on groundwater-dependent lowland streams. We use predictive uncertainty analysis and the Central Plains steady-state groundwater flow model to evaluate the worth of pressure head observations in the existing groundwater well monitoring network. The data worth of particular observations is dependent on the problem-specific prediction target under consideration. Therefore, the worth of individual observation locations may differ for different prediction targets. Our evaluation is based on predictions of lowland stream discharge resulting from changes in land use and irrigation in the upper Central Plains catchment. In our analysis, we adopt the model predictive uncertainty analysis method by Moore and Doherty (2005) which accounts for contributions from both measurement errors and uncertain structural heterogeneity. The method is robust and efficient due to a linearity assumption in the governing equations and readily implemented for application in the model-independent parameter estimation and uncertainty analysis toolkit PEST (Doherty, 2010). The proposed methods can be applied not only for the evaluation of monitoring networks, but also for the optimization of networks, to compare alternative monitoring strategies, as well as to identify best cost-benefit monitoring design even prior to any data acquisition.
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Comparative Analysis of River Flow Modelling by Using Supervised Learning Technique
NASA Astrophysics Data System (ADS)
Ismail, Shuhaida; Mohamad Pandiahi, Siraj; Shabri, Ani; Mustapha, Aida
2018-04-01
The goal of this research is to investigate the efficiency of three supervised learning algorithms for forecasting monthly river flow of the Indus River in Pakistan, spread over 550 square miles or 1800 square kilometres. The algorithms include the Least Square Support Vector Machine (LSSVM), Artificial Neural Network (ANN) and Wavelet Regression (WR). The forecasting models predict the monthly river flow obtained from the three models individually for river flow data and the accuracy of the all models were then compared against each other. The monthly river flow of the said river has been forecasted using these three models. The obtained results were compared and statistically analysed. Then, the results of this analytical comparison showed that LSSVM model is more precise in the monthly river flow forecasting. It was found that LSSVM has he higher r with the value of 0.934 compared to other models. This indicate that LSSVM is more accurate and efficient as compared to the ANN and WR model.
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Behavioral flexibility and problem solving in an invasive bird
2016-01-01
Behavioral flexibility is considered an important trait for adapting to environmental change, but it is unclear what it is, how it works, and whether it is a problem solving ability. I investigated behavioral flexibility and problem solving experimentally in great-tailed grackles, an invasive bird species and thus a likely candidate for possessing behavioral flexibility. Grackles demonstrated behavioral flexibility in two contexts, the Aesop’s Fable paradigm and a color association test. Contrary to predictions, behavioral flexibility did not correlate across contexts. Four out of 6 grackles exhibited efficient problem solving abilities, but problem solving efficiency did not appear to be directly linked with behavioral flexibility. Problem solving speed also did not significantly correlate with reversal learning scores, indicating that faster learners were not the most flexible. These results reveal how little we know about behavioral flexibility, and provide an immense opportunity for future research to explore how individuals and species can use behavior to react to changing environments. PMID:27168984
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Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits
Ujfalussy, Balázs B; Makara, Judit K; Branco, Tiago; Lengyel, Máté
2015-01-01
Cortical neurons integrate thousands of synaptic inputs in their dendrites in highly nonlinear ways. It is unknown how these dendritic nonlinearities in individual cells contribute to computations at the level of neural circuits. Here, we show that dendritic nonlinearities are critical for the efficient integration of synaptic inputs in circuits performing analog computations with spiking neurons. We developed a theory that formalizes how a neuron's dendritic nonlinearity that is optimal for integrating synaptic inputs depends on the statistics of its presynaptic activity patterns. Based on their in vivo preynaptic population statistics (firing rates, membrane potential fluctuations, and correlations due to ensemble dynamics), our theory accurately predicted the responses of two different types of cortical pyramidal cells to patterned stimulation by two-photon glutamate uncaging. These results reveal a new computational principle underlying dendritic integration in cortical neurons by suggesting a functional link between cellular and systems--level properties of cortical circuits. DOI: http://dx.doi.org/10.7554/eLife.10056.001 PMID:26705334
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Bustamante, Mauricio; Heinze, Jonas; Winter, Walter
Gamma-ray bursts (GRBs) are promising as sources of neutrinos and cosmic rays. In the internal shock scenario, blobs of plasma emitted from a central engine collide within a relativistic jet and form shocks, leading to particle acceleration and emission. Motivated by present experimental constraints and sensitivities, we improve the predictions of particle emission by investigating time-dependent effects from multiple shocks. We produce synthetic light curves with different variability timescales that stem from properties of the central engine. For individual GRBs, qualitative conclusions about model parameters, neutrino production efficiency, and delays in high-energy gamma-rays can be deduced from inspection of themore » gamma-ray light curves. GRBs with fast time variability without additional prominent pulse structure tend to be efficient neutrino emitters, whereas GRBs with fast variability modulated by a broad pulse structure can be inefficient neutrino emitters and produce delayed high-energy gamma-ray signals. Our results can be applied to quantitative tests of the GRB origin of ultra-high-energy cosmic rays, and have the potential to impact current and future multi-messenger searches.« less
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Energy and fuels from electrochemical interfaces
Stamenkovic, Vojislav R.; Strmcnik, Dusan; Lopes, Pietro P.; ...
2016-12-20
Advances in electrocatalysis at solid–liquid interfaces are vital for driving the technological innovations that are needed to deliver reliable, affordable and environmentally friendly energy. Here, in this paper, we highlight the key achievements in the development of new materials for efficient hydrogen and oxygen production in electrolysers and, in reverse, their use in fuel cells. A key issue addressed here is the degree to which the fundamental understanding of the synergy between covalent and non-covalent interactions can form the basis for any predictive ability in tailor-making real-world catalysts. Common descriptors such as the substrate–hydroxide binding energy and the interactions inmore » the double layer between hydroxide-oxides and H---OH are found to control individual parts of the hydrogen and oxygen electrochemistry that govern the efficiency of water-based energy conversion and storage systems. Lastly, links between aqueous- and organic-based environments are also established, encouraging the 'fuel cell' and 'battery' communities to move forward together.« less
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Modelling personality, plasticity and predictability in shelter dogs
2017-01-01
Behavioural assessments of shelter dogs (Canis lupus familiaris) typically comprise standardized test batteries conducted at one time point, but test batteries have shown inconsistent predictive validity. Longitudinal behavioural assessments offer an alternative. We modelled longitudinal observational data on shelter dog behaviour using the framework of behavioural reaction norms, partitioning variance into personality (i.e. inter-individual differences in behaviour), plasticity (i.e. inter-individual differences in average behaviour) and predictability (i.e. individual differences in residual intra-individual variation). We analysed data on interactions of 3263 dogs (n = 19 281) with unfamiliar people during their first month after arrival at the shelter. Accounting for personality, plasticity (linear and quadratic trends) and predictability improved the predictive accuracy of the analyses compared to models quantifying personality and/or plasticity only. While dogs were, on average, highly sociable with unfamiliar people and sociability increased over days since arrival, group averages were unrepresentative of all dogs and predictions made at the individual level entailed considerable uncertainty. Effects of demographic variables (e.g. age) on personality, plasticity and predictability were observed. Behavioural repeatability was higher one week after arrival compared to arrival day. Our results highlight the value of longitudinal assessments on shelter dogs and identify measures that could improve the predictive validity of behavioural assessments in shelters. PMID:28989764
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NASA Astrophysics Data System (ADS)
Tárnok, Attila; Mittag, Anja; Lenz, Dominik
2006-02-01
The goal of predictive medicine is the detection of changes in patient's state prior to the clinical manifestation of the deterioration of the patients current status. Therefore, both the diagnostic of diseases like cancer, coronary atherosclerosis or congenital heart failure and the prognosis of the effect specific therapeutics on patients outcome are the main fields of predictive medicine. Clinical Cytomcs is based on the analysis of specimens from the patient by Cytomic technologies that are mainly imaging based techniques and their combinations with other assays. Predictive medicine aims at the recognition of the "fate" of each individual patients in order to yield unequivocal indications for decision making (i.e. how does the patient respond to therapy, react to medication etc.). This individualized prediction is based on the Predictive Medicine by Clinical Cytomics concept. These considerations have recently stimulated the idea of the Human Cytome Project. A major focus of the Human Cytome Project is multiplexed cy-tomic analysis of individual cells of the patient, extraction of predictive information and individual prediction that merges into individualized therapy. Although still at the beginning, Clinical Cytomics is a promising new field that may change therapy in the near future for the benefit of the patients.
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NASA Technical Reports Server (NTRS)
Mulavara, A. P.; Seidler, R. D.; Feiveson, A.; Oddsson, L.; Zanello, S.; Oman, C. M.; Ploutz-Snyder, L.; Peters, B.; Cohen, H. S.; Reschke, M.;
2014-01-01
Astronauts experience sensorimotor disturbances during the initial exposure to microgravity and during the re-adapation phase following a return to an earth-gravitational environment. These alterations may disrupt the ability to perform mission critical functional tasks requiring ambulation, manual control and gaze stability. Interestingly, astronauts who return from space flight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. For such an approach to succeed, we must develop predictive measures of sensorimotor adaptability that will allow us to foresee, before actual space flight, which crewmembers are likely to experience the greatest challenges to their adaptive capacities. The goals of this project are to identify and characterize this set of predictive measures that include: 1) behavioral tests to assess sensory bias and adaptability quantified using both strategic and plastic-adaptive responses; 2) imaging to determine individual brain morphological and functional features using structural magnetic resonance imaging (MRI), diffusion tensor imaging, resting state functional connectivity MRI, and sensorimotor adaptation task-related functional brain activation; 3) genotype markers for genetic polymorphisms in Catechol-O-Methyl Transferase, Dopamine Receptor D2, Brain-derived neurotrophic factor and genetic polymorphism of alpha2-adrenergic receptor that play a role in the neural pathways underlying sensorimotor adaptation. We anticipate these predictive measures will be significantly correlated with individual differences in sensorimotor adaptability after long-duration space flight and an analog bed rest environment. We will be conducting a retrospective study leveraging data already collected from relevant ongoing/completed bed rest and space flight studies. These data will be combined with predictor metrics that will be collected prospectively - behavioral, brain imaging and genomic measures; from these returning subjects to build models for predicting post-mission (bed rest - non-astronauts or space flight - astronauts) adaptive capability as manifested in their outcome measures. Comparisons of model performance will allow us to better design and implement sensorimotor adaptability training countermeasures that are customized for each crewmember's sensory biases, adaptive capacity, brain structure and functional capacities, and genetic predispositions against decrements in post-mission adaptive capability. This ability will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to ensure expected outcomes.
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Predicting breast cancer using an expression values weighted clinical classifier.
Thomas, Minta; De Brabanter, Kris; Suykens, Johan A K; De Moor, Bart
2014-12-31
Clinical data, such as patient history, laboratory analysis, ultrasound parameters-which are the basis of day-to-day clinical decision support-are often used to guide the clinical management of cancer in the presence of microarray data. Several data fusion techniques are available to integrate genomics or proteomics data, but only a few studies have created a single prediction model using both gene expression and clinical data. These studies often remain inconclusive regarding an obtained improvement in prediction performance. To improve clinical management, these data should be fully exploited. This requires efficient algorithms to integrate these data sets and design a final classifier. LS-SVM classifiers and generalized eigenvalue/singular value decompositions are successfully used in many bioinformatics applications for prediction tasks. While bringing up the benefits of these two techniques, we propose a machine learning approach, a weighted LS-SVM classifier to integrate two data sources: microarray and clinical parameters. We compared and evaluated the proposed methods on five breast cancer case studies. Compared to LS-SVM classifier on individual data sets, generalized eigenvalue decomposition (GEVD) and kernel GEVD, the proposed weighted LS-SVM classifier offers good prediction performance, in terms of test area under ROC Curve (AUC), on all breast cancer case studies. Thus a clinical classifier weighted with microarray data set results in significantly improved diagnosis, prognosis and prediction responses to therapy. The proposed model has been shown as a promising mathematical framework in both data fusion and non-linear classification problems.
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Predicting Individuals' Learning Success from Patterns of Pre-Learning MRI Activity
Vo, Loan T. K.; Walther, Dirk B.; Kramer, Arthur F.; Erickson, Kirk I.; Boot, Walter R.; Voss, Michelle W.; Prakash, Ruchika S.; Lee, Hyunkyu; Fabiani, Monica; Gratton, Gabriele; Simons, Daniel J.; Sutton, Bradley P.; Wang, Michelle Y.
2011-01-01
Performance in most complex cognitive and psychomotor tasks improves with training, yet the extent of improvement varies among individuals. Is it possible to forecast the benefit that a person might reap from training? Several behavioral measures have been used to predict individual differences in task improvement, but their predictive power is limited. Here we show that individual differences in patterns of time-averaged T2*-weighted MRI images in the dorsal striatum recorded at the initial stage of training predict subsequent learning success in a complex video game with high accuracy. These predictions explained more than half of the variance in learning success among individuals, suggesting that individual differences in neuroanatomy or persistent physiology predict whether and to what extent people will benefit from training in a complex task. Surprisingly, predictions from white matter were highly accurate, while voxels in the gray matter of the dorsal striatum did not contain any information about future training success. Prediction accuracy was higher in the anterior than the posterior half of the dorsal striatum. The link between trainability and the time-averaged T2*-weighted signal in the dorsal striatum reaffirms the role of this part of the basal ganglia in learning and executive functions, such as task-switching and task coordination processes. The ability to predict who will benefit from training by using neuroimaging data collected in the early training phase may have far-reaching implications for the assessment of candidates for specific training programs as well as the study of populations that show deficiencies in learning new skills. PMID:21264257
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Modeling the impact of spatial relationships on horizontal curve safety.
Findley, Daniel J; Hummer, Joseph E; Rasdorf, William; Zegeer, Charles V; Fowler, Tyler J
2012-03-01
The curved segments of roadways are more hazardous because of the additional centripetalforces exerted on a vehicle, driver expectations, and other factors. The safety of a curve is dependent on various factors, most notably by geometric factors, but the location of a curve in relation to other curves is also thought to influence the safety of those curves because of a driver's expectation to encounter additional curves. The link between an individual curve's geometric characteristics and its safety performance has been established, but spatial considerations are typically not included in a safety analysis. The spatial considerations included in this research consisted of four components: distance to adjacent curves, direction of turn of the adjacent curves, and radius and length of the adjacent curves. The primary objective of this paper is to quantify the spatial relationship between adjacent horizontal curves and horizontal curve safety using a crash modification factor. Doing so enables a safety professional to more accurately estimate safety to allocate funding to reduce or prevent future collisions and more efficiently design new roadway sections to minimize crash risk where there will be a series of curves along a route. The most important finding from this research is the statistical significance of spatial considerations for the prediction of horizontal curve safety. The distances to adjacent curves were found to be a reliable predictor of observed collisions. This research recommends a model which utilizes spatial considerations for horizontal curve safety prediction in addition to current Highway Safety Manual prediction capabilities using individual curve geometric features. Copyright © 2011 Elsevier Ltd. All rights reserved.
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Rebaudo, François; Dangles, Olivier
2011-10-01
Worldwide, the theory and practice of agricultural extension system have been dominated for almost half a century by Rogers' "diffusion of innovation theory". In particular, the success of integrated pest management (IPM) extension programs depends on the effectiveness of IPM information diffusion from trained farmers to other farmers, an important assumption which underpins funding from development organizations. Here we developed an innovative approach through an agent-based model (ABM) combining social (diffusion theory) and biological (pest population dynamics) models to study the role of cooperation among small-scale farmers to share IPM information for controlling an invasive pest. The model was implemented with field data, including learning processes and control efficiency, from large scale surveys in the Ecuadorian Andes. Our results predict that although cooperation had short-term costs for individual farmers, it paid in the long run as it decreased pest infestation at the community scale. However, the slow learning process placed restrictions on the knowledge that could be generated within farmer communities over time, giving rise to natural lags in IPM diffusion and applications. We further showed that if individuals learn from others about the benefits of early prevention of new pests, then educational effort may have a sustainable long-run impact. Consistent with models of information diffusion theory, our results demonstrate how an integrated approach combining ecological and social systems would help better predict the success of IPM programs. This approach has potential beyond pest management as it could be applied to any resource management program seeking to spread innovations across populations.
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A novel mutation in KIF5A in a Malian family with spastic paraplegia and sensory loss.
Guinto, Cheick O; Diarra, Salimata; Diallo, Salimata; Cissé, Lassana; Coulibaly, Thomas; Diallo, Seybou H; Taméga, Abdoulaye; Chen, Ke-Lian; Schindler, Alice B; Bagayoko, Koumba; Simaga, Assiatou; Blackstone, Craig; Fischbeck, Kenneth H; Landouré, Guida
2017-04-01
Hereditary spastic paraplegias (HSPs) are well-characterized disorders but rarely reported in Africa. We evaluated a Malian family in which three individuals had HSP and distal muscle atrophy and sensory loss. HSP panel testing identified a novel heterozygous missense mutation in KIF5A (c.1086G>C, p.Lys362Asn) that segregated with the disease (SPG10). Lys362 is highly conserved across species and Lys362Asn is predicted to be damaging. This study shows that HSPs are present in sub-Saharan Africa, although likely underdiagnosed. Increasing efficiency and decreasing costs of DNA sequencing will make it more feasible to diagnose HSPs in developing countries.
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Performance of a supercharged direct-injection stratified-charge rotary combustion engine
NASA Technical Reports Server (NTRS)
Bartrand, Timothy A.; Willis, Edward A.
1990-01-01
A zero-dimensional thermodynamic performance computer model for direct-injection stratified-charge rotary combustion engines was modified and run for a single rotor supercharged engine. Operating conditions for the computer runs were a single boost pressure and a matrix of speeds, loads and engine materials. A representative engine map is presented showing the predicted range of efficient operation. After discussion of the engine map, a number of engine features are analyzed individually. These features are: heat transfer and the influence insulating materials have on engine performance and exhaust energy; intake manifold pressure oscillations and interactions with the combustion chamber; and performance losses and seal friction. Finally, code running times and convergence data are presented.
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The person with a spinal cord injury: an evolving prototype for life care planning.
Stiens, Steven A; Fawber, Heidi L; Yuhas, Steven A
2013-08-01
The sequela of spinal cord injury (SCI) can provide a prototype for life care planning because the segmental design of the vertebrate body allows assessments to be quantitative, repeatable, and predictive of the injured person's impairments, self-care capabilities, and required assistance. Life care planning for patients with SCI uses a standard method that is comparable between planner, yet individualizes assessment and seeks resources that meet unique patient-centered needs in their communities of choice. Clinical care and rehabilitation needs organized with an SCI problem list promotes collaboration by the interdisciplinary team, caregivers, and family in efficient achievement of patient-centered goals and completion of daily care plans. Published by Elsevier Inc.
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Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook 2008-2013
NASA Astrophysics Data System (ADS)
Stroeve, Julienne; Hamilton, Lawrence C.; Bitz, Cecilia M.; Blanchard-Wrigglesworth, Edward
2014-04-01
Since 2008, the Study of Environmental Arctic Change Sea Ice Outlook has solicited predictions of September sea-ice extent from the Arctic research community. Individuals and teams employ a variety of modeling, statistical, and heuristic approaches to make these predictions. Viewed as monthly ensembles each with one or two dozen individual predictions, they display a bimodal pattern of success. In years when observed ice extent is near its trend, the median predictions tend to be accurate. In years when the observed extent is anomalous, the median and most individual predictions are less accurate. Statistical analysis suggests that year-to-year variability, rather than methods, dominate the variation in ensemble prediction success. Furthermore, ensemble predictions do not improve as the season evolves. We consider the role of initial ice, atmosphere and ocean conditions, and summer storms and weather in contributing to the challenge of sea-ice prediction.
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Changing the approach to treatment choice in epilepsy using big data.
Devinsky, Orrin; Dilley, Cynthia; Ozery-Flato, Michal; Aharonov, Ranit; Goldschmidt, Ya'ara; Rosen-Zvi, Michal; Clark, Chris; Fritz, Patty
2016-03-01
A UCB-IBM collaboration explored the application of machine learning to large claims databases to construct an algorithm for antiepileptic drug (AED) choice for individual patients. Claims data were collected between January 2006 and September 2011 for patients with epilepsy > 16 years of age. A subset of patient claims with a valid index date of AED treatment change (new, add, or switch) were used to train the AED prediction model by retrospectively evaluating an index date treatment for subsequent treatment change. Based on the trained model, a model-predicted AED regimen with the lowest likelihood of treatment change was assigned to each patient in the group of test claims, and outcomes were evaluated to test model validity. The model had 72% area under receiver operator characteristic curve, indicating good predictive power. Patients who were given the model-predicted AED regimen had significantly longer survival rates (time until a treatment change event) and lower expected health resource utilization on average than those who received another treatment. The actual prescribed AED regimen at the index date matched the model-predicted AED regimen in only 13% of cases; there were large discrepancies in the frequency of use of certain AEDs/combinations between model-predicted AED regimens and those actually prescribed. Chances of treatment success were improved if patients received the model-predicted treatment. Using the model's prediction system may enable personalized, evidence-based epilepsy care, accelerating the match between patients and their ideal therapy, thereby delivering significantly better health outcomes for patients and providing health-care savings by applying resources more efficiently. Our goal will be to strengthen the predictive power of the model by integrating diverse data sets and potentially moving to prospective data collection. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.
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Baig, Sheharyar S; Strong, Mark; Rosser, Elisabeth; Taverner, Nicola V; Glew, Ruth; Miedzybrodzka, Zosia; Clarke, Angus; Craufurd, David; Quarrell, Oliver W
2016-10-01
Huntington's disease (HD) is a progressive neurodegenerative condition. At-risk individuals have accessed predictive testing via direct mutation testing since 1993. The UK Huntington's Prediction Consortium has collected anonymised data on UK predictive tests, annually, from 1993 to 2014: 9407 predictive tests were performed across 23 UK centres. Where gender was recorded, 4077 participants were male (44.3%) and 5122 were female (55.7%). The median age of participants was 37 years. The most common reason for predictive testing was to reduce uncertainty (70.5%). Of the 8441 predictive tests on individuals at 50% prior risk, 4629 (54.8%) were reported as mutation negative and 3790 (44.9%) were mutation positive, with 22 (0.3%) in the database being uninterpretable. Using a prevalence figure of 12.3 × 10(-5), the cumulative uptake of predictive testing in the 50% at-risk UK population from 1994 to 2014 was estimated at 17.4% (95% CI: 16.9-18.0%). We present the largest study conducted on predictive testing in HD. Our findings indicate that the vast majority of individuals at risk of HD (>80%) have not undergone predictive testing. Future therapies in HD will likely target presymptomatic individuals; therefore, identifying the at-risk population whose gene status is unknown is of significant public health value.
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Learning to Predict Combinatorial Structures
NASA Astrophysics Data System (ADS)
Vembu, Shankar
2009-12-01
The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions to ensure efficient, polynomial time estimation of model parameters. For several combinatorial structures, including cycles, partially ordered sets, permutations and other graph classes, these assumptions do not hold. In this thesis, we address the problem of designing learning algorithms for predicting combinatorial structures by introducing two new assumptions: (i) The first assumption is that a particular counting problem can be solved efficiently. The consequence is a generalisation of the classical ridge regression for structured prediction. (ii) The second assumption is that a particular sampling problem can be solved efficiently. The consequence is a new technique for designing and analysing probabilistic structured prediction models. These results can be applied to solve several complex learning problems including but not limited to multi-label classification, multi-category hierarchical classification, and label ranking.
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YEAR-TO-YEAR CHANGES IN LUNG FUNCTION IN INDIVIDUALS WITH CYSTIC FIBROSIS
Liou, Theodore G.; Elkin, Eric P.; Pasta, David J.; Jacobs, Joan R.; Konstan, Michael W.; Morgan, Wayne J.; Wagener, Jeffrey S.
2014-01-01
Background We examined the year-to-year change in FEV1 for individuals and the overall cystic fibrosis population to better understand how individual trends may differ from population trends. Methods We calculated individual yearly changes using the largest annual FEV1 percent predicted (FEV1%) measurement in 20,644 patients (6–45 years old) included in the Epidemiologic Study of Cystic Fibrosis. We calculated yearly population changes using age-specific medians. Results FEV1% predicted decreased 1–3 points per year for individuals, with maximal decreases in 14–15 year olds. Population changes agreed with individual changes up to age 15; however after age 30, yearly population change approximated zero while individual FEV1% predicted decreases were 1–2 points per year. Conclusions Adolescents have the greatest FEV1% predicted decreases; however. loss of FEV1 is a persistent risk in 6–45 year old CF patients. Recognizing individual year-to-year changes may improve patient-specific care and may suggest new methods for measuring program quality. PMID:20471331
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Exploring Cognitive Relations Between Prediction in Language and Music.
Patel, Aniruddh D; Morgan, Emily
2017-03-01
The online processing of both music and language involves making predictions about upcoming material, but the relationship between prediction in these two domains is not well understood. Electrophysiological methods for studying individual differences in prediction in language processing have opened the door to new questions. Specifically, we ask whether individuals with musical training predict upcoming linguistic material more strongly and/or more accurately than non-musicians. We propose two reasons why prediction in these two domains might be linked: (a) Musicians may have greater verbal short-term/working memory; (b) music may specifically reward predictions based on hierarchical structure. We provide suggestions as to how to expand upon recent work on individual differences in language processing to test these hypotheses. Copyright © 2016 Cognitive Science Society, Inc.
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Individualized prediction of lung-function decline in chronic obstructive pulmonary disease
Zafari, Zafar; Sin, Don D.; Postma, Dirkje S.; Löfdahl, Claes-Göran; Vonk, Judith; Bryan, Stirling; Lam, Stephen; Tammemagi, C. Martin; Khakban, Rahman; Man, S.F. Paul; Tashkin, Donald; Wise, Robert A.; Connett, John E.; McManus, Bruce; Ng, Raymond; Hollander, Zsuszanna; Sadatsafavi, Mohsen
2016-01-01
Background: The rate of lung-function decline in chronic obstructive pulmonary disease (COPD) varies substantially among individuals. We sought to develop and validate an individualized prediction model for forced expiratory volume at 1 second (FEV1) in current smokers with mild-to-moderate COPD. Methods: Using data from a large long-term clinical trial (the Lung Health Study), we derived mixed-effects regression models to predict future FEV1 values over 11 years according to clinical traits. We modelled heterogeneity by allowing regression coefficients to vary across individuals. Two independent cohorts with COPD were used for validating the equations. Results: We used data from 5594 patients (mean age 48.4 yr, 63% men, mean baseline FEV1 2.75 L) to create the individualized prediction equations. There was significant between-individual variability in the rate of FEV1 decline, with the interval for the annual rate of decline that contained 95% of individuals being −124 to −15 mL/yr for smokers and −83 to 15 mL/yr for sustained quitters. Clinical variables in the final model explained 88% of variation around follow-up FEV1. The C statistic for predicting severity grades was 0.90. Prediction equations performed robustly in the 2 external data sets. Interpretation: A substantial part of individual variation in FEV1 decline can be explained by easily measured clinical variables. The model developed in this work can be used for prediction of future lung health in patients with mild-to-moderate COPD. Trial registration: Lung Health Study — ClinicalTrials.gov, no. NCT00000568; Pan-Canadian Early Detection of Lung Cancer Study — ClinicalTrials.gov, no. NCT00751660 PMID:27486205
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de Oliveira, Saulo H P; Law, Eleanor C; Shi, Jiye; Deane, Charlotte M
2018-04-01
Most current de novo structure prediction methods randomly sample protein conformations and thus require large amounts of computational resource. Here, we consider a sequential sampling strategy, building on ideas from recent experimental work which shows that many proteins fold cotranslationally. We have investigated whether a pseudo-greedy search approach, which begins sequentially from one of the termini, can improve the performance and accuracy of de novo protein structure prediction. We observed that our sequential approach converges when fewer than 20 000 decoys have been produced, fewer than commonly expected. Using our software, SAINT2, we also compared the run time and quality of models produced in a sequential fashion against a standard, non-sequential approach. Sequential prediction produces an individual decoy 1.5-2.5 times faster than non-sequential prediction. When considering the quality of the best model, sequential prediction led to a better model being produced for 31 out of 41 soluble protein validation cases and for 18 out of 24 transmembrane protein cases. Correct models (TM-Score > 0.5) were produced for 29 of these cases by the sequential mode and for only 22 by the non-sequential mode. Our comparison reveals that a sequential search strategy can be used to drastically reduce computational time of de novo protein structure prediction and improve accuracy. Data are available for download from: http://opig.stats.ox.ac.uk/resources. SAINT2 is available for download from: https://github.com/sauloho/SAINT2. saulo.deoliveira@dtc.ox.ac.uk. Supplementary data are available at Bioinformatics online.
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Blot, Stijn I; Pea, Federico; Lipman, Jeffrey
2014-11-20
Critically ill patients are at high risk for development of life-threatening infection leading to sepsis and multiple organ failure. Adequate antimicrobial therapy is pivotal for optimizing the chances of survival. However, efficient dosing is problematic because pathophysiological changes associated with critical illness impact on pharmacokinetics of mainly hydrophilic antimicrobials. Concentrations of hydrophilic antimicrobials may be increased because of decreased renal clearance due to acute kidney injury. Alternatively, antimicrobial concentrations may be decreased because of increased volume of distribution and augmented renal clearance provoked by systemic inflammatory response syndrome, capillary leak, decreased protein binding and administration of intravenous fluids and inotropes. Often multiple conditions that may influence pharmacokinetics are present at the same time thereby excessively complicating the prediction of adequate concentrations. In general, conditions leading to underdosing are predominant. Yet, since prediction of serum concentrations remains difficult, therapeutic drug monitoring for individual fine-tuning of antimicrobial therapy seems the way forward. Copyright © 2014. Published by Elsevier B.V.
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Nonthermal X-ray emission from winds of OB supergiants
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, W.; White, R.L.
1991-01-01
The mechanisms responsible for the hard X-ray emission of OB supergiants (OBSGs) are investigated theoretically, modifying the periodic-shock model of Lucy (1982). The physical processes discussed include (1) the particle acceleration (PA) mechanism and its effect on the structure of individual shocks, (2) the energy cutoff and spectral index of the relativistic electrons and ions, and (3) the efficiency of PA by shocks and its implications for the number densities of relativistic particles. The model is used to predict the spectrum and intensity of the dominant nonthermal X-ray emission source from OBSGs, and the results are shown to be inmore » good agreement with Einstein Observatory Solid-State Spectrometer observations of three OBSGs in Orion (Cassinelli and Swank, 1983). It is inferred that the surface magnetic fields of OBSGs are no greater than a few G, and that the PA rates are significantly lower than generally predicted for collisionless astrophysical shocks. 66 refs.« less
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Road landslide information management and forecasting system base on GIS.
Wang, Wei Dong; Du, Xiang Gang; Xie, Cui Ming
2009-09-01
Take account of the characters of road geological hazard and its supervision, it is very important to develop the Road Landslides Information Management and Forecasting System based on Geographic Information System (GIS). The paper presents the system objective, function, component modules and key techniques in the procedure of system development. The system, based on the spatial information and attribute information of road geological hazard, was developed and applied in Guizhou, a province of China where there are numerous and typical landslides. The manager of communication, using the system, can visually inquire all road landslides information based on regional road network or on the monitoring network of individual landslide. Furthermore, the system, integrated with mathematical prediction models and the GIS's strongpoint on spatial analyzing, can assess and predict landslide developing procedure according to the field monitoring data. Thus, it can efficiently assists the road construction or management units in making decision to control the landslides and to reduce human vulnerability.
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Do institutional logics predict interpretation of contract rules at the dental chair-side?
Harris, Rebecca; Brown, Stephen; Holt, Robin; Perkins, Elizabeth
2014-12-01
In quasi-markets, contracts find purchasers influencing health care providers, although problems exist where providers use personal bias and heuristics to respond to written agreements, tending towards the moral hazard of opportunism. Previous research on quasi-market contracts typically understands opportunism as fully rational, individual responses selecting maximally efficient outcomes from a set of possibilities. We take a more emotive and collective view of contracting, exploring the influence of institutional logics in relation to the opportunistic behaviour of dentists. Following earlier qualitative work where we identified four institutional logics in English general dental practice, and six dental contract areas where there was scope for opportunism; in 2013 we surveyed 924 dentists to investigate these logics and whether they had predictive purchase over dentists' chair-side behaviour. Factor analysis involving 300 responses identified four logics entwined in (often technical) behaviour: entrepreneurial commercialism, duty to staff and patients, managerialism, public good. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.
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Hypertension and blood pressure awareness among American Indians of the northern plains.
Sharlin, K S; Heath, G W; Ford, E S; Welty, T K
1993-01-01
This study compared self-reported and measured blood pressure among American Indians of the northern plains. In 1986, a group of American Indians from the northern plains was administered the Centers for Disease Control Behavioral Risk Factor Survey (which included a question about previous blood pressure measurements) and a health risk appraisal (which included blood pressure measurement). Approximately 18% of the respondents reported being told by a doctor, nurse, or other health professional that they had high blood pressure, and 11% actually had measured blood pressures of at least 140/90 mm Hg. Overall, only 50% of hypertensive participants correctly identified themselves as hypertensive (sensitivity); specificity was 92%, predictive value positive was 43%, predictive value negative was 94%, and efficiency (the proportion of individuals who correctly classified their blood pressure status as high or normal) was 87%. These findings agree with similar studies of hypertension awareness, and they indicate that lack of this awareness remains a significant problem in the fight against cardiovascular diseases and premature death among American Indians.
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Self-rated imagery and encoding strategies in visual memory.
Berger, G H; Gaunitz, S C
1979-02-01
The value of self-rated vividness of imagery in predicting performance was investigated, taking into account the mnemonic strategies utilized among subjects performing a visual-memory task. Subjects classified as 'good' or 'poor' imagers, according to their scores in the Vividness of Visual Imagery Questionnaire (VVIQ; Marks, 1972), were to detect as rapidly as possible differences between pairs of similar pictures presented consecutively. No coding instructions were given and the mnemonic strategies used were analysed by studying subjective reports and objective performance measurements. The results indicated that the subjects utilized two main strategies--a detail or an image strategy. The detail strategy was the more efficient. In accordance with a previous study (Berger & Gaunitz, 1977), it was found that the VVIQ did not discriminate between performance by 'good' and 'poor' imagers. However, among subjects who used the image strategy, 'good' imagers performed more rapidly than 'poor' imagers. Self-rated imagery may then have some value in predicting performance among individuals shown to have utilized an image strategy.
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Predictive value and efficiency of laboratory testing.
Galen, R S
1980-11-01
Literature on determining reference values and reference intervals on "normal" or "healthy" individuals is abundant. It is impossible, however, to evaluate a data set of reference values and select a suitable reference interval that will be meaningful for the practice of medicine. The reference interval, no matter how derived statistically, tells us nothing about disease. This is the main reason the concepts of "normal values" have failed us and why "reference values" will prove similarly disappointing. By studying these same constituents in a variety of disease states as well, it will be possible to select "referent values" that will make the test procedure meaningful for diagnostic purposes. In order to obtain meaningful referent values for predicting disease, it is necessary to study not only the "healthy" reference population, but patients with the disease in question, and patients who are free of the disease in question but who have other diseases. Studies of this type are not frequently found for laboratory tests that are in common use today.
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Dong, Yuwen; Deshpande, Sunil; Rivera, Daniel E; Downs, Danielle S; Savage, Jennifer S
2014-06-01
Control engineering offers a systematic and efficient method to optimize the effectiveness of individually tailored treatment and prevention policies known as adaptive or "just-in-time" behavioral interventions. The nature of these interventions requires assigning dosages at categorical levels, which has been addressed in prior work using Mixed Logical Dynamical (MLD)-based hybrid model predictive control (HMPC) schemes. However, certain requirements of adaptive behavioral interventions that involve sequential decision making have not been comprehensively explored in the literature. This paper presents an extension of the traditional MLD framework for HMPC by representing the requirements of sequential decision policies as mixed-integer linear constraints. This is accomplished with user-specified dosage sequence tables, manipulation of one input at a time, and a switching time strategy for assigning dosages at time intervals less frequent than the measurement sampling interval. A model developed for a gestational weight gain (GWG) intervention is used to illustrate the generation of these sequential decision policies and their effectiveness for implementing adaptive behavioral interventions involving multiple components.
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Predicting successful tactile mapping of virtual objects.
Brayda, Luca; Campus, Claudio; Gori, Monica
2013-01-01
Improving spatial ability of blind and visually impaired people is the main target of orientation and mobility (O&M) programs. In this study, we use a minimalistic mouse-shaped haptic device to show a new approach aimed at evaluating devices providing tactile representations of virtual objects. We consider psychophysical, behavioral, and subjective parameters to clarify under which circumstances mental representations of spaces (cognitive maps) can be efficiently constructed with touch by blindfolded sighted subjects. We study two complementary processes that determine map construction: low-level perception (in a passive stimulation task) and high-level information integration (in an active exploration task). We show that jointly considering a behavioral measure of information acquisition and a subjective measure of cognitive load can give an accurate prediction and a practical interpretation of mapping performance. Our simple TActile MOuse (TAMO) uses haptics to assess spatial ability: this may help individuals who are blind or visually impaired to be better evaluated by O&M practitioners or to evaluate their own performance.
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Grecian, W James; Lane, Jude V; Michelot, Théo; Wade, Helen M; Hamer, Keith C
2018-06-01
The development of foraging strategies that enable juveniles to efficiently identify and exploit predictable habitat features is critical for survival and long-term fitness. In the marine environment, meso- and sub-mesoscale features such as oceanographic fronts offer a visible cue to enhanced foraging conditions, but how individuals learn to identify these features is a mystery. In this study, we investigate age-related differences in the fine-scale foraging behaviour of adult (aged ≥ 5 years) and immature (aged 2-4 years) northern gannets Morus bassanus Using high-resolution GPS-loggers, we reveal that adults have a much narrower foraging distribution than immature birds and much higher individual foraging site fidelity. By conditioning the transition probabilities of a hidden Markov model on satellite-derived measures of frontal activity, we then demonstrate that adults show a stronger response to frontal activity than immature birds, and are more likely to commence foraging behaviour as frontal intensity increases. Together, these results indicate that adult gannets are more proficient foragers than immatures, supporting the hypothesis that foraging specializations are learned during individual exploratory behaviour in early life. Such memory-based individual foraging strategies may also explain the extended period of immaturity observed in gannets and many other long-lived species. © 2018 The Authors.
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Opposing effects of allogrooming on disease transmission in ant societies
Theis, Fabian J.; Ugelvig, Line V.; Marr, Carsten; Cremer, Sylvia
2015-01-01
To prevent epidemics, insect societies have evolved collective disease defences that are highly effective at curing exposed individuals and limiting disease transmission to healthy group members. Grooming is an important sanitary behaviour—either performed towards oneself (self-grooming) or towards others (allogrooming)—to remove infectious agents from the body surface of exposed individuals, but at the risk of disease contraction by the groomer. We use garden ants (Lasius neglectus) and the fungal pathogen Metarhizium as a model system to study how pathogen presence affects self-grooming and allogrooming between exposed and healthy individuals. We develop an epidemiological SIS model to explore how experimentally observed grooming patterns affect disease spread within the colony, thereby providing a direct link between the expression and direction of sanitary behaviours, and their effects on colony-level epidemiology. We find that fungus-exposed ants increase self-grooming, while simultaneously decreasing allogrooming. This behavioural modulation seems universally adaptive and is predicted to contain disease spread in a great variety of host–pathogen systems. In contrast, allogrooming directed towards pathogen-exposed individuals might both increase and decrease disease risk. Our model reveals that the effect of allogrooming depends on the balance between pathogen infectiousness and efficiency of social host defences, which are likely to vary across host–pathogen systems. PMID:25870394
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Genetics of alternative definitions of feed efficiency in grazing lactating dairy cows.
Hurley, A M; López-Villalobos, N; McParland, S; Lewis, E; Kennedy, E; O'Donovan, M; Burke, J L; Berry, D P
2017-07-01
The objective of the present study was to estimate genetic parameters across lactation for measures of energy balance (EB) and a range of feed efficiency variables as well as to quantify the genetic inter-relationships between them. Net energy intake (NEI) from pasture and concentrate intake was estimated up to 8 times per lactation for 2,481 lactations from 1,274 Holstein-Friesian cows. A total of 8,134 individual feed intake measurements were used. Efficiency traits were either ratio based or residual based; the latter were derived from least squares regression models. Residual energy intake (REI) was defined as NEI minus predicted energy requirements [e.g., net energy of lactation (NE L ), maintenance, and body tissue anabolism] or supplied from body tissue mobilization; residual energy production was defined as the difference between actual NE L and predicted NE L based on NEI, maintenance, and body tissue anabolism/catabolism. Energy conversion efficiency was defined as NE L divided by NEI. Random regression animal models were used to estimate residual, additive genetic, and permanent environmental (co)variances across lactation. Heritability across lactation stages varied from 0.03 to 0.36 for all efficiency traits. Within-trait genetic correlations tended to weaken as the interval between lactation stages compared lengthened for EB, REI, residual energy production, and NEI. Analysis of eigenvalues and associated eigenfunctions for EB and the efficiency traits indicate the ability to genetically alter the profile of these lactation curves to potentially improve dairy cow efficiency differently at different stages of lactation. Residual energy intake and EB were moderately to strongly genetically correlated with each other across lactation (genetic correlations ranged from 0.45 to 0.90), indicating that selection for lower REI alone (i.e., deemed efficient cows) would favor cows with a compromised energy status; nevertheless, selection for REI within a holistic breeding goal could be used to overcome such antagonisms. The smallest (8.90% of genetic variance) and middle (11.22% of genetic variance) eigenfunctions for REI changed sign during lactation, indicating the potential to alter the shape of the REI lactation profile. Results from the present study suggest exploitable genetic variation exists for a range of efficiency traits, and the magnitude of this variation is sufficiently large to justify consideration of the feed efficiency complex in future dairy breeding goals. Moreover, it is possible to alter the trajectories of the efficiency traits to suit a particular breeding objective, although this relies on very precise across-parity genetic parameter estimates, including genetic correlations with health and fertility traits (as well as other traits). Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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Taylor, Samuel H; Long, Stephen P
2017-09-26
Wheat is the second most important direct source of food calories in the world. After considerable improvement during the Green Revolution, increase in genetic yield potential appears to have stalled. Improvement of photosynthetic efficiency now appears a major opportunity in addressing the sustainable yield increases needed to meet future food demand. Effort, however, has focused on increasing efficiency under steady-state conditions. In the field, the light environment at the level of individual leaves is constantly changing. The speed of adjustment of photosynthetic efficiency can have a profound effect on crop carbon gain and yield. Flag leaves of wheat are the major photosynthetic organs supplying the grain of wheat, and will be intermittently shaded throughout a typical day. Here, the speed of adjustment to a shade to sun transition in these leaves was analysed. On transfer to sun conditions, the leaf required about 15 min to regain maximum photosynthetic efficiency. In vivo analysis based on the responses of leaf CO 2 assimilation ( A ) to intercellular CO 2 concentration ( c i ) implied that the major limitation throughout this induction was activation of the primary carboxylase of C3 photosynthesis, ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco). This was followed in importance by stomata, which accounted for about 20% of the limitation. Except during the first few seconds, photosynthetic electron transport and regeneration of the CO 2 acceptor molecule, ribulose-1,5-bisphosphate (RubP), did not affect the speed of induction. The measured kinetics of Rubisco activation in the sun and de-activation in the shade were predicted from the measurements. These were combined with a canopy ray tracing model that predicted intermittent shading of flag leaves over the course of a June day. This indicated that the slow adjustment in shade to sun transitions could cost 21% of potential assimilation.This article is part of the themed issue 'Enhancing photosynthesis in crop plants: targets for improvement'. © 2017 The Authors.
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Kollmeier, Birger; Schädler, Marc René; Warzybok, Anna; Meyer, Bernd T; Brand, Thomas
2016-09-07
To characterize the individual patient's hearing impairment as obtained with the matrix sentence recognition test, a simulation Framework for Auditory Discrimination Experiments (FADE) is extended here using the Attenuation and Distortion (A+D) approach by Plomp as a blueprint for setting the individual processing parameters. FADE has been shown to predict the outcome of both speech recognition tests and psychoacoustic experiments based on simulations using an automatic speech recognition system requiring only few assumptions. It builds on the closed-set matrix sentence recognition test which is advantageous for testing individual speech recognition in a way comparable across languages. Individual predictions of speech recognition thresholds in stationary and in fluctuating noise were derived using the audiogram and an estimate of the internal level uncertainty for modeling the individual Plomp curves fitted to the data with the Attenuation (A-) and Distortion (D-) parameters of the Plomp approach. The "typical" audiogram shapes from Bisgaard et al with or without a "typical" level uncertainty and the individual data were used for individual predictions. As a result, the individualization of the level uncertainty was found to be more important than the exact shape of the individual audiogram to accurately model the outcome of the German Matrix test in stationary or fluctuating noise for listeners with hearing impairment. The prediction accuracy of the individualized approach also outperforms the (modified) Speech Intelligibility Index approach which is based on the individual threshold data only. © The Author(s) 2016.
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Zhang, Lei; Zhang, Jing
2017-08-07
A Smart Grid (SG) facilitates bidirectional demand-response communication between individual users and power providers with high computation and communication performance but also brings about the risk of leaking users' private information. Therefore, improving the individual power requirement and distribution efficiency to ensure communication reliability while preserving user privacy is a new challenge for SG. Based on this issue, we propose an efficient and privacy-preserving power requirement and distribution aggregation scheme (EPPRD) based on a hierarchical communication architecture. In the proposed scheme, an efficient encryption and authentication mechanism is proposed for better fit to each individual demand-response situation. Through extensive analysis and experiment, we demonstrate how the EPPRD resists various security threats and preserves user privacy while satisfying the individual requirement in a semi-honest model; it involves less communication overhead and computation time than the existing competing schemes.
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Zhang, Lei; Zhang, Jing
2017-01-01
A Smart Grid (SG) facilitates bidirectional demand-response communication between individual users and power providers with high computation and communication performance but also brings about the risk of leaking users’ private information. Therefore, improving the individual power requirement and distribution efficiency to ensure communication reliability while preserving user privacy is a new challenge for SG. Based on this issue, we propose an efficient and privacy-preserving power requirement and distribution aggregation scheme (EPPRD) based on a hierarchical communication architecture. In the proposed scheme, an efficient encryption and authentication mechanism is proposed for better fit to each individual demand-response situation. Through extensive analysis and experiment, we demonstrate how the EPPRD resists various security threats and preserves user privacy while satisfying the individual requirement in a semi-honest model; it involves less communication overhead and computation time than the existing competing schemes. PMID:28783122
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Cross-validation of recent and longstanding resting metabolic rate prediction equations
USDA-ARS?s Scientific Manuscript database
Resting metabolic rate (RMR) measurement is time consuming and requires specialized equipment. Prediction equations provide an easy method to estimate RMR; however, their accuracy likely varies across individuals. Understanding the factors that influence predicted RMR accuracy at the individual lev...
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Buzdin, Anton; Sorokin, Maxim; Garazha, Andrew; Sekacheva, Marina; Kim, Ella; Zhukov, Nikolay; Wang, Ye; Li, Xinmin; Kar, Souvik; Hartmann, Christian; Samii, Amir; Giese, Alf; Borisov, Nicolas
2018-06-20
Anticancer target drugs (ATDs) specifically bind and inhibit molecular targets that play important roles in cancer development and progression, being deeply implicated in intracellular signaling pathways. To date, hundreds of different ATDs were approved for clinical use in the different countries. Compared to previous chemotherapy treatments, ATDs often demonstrate reduced side effects and increased efficiency, but also have higher costs. However, the efficiency of ATDs for the advanced stage tumors is still insufficient. Different ATDs have different mechanisms of action and are effective in different cohorts of patients. Personalized approaches are therefore needed to select the best ATD candidates for the individual patients. In this review, we focus on a new generation of biomarkers - molecular pathway activation - and on their applications for predicting individual tumor response to ATDs. The success in high throughput gene expression profiling and emergence of novel bioinformatic tools reinforced quick development of pathway related field of molecular biomedicine. The ability to quantitatively measure degree of a pathway activation using gene expression data has revolutionized this field and made the corresponding analysis quick, robust and inexpensive. This success was further enhanced by using machine learning algorithms for selection of the best biomarkers. We review here the current progress in translating these studies to clinical oncology and patient-oriented adjustment of cancer therapy. Copyright © 2018. Published by Elsevier Ltd.
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Schwanz, Lisa; Warner, Daniel A; McGaugh, Suzanne; Di Terlizzi, Roberta; Bronikowski, Anne
2011-01-01
Energy allocation among somatic maintenance, reproduction and growth varies not only among species, but among individuals according to states such as age, sex and season. Little research has been conducted on the somatic (physiological) maintenance of long-lived organisms, particularly ectotherms such as reptiles. In this study, we examined sex differences and age- and season-related variation in immune function and DNA repair efficiency in a long-lived reptile, the painted turtle (Chrysemys picta). Immune components tended to be depressed during hibernation, in winter, compared with autumn or spring. Increased heterophil count during hibernation provided the only support for winter immunoenhancement. In juvenile and adult turtles, we found little evidence for senescence in physiological maintenance, consistent with predictions for long-lived organisms. Among immune components, swelling in response to phytohemagglutinin (PHA) and control injection increased with age, whereas basophil count decreased with age. Hatchling turtles had reduced basophil counts and natural antibodies, indicative of an immature immune system, but demonstrated higher DNA repair efficiency than older turtles. Reproductively mature turtles had reduced lymphocytes compared with juvenile turtles in the spring, presumably driven by a trade-off between maintenance and reproduction. Sex had little influence on physiological maintenance. These results suggest that components of physiological maintenance are modulated differentially according to individual state and highlight the need for more research on the multiple components of physiological maintenance in animals of variable states.
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Teeguarden, Justin. G.; Tan, Yu-Mei; Edwards, Stephen W.; Leonard, Jeremy A.; Anderson, Kim A.; Corley, Richard A.; Harding, Anna K; Kile, Molly L.; Simonich, Staci M; Stone, David; Tanguay, Robert L.; Waters, Katrina M.; Harper, Stacey L.; Williams, David E.
2016-01-01
Synopsis Driven by major scientific advances in analytical methods, biomonitoring, computational tools, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the “systems approaches” used in the biological sciences is a necessary step in this evolution. Here we propose the Aggregate Exposure Pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the Adverse Outcome Pathway (AOP) concept in the toxicological sciences. Aggregate exposure pathways offer an intuitive framework to organize exposure data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathways and adverse outcome pathways, completing the source to outcome continuum for more efficient integration of exposure assessment and hazard identification. Together, the two pathways form and inform a decision-making framework with the flexibility for risk-based, hazard-based, or exposure-based decision making. PMID:26759916
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Does probability guided hysteroscopy reduce costs in women investigated for postmenopausal bleeding?
Breijer, M C; van Hanegem, N; Visser, N C M; Verheijen, R H M; Mol, B W J; Pijnenborg, J M A; Opmeer, B C; Timmermans, A
2015-01-01
To evaluate whether a model to predict a failed endometrial biopsy in women with postmenopausal bleeding (PMB) and a thickened endometrium can reduce costs without compromising diagnostic accuracy. Model based cost-minimization analysis. A decision analytic model was designed to compare two diagnostic strategies for women with PMB: (I) attempting office endometrial biopsy and performing outpatient hysteroscopy after failed biopsy and (II) predicted probability of a failed endometrial biopsy based on patient characteristics to guide the decision for endometrial biopsy or immediate hysteroscopy. Robustness of assumptions regarding costs was evaluated in sensitivity analyses. Costs for the different strategies. At different cut-offs for the predicted probability of failure of an endometrial biopsy, strategy I was generally less expensive than strategy II. The costs for strategy I were always € 460; the costs for strategy II varied between € 457 and € 475. At a 65% cut-off, a possible saving of € 3 per woman could be achieved. Individualizing the decision to perform an endometrial biopsy or immediate hysteroscopy in women presenting with postmenopausal bleeding based on patient characteristics does not increase the efficiency of the diagnostic work-up.
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A nucleobase-centered coarse-grained representation for structure prediction of RNA motifs
Poblete, Simón; Bottaro, Sandro; Bussi, Giovanni
2018-01-01
Abstract We introduce the SPlit-and-conQueR (SPQR) model, a coarse-grained (CG) representation of RNA designed for structure prediction and refinement. In our approach, the representation of a nucleotide consists of a point particle for the phosphate group and an anisotropic particle for the nucleoside. The interactions are, in principle, knowledge-based potentials inspired by the \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$\\mathcal {E}$\\end{document}SCORE function, a base-centered scoring function. However, a special treatment is given to base-pairing interactions and certain geometrical conformations which are lost in a raw knowledge-based model. This results in a representation able to describe planar canonical and non-canonical base pairs and base–phosphate interactions and to distinguish sugar puckers and glycosidic torsion conformations. The model is applied to the folding of several structures, including duplexes with internal loops of non-canonical base pairs, tetraloops, junctions and a pseudoknot. For the majority of these systems, experimental structures are correctly predicted at the level of individual contacts. We also propose a method for efficiently reintroducing atomistic detail from the CG representation. PMID:29272539
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Lin, Lung-Chang; Chen, Sharon Chia-Ju; Chiang, Ching-Tai; Wu, Hui-Chuan; Yang, Rei-Cheng; Ouyang, Chen-Sen
2017-03-01
The life quality of patients with refractory epilepsy is extremely affected by abrupt and unpredictable seizures. A reliable method for predicting seizures is important in the management of refractory epilepsy. A critical factor in seizure prediction involves the classification of the preictal and interictal stages. This study aimed to develop an efficient, automatic, quantitative, and individualized approach for preictal/interictal stage identification. Five epileptic children, who had experienced at least 2 episodes of seizures during a 24-hour video EEG recording, were included. Artifact-free preictal and interictal EEG epochs were acquired, respectively, and characterized with 216 global feature descriptors. The best subset of 5 discriminative descriptors was identified. The best subsets showed differences among the patients. Statistical analysis revealed most of the 5 descriptors in each subset were significantly different between the preictal and interictal stages for each patient. The proposed approach yielded weighted averages of 97.50% correctness, 96.92% sensitivity, 97.78% specificity, and 95.45% precision on classifying test epochs. Although the case number was limited, this study successfully integrated a new EEG analytical method to classify preictal and interictal EEG segments and might be used further in predicting the occurrence of seizures.
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Multicomponent model of deformation and detachment of a biofilm under fluid flow
Tierra, Giordano; Pavissich, Juan P.; Nerenberg, Robert; Xu, Zhiliang; Alber, Mark S.
2015-01-01
A novel biofilm model is described which systemically couples bacteria, extracellular polymeric substances (EPS) and solvent phases in biofilm. This enables the study of contributions of rheology of individual phases to deformation of biofilm in response to fluid flow as well as interactions between different phases. The model, which is based on first and second laws of thermodynamics, is derived using an energetic variational approach and phase-field method. Phase-field coupling is used to model structural changes of a biofilm. A newly developed unconditionally energy-stable numerical splitting scheme is implemented for computing the numerical solution of the model efficiently. Model simulations predict biofilm cohesive failure for the flow velocity between and m s−1 which is consistent with experiments. Simulations predict biofilm deformation resulting in the formation of streamers for EPS exhibiting a viscous-dominated mechanical response and the viscosity of EPS being less than . Higher EPS viscosity provides biofilm with greater resistance to deformation and to removal by the flow. Moreover, simulations show that higher EPS elasticity yields the formation of streamers with complex geometries that are more prone to detachment. These model predictions are shown to be in qualitative agreement with experimental observations. PMID:25808342
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Workman, Megan; Baker, Jack; Lancaster, Jane B; Mermier, Christine; Alcock, Joe
2016-07-01
Aiming to test the evolutionary significance of relationships linking prenatal growth conditions to adult phenotypes, this study examined whether birth size predicts energetic savings during fasting. We specifically tested a Predictive Adaptive Response (PAR) model that predicts greater energetic saving among adults who were born small. Data were collected from a convenience sample of young adults living in Albuquerque, NM (n = 34). Indirect calorimetry quantified changes in resting energy expenditure (REE) and active muscular efficiency that occurred in response to a 29-h fast. Multiple regression analyses linked birth weight to baseline and postfast metabolic values while controlling for appropriate confounders (e.g., sex, body mass). Birth weight did not moderate the relationship between body size and energy expenditure, nor did it predict the magnitude change in REE or muscular efficiency observed from baseline to after fasting. Alternative indicators of birth size were also examined (e.g., low v. normal birth weight, comparison of tertiles), with no effects found. However, baseline muscular efficiency improved by 1.1% per 725 g (S.D.) increase in birth weight (P = 0.037). Birth size did not influence the sensitivity of metabolic demands to fasting-neither at rest nor during activity. Moreover, small birth size predicted a reduction in the efficiency with which muscles convert energy expended into work accomplished. These results do not support the ascription of adaptive function to phenotypes associated with small birth size. © 2015 Wiley Periodicals, Inc. Am. J. Hum. Biol. 28:484-492, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
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Can nutrient status of four woody plant species be predicted using field spectrometry?
NASA Astrophysics Data System (ADS)
Ferwerda, Jelle G.; Skidmore, Andrew K.
This paper demonstrates the potential of hyperspectral remote sensing to predict the chemical composition (i.e., nitrogen, phosphorous, calcium, potassium, sodium, and magnesium) of three tree species (i.e., willow, mopane and olive) and one shrub species (i.e., heather). Reflectance spectra, derivative spectra and continuum-removed spectra were compared in terms of predictive power. Results showed that the best predictions for nitrogen, phosphorous, and magnesium occur when using derivative spectra, and the best predictions for sodium, potassium, and calcium occur when using continuum-removed data. To test whether a general model for multiple species is also valid for individual species, a bootstrapping routine was applied. Prediction accuracies for the individual species were lower then prediction accuracies obtained for the combined dataset for all except one element/species combination, indicating that indices with high prediction accuracies at the landscape scale are less appropriate to detect the chemical content of individual species.
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Improved Genetic Profiling of Anthropometric Traits Using a Big Data Approach.
Canela-Xandri, Oriol; Rawlik, Konrad; Woolliams, John A; Tenesa, Albert
2016-01-01
Genome-wide association studies (GWAS) promised to translate their findings into clinically beneficial improvements of patient management by tailoring disease management to the individual through the prediction of disease risk. However, the ability to translate genetic findings from GWAS into predictive tools that are of clinical utility and which may inform clinical practice has, so far, been encouraging but limited. Here we propose to use a more powerful statistical approach, the use of which has traditionally been limited due to computational requirements and lack of sufficiently large individual level genotyped cohorts, but which improve the prediction of multiple medically relevant phenotypes using the same panel of SNPs. As a proof of principle, we used a shared panel of 319,038 common SNPs with MAF > 0.05 to train the prediction models in 114,264 unrelated White-British individuals for height and four obesity related traits (body mass index, basal metabolic rate, body fat percentage, and waist-to-hip ratio). We obtained prediction accuracies that ranged between 46% and 75% of the maximum achievable given the captured heritable component. For height, this represents an improvement in prediction accuracy of up to 68% (184% more phenotypic variance explained) over SNPs reported to be robustly associated with height in a previous GWAS meta-analysis of similar size. Across-population predictions in White non-British individuals were similar to those in White-British whilst those in Asian and Black individuals were informative but less accurate. We estimate that the genotyping of circa 500,000 unrelated individuals will yield predictions between 66% and 82% of the SNP-heritability captured by common variants in our array. Prediction accuracies did not improve when including rarer SNPs or when fitting multiple traits jointly in multivariate models.
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Division of labour and the evolution of extreme specialization.
Cooper, Guy A; West, Stuart A
2018-05-28
Division of labour is a common feature of social groups, from biofilms to complex animal societies. However, we lack a theoretical framework that can explain why division of labour has evolved on certain branches of the tree of life but not others. Here, we model the division of labour over a cooperative behaviour, considering both when it should evolve and the extent to which the different types should become specialized. We found that: (1) division of labour is usually-but not always-favoured by high efficiency benefits to specialization and low within-group conflict; and (2) natural selection favours extreme specialization, where some individuals are completely dependent on the helping behaviour of others. We make a number of predictions, several of which are supported by the existing empirical data, from microbes and animals, while others suggest novel directions for empirical work. More generally, we show how division of labour can lead to mutual dependence between different individuals and hence drive major evolutionary transitions, such as those to multicellularity and eusociality.
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Butkovskyi, Andrii; Bruning, Harry; Kools, Stefan A E; Rijnaarts, Huub H M; Van Wezel, Annemarie P
2017-05-02
Organic contaminants in shale gas flowback and produced water (FPW) are traditionally expressed as total organic carbon (TOC) or chemical oxygen demand (COD), though these parameters do not provide information on the toxicity and environmental fate of individual components. This review addresses identification of individual organic contaminants in FPW, and stresses the gaps in the knowledge on FPW composition that exist so far. Furthermore, the risk quotient approach was applied to predict the toxicity of the quantified organic compounds for fresh water organisms in recipient surface waters. This resulted in an identification of a number of FPW related organic compounds that are potentially harmful namely those compounds originating from shale formations (e.g., polycyclic aromatic hydrocarbons, phthalates), fracturing fluids (e.g., quaternary ammonium biocides, 2-butoxyethanol) and downhole transformations of organic compounds (e.g., carbon disulfide, halogenated organic compounds). Removal of these compounds by FPW treatment processes is reviewed and potential and efficient abatement strategies are defined.
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Population Viability Analysis of Riverine Fishes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bates, P.; Chandler, J.; Jager, H.I.
Many utilities face conflkts between two goals: cost-efficient hydropower generation and protecting riverine fishes. Research to develop ecological simulation tools that can evaluate alternative mitigation strategies in terms of their benefits to fish populations is vital to informed decision-making. In this paper, we describe our approach to population viability analysis of riverine fishes in general and Snake River white sturgeon in particular. We are finding that the individual-based modeling approach used in previous in-stream flow applications is well suited to addressing questions about the viability of species of concern for several reasons. Chief among these are: (1) the abiIity tomore » represent the effects of individual variation in life history characteristics on predicted population viabili~, (2) the flexibili~ needed to quanti~ the ecological benefits of alternative flow management options by representing spatial and temporal variation in flow and temperaturty and (3) the flexibility needed to quantifi the ecological benefits of non-flow related manipulations (i.e., passage, screening and hatchery supplementation).« less
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2017-01-01
Organic contaminants in shale gas flowback and produced water (FPW) are traditionally expressed as total organic carbon (TOC) or chemical oxygen demand (COD), though these parameters do not provide information on the toxicity and environmental fate of individual components. This review addresses identification of individual organic contaminants in FPW, and stresses the gaps in the knowledge on FPW composition that exist so far. Furthermore, the risk quotient approach was applied to predict the toxicity of the quantified organic compounds for fresh water organisms in recipient surface waters. This resulted in an identification of a number of FPW related organic compounds that are potentially harmful namely those compounds originating from shale formations (e.g., polycyclic aromatic hydrocarbons, phthalates), fracturing fluids (e.g., quaternary ammonium biocides, 2-butoxyethanol) and downhole transformations of organic compounds (e.g., carbon disulfide, halogenated organic compounds). Removal of these compounds by FPW treatment processes is reviewed and potential and efficient abatement strategies are defined. PMID:28376616
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FEENAUGHTY, LYNDA; TJADEN, KRIS; BENEDICT, RALPH H.B.; WEINSTOCK-GUTTMAN, BIANCA
2017-01-01
This preliminary study investigated how cognitive-linguistic status in multiple sclerosis (MS) is reflected in two speech tasks (i.e. oral reading, narrative) that differ in cognitive-linguistic demand. Twenty individuals with MS were selected to comprise High and Low performance groups based on clinical tests of executive function and information processing speed and efficiency. Ten healthy controls were included for comparison. Speech samples were audio-recorded and measures of global speech timing were obtained. Results indicated predicted differences in global speech timing (i.e. speech rate and pause characteristics) for speech tasks differing in cognitive-linguistic demand, but the magnitude of these task-related differences was similar for all speaker groups. Findings suggest that assumptions concerning the cognitive-linguistic demands of reading aloud as compared to spontaneous speech may need to be re-considered for individuals with cognitive impairment. Qualitative trends suggest that additional studies investigating the association between cognitive-linguistic and speech motor variables in MS are warranted. PMID:23294227
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Ethical issues raised by genetic testing with oligonucleotide microarrays.
Grody, Wayne W
2003-02-01
Because genes and alterations within them determine the identity, characteristics, and inheritance of every individual, the application of genetic science to humans has long been surrounded by apprehension, controversy, and real or perceived potential for abuse. Crude eugenics practices of the past now find a theoretical rebirth and transformation through the use of modern molecular genetic technologies for mutation detection, predictive and prenatal diagnosis, and, ultimately, gene replacement. The advent of oligonucleotide microarray analysis, in which hundreds or thousands of genes and mutations can be tested in parallel, offers tremendous promise for more accurate, sensitive, and efficient genetic testing. At the same time, however, this powerful technology dramatically increases the number and scope of ethical concerns accompanying each individual test request. This article considers the evolution and implications of these concerns, from the initial ordering of a microarray test by the physician to such issues as informed consent, privacy, confidentiality, clinical utility, discrimination, stigmatization, ethnic and population impact, and reimbursement.
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On the shape of the hospital industry long run average cost curve.
Finkler, S A
1979-01-01
Empirical studies of the hospital industry have produced conflicting results with respect to the shape of the industry's long run average cost (LRAC) curve. Some of the studies have found a classical U-shaped curve. Others have produced results indicating that the LRAC curve is much closer to being L-shaped. Some theoretical support exists for both sets of findings. While classical theory predicts that the LRAC curve will be U-shaped, Alchian has presented theoretical arguments explaining why such curves would be L-shaped. This paper reconciles the results of these studies. The basis for the reconciliation is recognition of the failure of individual hospitals to produce all their individual product lines at efficient volumes. Such inefficient production is feasible and perhaps common, given the incentive structure which exists under current cost reimbursement systems. The implication of this paper is that large hospitals may have a greater potential for scale economies than has previously been recognized. PMID:528221
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On the shape of the hospital industry long run average cost curve.
Finkler, S A
1979-01-01
Empirical studies of the hospital industry have produced conflicting results with respect to the shape of the industry's long run average cost (LRAC) curve. Some of the studies have found a classical U-shaped curve. Others have produced results indicating that the LRAC curve is much closer to being L-shaped. Some theoretical support exists for both sets of findings. While classical theory predicts that the LRAC curve will be U-shaped, Alchian has presented theoretical arguments explaining why such curves would be L-shaped. This paper reconciles the results of these studies. The basis for the reconciliation is recognition of the failure of individual hospitals to produce all their individual product lines at efficient volumes. Such inefficient production is feasible and perhaps common, given the incentive structure which exists under current cost reimbursement systems. The implication of this paper is that large hospitals may have a greater potential for scale economies than has previously been recognized.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Goodsman, Devin W.; Aukema, Brian H.; McDowell, Nate G.
Phenology models are becoming increasingly important tools to accurately predict how climate change will impact the life histories of organisms. We propose a class of integral projection phenology models derived from stochastic individual-based models of insect development and demography.Our derivation, which is based on the rate-summation concept, produces integral projection models that capture the effect of phenotypic rate variability on insect phenology, but which are typically more computationally frugal than equivalent individual-based phenology models. We demonstrate our approach using a temperature-dependent model of the demography of the mountain pine beetle (Dendroctonus ponderosae Hopkins), an insect that kills mature pine trees.more » This work illustrates how a wide range of stochastic phenology models can be reformulated as integral projection models. Due to their computational efficiency, these integral projection models are suitable for deployment in large-scale simulations, such as studies of altered pest distributions under climate change.« less
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Pictorial communication in virtual and real environments
NASA Technical Reports Server (NTRS)
Ellis, Stephen R. (Editor)
1991-01-01
Papers about the communication between human users and machines in real and synthetic environments are presented. Individual topics addressed include: pictorial communication, distortions in memory for visual displays, cartography and map displays, efficiency of graphical perception, volumetric visualization of 3D data, spatial displays to increase pilot situational awareness, teleoperation of land vehicles, computer graphics system for visualizing spacecraft in orbit, visual display aid for orbital maneuvering, multiaxis control in telemanipulation and vehicle guidance, visual enhancements in pick-and-place tasks, target axis effects under transformed visual-motor mappings, adapting to variable prismatic displacement. Also discussed are: spatial vision within egocentric and exocentric frames of reference, sensory conflict in motion sickness, interactions of form and orientation, perception of geometrical structure from congruence, prediction of three-dimensionality across continuous surfaces, effects of viewpoint in the virtual space of pictures, visual slant underestimation, spatial constraints of stereopsis in video displays, stereoscopic stance perception, paradoxical monocular stereopsis and perspective vergence. (No individual items are abstracted in this volume)
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Hernando, Barbara; Ibañez, Maria Victoria; Deserio-Cuesta, Julio Alberto; Soria-Navarro, Raquel; Vilar-Sastre, Inca; Martinez-Cadenas, Conrado
2018-03-01
Prediction of human pigmentation traits, one of the most differentiable externally visible characteristics among individuals, from biological samples represents a useful tool in the field of forensic DNA phenotyping. In spite of freckling being a relatively common pigmentation characteristic in Europeans, little is known about the genetic basis of this largely genetically determined phenotype in southern European populations. In this work, we explored the predictive capacity of eight freckle and sunlight sensitivity-related genes in 458 individuals (266 non-freckled controls and 192 freckled cases) from Spain. Four loci were associated with freckling (MC1R, IRF4, ASIP and BNC2), and female sex was also found to be a predictive factor for having a freckling phenotype in our population. After identifying the most informative genetic variants responsible for human ephelides occurrence in our sample set, we developed a DNA-based freckle prediction model using a multivariate regression approach. Once developed, the capabilities of the prediction model were tested by a repeated 10-fold cross-validation approach. The proportion of correctly predicted individuals using the DNA-based freckle prediction model was 74.13%. The implementation of sex into the DNA-based freckle prediction model slightly improved the overall prediction accuracy by 2.19% (76.32%). Further evaluation of the newly-generated prediction model was performed by assessing the model's performance in a new cohort of 212 Spanish individuals, reaching a classification success rate of 74.61%. Validation of this prediction model may be carried out in larger populations, including samples from different European populations. Further research to validate and improve this newly-generated freckle prediction model will be needed before its forensic application. Together with DNA tests already validated for eye and hair colour prediction, this freckle prediction model may lead to a substantially more detailed physical description of unknown individuals from DNA found at the crime scene. Copyright © 2017 Elsevier B.V. All rights reserved.
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Brandsch, Rainer
2017-10-01
Migration modelling provides reliable migration estimates from food-contact materials (FCM) to food or food simulants based on mass-transfer parameters like diffusion and partition coefficients related to individual materials. In most cases, mass-transfer parameters are not readily available from the literature and for this reason are estimated with a given uncertainty. Historically, uncertainty was accounted for by introducing upper limit concepts first, turning out to be of limited applicability due to highly overestimated migration results. Probabilistic migration modelling gives the possibility to consider uncertainty of the mass-transfer parameters as well as other model inputs. With respect to a functional barrier, the most important parameters among others are the diffusion properties of the functional barrier and its thickness. A software tool that accepts distribution as inputs and is capable of applying Monte Carlo methods, i.e., random sampling from the input distributions of the relevant parameters (i.e., diffusion coefficient and layer thickness), predicts migration results with related uncertainty and confidence intervals. The capabilities of probabilistic migration modelling are presented in the view of three case studies (1) sensitivity analysis, (2) functional barrier efficiency and (3) validation by experimental testing. Based on the predicted migration by probabilistic migration modelling and related exposure estimates, safety evaluation of new materials in the context of existing or new packaging concepts is possible. Identifying associated migration risk and potential safety concerns in the early stage of packaging development is possible. Furthermore, dedicated material selection exhibiting required functional barrier efficiency under application conditions becomes feasible. Validation of the migration risk assessment by probabilistic migration modelling through a minimum of dedicated experimental testing is strongly recommended.
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Duke, Joseph W; Elliott, Jonathan E; Laurie, Steven S; Beasley, Kara M; Mangum, Tyler S; Hawn, Jerold A; Gladstone, Igor M; Lovering, Andrew T
2014-09-01
Adults with a history of very preterm birth (<32 wk gestational age; PRET) have reduced lung function and significantly lower lung diffusion capacity for carbon monoxide (DLCO) relative to individuals born at term (CONT). Low DLCO may predispose PRET to diffusion limitation during exercise, particularly while breathing hypoxic gas because of a reduced O2 driving gradient and pulmonary capillary transit time. We hypothesized that PRET would have significantly worse pulmonary gas exchange efficiency [i.e., increased alveolar-to-arterial Po2 difference (AaDO2)] during exercise breathing room air or hypoxic gas (FiO2 = 0.12) compared with CONT. To test this hypothesis, we compared the AaDO2 in PRET (n = 13) with a clinically mild reduction in DLCO (72 ± 7% of predicted) and CONT (n = 14) with normal DLCO (105 ± 10% of predicted) pre- and during exercise breathing room air and hypoxic gas. Measurements of temperature-corrected arterial blood gases, and direct measure of O2 saturation (SaO2), were made prior to and during exercise at 25, 50, and 75% of peak oxygen consumption (V̇o2peak) while breathing room air and hypoxic gas. In addition to DLCO, pulmonary function and exercise capacity were significantly less in PRET. Despite PRET having low DLCO, no differences were observed in the AaDO2 or SaO2 pre- or during exercise breathing room air or hypoxic gas compared with CONT. Although our findings were unexpected, we conclude that reduced pulmonary function and low DLCO resulting from very preterm birth does not cause a measureable reduction in pulmonary gas exchange efficiency. Copyright © 2014 the American Physiological Society.
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NASA Astrophysics Data System (ADS)
Schoups, G.; Vrugt, J. A.; Fenicia, F.; van de Giesen, N. C.
2010-10-01
Conceptual rainfall-runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first-order, explicit, fixed-step integration methods leads to computationally cheap simulation models that are easy to implement. Computational speed is especially desirable for estimating parameter and predictive uncertainty using Markov chain Monte Carlo (MCMC) methods. Confirming earlier work of Kavetski et al. (2003), we show here that the computational speed of first-order, explicit, fixed-step integration methods comes at a cost: for a case study with a spatially lumped conceptual rainfall-runoff model, it introduces artificial bimodality in the marginal posterior parameter distributions, which is not present in numerically accurate implementations of the same model. The resulting effects on MCMC simulation include (1) inconsistent estimates of posterior parameter and predictive distributions, (2) poor performance and slow convergence of the MCMC algorithm, and (3) unreliable convergence diagnosis using the Gelman-Rubin statistic. We studied several alternative numerical implementations to remedy these problems, including various adaptive-step finite difference schemes and an operator splitting method. Our results show that adaptive-step, second-order methods, based on either explicit finite differencing or operator splitting with analytical integration, provide the best alternative for accurate and efficient MCMC simulation. Fixed-step or adaptive-step implicit methods may also be used for increased accuracy, but they cannot match the efficiency of adaptive-step explicit finite differencing or operator splitting. Of the latter two, explicit finite differencing is more generally applicable and is preferred if the individual hydrologic flux laws cannot be integrated analytically, as the splitting method then loses its advantage.
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Sheffield, Julia M; Kandala, Sridhar; Burgess, Gregory C; Harms, Michael P; Barch, Deanna M
2016-11-01
Psychosis is hypothesized to occur on a spectrum between psychotic disorders and healthy individuals. In the middle of the spectrum are individuals who endorse psychotic-like experiences (PLEs) that may not impact daily functioning or cause distress. Individuals with PLEs show alterations in both cognitive ability and functional connectivity of several brain networks, but the relationship between PLEs, cognition, and functional networks remains poorly understood. We analyzed resting-state fMRI data, a range of neuropsychological tasks, and questions from the Achenbach Adult Self Report (ASR) in 468 individuals from the Human Connectome Project. We aimed to determine whether global efficiency of specific functional brain networks supporting higher-order cognition (the fronto-parietal network (FPN), cingulo-opercular network (CON), and default mode network (DMN)) was associated with PLEs and cognitive ability in a non-psychiatric sample. 21.6% of individuals in our sample endorsed at least one PLE. PLEs were significantly negatively associated with higher-order cognitive ability, CON global efficiency, and DMN global efficiency, but not crystallized knowledge. Higher-order cognition was significantly positively associated with CON and DMN global efficiency. Interestingly, the association between PLEs and cognitive ability was partially mediated by CON global efficiency and, in a subset of individuals who tested negative for drugs (N=405), the participation coefficient of the right anterior insula (a hub within the CON). These findings suggest that CON integrity may represent a shared mechanism that confers risk for psychotic experiences and the cognitive deficits observed across the psychosis spectrum.
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Kouros, Chrystyna D.; Morris, Matthew C.; Garber, Judy
2015-01-01
The current longitudinal study examined which individual symptoms of depression uniquely predicted a subsequent Major Depressive Episode (MDE) in adolescents, and whether these relations differed by sex. Adolescents (N=240) were first interviewed in grade 6 (M=11.86 years old; SD = 0.56; 54% female; 81.5% Caucasian) and then annually through grade 12 regarding their individual symptoms of depression as well as the occurrence of MDEs. Individual symptoms of depression were assessed with the Children’s Depression Rating Scale-Revised (CDRS-R) and depressive episodes were assessed with the Longitudinal Interval Follow-up Evaluation (LIFE). Results showed that within-person changes in sleep problems and low self-esteem/excessive guilt positively predicted an increased likelihood of an MDE for both boys and girls. Significant sex differences also were found. Within-person changes in anhedonia predicted an increased likelihood of a subsequent MDE among boys, whereas irritability predicted a decreased likelihood of a future MDE among boys, and concentration difficulties predicted a decreased likelihood of an MDE in girls. These results identified individual depressive symptoms that predicted subsequent depressive episodes in male and female adolescents, and may be used to guide the early detection, treatment, and prevention of depressive disorders in youth. PMID:26105209
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Experimental evidence for adaptive personalities in a wild passerine bird
Nicolaus, Marion; Tinbergen, Joost M.; Bouwman, Karen M.; Michler, Stephanie P. M.; Ubels, Richard; Both, Christiaan; Kempenaers, Bart; Dingemanse, Niels J.
2012-01-01
Individuals of the same species differ consistently in risky actions. Such ‘animal personality’ variation is intriguing because behavioural flexibility is often assumed to be the norm. Recent theory predicts that between-individual differences in propensity to take risks should evolve if individuals differ in future fitness expectations: individuals with high long-term fitness expectations (i.e. that have much to lose) should behave consistently more cautious than individuals with lower expectations. Consequently, any manipulation of future fitness expectations should result in within-individual changes in risky behaviour in the direction predicted by this adaptive theory. We tested this prediction and confirmed experimentally that individuals indeed adjust their ‘exploration behaviour’, a proxy for risk-taking behaviour, to their future fitness expectations. We show for wild great tits (Parus major) that individuals with experimentally decreased survival probability become faster explorers (i.e. increase risk-taking behaviour) compared to individuals with increased survival probability. We also show, using quantitative genetics approaches, that non-genetic effects (i.e. permanent environment effects) underpin adaptive personality variation in this species. This study thereby confirms a key prediction of adaptive personality theory based on life-history trade-offs, and implies that selection may indeed favour the evolution of personalities in situations where individuals differ in future fitness expectations. PMID:23097506
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Energy efficient engine fan component detailed design report
NASA Technical Reports Server (NTRS)
Halle, J. E.; Michael, C. J.
1981-01-01
The fan component which was designed for the energy efficient engine is an advanced high performance, single stage system and is based on technology advancements in aerodynamics and structure mechanics. Two fan components were designed, both meeting the integrated core/low spool engine efficiency goal of 84.5%. The primary configuration, envisioned for a future flight propulsion system, features a shroudless, hollow blade and offers a predicted efficiency of 87.3%. A more conventional blade was designed, as a back up, for the integrated core/low spool demonstrator engine. The alternate blade configuration has a predicted efficiency of 86.3% for the future flight propulsion system. Both fan configurations meet goals established for efficiency surge margin, structural integrity and durability.
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SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition
Melvin, Iain; Ie, Eugene; Kuang, Rui; Weston, Jason; Stafford, William Noble; Leslie, Christina
2007-01-01
Background Predicting a protein's structural class from its amino acid sequence is a fundamental problem in computational biology. Much recent work has focused on developing new representations for protein sequences, called string kernels, for use with support vector machine (SVM) classifiers. However, while some of these approaches exhibit state-of-the-art performance at the binary protein classification problem, i.e. discriminating between a particular protein class and all other classes, few of these studies have addressed the real problem of multi-class superfamily or fold recognition. Moreover, there are only limited software tools and systems for SVM-based protein classification available to the bioinformatics community. Results We present a new multi-class SVM-based protein fold and superfamily recognition system and web server called SVM-Fold, which can be found at . Our system uses an efficient implementation of a state-of-the-art string kernel for sequence profiles, called the profile kernel, where the underlying feature representation is a histogram of inexact matching k-mer frequencies. We also employ a novel machine learning approach to solve the difficult multi-class problem of classifying a sequence of amino acids into one of many known protein structural classes. Binary one-vs-the-rest SVM classifiers that are trained to recognize individual structural classes yield prediction scores that are not comparable, so that standard "one-vs-all" classification fails to perform well. Moreover, SVMs for classes at different levels of the protein structural hierarchy may make useful predictions, but one-vs-all does not try to combine these multiple predictions. To deal with these problems, our method learns relative weights between one-vs-the-rest classifiers and encodes information about the protein structural hierarchy for multi-class prediction. In large-scale benchmark results based on the SCOP database, our code weighting approach significantly improves on the standard one-vs-all method for both the superfamily and fold prediction in the remote homology setting and on the fold recognition problem. Moreover, our code weight learning algorithm strongly outperforms nearest-neighbor methods based on PSI-BLAST in terms of prediction accuracy on every structure classification problem we consider. Conclusion By combining state-of-the-art SVM kernel methods with a novel multi-class algorithm, the SVM-Fold system delivers efficient and accurate protein fold and superfamily recognition. PMID:17570145
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Gowin, Joshua L; Ball, Tali M; Wittmann, Marc; Tapert, Susan F; Paulus, Martin P
2015-07-01
Nearly half of individuals with substance use disorders relapse in the year after treatment. A diagnostic tool to help clinicians make decisions regarding treatment does not exist for psychiatric conditions. Identifying individuals with high risk for relapse to substance use following abstinence has profound clinical consequences. This study aimed to develop neuroimaging as a robust tool to predict relapse. 68 methamphetamine-dependent adults (15 female) were recruited from 28-day inpatient treatment. During treatment, participants completed a functional MRI scan that examined brain activation during reward processing. Patients were followed 1 year later to assess abstinence. We examined brain activation during reward processing between relapsing and abstaining individuals and employed three random forest prediction models (clinical and personality measures, neuroimaging measures, a combined model) to generate predictions for each participant regarding their relapse likelihood. 18 individuals relapsed. There were significant group by reward-size interactions for neural activation in the left insula and right striatum for rewards. Abstaining individuals showed increased activation for large, risky relative to small, safe rewards, whereas relapsing individuals failed to show differential activation between reward types. All three random forest models yielded good test characteristics such that a positive test for relapse yielded a likelihood ratio 2.63, whereas a negative test had a likelihood ratio of 0.48. These findings suggest that neuroimaging can be developed in combination with other measures as an instrument to predict relapse, advancing tools providers can use to make decisions about individualized treatment of substance use disorders. Published by Elsevier Ireland Ltd.
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Baig, Sheharyar S; Strong, Mark; Rosser, Elisabeth; Taverner, Nicola V; Glew, Ruth; Miedzybrodzka, Zosia; Clarke, Angus; Craufurd, David; Quarrell, Oliver W
2016-01-01
Huntington's disease (HD) is a progressive neurodegenerative condition. At-risk individuals have accessed predictive testing via direct mutation testing since 1993. The UK Huntington's Prediction Consortium has collected anonymised data on UK predictive tests, annually, from 1993 to 2014: 9407 predictive tests were performed across 23 UK centres. Where gender was recorded, 4077 participants were male (44.3%) and 5122 were female (55.7%). The median age of participants was 37 years. The most common reason for predictive testing was to reduce uncertainty (70.5%). Of the 8441 predictive tests on individuals at 50% prior risk, 4629 (54.8%) were reported as mutation negative and 3790 (44.9%) were mutation positive, with 22 (0.3%) in the database being uninterpretable. Using a prevalence figure of 12.3 × 10−5, the cumulative uptake of predictive testing in the 50% at-risk UK population from 1994 to 2014 was estimated at 17.4% (95% CI: 16.9–18.0%). We present the largest study conducted on predictive testing in HD. Our findings indicate that the vast majority of individuals at risk of HD (>80%) have not undergone predictive testing. Future therapies in HD will likely target presymptomatic individuals; therefore, identifying the at-risk population whose gene status is unknown is of significant public health value. PMID:27165004
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Liu, Yun; Zhong, Zhang-cheng; Wang, Xiao-xue; Xie, Jun; Yang, Wen-ying
2011-03-01
A field research was conducted on the photosynthesis and transpiration characteristics of dioecious Trichosanthes kirilowii individuals at four key development stages. At vegetative growth stage, the photosynthesis rate, transpiration rate, stomatal conductance, and water use efficiency of male individuals were higher than those of female individuals, and hence, male individuals entered into reproductive growth stage 22 days earlier than female individuals. After entering into reproductive growth stage, male individuals had higher photosynthesis rate, transpiration rate, and stomatal conductance, but slightly lower water use efficiency than female individuals. As the female individuals started to reproductive growth, their photosynthesis rate and water use efficiency were significantly lower, while the transpiration rate and stomatal conductance were higher than those of the male individuals. The effects of climate factors on the growth and development of T. kirilowii mainly occurred at its vegetative growth and early reproductive growth stages, and weakened at later reproductive growth stages. Higher temperature and lower relative humidity benefited the growth and development of T. kirilowii, and illumination could enhance the photosynthesis rate of T. kirilowii, especially its male individuals. After entering into reproductive growth stage, the photosynthesis rate of male individuals increased significantly with increasing illumination, but that of female individuals only had a slight increase, and the transpiration rate of male individuals as well as the photosynthesis rate of female individuals all increased significantly with increasing temperature.
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Making Predictions in a Changing World: The Benefits of Individual-Based Ecology
Stillman, Richard A.; Railsback, Steven F.; Giske, Jarl; Berger, Uta; Grimm, Volker
2014-01-01
Ecologists urgently need a better ability to predict how environmental change affects biodiversity. We examine individual-based ecology (IBE), a research paradigm that promises better a predictive ability by using individual-based models (IBMs) to represent ecological dynamics as arising from how individuals interact with their environment and with each other. A key advantage of IBMs is that the basis for predictions—fitness maximization by individual organisms—is more general and reliable than the empirical relationships that other models depend on. Case studies illustrate the usefulness and predictive success of long-term IBE programs. The pioneering programs had three phases: conceptualization, implementation, and diversification. Continued validation of models runs throughout these phases. The breakthroughs that make IBE more productive include standards for describing and validating IBMs, improved and standardized theory for individual traits and behavior, software tools, and generalized instead of system-specific IBMs. We provide guidelines for pursuing IBE and a vision for future IBE research. PMID:26955076
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Lipinska, Malgorzata; Timol, Ridwana; Kaminer, Debra; Thomas, Kevin G F
2014-06-01
Successful memory consolidation during sleep depends on healthy slow-wave and rapid eye movement sleep, and on successful transition across sleep stages. In post-traumatic stress disorder, sleep is disrupted and memory is impaired, but relations between these two variables in the psychiatric condition remain unexplored. We examined whether disrupted sleep, and consequent disrupted memory consolidation, is a mechanism underlying declarative memory deficits in post-traumatic stress disorder. We recruited three matched groups of participants: post-traumatic stress disorder (n = 16); trauma-exposed non-post-traumatic stress disorder (n = 15); and healthy control (n = 14). They completed memory tasks before and after 8 h of sleep. We measured sleep variables using sleep-adapted electroencephalography. Post-traumatic stress disorder-diagnosed participants experienced significantly less sleep efficiency and rapid eye movement sleep percentage, and experienced more awakenings and wake percentage in the second half of the night than did participants in the other two groups. After sleep, post-traumatic stress disorder-diagnosed participants retained significantly less information on a declarative memory task than controls. Rapid eye movement percentage, wake percentage and sleep efficiency correlated with retention of information over the night. Furthermore, lower rapid eye movement percentage predicted poorer retention in post-traumatic stress disorder-diagnosed individuals. Our results suggest that declarative memory consolidation is disrupted during sleep in post-traumatic stress disorder. These data are consistent with theories suggesting that sleep benefits memory consolidation via predictable neurobiological mechanisms, and that rapid eye movement disruption is more than a symptom of post-traumatic stress disorder. © 2014 European Sleep Research Society.