The Effect of Neurocognitive Function on Math Computation in Pediatric ADHD: Moderating Influences of Anxious Perfectionism and Gender.

PubMed

Sturm, Alexandra; Rozenman, Michelle; Piacentini, John C; McGough, James J; Loo, Sandra K; McCracken, James T

2018-03-20

Predictors of math achievement in attention-deficit/hyperactivity disorder (ADHD) are not well-known. To address this gap in the literature, we examined individual differences in neurocognitive functioning domains on math computation in a cross-sectional sample of youth with ADHD. Gender and anxiety symptoms were explored as potential moderators. The sample consisted of 281 youth (aged 8-15 years) diagnosed with ADHD. Neurocognitive tasks assessed auditory-verbal working memory, visuospatial working memory, and processing speed. Auditory-verbal working memory speed significantly predicted math computation. A three-way interaction revealed that at low levels of anxious perfectionism, slower processing speed predicted poorer math computation for boys compared to girls. These findings indicate the uniquely predictive values of auditory-verbal working memory and processing speed on math computation, and their differential moderation. These findings provide preliminary support that gender and anxious perfectionism may influence the relationship between neurocognitive functioning and academic achievement.

Which Working Memory Functions Predict Intelligence?

ERIC Educational Resources Information Center

Oberauer, Klaus; Sub, Heinz-Martin; Wilhelm, Oliver; Wittmann, Werner W.

2008-01-01

Investigates the relationship between three factors of working memory (storage and processing, relational integration, and supervision) and four factors of intelligence (reasoning, speed, memory, and creativity) using structural equation models. Relational integration predicted reasoning ability at least as well as the storage-and-processing…

Emotional processing during experiential treatment of depression.

PubMed

Pos, Alberta E; Greenberg, Leslie S; Goldman, Rhonda N; Korman, Lorne M

2003-12-01

This study explored the importance of early and late emotional processing to change in depressive and general symptomology, self-esteem, and interpersonal problems for 34 clients who received 16-20 sessions of experiential treatment for depression. The independent contribution to outcome of the early working alliance was also explored. Early and late emotional processing predicted reductions in reported symptoms and gains in self-esteem. More important, emotional-processing skill significantly improved during treatment. Hierarchical regression models demonstrated that late emotional processing both mediated the relationship between clients' early emotional processing capacity and outcome and was the sole emotional-processing variable that independently predicted improvement. After controlling for emotional processing, the working alliance added an independent contribution to explaining improvement in reported symptomology only. (c) 2003 APA

Using Earth Observations to Understand and Predict Infectious Diseases

NASA Technical Reports Server (NTRS)

Soebiyanto, Radina P.; Kiang, Richard

2015-01-01

This presentation discusses the processes from data collection and processing to analysis involved in unraveling patterns between disease outbreaks and the surrounding environment and meteorological conditions. We used these patterns to estimate when and where disease outbreaks will occur. As a case study, we will present our work on assessing the relationship between meteorological conditions and influenza in Central America. Our work represents the discovery, prescriptive and predictive aspects of data analytics.

The role of processing difficulty in the predictive utility of working memory span.

PubMed

Bunting, Michael

2006-12-01

Storage-plus-processing working memory span tasks (e.g., operation span [OSPAN]) are strong predictors of higher order cognition, including general fluid intelligence. This is due, in part, to the difficulty of the processing component. When the processing component prevents only articulatory rehearsal, but not executive attentional control, the predictive utility is attenuated. Participants in one experiment (N = 59) completed Raven's Advanced Progressive Matrices (RAPM) and multiple versions of OSPAN and probed recall (PR). A distractor task (high or low difficulty) was added to PR, and OSPAN's processing component was manipulated for difficulty. OSPAN and PR correlated with RAPM when the processing component took executive attentional control. These results are suggestive of resource sharing between processing and storage.

Predictability of process resource usage - A measurement-based study on UNIX

NASA Technical Reports Server (NTRS)

Devarakonda, Murthy V.; Iyer, Ravishankar K.

1989-01-01

A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient betweeen the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82 percent of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Predictability of process resource usage: A measurement-based study of UNIX

NASA Technical Reports Server (NTRS)

Devarakonda, Murthy V.; Iyer, Ravishankar K.

1987-01-01

A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Grief processing and deliberate grief avoidance: a prospective comparison of bereaved spouses and parents in the United States and the People's Republic of China.

PubMed

Bonanno, George A; Papa, Anthony; Lalande, Kathleen; Zhang, Nanping; Noll, Jennie G

2005-02-01

In this study, the authors measured grief processing and deliberate grief avoidance and examined their relationship to adjustment at 4 and 18 months of bereavement for 2 types of losses (spouse, child) in 2 cultures (People's Republic of China, United States). Three hypotheses were compared: the traditional grief work assumption, a conditional grief work hypothesis, and a view of grief processing as a form of rumination absent among resilient individuals. Although cultural differences in grief processing and avoidance were observed, the factor structure of these measures proved invariant across cultures. Consistent with the grief work as rumination hypothesis, both grief processing and deliberate grief avoidance predicted poor long-term adjustment for U.S. participants. Furthermore, initial grief processing predicted later grief processing in both cultures. However, among the participants in the People's Republic of China, neither grief processing nor deliberate avoidance evidenced clear psychological consequences. Copyright 2005 APA.

The contents of visual working memory reduce uncertainty during visual search.

PubMed

Cosman, Joshua D; Vecera, Shaun P

2011-05-01

Information held in visual working memory (VWM) influences the allocation of attention during visual search, with targets matching the contents of VWM receiving processing benefits over those that do not. Such an effect could arise from multiple mechanisms: First, it is possible that the contents of working memory enhance the perceptual representation of the target. Alternatively, it is possible that when a target is presented among distractor items, the contents of working memory operate postperceptually to reduce uncertainty about the location of the target. In both cases, a match between the contents of VWM and the target should lead to facilitated processing. However, each effect makes distinct predictions regarding set-size manipulations; whereas perceptual enhancement accounts predict processing benefits regardless of set size, uncertainty reduction accounts predict benefits only with set sizes larger than 1, when there is uncertainty regarding the target location. In the present study, in which briefly presented, masked targets were presented in isolation, there was a negligible effect of the information held in VWM on target discrimination. However, in displays containing multiple masked items, information held in VWM strongly affected target discrimination. These results argue that working memory representations act at a postperceptual level to reduce uncertainty during visual search.

Explicit processing demands reveal language modality-specific organization of working memory.

PubMed

Rudner, Mary; Rönnberg, Jerker

2008-01-01

The working memory model for Ease of Language Understanding (ELU) predicts that processing differences between language modalities emerge when cognitive demands are explicit. This prediction was tested in three working memory experiments with participants who were Deaf Signers (DS), Hearing Signers (HS), or Hearing Nonsigners (HN). Easily nameable pictures were used as stimuli to avoid confounds relating to sensory modality. Performance was largely similar for DS, HS, and HN, suggesting that previously identified intermodal differences may be due to differences in retention of sensory information. When explicit processing demands were high, differences emerged between DS and HN, suggesting that although working memory storage in both groups is sensitive to temporal organization, retrieval is not sensitive to temporal organization in DS. A general effect of semantic similarity was also found. These findings are discussed in relation to the ELU model.

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

Zamecnik, J. R.; Edwards, T. B.

The conversions of nitrite to nitrate, the destruction of glycolate, and the conversion of glycolate to formate and oxalate were modeled for the Nitric-Glycolic flowsheet using data from Chemical Process Cell (CPC) simulant runs conducted by SRNL from 2011 to 2015. The goal of this work was to develop empirical correlations for these variables versus measureable variables from the chemical process so that these quantities could be predicted a-priori from the sludge composition and measurable processing variables. The need for these predictions arises from the need to predict the REDuction/OXidation (REDOX) state of the glass from the Defense Waste Processingmore » Facility (DWPF) melter. This report summarizes the initial work on these correlations based on the aforementioned data. Further refinement of the models as additional data is collected is recommended.« less

File Usage Analysis and Resource Usage Prediction: a Measurement-Based Study. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Devarakonda, Murthy V.-S.

1987-01-01

A probabilistic scheme was developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The coefficient of correlation between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Cognitive processes in children's reading and attention: the role of working memory, divided attention, and response inhibition.

PubMed

Savage, Robert; Cornish, Kim; Manly, Tom; Hollis, Chris

2006-08-01

Children experiencing attention difficulties have documented cognitive deficits in working memory (WM), response inhibition and dual tasks. Recent evidence suggests however that these same cognitive processes are also closely associated with reading acquisition. This paper therefore explores whether these variables predicted attention difficulties or reading among 123 children with and without significant attention problems sampled from the school population. Children were screened using current WM and attention task measures. Three factors explained variance in WM and attention tasks. Response inhibition tasks loaded mainly with central executive measures, but a dual processing task loaded with the visual-spatial WM measures. Phonological loop measures loaded independently of attention measures. After controls for age, IQ and attention-group membership, phonological loop and 'central processing' measures both predicted reading ability. A 'visual memory/dual-task' factor predicted attention group membership after controls for age, IQ and reading ability. Results thus suggest that some of the processes previously assumed to be predictive of attention problems may reflect processes involved in reading acquisition. Visual memory and dual-task functioning are, however, purer indices of cognitive difficulty in children experiencing attention problems.

Emotion perception and executive functioning predict work status in euthymic bipolar disorder.

PubMed

Ryan, Kelly A; Vederman, Aaron C; Kamali, Masoud; Marshall, David; Weldon, Anne L; McInnis, Melvin G; Langenecker, Scott A

2013-12-15

Functional recovery, including return to work, in Bipolar Disorder (BD) lags behind clinical recovery and may be incomplete when acute mood symptoms have subsided. We examined impact of cognition on work status and underemployment in a sample of 156 Euthymic-BD and 143 controls (HC) who were divided into working/not working groups. Clinical, health, social support, and personality data were collected, and eight cognitive factors were derived from a battery of neuropsychological tests. The HC groups outperformed the BD groups on seven of eight cognitive factors. The working-BD group outperformed the not working-BD group on 4 cognitive factors composed of tasks of emotion processing and executive functioning including processing speed and set shifting. Emotion processing and executive tasks were predictive of BD unemployment, after accounting for number of mood episodes. Four cognitive factors accounted for a significant amount of the variance in work status among the BD participants. Results indicate that patients with BD who are unemployed/unable to work exhibit greater difficulties processing emotional information and on executive tasks that comprise a set shifting or interference resolution component as compared to those who are employed, independent of other factors. These cognitive and affective factors are suggested as targets for treatment and/or accommodations. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Work overload, burnout, and psychological ill-health symptoms: a three-wave mediation model of the employee health impairment process.

PubMed

de Beer, Leon T; Pienaar, Jaco; Rothmann, Sebastiaan

2016-07-01

The study reported here investigated the causal relationships in the health impairment process of employee well-being, and the mediating role of burnout in the relationship between work overload and psychological ill-health symptoms, over time. The research is deemed important due to the need for longitudinal evidence of the health impairment process of employee well-being over three waves of data. A quantitative survey design was followed. Participants constituted a longitudinal sample of 370 participants, at three time points, after attrition. Descriptive statistics and structural equation modeling methods were implemented. Work overload at time one predicted burnout at time two, and burnout at time two predicted psychological ill-health symptoms at time three. Indirect effects were found between work overload time one and psychological ill-health symptoms time three via burnout time two, and also between burnout time one and psychological ill-health symptoms time three, via burnout time two. The results provided supportive evidence for an "indirect-only" mediation effect, for burnout's causal mediation mechanism in the health impairment process between work overload and psychological ill-health symptoms.

Decision Making Processes and Outcomes

PubMed Central

Hicks Patrick, Julie; Steele, Jenessa C.; Spencer, S. Melinda

2013-01-01

The primary aim of this study was to examine the contributions of individual characteristics and strategic processing to the prediction of decision quality. Data were provided by 176 adults, ages 18 to 93 years, who completed computerized decision-making vignettes and a battery of demographic and cognitive measures. We examined the relations among age, domain-specific experience, working memory, and three measures of strategic information search to the prediction of solution quality using a 4-step hierarchical linear regression analysis. Working memory and two measures of strategic processing uniquely contributed to the variance explained. Results are discussed in terms of potential advances to both theory and intervention efforts. PMID:24282638

Profiles of Verbal Working Memory Growth Predict Speech and Language Development in Children with Cochlear Implants

ERIC Educational Resources Information Center

Kronenberger, William G.; Pisoni, David B.; Harris, Michael S.; Hoen, Helena M.; Xu, Huiping; Miyamoto, Richard T.

2013-01-01

Purpose: Verbal short-term memory (STM) and working memory (WM) skills predict speech and language outcomes in children with cochlear implants (CIs) even after conventional demographic, device, and medical factors are taken into account. However, prior research has focused on single end point outcomes as opposed to the longitudinal process of…

Toward an Integrative Model of Creativity and Personality: Theoretical Suggestions and Preliminary Empirical Testing

ERIC Educational Resources Information Center

Fü rst, Guillaume; Ghisletta, Paolo; Lubart, Todd

2016-01-01

The present work proposes an integrative model of creativity that includes personality traits and cognitive processes. This model hypothesizes that three high-order personality factors predict two main process factors, which in turn predict intensity and achievement of creative activities. The personality factors are: "Plasticity" (high…

The Relationships of Working Memory, Secondary Memory, and General Fluid Intelligence: Working Memory is Special

PubMed Central

Shelton, Jill Talley; Elliott, Emily M.; Matthews, Russell A.; Hill, B. D.; Gouvier, Wm. Drew

2010-01-01

Recent efforts have been made to elucidate the commonly observed link between working memory and reasoning ability. The results have been inconsistent, with some work suggesting the emphasis placed on retrieval from secondary memory by working memory tests is the driving force behind this association (Mogle, Lovett, Stawski, & Sliwinski, 2008), while other research suggests retrieval from secondary memory is only partly responsible for the observed link between working memory and reasoning (Unsworth & Engle, 2006, 2007b). The present study investigates the relationship between processing speed, working memory, secondary memory, primary memory, and fluid intelligence. Although our findings show all constructs are significantly correlated with fluid intelligence, working memory, but not secondary memory, accounts for significant unique variance in fluid intelligence. Our data support predictions made by Unsworth and Engle, and suggest that the combined need for maintenance and retrieval processes present in working memory tests makes them “special” in their prediction of higher-order cognition. PMID:20438278

Fatigue Life Variability in Large Aluminum Forgings with Residual Stress

DTIC Science & Technology

2011-07-01

been conducted. A detailed finite element analysis of the forge/ quench /coldwork/machine process was performed in order to predict the bulk residual...forge/ quench /coldwork/machine process was performed in order to predict the bulk residual stresses in a fictitious aluminum bulkhead. The residual...continues to develop the capability for computational simulation of the forge, quench , cold work and machining processes. In order to handle the

Working memory regulates trait anxiety-related threat processing biases.

PubMed

Booth, Robert W; Mackintosh, Bundy; Sharma, Dinkar

2017-06-01

High trait anxious individuals tend to show biased processing of threat. Correlational evidence suggests that executive control could be used to regulate such threat-processing. On this basis, we hypothesized that trait anxiety-related cognitive biases regarding threat should be exaggerated when executive control is experimentally impaired by loading working memory. In Study 1, 68 undergraduates read ambiguous vignettes under high and low working memory load; later, their interpretations of these vignettes were assessed via a recognition test. Trait anxiety predicted biased interpretation of social threat vignettes under high working memory load, but not under low working memory load. In Study 2, 53 undergraduates completed a dot probe task with fear-conditioned Japanese characters serving as threat stimuli. Trait anxiety predicted attentional bias to the threat stimuli but, again, this only occurred under high working memory load. Interestingly however, actual eye movements toward the threat stimuli were only associated with state anxiety, and this was not moderated by working memory load, suggesting that executive control regulates biased threat-processing downstream of initial input processes such as orienting. These results suggest that cognitive loads can exacerbate trait anxiety-related cognitive biases, and therefore represent a useful tool for assessing cognitive biases in future research. More importantly, since biased threat-processing has been implicated in the etiology and maintenance of anxiety, poor executive control may be a risk factor for anxiety disorders. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Sense of coherence and the motivational process of the job-demands-resources model.

PubMed

Vogt, Katharina; Hakanen, Jari J; Jenny, Gregor J; Bauer, Georg F

2016-04-01

This longitudinal study systematically examines the various roles played by the personal resource "sense of coherence" (SoC) in the motivational process described by the job-demands-resources model. SoC captures the extent to which people perceive their life as comprehensible, manageable and meaningful, and there is evidence of its influence in many health-related outcomes. The first aim here was to establish whether a resourceful working environment builds up SoC and whether SoC leads to work engagement. A second aim was to test reverse relationships: how work engagement leads to SoC and how SoC in turn relates to job resources. A third aim was to assess whether SoC boosts the relationship between job resources and work engagement. The study utilized a 3-wave, 3-month panel design, involving 940 employees working in a broad range of occupations and economic sectors. The results of longitudinal structural equation modeling show that job resources predict SoC and SoC predicts work engagement, suggesting a mediating role of SoC. In addition, SoC predicts job resources, suggesting reciprocal relationships between job resources and SoC. No boosting effect of SoC was found. Overall, the present findings support the view that providing employees with a resourceful working environment will help to build their SoC. The effects of SoC on perceptual, appraisal, and behavioral processes may in turn lead to enhanced job resources and positive outcomes such as greater work engagement. (c) 2016 APA, all rights reserved).

Self-Regulation, Executive Function, Working Memory, and Academic Achievement of Female High School Students

ERIC Educational Resources Information Center

Halloran, Roberta Kathryn

2011-01-01

Self-regulation, executive function and working memory are areas of cognitive processing that have been studied extensively. Although many studies have examined the constructs, there is limited empirical support suggesting a formal link between the three cognitive processes and their prediction of academic achievement. Thus, the present study…

Prediction of composites behavior undergoing an ATP process through data-mining

NASA Astrophysics Data System (ADS)

Martin, Clara Argerich; Collado, Angel Leon; Pinillo, Rubén Ibañez; Barasinski, Anaïs; Abisset-Chavanne, Emmanuelle; Chinesta, Francisco

2018-05-01

The need to characterize composite surfaces for distinct mechanical or physical processes leads to different manners of evaluate the state of the surface. During many manufacturing processes deformation occurs, thus hindering composite classification for fabrication processes. In this work we focus on the challenge of a priori identifying the surfaces' behavior in order to optimize manufacturing. We will propose and validate the curvature of the surface as a reliable parameter and we will develop a tool that allows the prediction of the surface behavior.

Changing work, changing health: can real work-time flexibility promote health behaviors and well-being?

PubMed

Moen, Phyllis; Kelly, Erin L; Tranby, Eric; Huang, Qinlei

2011-12-01

This article investigates a change in the structuring of work time, using a natural experiment to test whether participation in a corporate initiative (Results Only Work Environment; ROWE) predicts corresponding changes in health-related outcomes. Drawing on job strain and stress process models, we theorize greater schedule control and reduced work-family conflict as key mechanisms linking this initiative with health outcomes. Longitudinal survey data from 659 employees at a corporate headquarters shows that ROWE predicts changes in health-related behaviors, including almost an extra hour of sleep on work nights. Increasing employees' schedule control and reducing their work-family conflict are key mechanisms linking the ROWE innovation with changes in employees' health behaviors; they also predict changes in well-being measures, providing indirect links between ROWE and well-being. This study demonstrates that organizational changes in the structuring of time can promote employee wellness, particularly in terms of prevention behaviors.

Improving Working Memory Efficiency by Reframing Metacognitive Interpretation of Task Difficulty

ERIC Educational Resources Information Center

Autin, Frederique; Croizet, Jean-Claude

2012-01-01

Working memory capacity, our ability to manage incoming information for processing purposes, predicts achievement on a wide range of intellectual abilities. Three randomized experiments (N = 310) tested the effectiveness of a brief psychological intervention designed to boost working memory efficiency (i.e., state working memory capacity) by…

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.

Working Memory in Children with Cochlear Implants: Problems are in Storage, not Processing

PubMed Central

Nittrouer, Susan; Caldwell-Tarr, Amanda; Lowenstein, Joanna H

2013-01-01

Background There is growing consensus that hearing loss and consequent amplification likely interact with cognitive systems. A phenomenon often examined in regards to these potential interactions is working memory, modeled as consisting of one component responsible for storage of information and another component responsible for processing of that information. Signal degradation associated with cochlear implants should selectively inhibit storage without affecting processing. This study examined two hypotheses: (1) A single task can be used to measure storage and processing in working memory, with recall accuracy indexing storage and rate of recall indexing processing; (2) Storage is negatively impacted for children with CIs, but not processing. Method Two experiments were conducted. Experiment 1 included adults and children, 8 and 6 years of age, with NH. Procedures tested the prediction that accuracy of recall could index storage and rate of recall could index processing. Both measures were obtained during a serial-recall task using word lists designed to manipulate storage and processing demands independently: non-rhyming nouns were the standard condition; rhyming nouns were predicted to diminish storage capacity; and non-rhyming adjectives were predicted to increase processing load. Experiment 2 included 98 8-year-olds, 48 with NH and 50 with CIs, in the same serial-recall task using the non-rhyming and rhyming nouns. Results Experiment 1 showed that recall accuracy was poorest for the rhyming nouns and rate of recall was slowest for the non-rhyming adjectives, demonstrating that storage and processing can be indexed separately within a single task. In Experiment 2, children with CIs showed less accurate recall of serial order than children with NH, but rate of recall did not differ. Recall accuracy and rate of recall were not correlated in either experiment, reflecting independence of these mechanisms. Conclusions It is possible to measure the operations of storage and processing mechanisms in working memory in a single task, and only storage is impaired for children with CIs. These findings suggest that research and clinical efforts should focus on enhancing the saliency of representation for children with CIs. Direct instruction of syntax and semantics could facilitate storage in real-world working memory tasks. PMID:24090697

Working memory in children with cochlear implants: problems are in storage, not processing.

PubMed

Nittrouer, Susan; Caldwell-Tarr, Amanda; Lowenstein, Joanna H

2013-11-01

There is growing consensus that hearing loss and consequent amplification likely interact with cognitive systems. A phenomenon often examined in regards to these potential interactions is working memory, modeled as consisting of one component responsible for storage of information and another component responsible for processing of that information. Signal degradation associated with cochlear implants should selectively inhibit storage without affecting processing. This study examined two hypotheses: (1) A single task can be used to measure storage and processing in working memory, with recall accuracy indexing storage and rate of recall indexing processing; (2) Storage is negatively impacted for children with CIs, but not processing. Two experiments were conducted. Experiment 1 included adults and children, 8 and 6 years of age, with NH. Procedures tested the prediction that accuracy of recall could index storage and rate of recall could index processing. Both measures were obtained during a serial-recall task using word lists designed to manipulate storage and processing demands independently: non-rhyming nouns were the standard condition; rhyming nouns were predicted to diminish storage capacity; and non-rhyming adjectives were predicted to increase processing load. Experiment 2 included 98 8-year-olds, 48 with NH and 50 with CIs, in the same serial-recall task using the non-rhyming and rhyming nouns. Experiment 1 showed that recall accuracy was poorest for the rhyming nouns and rate of recall was slowest for the non-rhyming adjectives, demonstrating that storage and processing can be indexed separately within a single task. In Experiment 2, children with CIs showed less accurate recall of serial order than children with NH, but rate of recall did not differ. Recall accuracy and rate of recall were not correlated in either experiment, reflecting independence of these mechanisms. It is possible to measure the operations of storage and processing mechanisms in working memory in a single task, and only storage is impaired for children with CIs. These findings suggest that research and clinical efforts should focus on enhancing the saliency of representation for children with CIs. Direct instruction of syntax and semantics could facilitate storage in real-world working memory tasks. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Finite Element Simulation of Temperature and Strain Distribution during Friction Stir Welding of AA2024 Aluminum Alloy

NASA Astrophysics Data System (ADS)

Jain, Rahul; Pal, Surjya Kanta; Singh, Shiv Brat

2017-02-01

Friction Stir Welding (FSW) is a solid state joining process and is handy for welding aluminum alloys. Finite Element Method (FEM) is an important tool to predict state variables of the process but numerical simulation of FSW is highly complex due to non-linear contact interactions between tool and work piece and interdependency of displacement and temperature. In the present work, a three dimensional coupled thermo-mechanical method based on Lagrangian implicit method is proposed to study the thermal history, strain distribution and thermo-mechanical process in butt welding of Aluminum alloy 2024 using DEFORM-3D software. Workpiece is defined as rigid-visco plastic material and sticking condition between tool and work piece is defined. Adaptive re-meshing is used to tackle high mesh distortion. Effect of tool rotational and welding speed on plastic strain is studied and insight is given on asymmetric nature of FSW process. Temperature distribution on the workpiece and tool is predicted and maximum temperature is found in workpiece top surface.

A comparison of neural network architectures for the prediction of MRR in EDM

NASA Astrophysics Data System (ADS)

Jena, A. R.; Das, Raja

2017-11-01

The aim of the research work is to predict the material removal rate of a work-piece in electrical discharge machining (EDM). Here, an effort has been made to predict the material removal rate through back-propagation neural network (BPN) and radial basis function neural network (RBFN) for a work-piece of AISI D2 steel. The input parameters for the architecture are discharge-current (Ip), pulse-duration (Ton), and duty-cycle (τ) taken for consideration to obtained the output for material removal rate of the work-piece. In the architecture, it has been observed that radial basis function neural network is comparatively faster than back-propagation neural network but logically back-propagation neural network results more real value. Therefore BPN may consider as a better process in this architecture for consistent prediction to save time and money for conducting experiments.

Cognitive processes involved in smooth pursuit eye movements: behavioral evidence, neural substrate and clinical correlation

PubMed Central

Fukushima, Kikuro; Fukushima, Junko; Warabi, Tateo; Barnes, Graham R.

2013-01-01

Smooth-pursuit eye movements allow primates to track moving objects. Efficient pursuit requires appropriate target selection and predictive compensation for inherent processing delays. Prediction depends on expectation of future object motion, storage of motion information and use of extra-retinal mechanisms in addition to visual feedback. We present behavioral evidence of how cognitive processes are involved in predictive pursuit in normal humans and then describe neuronal responses in monkeys and behavioral responses in patients using a new technique to test these cognitive controls. The new technique examines the neural substrate of working memory and movement preparation for predictive pursuit by using a memory-based task in macaque monkeys trained to pursue (go) or not pursue (no-go) according to a go/no-go cue, in a direction based on memory of a previously presented visual motion display. Single-unit task-related neuronal activity was examined in medial superior temporal cortex (MST), supplementary eye fields (SEF), caudal frontal eye fields (FEF), cerebellar dorsal vermis lobules VI–VII, caudal fastigial nuclei (cFN), and floccular region. Neuronal activity reflecting working memory of visual motion direction and go/no-go selection was found predominantly in SEF, cerebellar dorsal vermis and cFN, whereas movement preparation related signals were found predominantly in caudal FEF and the same cerebellar areas. Chemical inactivation produced effects consistent with differences in signals represented in each area. When applied to patients with Parkinson's disease (PD), the task revealed deficits in movement preparation but not working memory. In contrast, patients with frontal cortical or cerebellar dysfunction had high error rates, suggesting impaired working memory. We show how neuronal activity may be explained by models of retinal and extra-retinal interaction in target selection and predictive control and thus aid understanding of underlying pathophysiology. PMID:23515488

Through-process modelling of texture and anisotropy in AA5182

NASA Astrophysics Data System (ADS)

Crumbach, M.; Neumann, L.; Goerdeler, M.; Aretz, H.; Gottstein, G.; Kopp, R.

2006-07-01

A through-process texture and anisotropy prediction for AA5182 sheet production from hot rolling through cold rolling and annealing is reported. Thermo-mechanical process data predicted by the finite element method (FEM) package T-Pack based on the software LARSTRAN were fed into a combination of physics based microstructure models for deformation texture (GIA), work hardening (3IVM), nucleation texture (ReNuc), and recrystallization texture (StaRT). The final simulated sheet texture was fed into a FEM simulation of cup drawing employing a new concept of interactively updated texture based yield locus predictions. The modelling results of texture development and anisotropy were compared to experimental data. The applicability to other alloys and processes is discussed.

Trait rumination and response to negative evaluative lab-induced stress: neuroendocrine, affective, and cognitive outcomes.

PubMed

Vrshek-Schallhorn, Suzanne; Velkoff, Elizabeth A; Zinbarg, Richard E

2018-04-06

Theoretical models of depression posit that, under stress, elevated trait rumination predicts more pronounced or prolonged negative affective and neuroendocrine responses, and that trait rumination hampers removing irrelevant negative information from working memory. We examined several gaps regarding these models in the context of lab-induced stress. Non-depressed undergraduates completed a rumination questionnaire and either a negative-evaluative Trier Social Stress Test (n = 55) or a non-evaluative control condition (n = 69), followed by a modified Sternberg affective working memory task assessing the extent to which irrelevant negative information can be emptied from working memory. We measured shame, negative and positive affect, and salivary cortisol four times. Multilevel growth curve models showed rumination and stress interactively predicted cortisol reactivity; however, opposite predictions, greater rumination was associated with blunted cortisol reactivity to stress. Elevated trait rumination interacted with stress to predict augmented shame reactivity. Rumination and stress did not significantly interact to predict working memory performance, but under control conditions, rumination predicted greater difficulty updating working memory. Results support a vulnerability-stress model of trait rumination with heightened shame reactivity and cortisol dysregulation rather than hyper-reactivity in non-depressed emerging adults, but we cannot provide evidence that working memory processes are critical immediately following acute stress.

Objectively-Measured Impulsivity and Attention-Deficit/Hyperactivity Disorder (ADHD): Testing Competing Predictions from the Working Memory and Behavioral Inhibition Models of ADHD

ERIC Educational Resources Information Center

Raiker, Joseph S.; Rapport, Mark D.; Kofler, Michael J.; Sarver, Dustin E.

2012-01-01

Impulsivity is a hallmark of two of the three DSM-IV ADHD subtypes and is associated with myriad adverse outcomes. Limited research, however, is available concerning the mechanisms and processes that contribute to impulsive responding by children with ADHD. The current study tested predictions from two competing models of ADHD--working memory (WM)…

Family Roles and Work Values: Processes of Selection and Change

ERIC Educational Resources Information Center

Kirkpatrick Johnson, Monica

2005-01-01

This study focuses on whether marriage and parenthood influence work values after taking into account the influence of work values on family formation. In a recent panel of young adults (N=709), stronger extrinsic and weaker intrinsic work values during adolescence predicted marriage and parenthood 9 years out of high school. Controlling these…

Gaining the Long View: Reforming Organization and Empowering Knowledge Workers to Improve Strategy and Intelligence

DTIC Science & Technology

2017-03-31

processes. Hierarchal bureaucracies also provide the workforce with a predictable, structured work environment , a sense of status, and other...processes in response to changes in the environment . As they age and acquire a corporate culture, members become more entrenched in their work ...inability of managers and leaders of knowledge workers to foster a work environment that effectively exploits the knowledge worker’s drive to apply his or

Organizational work-family resources as predictors of job performance and attitudes: the process of work-family conflict and enrichment.

PubMed

Odle-Dusseau, Heather N; Britt, Thomas W; Greene-Shortridge, Tiffany M

2012-01-01

The goal of the current study was to test a model where organizational resources (aimed at managing work and family responsibilities) predict job attitudes and supervisor ratings of performance through the mechanisms of work-family conflict and work-family enrichment. Employees (n = 174) at a large metropolitan hospital were surveyed at two time periods regarding perceptions of family supportive supervisor behaviors (FSSB), family supportive organizational perceptions (FSOP), bidirectional work-family conflict, bidirectional work-family enrichment, and job attitudes. Supervisors were also asked to provide performance ratings at Time 2. Results revealed FSSB at Time 1 predicted job satisfaction, organizational commitment and intention to leave, as well as supervisor ratings of performance, at Time 2. In addition, both work-family enrichment and family-work enrichment were found to mediate relationships between FSSB and various organizational outcomes, while work-family conflict was not a significant mediator. Results support further testing of supervisor behaviors specific to family support, as well models that include bidirectional work-family enrichment as the mechanism by which work-family resources predict employee and organizational outcomes.

Mechanochemical Synthesis of Pharmaceutical Cocrystal Suspensions via Hot Melt Extrusion: Enhancing Cocrystal Yield.

PubMed

Li, Shu; Yu, Tao; Tian, Yiwei; Lagan, Colette; Jones, David S; Andrews, Gavin P

2017-11-22

Pharmaceutical cocrystals have attracted increasing attention over the past decade as an alternative way to modify the physicochemical properties and hence improve the bioavailability of a drug, without sacrificing thermodynamic stability. Our previous work has demonstrated the viability of in-situ formation of ibuprofen/isonicotinamide cocrystal suspensions within a matrix carrier via a single-step hot-melt extrusion (HME) process. The key aim of the current work is to establish optimised processing conditions to improve cocrystal yield within extruded matrices. The solubility of each individual cocrystal component in the matrix carrier was estimated using two different methods, calculation of Hansen solubility parameters, and Flory-Huggins solution theory using melting point depression measurement, respectively. The latter was found to be more relevant to extrusion cocrystallisation because of the ability to predict miscibility across a range of temperatures. The predictions obtained from the F-H phase diagrams were verified using ternary extrusion processing. Temperatures that promote solubilisation of the parent reagents during processing, and precipitation of the newly formed cocrystal were found to be the most suitable in generating high cocrystal yields. The incorporation of intensive mixing/kneading elements to the screw configuration was also shown to significantly improve the cocrystal yield when utilising a matrix platform. This work has shown that intensive mixing in combination with appropriate temperature selection, can significantly improve the cocrystal yield within a stable and low viscosity carrier during HME processing. Most importantly, this work reports, for the very first time in the literature, the use of the F-H phase diagrams to predict the most appropriate HME processing window to drive higher cocrystal yield.

A multisensory perspective of working memory

PubMed Central

Quak, Michel; London, Raquel Elea; Talsma, Durk

2015-01-01

Although our sensory experience is mostly multisensory in nature, research on working memory representations has focused mainly on examining the senses in isolation. Results from the multisensory processing literature make it clear that the senses interact on a more intimate manner than previously assumed. These interactions raise questions regarding the manner in which multisensory information is maintained in working memory. We discuss the current status of research on multisensory processing and the implications of these findings on our theoretical understanding of working memory. To do so, we focus on reviewing working memory research conducted from a multisensory perspective, and discuss the relation between working memory, attention, and multisensory processing in the context of the predictive coding framework. We argue that a multisensory approach to the study of working memory is indispensable to achieve a realistic understanding of how working memory processes maintain and manipulate information. PMID:25954176

Work flow of signal processing data of ground penetrating radar case of rigid pavement measurements

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

Handayani, Gunawan

The signal processing of Ground Penetrating Radar (GPR) requires a certain work flow to obtain good results. Even though the Ground Penetrating Radar data looks similar with seismic reflection data, but the GPR data has particular signatures that the seismic reflection data does not have. This is something to do with coupling between antennae and the ground surface. Because of this, the GPR data should be treated differently from the seismic signal data processing work flow. Even though most of the processing steps still follow the same work flow of seismic reflection data such as: filtering, predictive deconvolution etc. Thismore » paper presents the work flow of GPR processing data on rigid pavement measurements. The processing steps start from raw data, de-Wow process, remove DC and continue with the standard process to get rid of noises i.e. filtering process. Some radargram particular features of rigid pavement along with pile foundations are presented.« less

Which neuropsychological functions predict various processing speed components in children with and without attention-deficit/hyperactivity disorder?

PubMed

Vadnais, Sarah A; Kibby, Michelle Y; Jagger-Rickels, Audreyana C

2018-01-01

We identified statistical predictors of four processing speed (PS) components in a sample of 151 children with and without attention-deficit/hyperactivity disorder (ADHD). Performance on perceptual speed was predicted by visual attention/short-term memory, whereas incidental learning/psychomotor speed was predicted by verbal working memory. Rapid naming was predictive of each PS component assessed, and inhibition predicted all but one task, suggesting a shared need to identify/retrieve stimuli rapidly and inhibit incorrect responding across PS components. Hence, we found both shared and unique predictors of perceptual, cognitive, and output speed, suggesting more specific terminology should be used in future research on PS in ADHD.

Changing Work, Changing Health: Can Real Work-Time Flexibility Promote Health Behaviors and Well-Being?

PubMed Central

Moen, Phyllis; Kelly, Erin L.; Tranby, Eric; Huang, Qinlei

2012-01-01

This article investigates a change in the structuring of work time, using a natural experiment to test whether participation in a corporate initiative (Results Only Work Environment; ROWE) predicts corresponding changes in health-related outcomes. Drawing on job strain and stress process models, we theorize greater schedule control and reduced work-family conflict as key mechanisms linking this initiative with health outcomes. Longitudinal survey data from 659 employees at a corporate headquarters shows that ROWE predicts changes in health-related behaviors, including almost an extra hour of sleep on work nights. Increasing employees’ schedule control and reducing their work-family conflict are key mechanisms linking the ROWE innovation with changes in employees’ health behaviors; they also predict changes in well-being measures, providing indirect links between ROWE and well-being. This study demonstrates that organizational changes in the structuring of time can promote employee wellness, particularly in terms of prevention behaviors. PMID:22144731

Visuospatial Working Memory Capacity Predicts Physiological Arousal in a Narrative Task.

PubMed

Smithson, Lisa; Nicoladis, Elena

2016-06-01

Physiological arousal that occurs during narrative production is thought to reflect emotional processing and cognitive effort (Bar-Haim et al. in Dev Psychobiol 44:238-249, 2004). The purpose of this study was to determine whether individual differences in visuospatial working memory and/or verbal working memory capacity predict physiological arousal in a narrative task. Visuospatial working memory was a significant predictor of skin conductance level (SCL); verbal working memory was not. When visuospatial working memory interference was imposed, visuospatial working memory was no longer a significant predictor of SCL. Visuospatial interference also resulted in a significant reduction in SCL. Furthermore, listener ratings of narrative quality were contingent upon the visuospatial working memory resources of the narrator. Potential implications for educators and clinical practitioners are discussed.

Predicting non-stationary algal dynamics following changes in hydrometeorological conditions using data assimilation techniques

NASA Astrophysics Data System (ADS)

Kim, S.; Seo, D. J.

2017-12-01

When water temperature (TW) increases due to changes in hydrometeorological conditions, the overall ecological conditions change in the aquatic system. The changes can be harmful to human health and potentially fatal to fish habitat. Therefore, it is important to assess the impacts of thermal disturbances on in-stream processes of water quality variables and be able to predict effectiveness of possible actions that may be taken for water quality protection. For skillful prediction of in-stream water quality processes, it is necessary for the watershed water quality models to be able to reflect such changes. Most of the currently available models, however, assume static parameters for the biophysiochemical processes and hence are not able to capture nonstationaries seen in water quality observations. In this work, we assess the performance of the Hydrological Simulation Program-Fortran (HSPF) in predicting algal dynamics following TW increase. The study area is located in the Republic of Korea where waterway change due to weir construction and drought concurrently occurred around 2012. In this work we use data assimilation (DA) techniques to update model parameters as well as the initial condition of selected state variables for in-stream processes relevant to algal growth. For assessment of model performance and characterization of temporal variability, various goodness-of-fit measures and wavelet analysis are used.

Gibberllin driven growth in elf3 mutants requires PIF4 and PIF5

USDA-ARS?s Scientific Manuscript database

The regulatory connections between the circadian clock and hormone signaling are essential to understand, as these two regulatory processes work together to time growth processes relative to predictable environmental events. Gibberellins (GAs) are phytohormones that control many growth processes thr...

[Effects of an implicit internal working model on attachment in information processing assessed using Go/No-Go Association Task].

PubMed

Fujii, Tsutomu; Uebuchi, Hisashi; Yamada, Kotono; Saito, Masahiro; Ito, Eriko; Tonegawa, Akiko; Uebuchi, Marie

2015-06-01

The purposes of the present study were (a) to use both a relational-anxiety Go/No-Go Association Task (GNAT) and an avoidance-of-intimacy GNAT in order to assess an implicit Internal Working Model (IWM) of attachment; (b) to verify the effects of both measured implicit relational anxiety and implicit avoidance of intimacy on information processing. The implicit IWM measured by GNAT differed from the explicit IWM measured by questionnaires in terms of the effects on information processing. In particular, in subliminal priming tasks involving with others, implicit avoidance of intimacy predicted accelerated response times with negative stimulus words about attachment. Moreover, after subliminally priming stimulus words about self, implicit relational anxiety predicted delayed response times with negative stimulus words about attachment.

Dealing with the genetic load in bacterial synthetic biology circuits: convergences with the Ohm's law

PubMed Central

Carbonell-Ballestero, M.; Garcia-Ramallo, E.; Montañez, R.; Rodriguez-Caso, C.; Macía, J.

2016-01-01

Synthetic biology seeks to envision living cells as a matter of engineering. However, increasing evidence suggests that the genetic load imposed by the incorporation of synthetic devices in a living organism introduces a sort of unpredictability in the design process. As a result, individual part characterization is not enough to predict the behavior of designed circuits and thus, a costly trial-error process is eventually required. In this work, we provide a new theoretical framework for the predictive treatment of the genetic load. We mathematically and experimentally demonstrate that dependences among genes follow a quantitatively predictable behavior. Our theory predicts the observed reduction of the expression of a given synthetic gene when an extra genetic load is introduced in the circuit. The theory also explains that such dependence qualitatively differs when the extra load is added either by transcriptional or translational modifications. We finally show that the limitation of the cellular resources for gene expression leads to a mathematical formulation that converges to an expression analogous to the Ohm's law for electric circuits. Similitudes and divergences with this law are outlined. Our work provides a suitable framework with predictive character for the design process of complex genetic devices in synthetic biology. PMID:26656950

Solar prediction and intelligent machines

NASA Technical Reports Server (NTRS)

Johnson, Gordon G.

1987-01-01

The solar prediction program is aimed at reducing or eliminating the need to throughly understand the process previously developed and to still be able to produce a prediction. Substantial progress was made in identifying the procedures to be coded as well as testing some of the presently coded work. Another project involves work on developing ideas and software that should result in a machine capable of learning as well as carrying on an intelligent conversation over a wide range of topics. The underlying idea is to use primitive ideas and construct higher order ideas from these, which can then be easily related one to another.

Predicting Bacillus coagulans spores inactivation in tomato pulp under nonisothermal heat treatments.

PubMed

Zimmermann, Morgana; Longhi, Daniel A; Schaffner, Donald W; Aragão, Gláucia M F

2014-05-01

The knowledge and understanding of Bacillus coagulans inactivation during a thermal treatment in tomato pulp, as well as the influence of temperature variation during thermal processes are essential for design, calculation, and optimization of the process. The aims of this work were to predict B. coagulans spores inactivation in tomato pulp under varying time-temperature profiles with Gompertz-inspired inactivation model and to validate the model's predictions by comparing the predicted values with experimental data. B. coagulans spores in pH 4.3 tomato pulp at 4 °Brix were sealed in capillary glass tubes and heated in thermostatically controlled circulating oil baths. Seven different nonisothermal profiles in the range from 95 to 105 °C were studied. Predicted inactivation kinetics showed similar behavior to experimentally observed inactivation curves when the samples were exposed to temperatures in the upper range of this study (99 to 105 °C). Profiles that resulted in less accurate predictions were those where the range of temperatures analyzed were comparatively lower (inactivation profiles starting at 95 °C). The link between fail prediction and both lower starting temperature and magnitude of the temperature shift suggests some chemical or biological mechanism at work. Statistical analysis showed that overall model predictions were acceptable, with bias factors from 0.781 to 1.012, and accuracy factors from 1.049 to 1.351, and confirm that the models used were adequate to estimate B. coagulans spores inactivation under fluctuating temperature conditions in the range from 95 to 105 °C. How can we estimate Bacillus coagulans inactivation during sudden temperature shifts in heat processing? This article provides a validated model that can be used to predict B. coagulans under changing temperature conditions. B. coagulans is a spore-forming bacillus that spoils acidified food products. The mathematical model developed here can be used to predict the spoilage risk following thermal process deviations for tomato products. © 2014 Institute of Food Technologists®

Is rapid automatized naming related to reading and mathematics for the same reason(s)? A follow-up study from kindergarten to Grade 1.

PubMed

Georgiou, George K; Tziraki, Niki; Manolitsis, George; Fella, Argyro

2013-07-01

We examined (a) what rapid automatized naming (RAN) components (articulation time and/or pause time) predict reading and mathematics ability and (b) what processing skills involved in RAN (speed of processing, response inhibition, working memory, and/or phonological awareness) may explain its relationship with reading and mathematics. A sample of 72 children were followed from the beginning of kindergarten until the end of Grade 1 and were assessed on measures of RAN, general cognitive ability, speed of processing, attention, working memory, phonological awareness, reading, and mathematics. The results indicated that pause time was the critical component in both the RAN-reading and RAN-mathematics relationships and that it shared most of its predictive variance in reading and mathematics with speed of processing and working memory. Our findings further suggested that, unlike the relationship between RAN and reading fluency in Grade 1, there is nothing in the RAN task that is uniquely related to math. Copyright © 2013 Elsevier Inc. All rights reserved.

Big data learning and suggestions in modern apps

NASA Astrophysics Data System (ADS)

Sharma, G.; Nadesh, R. K.; ArivuSelvan, K.

2017-11-01

Among many other tasks involved for emergent location-based applications such as those involved in prescribing touring places and those focused on publicizing based on destination, destination prediction is vital. Dealing with destination prediction involves determining the probability of a location (destination) depending on historical trajectories. In this paper, a destination prediction based on probabilistic model (Machine Learning Model) feed-forward neural networks will be presented, which will work by making the observation of driver’s habits. Some individuals drive to same locations such as work involving same route every day of the working week. Here, streaming of real-time driving data will be sent through Kafka queue in apache storm for real-time processing and finally storing the data in MongoDB.

The role of work habits in the motivation of food safety behaviors.

PubMed

Hinsz, Verlin B; Nickell, Gary S; Park, Ernest S

2007-06-01

The authors considered work habits within an integrated framework of motivated behavior. A distinction made between automatic and controlled action led to 2 measures of work habits: a habit strength measure reflecting the 4 characteristics of automaticity and a measure of work routines under conscious control. Workers at a turkey processing plant (N = 162) responded to an extensive survey of these work habits measures with regard to food safety. Results indicated that attitudes and subjective norms predicted food safety intentions. These intentions, along with perceived behavior control and work habits, predicted reports of food safety behaviors. A mediation analysis indicated that the work routines measure accounted for the variance in self-reported behavior and mediated any effect of the habit strength measure. ((c) 2007 APA, all rights reserved).

Prognostics using Engineering and Environmental Parameters as Applied to State of Health (SOH) Radionuclide Aerosol Sampler Analyzer (RASA) Real-Time Monitoring

NASA Astrophysics Data System (ADS)

Hutchenson, K. D.; Hartley-McBride, S.; Saults, T.; Schmidt, D. P.

2006-05-01

The International Monitoring System (IMS) is composed in part of radionuclide particulate and gas monitoring systems. Monitoring the operational status of these systems is an important aspect of nuclear weapon test monitoring. Quality data, process control techniques, and predictive models are necessary to detect and predict system component failures. Predicting failures in advance provides time to mitigate these failures, thus minimizing operational downtime. The Provisional Technical Secretariat (PTS) requires IMS radionuclide systems be operational 95 percent of the time. The United States National Data Center (US NDC) offers contributing components to the IMS. This effort focuses on the initial research and process development using prognostics for monitoring and predicting failures of the RASA two (2) days into the future. The predictions, using time series methods, are input to an expert decision system, called SHADES (State of Health Airflow and Detection Expert System). The results enable personnel to make informed judgments about the health of the RASA system. Data are read from a relational database, processed, and displayed to the user in a GIS as a prototype GUI. This procedure mimics the real time application process that could be implemented as an operational system, This initial proof-of-concept effort developed predictive models focused on RASA components for a single site (USP79). Future work shall include the incorporation of other RASA systems, as well as their environmental conditions that play a significant role in performance. Similarly, SHADES currently accommodates specific component behaviors at this one site. Future work shall also include important environmental variables that play an important part of the prediction algorithms.

Statistical Learning Induces Discrete Shifts in the Allocation of Working Memory Resources

ERIC Educational Resources Information Center

Umemoto, Akina; Scolari, Miranda; Vogel, Edward K.; Awh, Edward

2010-01-01

Observers can voluntarily select which items are encoded into working memory, and the efficiency of this process strongly predicts memory capacity. Nevertheless, the present work suggests that voluntary intentions do not exclusively determine what is encoded into this online workspace. Observers indicated whether any items from a briefly stored…

Concurrent working memory load can facilitate selective attention: evidence for specialized load.

PubMed

Park, Soojin; Kim, Min-Shik; Chun, Marvin M

2007-10-01

Load theory predicts that concurrent working memory load impairs selective attention and increases distractor interference (N. Lavie, A. Hirst, J. W. de Fockert, & E. Viding). Here, the authors present new evidence that the type of concurrent working memory load determines whether load impairs selective attention or not. Working memory load was paired with a same/different matching task that required focusing on targets while ignoring distractors. When working memory items shared the same limited-capacity processing mechanisms with targets in the matching task, distractor interference increased. However, when working memory items shared processing with distractors in the matching task, distractor interference decreased, facilitating target selection. A specialized load account is proposed to describe the dissociable effects of working memory load on selective processing depending on whether the load overlaps with targets or with distractors. (c) 2007 APA

Individual differences in executive processing predict susceptibility to interference in verbal working memory.

PubMed

Hedden, Trey; Yoon, Carolyn

2006-09-01

Recent theories have suggested that resistance to interference is a unifying principle of executive function and that individual differences in interference may be explained by executive function (M. J. Kane & R. W. Engle, 2002). Measures of executive function, memory, and perceptual speed were obtained from 121 older adults (ages 63-82). We used structural equation modeling to investigate the relationships of these constructs with interference in a working memory task. Executive function was best described as two related subcomponent processes: shifting and updating goal-relevant representations and inhibition of proactive interference. These subcomponents were distinct from verbal and visual memory and speed. Individual differences in interference susceptibility and recollection were best predicted by shifting and updating and by resistance to proactive interference, and variability in familiarity was predicted by resistance to proactive interference and speed. ((c) 2006 APA, all rights reserved).

Machinery health prognostics: A systematic review from data acquisition to RUL prediction

NASA Astrophysics Data System (ADS)

Lei, Yaguo; Li, Naipeng; Guo, Liang; Li, Ningbo; Yan, Tao; Lin, Jing

2018-05-01

Machinery prognostics is one of the major tasks in condition based maintenance (CBM), which aims to predict the remaining useful life (RUL) of machinery based on condition information. A machinery prognostic program generally consists of four technical processes, i.e., data acquisition, health indicator (HI) construction, health stage (HS) division, and RUL prediction. Over recent years, a significant amount of research work has been undertaken in each of the four processes. And much literature has made an excellent overview on the last process, i.e., RUL prediction. However, there has not been a systematic review that covers the four technical processes comprehensively. To fill this gap, this paper provides a review on machinery prognostics following its whole program, i.e., from data acquisition to RUL prediction. First, in data acquisition, several prognostic datasets widely used in academic literature are introduced systematically. Then, commonly used HI construction approaches and metrics are discussed. After that, the HS division process is summarized by introducing its major tasks and existing approaches. Afterwards, the advancements of RUL prediction are reviewed including the popular approaches and metrics. Finally, the paper provides discussions on current situation, upcoming challenges as well as possible future trends for researchers in this field.

Evaluation of ceramics for stator application: Gas turbine engine report

NASA Technical Reports Server (NTRS)

Trela, W.; Havstad, P. H.

1978-01-01

Current ceramic materials, component fabrication processes, and reliability prediction capability for ceramic stators in an automotive gas turbine engine environment are assessed. Simulated engine duty cycle testing of stators conducted at temperatures up to 1093 C is discussed. Materials evaluated are SiC and Si3N4 fabricated from two near-net-shape processes: slip casting and injection molding. Stators for durability cycle evaluation and test specimens for material property characterization, and reliability prediction model prepared to predict stator performance in the simulated engine environment are considered. The status and description of the work performed for the reliability prediction modeling, stator fabrication, material property characterization, and ceramic stator evaluation efforts are reported.

Origins and Outcomes of Judgments about Work

PubMed Central

Johnson, Monica Kirkpatrick; Mortimer, Jeylan T.

2010-01-01

We evaluate the importance of judgments about work for the attainment process in the “new economy.” Findings show continuing links between social origins and work orientations at age 21/22, as well as significant impacts of work orientations on occupational outcomes at age 31/32. Higher socioeconomic status background, and stronger self-perceived ability, are tied to weaker extrinsic orientations. Young women are more intrinsically oriented than young men. Stronger intrinsic orientations predict holding jobs that offer more intrinsic rewards, self-direction, and security. Stronger extrinsic orientations predict higher biweekly earnings (largely via work hours), but not more prestigious, better paying, or more secure jobs. Judgments about work, and especially intrinsic orientations, thus remain important precursors of occupational attainments, despite economic turbulence and change in the transition to adulthood. PMID:21765555

Deception and Cognitive Load: Expanding Our Horizon with a Working Memory Model

PubMed Central

Sporer, Siegfried L.

2016-01-01

Recently, studies on deception and its detection have increased dramatically. Many of these studies rely on the “cognitive load approach” as the sole explanatory principle to understand deception. These studies have been exclusively on lies about negative actions (usually lies of suspects of [mock] crimes). Instead, we need to re-focus more generally on the cognitive processes involved in generating both lies and truths, not just on manipulations of cognitive load. Using Baddeley’s (2000, 2007, 2012) working memory model, which integrates verbal and visual processes in working memory with retrieval from long-term memory and control of action, not only verbal content cues but also nonverbal, paraverbal, and linguistic cues can be investigated within a single framework. The proposed model considers long-term semantic, episodic and autobiographical memory and their connections with working memory and action. It also incorporates ironic processes of mental control (Wegner, 1994, 2009), the role of scripts and schemata and retrieval cues and retrieval processes. Specific predictions of the model are outlined and support from selective studies is presented. The model is applicable to different types of reports, particularly about lies and truths about complex events, and to different modes of production (oral, hand-written, typed). Predictions regarding several moderator variables and methods to investigate them are proposed. PMID:27092090

Deception and Cognitive Load: Expanding Our Horizon with a Working Memory Model.

PubMed

Sporer, Siegfried L

2016-01-01

Recently, studies on deception and its detection have increased dramatically. Many of these studies rely on the "cognitive load approach" as the sole explanatory principle to understand deception. These studies have been exclusively on lies about negative actions (usually lies of suspects of [mock] crimes). Instead, we need to re-focus more generally on the cognitive processes involved in generating both lies and truths, not just on manipulations of cognitive load. Using Baddeley's (2000, 2007, 2012) working memory model, which integrates verbal and visual processes in working memory with retrieval from long-term memory and control of action, not only verbal content cues but also nonverbal, paraverbal, and linguistic cues can be investigated within a single framework. The proposed model considers long-term semantic, episodic and autobiographical memory and their connections with working memory and action. It also incorporates ironic processes of mental control (Wegner, 1994, 2009), the role of scripts and schemata and retrieval cues and retrieval processes. Specific predictions of the model are outlined and support from selective studies is presented. The model is applicable to different types of reports, particularly about lies and truths about complex events, and to different modes of production (oral, hand-written, typed). Predictions regarding several moderator variables and methods to investigate them are proposed.

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

NASA Astrophysics Data System (ADS)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we contend that creating believable soil carbon predictions requires a robust, transparent, and community-available benchmarking framework. I will present an ILAMB evaluation of several of the above-mentioned approaches in ACME, and attempt to motivate community adoption of this evaluation approach.

Process Optimization of Dual-Laser Beam Welding of Advanced Al-Li Alloys Through Hot Cracking Susceptibility Modeling

NASA Astrophysics Data System (ADS)

Tian, Yingtao; Robson, Joseph D.; Riekehr, Stefan; Kashaev, Nikolai; Wang, Li; Lowe, Tristan; Karanika, Alexandra

2016-07-01

Laser welding of advanced Al-Li alloys has been developed to meet the increasing demand for light-weight and high-strength aerospace structures. However, welding of high-strength Al-Li alloys can be problematic due to the tendency for hot cracking. Finding suitable welding parameters and filler material for this combination currently requires extensive and costly trial and error experimentation. The present work describes a novel coupled model to predict hot crack susceptibility (HCS) in Al-Li welds. Such a model can be used to shortcut the weld development process. The coupled model combines finite element process simulation with a two-level HCS model. The finite element process model predicts thermal field data for the subsequent HCS hot cracking prediction. The model can be used to predict the influences of filler wire composition and welding parameters on HCS. The modeling results have been validated by comparing predictions with results from fully instrumented laser welds performed under a range of process parameters and analyzed using high-resolution X-ray tomography to identify weld defects. It is shown that the model is capable of accurately predicting the thermal field around the weld and the trend of HCS as a function of process parameters.

Memory processes of flight situation awareness: interactive roles of working memory capacity, long-term working memory, and expertise.

PubMed

Sohn, Young Woo; Doane, Stephanie M

2004-01-01

This research examined the role of working memory (WM) capacity and long-term working memory (LT-WM) in flight situation awareness (SA). We developed spatial and verbal measures of WM capacity and LT-WM skill and then determined the ability of these measures to predict pilot performance on SA tasks. Although both spatial measures of WM capacity and LT-WM skills were important predictors of SA performance, their importance varied as a function of pilot expertise. Spatial WM capacity was most predictive of SA performance for novices, whereas spatial LT-WM skill based on configurations of control flight elements (attitude and power) was most predictive for experts. Furthermore, evidence for an interactive role of WM and LT-WM mechanisms was indicated. Actual or potential applications of this research include cognitive analysis of pilot expertise and aviation training.

Fast and Accurate Prediction of Stratified Steel Temperature During Holding Period of Ladle

NASA Astrophysics Data System (ADS)

Deodhar, Anirudh; Singh, Umesh; Shukla, Rishabh; Gautham, B. P.; Singh, Amarendra K.

2017-04-01

Thermal stratification of liquid steel in a ladle during the holding period and the teeming operation has a direct bearing on the superheat available at the caster and hence on the caster set points such as casting speed and cooling rates. The changes in the caster set points are typically carried out based on temperature measurements at the end of tundish outlet. Thermal prediction models provide advance knowledge of the influence of process and design parameters on the steel temperature at various stages. Therefore, they can be used in making accurate decisions about the caster set points in real time. However, this requires both fast and accurate thermal prediction models. In this work, we develop a surrogate model for the prediction of thermal stratification using data extracted from a set of computational fluid dynamics (CFD) simulations, pre-determined using design of experiments technique. Regression method is used for training the predictor. The model predicts the stratified temperature profile instantaneously, for a given set of process parameters such as initial steel temperature, refractory heat content, slag thickness, and holding time. More than 96 pct of the predicted values are within an error range of ±5 K (±5 °C), when compared against corresponding CFD results. Considering its accuracy and computational efficiency, the model can be extended for thermal control of casting operations. This work also sets a benchmark for developing similar thermal models for downstream processes such as tundish and caster.

The U.S. Earthquake Prediction Program

USGS Publications Warehouse

Wesson, R.L.; Filson, J.R.

1981-01-01

There are two distinct motivations for earthquake prediction. The mechanistic approach aims to understand the processes leading to a large earthquake. The empirical approach is governed by the immediate need to protect lives and property. With our current lack of knowledge about the earthquake process, future progress cannot be made without gathering a large body of measurements. These are required not only for the empirical prediction of earthquakes, but also for the testing and development of hypotheses that further our understanding of the processes at work. The earthquake prediction program is basically a program of scientific inquiry, but one which is motivated by social, political, economic, and scientific reasons. It is a pursuit that cannot rely on empirical observations alone nor can it carried out solely on a blackboard or in a laboratory. Experiments must be carried out in the real Earth. 

Self Improving Methods for Materials and Process Design

DTIC Science & Technology

1998-08-31

using inductive coupling techniques. The first phase of the work focuses on developing an artificial neural network learning for function approximation...developing an artificial neural network learning algorithm for time-series prediction. The third phase of the work focuses on model selection. We have

Competing Core Processes in Attention-Deficit/Hyperactivity Disorder (ADHD): Do Working Memory Deficiencies Underlie Behavioral Inhibition Deficits?

ERIC Educational Resources Information Center

Alderson, R. Matt; Rapport, Mark D.; Hudec, Kristen L.; Sarver, Dustin E.; Kofler, Michael J.

2010-01-01

The current study examined competing predictions of the working memory and behavioral inhibition models of ADHD. Behavioral inhibition was measured using a conventional stop-signal task, and central executive, phonological, and visuospatial working memory components (Baddeley 2007) were assessed in 14 children with ADHD and 13 typically developing…

Word-Decoding Skill Interacts with Working Memory Capacity to Influence Inference Generation during Reading

ERIC Educational Resources Information Center

Hamilton, Stephen; Freed, Erin; Long, Debra L.

2016-01-01

The aim of this study was to examine predictions derived from a proposal about the relation between word-decoding skill and working memory capacity, called verbal efficiency theory. The theory states that poor word representations and slow decoding processes consume resources in working memory that would otherwise be used to execute high-level…

Effects of emotional content on working memory capacity.

PubMed

Garrison, Katie E; Schmeichel, Brandon J

2018-02-13

Emotional events tend to be remembered better than neutral events, but emotional states and stimuli may also interfere with cognitive processes that underlie memory performance. The current study investigated the effects of emotional content on working memory capacity (WMC), which involves both short term storage and executive attention control. We tested competing hypotheses in a preregistered experiment (N = 297). The emotional enhancement hypothesis predicts that emotional stimuli attract attention and additional processing resources relative to neutral stimuli, thereby making it easier to encode and store emotional information in WMC. The emotional impairment hypothesis, by contrast, predicts that emotional stimuli interfere with attention control and the active maintenance of information in working memory. Participants completed a common measure of WMC (the operation span task; Turner, M. L., & Engle, R. W. [1989]. Is working memory capacity task dependent? Journal of Memory and Language, 28, 127-154) that included either emotional or neutral words. Results revealed that WMC was reduced for emotional words relative to neutral words, consistent with the emotional impairment hypothesis.

Safety behavior: Job demands, job resources, and perceived management commitment to safety.

PubMed

Hansez, Isabelle; Chmiel, Nik

2010-07-01

The job demands-resources model posits that job demands and resources influence outcomes through job strain and work engagement processes. We test whether the model can be extended to effort-related "routine" safety violations and "situational" safety violations provoked by the organization. In addition we test more directly the involvement of job strain than previous studies which have used burnout measures. Structural equation modeling provided, for the first time, evidence of predicted relationships between job strain and "routine" violations and work engagement with "routine" and "situational" violations, thereby supporting the extension of the job demands-resources model to safety behaviors. In addition our results showed that a key safety-specific construct 'perceived management commitment to safety' added to the explanatory power of the job demands-resources model. A predicted path from job resources to perceived management commitment to safety was highly significant, supporting the view that job resources can influence safety behavior through both general motivational involvement in work (work engagement) and through safety-specific processes.

[Formula: see text]Executive functions and social information processing in adolescents with severe behavior problems.

PubMed

Van Nieuwenhuijzen, M; Van Rest, M M; Embregts, P J C M; Vriens, A; Oostermeijer, S; Van Bokhoven, I; Matthys, W

2017-02-01

One tradition in research for explaining aggression and antisocial behavior has focused on social information processing (SIP). Aggression and antisocial behavior have also been studied from the perspective of executive functions (EFs), the higher-order cognitive abilities that affect other cognitive processes, such as social cognitive processes. The main goal of the present study is to provide insight into the relation between EFs and SIP in adolescents with severe behavior problems. Because of the hierarchical relation between EFs and SIP, we examined EFs as predictors of SIP. We hypothesized that, first, focused attention predicts encoding and interpretation, second, inhibition predicts interpretation, response generation, evaluation, and selection, and third, working memory predicts response generation and selection. The participants consisted of 94 respondents living in residential facilities aged 12-20 years, all showing behavior problems in the clinical range according to care staff. EFs were assessed using subtests from the Amsterdam Neuropsychological Test battery. Focused attention was measured by the Flanker task, inhibition by the GoNoGo task, and working memory by the Visual Spatial Sequencing task. SIP was measured by video vignettes and a structured interview. The results indicate that positive evaluation of aggressive responses is predicted by impaired inhibition and selection of aggressive responses by a combination of impaired focused attention and inhibition. It is concluded that different components of EFs as higher-order cognitive abilities affect SIP.

Design of high-performance parallelized gene predictors in MATLAB.

PubMed

Rivard, Sylvain Robert; Mailloux, Jean-Gabriel; Beguenane, Rachid; Bui, Hung Tien

2012-04-10

This paper proposes a method of implementing parallel gene prediction algorithms in MATLAB. The proposed designs are based on either Goertzel's algorithm or on FFTs and have been implemented using varying amounts of parallelism on a central processing unit (CPU) and on a graphics processing unit (GPU). Results show that an implementation using a straightforward approach can require over 4.5 h to process 15 million base pairs (bps) whereas a properly designed one could perform the same task in less than five minutes. In the best case, a GPU implementation can yield these results in 57 s. The present work shows how parallelism can be used in MATLAB for gene prediction in very large DNA sequences to produce results that are over 270 times faster than a conventional approach. This is significant as MATLAB is typically overlooked due to its apparent slow processing time even though it offers a convenient environment for bioinformatics. From a practical standpoint, this work proposes two strategies for accelerating genome data processing which rely on different parallelization mechanisms. Using a CPU, the work shows that direct access to the MEX function increases execution speed and that the PARFOR construct should be used in order to take full advantage of the parallelizable Goertzel implementation. When the target is a GPU, the work shows that data needs to be segmented into manageable sizes within the GFOR construct before processing in order to minimize execution time.

Working memory and the strategic control of attention in older and younger adults.

PubMed

Hayes, Melissa G; Kelly, Andrew J; Smith, Anderson D

2013-03-01

The objective of this study was to investigate the effects of aging on the strategic control of attention and the extent to which this relationship is mediated by working memory capacity (WMC). This study also sought to investigate boundary conditions wherein age differences in selectivity may occur. Across 2 studies, the value-directed remembering task used by Castel and colleagues (Castel, A. D., Balota, D. A., & McCabe, D. P. (2009). Memory efficiency and the strategic control of attention at encoding: Impairments of value-directed remembering in Alzheimer's Disease. Neuropsychology, 23, 297-306) was modified to include value-directed forgetting. Study 2 incorporated valence as an additional task demand, and age differences were predicted in both studies due to increased demands of controlled processing. Automated operation span and Stroop span were included as working memory measures, and working memory was predicted to mediate performance. Results confirmed these predictions, as older adults were less efficient in maximizing selectivity scores when high demands were placed on selectivity processes, and working memory was found to mediate performance on this task. When list length was increased from previous studies and participants were required to actively forget negative-value words, older adults were not able to selectively encode high-value information to the same degree as younger adults. Furthermore, WMC appears to support the ability to selectively encode information.

Prediction of Cutting Force in Turning Process-an Experimental Approach

NASA Astrophysics Data System (ADS)

Thangarasu, S. K.; Shankar, S.; Thomas, A. Tony; Sridhar, G.

2018-02-01

This Paper deals with a prediction of Cutting forces in a turning process. The turning process with advanced cutting tool has a several advantages over grinding such as short cycle time, process flexibility, compatible surface roughness, high material removal rate and less environment problems without the use of cutting fluid. In this a full bridge dynamometer has been used to measure the cutting forces over mild steel work piece and cemented carbide insert tool for different combination of cutting speed, feed rate and depth of cut. The experiments are planned based on taguchi design and measured cutting forces were compared with the predicted forces in order to validate the feasibility of the proposed design. The percentage contribution of each process parameter had been analyzed using Analysis of Variance (ANOVA). Both the experimental results taken from the lathe tool dynamometer and the designed full bridge dynamometer were analyzed using Taguchi design of experiment and Analysis of Variance.

The combined effects of self-referent information processing and ruminative responses on adolescent depression.

PubMed

Black, Stephanie Winkeljohn; Pössel, Patrick

2013-08-01

Adolescents who develop depression have worse interpersonal and affective experiences and are more likely to develop substance problems and/or suicidal ideation compared to adolescents who do not develop depression. This study examined the combined effects of negative self-referent information processing and rumination (i.e., brooding and reflection) on adolescent depressive symptoms. It was hypothesized that the interaction of negative self-referent information processing and brooding would significantly predict depressive symptoms, while the interaction of negative self-referent information processing and reflection would not predict depressive symptoms. Adolescents (n = 92; 13-15 years; 34.7% female) participated in a 6-month longitudinal study. Self-report instruments measured depressive symptoms and rumination; a cognitive task measured information processing. Path modelling in Amos 19.0 analyzed the data. The interaction of negative information processing and brooding significantly predicted an increase in depressive symptoms 6 months later. The interaction of negative information processing and reflection did not significantly predict depression, however, the model not meet a priori standards to accept the null hypothesis. Results suggest clinicians working with adolescents at-risk for depression should consider focusing on the reduction of brooding and negative information processing to reduce long-term depressive symptoms.

Application of indoor noise prediction in the real world

NASA Astrophysics Data System (ADS)

Lewis, David N.

2002-11-01

Predicting indoor noise in industrial workrooms is an important part of the process of designing industrial plants. Predicted levels are used in the design process to determine compliance with occupational-noise regulations, and to estimate levels inside the walls in order to predict community noise radiated from the building. Once predicted levels are known, noise-control strategies can be developed. In this paper an overview of over 20 years of experience is given with the use of various prediction approaches to manage noise in Unilever plants. This work has applied empirical and ray-tracing approaches separately, and in combination, to design various packaging and production plants and other facilities. The advantages of prediction methods in general, and of the various approaches in particular, will be discussed. A case-study application of prediction methods to the optimization of noise-control measures in a food-packaging plant will be presented. Plans to acquire a simplified prediction model for use as a company noise-screening tool will be discussed.

A Systematic Review of the Reliability and Validity of Behavioural Tests Used to Assess Behavioural Characteristics Important in Working Dogs.

PubMed

Brady, Karen; Cracknell, Nina; Zulch, Helen; Mills, Daniel Simon

2018-01-01

Working dogs are selected based on predictions from tests that they will be able to perform specific tasks in often challenging environments. However, withdrawal from service in working dogs is still a big problem, bringing into question the reliability of the selection tests used to make these predictions. A systematic review was undertaken aimed at bringing together available information on the reliability and predictive validity of the assessment of behavioural characteristics used with working dogs to establish the quality of selection tests currently available for use to predict success in working dogs. The search procedures resulted in 16 papers meeting the criteria for inclusion. A large range of behaviour tests and parameters were used in the identified papers, and so behaviour tests and their underpinning constructs were grouped on the basis of their relationship with positive core affect (willingness to work, human-directed social behaviour, object-directed play tendencies) and negative core affect (human-directed aggression, approach withdrawal tendencies, sensitivity to aversives). We then examined the papers for reports of inter-rater reliability, within-session intra-rater reliability, test-retest validity and predictive validity. The review revealed a widespread lack of information relating to the reliability and validity of measures to assess behaviour and inconsistencies in terminologies, study parameters and indices of success. There is a need to standardise the reporting of these aspects of behavioural tests in order to improve the knowledge base of what characteristics are predictive of optimal performance in working dog roles, improving selection processes and reducing working dog redundancy. We suggest the use of a framework based on explaining the direct or indirect relationship of the test with core affect.

Predicting color traits of intact broiler breast fillets using visible and infrared-light

USDA-ARS?s Scientific Manuscript database

The ability of using visible and near-infrared (Vis/NIR) spectroscopy with wavelengths ranging from 400 to 2500nm to predict broiler breast fillets color traits was assessed in this study. Deboning fillets from 214 carcasses slaughtered in a commercial processing plant were included in this work, sp...

Historical Note: The Past Thirty Years in Information Retrieval.

ERIC Educational Resources Information Center

Salton, Gerard

1987-01-01

Briefly reviews early work in documentation and text processing, and predictions that were made about the creative role of computers in information retrieval. An attempt is made to explain why these predictions were not fulfilled and conclusions are drawn regarding the limits of computer power in text retrieval applications. (Author/CLB)

Predicting Word Reading and Comprehension with Executive Function and Speed Measures across Development: A Latent Variable Analysis

ERIC Educational Resources Information Center

Christopher, Micaela E.; Miyake, Akira; Keenan, Janice M.; Pennington, Bruce; DeFries, John C.; Wadsworth, Sally J.; Willcutt, Erik; Olson, Richard K.

2012-01-01

The present study explored whether different executive control and speed measures (working memory, inhibition, processing speed, and naming speed) independently predict individual differences in word reading and reading comprehension. Although previous studies suggest these cognitive constructs are important for reading, the authors analyze the…

Probabilistic framework for product design optimization and risk management

NASA Astrophysics Data System (ADS)

Keski-Rahkonen, J. K.

2018-05-01

Probabilistic methods have gradually gained ground within engineering practices but currently it is still the industry standard to use deterministic safety margin approaches to dimensioning components and qualitative methods to manage product risks. These methods are suitable for baseline design work but quantitative risk management and product reliability optimization require more advanced predictive approaches. Ample research has been published on how to predict failure probabilities for mechanical components and furthermore to optimize reliability through life cycle cost analysis. This paper reviews the literature for existing methods and tries to harness their best features and simplify the process to be applicable in practical engineering work. Recommended process applies Monte Carlo method on top of load-resistance models to estimate failure probabilities. Furthermore, it adds on existing literature by introducing a practical framework to use probabilistic models in quantitative risk management and product life cycle costs optimization. The main focus is on mechanical failure modes due to the well-developed methods used to predict these types of failures. However, the same framework can be applied on any type of failure mode as long as predictive models can be developed.

The components of working memory updating: an experimental decomposition and individual differences.

PubMed

Ecker, Ullrich K H; Lewandowsky, Stephan; Oberauer, Klaus; Chee, Abby E H

2010-01-01

Working memory updating (WMU) has been identified as a cognitive function of prime importance for everyday tasks and has also been found to be a significant predictor of higher mental abilities. Yet, little is known about the constituent processes of WMU. We suggest that operations required in a typical WMU task can be decomposed into 3 major component processes: retrieval, transformation, and substitution. We report a large-scale experiment that instantiated all possible combinations of those 3 component processes. Results show that the 3 components make independent contributions to updating performance. We additionally present structural equation models that link WMU task performance and working memory capacity (WMC) measures. These feature the methodological advancement of estimating interindividual covariation and experimental effects on mean updating measures simultaneously. The modeling results imply that WMC is a strong predictor of WMU skills in general, although some component processes-in particular, substitution skills-were independent of WMC. Hence, the reported predictive power of WMU measures may rely largely on common WM functions also measured in typical WMC tasks, although substitution skills may make an independent contribution to predicting higher mental abilities. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Implementation Plan for Flexible Automation in U.S. Shipyards

DTIC Science & Technology

1985-01-01

process steps, cramped work sites, interrupted geometries , irregular or novel shapes, and other factors that affect automatability. We also try to...held by 2 hands in awkward places. Interrupt geometry of plates and beams. Cannot predict outcome. Creates need to measure and recut. Automation, if...of standard. enough over time I every job. I Rearrange work.Redefine work units. Too many interruptions Time, space, geometry only a little work gets

Predictors of Processing-Based Task Performance in Bilingual and Monolingual Children

PubMed Central

Buac, Milijana; Gross, Megan; Kaushanskaya, Margarita

2016-01-01

In the present study we examined performance of bilingual Spanish-English-speaking and monolingual English-speaking school-age children on a range of processing-based measures within the framework of Baddeley’s working memory model. The processing-based measures included measures of short-term memory, measures of working memory, and a novel word-learning task. Results revealed that monolinguals outperformed bilinguals on the short-term memory tasks but not the working memory and novel word-learning tasks. Further, children’s vocabulary skills and socioeconomic status (SES) were more predictive of processing-based task performance in the bilingual group than the monolingual group. Together, these findings indicate that processing-based tasks that engage verbal working memory rather than short-term memory may be better-suited for diagnostic purposes with bilingual children. However, even verbal working memory measures are sensitive to bilingual children’s language-specific knowledge and demographic characteristics, and therefore may have limited clinical utility. PMID:27179914

Dopamine D1 Sensitivity in the Prefrontal Cortex Predicts General Cognitive Abilities and is Modulated by Working Memory Training

ERIC Educational Resources Information Center

Wass, Christopher; Pizzo, Alessandro; Sauce, Bruno; Kawasumi, Yushi; Sturzoiu, Tudor; Ree, Fred; Otto, Tim; Matzel, Louis D.

2013-01-01

A common source of variance (i.e., "general intelligence") underlies an individual's performance across diverse tests of cognitive ability, and evidence indicates that the processing efficacy of working memory may serve as one such source of common variance. One component of working memory, selective attention, has been reported to…

Computational Modeling of Hydrodynamics and Scour around Underwater Munitions

NASA Astrophysics Data System (ADS)

Liu, X.; Xu, Y.

2017-12-01

Munitions deposited in water bodies are a big threat to human health, safety, and environment. It is thus imperative to predict the motion and the resting status of the underwater munitions. A multitude of physical processes are involved, which include turbulent flows, sediment transport, granular material mechanics, 6 degree-of-freedom motion of the munition, and potential liquefaction. A clear understanding of this unique physical setting is currently lacking. Consequently, it is extremely hard to make reliable predictions. In this work, we present the computational modeling of two importance processes, i.e., hydrodynamics and scour, around munition objects. Other physical processes are also considered in our comprehensive model. However, they are not shown in this talk. To properly model the dynamics of the deforming bed and the motion of the object, an immersed boundary method is implemented in the open source CFD package OpenFOAM. Fixed bed and scour cases are simulated and compared with laboratory experiments. The future work of this project will implement the coupling between all the physical processes.

The Ease of Language Understanding (ELU) model: theoretical, empirical, and clinical advances

PubMed Central

Rönnberg, Jerker; Lunner, Thomas; Zekveld, Adriana; Sörqvist, Patrik; Danielsson, Henrik; Lyxell, Björn; Dahlström, Örjan; Signoret, Carine; Stenfelt, Stefan; Pichora-Fuller, M. Kathleen; Rudner, Mary

2013-01-01

Working memory is important for online language processing during conversation. We use it to maintain relevant information, to inhibit or ignore irrelevant information, and to attend to conversation selectively. Working memory helps us to keep track of and actively participate in conversation, including taking turns and following the gist. This paper examines the Ease of Language Understanding model (i.e., the ELU model, Rönnberg, 2003; Rönnberg et al., 2008) in light of new behavioral and neural findings concerning the role of working memory capacity (WMC) in uni-modal and bimodal language processing. The new ELU model is a meaning prediction system that depends on phonological and semantic interactions in rapid implicit and slower explicit processing mechanisms that both depend on WMC albeit in different ways. It is based on findings that address the relationship between WMC and (a) early attention processes in listening to speech, (b) signal processing in hearing aids and its effects on short-term memory, (c) inhibition of speech maskers and its effect on episodic long-term memory, (d) the effects of hearing impairment on episodic and semantic long-term memory, and finally, (e) listening effort. New predictions and clinical implications are outlined. Comparisons with other WMC and speech perception models are made. PMID:23874273

The predictive mind and the experience of visual art work

PubMed Central

Kesner, Ladislav

2014-01-01

Among the main challenges of the predictive brain/mind concept is how to link prediction at the neural level to prediction at the cognitive-psychological level and finding conceptually robust and empirically verifiable ways to harness this theoretical framework toward explaining higher-order mental and cognitive phenomena, including the subjective experience of aesthetic and symbolic forms. Building on the tentative prediction error account of visual art, this article extends the application of the predictive coding framework to the visual arts. It does so by linking this theoretical discussion to a subjective, phenomenological account of how a work of art is experienced. In order to engage more deeply with a work of art, viewers must be able to tune or adapt their prediction mechanism to recognize art as a specific class of objects whose ontological nature defies predictability, and they must be able to sustain a productive flow of predictions from low-level sensory, recognitional to abstract semantic, conceptual, and affective inferences. The affective component of the process of predictive error optimization that occurs when a viewer enters into dialog with a painting is constituted both by activating the affective affordances within the image and by the affective consequences of prediction error minimization itself. The predictive coding framework also has implications for the problem of the culturality of vision. A person’s mindset, which determines what top–down expectations and predictions are generated, is co-constituted by culture-relative skills and knowledge, which form hyperpriors that operate in the perception of art. PMID:25566111

The predictive mind and the experience of visual art work.

PubMed

Kesner, Ladislav

2014-01-01

Among the main challenges of the predictive brain/mind concept is how to link prediction at the neural level to prediction at the cognitive-psychological level and finding conceptually robust and empirically verifiable ways to harness this theoretical framework toward explaining higher-order mental and cognitive phenomena, including the subjective experience of aesthetic and symbolic forms. Building on the tentative prediction error account of visual art, this article extends the application of the predictive coding framework to the visual arts. It does so by linking this theoretical discussion to a subjective, phenomenological account of how a work of art is experienced. In order to engage more deeply with a work of art, viewers must be able to tune or adapt their prediction mechanism to recognize art as a specific class of objects whose ontological nature defies predictability, and they must be able to sustain a productive flow of predictions from low-level sensory, recognitional to abstract semantic, conceptual, and affective inferences. The affective component of the process of predictive error optimization that occurs when a viewer enters into dialog with a painting is constituted both by activating the affective affordances within the image and by the affective consequences of prediction error minimization itself. The predictive coding framework also has implications for the problem of the culturality of vision. A person's mindset, which determines what top-down expectations and predictions are generated, is co-constituted by culture-relative skills and knowledge, which form hyperpriors that operate in the perception of art.

On the role of passion for work in burnout: a process model.

PubMed

Vallerand, Robert J; Paquet, Yvan; Philippe, Frederick L; Charest, Julie

2010-02-01

The purpose of the present research was to test a model on the role of passion for work in professional burnout. This model posits that obsessive passion produces conflict between work and other life activities because the person cannot let go of the work activity. Conversely, harmonious passion is expected to prevent conflict while positively contributing to work satisfaction. Finally, conflict is expected to contribute to burnout, whereas work satisfaction should prevent its occurrence. This model was tested in 2 studies with nurses in 2 cultures. Using a cross-sectional design, Study 1 (n=97) provided support for the model with nurses from France. In Study 2 (n=258), a prospective design was used to further test the model with nurses from the Province of Quebec over a 6-month period. Results provided support for the model. Specifically, harmonious passion predicted an increase in work satisfaction and a decrease in conflict. Conversely, obsessive passion predicted an increase of conflict. In turn, work satisfaction and conflict predicted decreases and increases in burnout changes that took place over time. The results have important implications for theory and research on passion as well as burnout.

Numerical predictors of arithmetic success in grades 1-6.

PubMed

Lyons, Ian M; Price, Gavin R; Vaessen, Anniek; Blomert, Leo; Ansari, Daniel

2014-09-01

Math relies on mastery and integration of a wide range of simpler numerical processes and concepts. Recent work has identified several numerical competencies that predict variation in math ability. We examined the unique relations between eight basic numerical skills and early arithmetic ability in a large sample (N = 1391) of children across grades 1-6. In grades 1-2, children's ability to judge the relative magnitude of numerical symbols was most predictive of early arithmetic skills. The unique contribution of children's ability to assess ordinality in numerical symbols steadily increased across grades, overtaking all other predictors by grade 6. We found no evidence that children's ability to judge the relative magnitude of approximate, nonsymbolic numbers was uniquely predictive of arithmetic ability at any grade. Overall, symbolic number processing was more predictive of arithmetic ability than nonsymbolic number processing, though the relative importance of symbolic number ability appears to shift from cardinal to ordinal processing. © 2014 John Wiley & Sons Ltd.

The Role of Working Memory in Metaphor Production and Comprehension

ERIC Educational Resources Information Center

Chiappe, Dan L.; Chiappe, Penny

2007-01-01

The following tested Kintsch's [Kintsch, W. (2000). "Metaphor comprehension: a computational theory." "Psychonomic Bulletin & Review," 7, 257-266 and Kintsch, W. (2001). "Predication." "Cognitive Science," 25, 173-202] Predication Model, which predicts that working memory capacity is an important factor in metaphor processing. In support of his…

Compression in Working Memory and Its Relationship With Fluid Intelligence.

PubMed

Chekaf, Mustapha; Gauvrit, Nicolas; Guida, Alessandro; Mathy, Fabien

2018-06-01

Working memory has been shown to be strongly related to fluid intelligence; however, our goal is to shed further light on the process of information compression in working memory as a determining factor of fluid intelligence. Our main hypothesis was that compression in working memory is an excellent indicator for studying the relationship between working-memory capacity and fluid intelligence because both depend on the optimization of storage capacity. Compressibility of memoranda was estimated using an algorithmic complexity metric. The results showed that compressibility can be used to predict working-memory performance and that fluid intelligence is well predicted by the ability to compress information. We conclude that the ability to compress information in working memory is the reason why both manipulation and retention of information are linked to intelligence. This result offers a new concept of intelligence based on the idea that compression and intelligence are equivalent problems. Copyright © 2018 Cognitive Science Society, Inc.

The working alliance and Clinician-assisted Emotional Disclosure for rheumatoid arthritis.

PubMed

Lumley, Mark A; Anderson, Timothy; Ankawi, Brett; Goldman, Gregory; Perri, LisaCaitlin M; Bianco, Joseph A; Keefe, Francis J

2018-01-01

The working alliance predicts improvement following general psychotherapy, but how it operates in brief interventions conducted with medically ill patients is unknown. Also, the role of the working alliance may differ in emotion-focused versus educational interventions. We report secondary analyses of a randomized clinical trial (Keefe et al.) [35], in which patients with rheumatoid arthritis (RA) received four nurse-provided sessions of either a) Clinician-assisted Emotional Disclosure (CAED), which emphasized the disclosure, expression, and processing of emotions related to stressful events; or b) Arthritis Education (AE), which provided basic education about RA. The Working Alliance Inventory was completed by both patient and nurse after each session. Patients were evaluated on multiple health measures at baseline and 1, 3, and 12months post-treatment. Analyses compared the alliance between interventions and related the alliance to outcomes within interventions. Patients in CAED reported a lower alliance than patients in AE. Interestingly, in CAED, lower alliance ratings predicted better outcomes (improved functioning, lower pain behaviors, lower inflammation, lower daily stress), whereas in AE, the working alliance was largely not predictive of outcomes. Having nurses encourage emotional disclosure among patients with RA reduced the patients' working alliance, but a lower alliance nonetheless predicted better patient outcomes, perhaps reflecting successful engagement in an intervention that is emotionally and relationally challenging. The level and predictive validity of the working alliance likely depends on patient, provider, and intervention factors, and further study of the working alliance in psychosocial interventions in the medical context is needed. Copyright © 2017 Elsevier Inc. All rights reserved.

A Thermo-Poromechanics Finite Element Model for Predicting Arterial Tissue Fusion

NASA Astrophysics Data System (ADS)

Fankell, Douglas P.

This work provides modeling efforts and supplemental experimental work performed towards the ultimate goal of modeling heat transfer, mass transfer, and deformation occurring in biological tissue, in particular during arterial fusion and cutting. Developing accurate models of these processes accomplishes two goals. First, accurate models would enable engineers to design devices to be safer and less expensive. Second, the mechanisms behind tissue fusion and cutting are widely unknown; models with the ability to accurately predict physical phenomena occurring in the tissue will allow for insight into the underlying mechanisms of the processes. This work presents three aims and the efforts in achieving them, leading to an accurate model of tissue fusion and more broadly the thermo-poromechanics (TPM) occurring within biological tissue. Chapters 1 and 2 provide the motivation for developing accurate TPM models of biological tissue and an overview of previous modeling efforts. In Chapter 3, a coupled thermo-structural finite element (FE) model with the ability to predict arterial cutting is offered. From the work presented in Chapter 3, it became obvious a more detailed model was needed. Chapter 4 meets this need by presenting small strain TPM theory and its implementation in an FE code. The model is then used to simulate thermal tissue fusion. These simulations show the model's promise in predicting the water content and temperature of arterial wall tissue during the fusion process, but it is limited by its small deformation assumptions. Chapters 5-7 attempt to address this limitation by developing and implementing a large deformation TPM FE model. Chapters 5, 6, and 7 present a thermodynamically consistent, large deformation TPM FE model and its ability to simulate tissue fusion. Ultimately, this work provides several methods of simulating arterial tissue fusion and the thermo-poromechanics of biological tissue. It is the first work, to the author's knowledge, to simulate the fully coupled TPM of biological tissue and the first to present a fully coupled large deformation TPM FE model. In doing so, a stepping stone for more advanced modeling of biological tissue has been laid.

The influence of work characteristics, emotional display rules and affectivity on burnout and job satisfaction: A survey among geriatric care workers.

PubMed

Rouxel, Géraldine; Michinov, Estelle; Dodeler, Virginie

2016-10-01

Previous studies have demonstrated that geriatric care employees are exposed to a large number of factors that can affect their levels of job satisfaction and occupational stress. Although working with elderly people is emotionally demanding, little research has been done on the role played by perceptions of emotional display rules, alongside more traditional work characteristics and individual factors, in the prediction of geriatric care employees' wellbeing. The aim of the present study was to examine the role played by work characteristics (job demands, job control, emotional display rules) and individual (affectivity) factors to predict job satisfaction and burnout among French geriatric care nurses. Questionnaires were sent to 891 employees working in 32 geriatric care centers in France. A total of 371 valid questionnaires (response rate: 41.60%) were analyzed using structural equation modeling techniques. Results revealed two main processes of burnout and job satisfaction among women geriatric care workers, namely a salutogenic process and a pathogenic process. As expected, negative affectivity, low job status, perceived negative display rules and job demands are involved in the pathogenic process; while positive affectivity, perceived positive display rules and job control are implied in the salutogenic one. More specifically, as expected, negative affectivity is a positive predictor of burnout, both directly and indirectly through its impact on perceived negative display rules and job demands. Moreover, negative affectivity was negatively related to job satisfaction. Simultaneously, positive affectivity can predict job satisfaction, both directly and indirectly through its impact on perceived positive display rules and job control. Positive affectivity is also a negative predictor of burnout. Practical implications are discussed to support intervention programs that develop healthy workplaces, and also to inform nurses about how to manage emotional display rules in retirement homes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prediction of Continuous Cooling Transformation Diagrams for Dual-Phase Steels from the Intercritical Region

NASA Astrophysics Data System (ADS)

Colla, V.; Desanctis, M.; Dimatteo, A.; Lovicu, G.; Valentini, R.

2011-09-01

The purpose of the present work is the implementation and validation of a model able to predict the microstructure changes and the mechanical properties in the modern high-strength dual-phase steels after the continuous annealing process line (CAPL) and galvanizing (Galv) process. Experimental continuous cooling transformation (CCT) diagrams for 13 differently alloying dual-phase steels were measured by dilatometry from the intercritical range and were used to tune the parameters of the microstructural prediction module of the model. Mechanical properties and microstructural features were measured for more than 400 dual-phase steels simulating the CAPL and Galv industrial process, and the results were used to construct the mechanical model that predicts mechanical properties from microstructural features, chemistry, and process parameters. The model was validated and proved its efficiency in reproducing the transformation kinetic and mechanical properties of dual-phase steels produced by typical industrial process. Although it is limited to the dual-phase grades and chemical compositions explored, this model will constitute a useful tool for the steel industry.

Eliminating Unpredictable Variation through Iterated Learning

ERIC Educational Resources Information Center

Smith, Kenny; Wonnacott, Elizabeth

2010-01-01

Human languages may be shaped not only by the (individual psychological) processes of language acquisition, but also by population-level processes arising from repeated language learning and use. One prevalent feature of natural languages is that they avoid unpredictable variation. The current work explores whether linguistic predictability might…

Machine learning for the New York City power grid.

PubMed

Rudin, Cynthia; Waltz, David; Anderson, Roger N; Boulanger, Albert; Salleb-Aouissi, Ansaf; Chow, Maggie; Dutta, Haimonti; Gross, Philip N; Huang, Bert; Ierome, Steve; Isaac, Delfina F; Kressner, Arthur; Passonneau, Rebecca J; Radeva, Axinia; Wu, Leon

2012-02-01

Power companies can benefit from the use of knowledge discovery methods and statistical machine learning for preventive maintenance. We introduce a general process for transforming historical electrical grid data into models that aim to predict the risk of failures for components and systems. These models can be used directly by power companies to assist with prioritization of maintenance and repair work. Specialized versions of this process are used to produce 1) feeder failure rankings, 2) cable, joint, terminator, and transformer rankings, 3) feeder Mean Time Between Failure (MTBF) estimates, and 4) manhole events vulnerability rankings. The process in its most general form can handle diverse, noisy, sources that are historical (static), semi-real-time, or realtime, incorporates state-of-the-art machine learning algorithms for prioritization (supervised ranking or MTBF), and includes an evaluation of results via cross-validation and blind test. Above and beyond the ranked lists and MTBF estimates are business management interfaces that allow the prediction capability to be integrated directly into corporate planning and decision support; such interfaces rely on several important properties of our general modeling approach: that machine learning features are meaningful to domain experts, that the processing of data is transparent, and that prediction results are accurate enough to support sound decision making. We discuss the challenges in working with historical electrical grid data that were not designed for predictive purposes. The “rawness” of these data contrasts with the accuracy of the statistical models that can be obtained from the process; these models are sufficiently accurate to assist in maintaining New York City’s electrical grid.

Working memory - not processing speed - mediates fluid intelligence deficits associated with attention deficit/hyperactivity disorder symptoms.

PubMed

Brydges, Christopher R; Ozolnieks, Krista L; Roberts, Gareth

2017-09-01

Attention deficit/hyperactivity disorder (ADHD) is a psychological condition characterized by inattention and hyperactivity. Cognitive deficits are commonly observed in ADHD patients, including impaired working memory, processing speed, and fluid intelligence, the three of which are theorized to be closely associated with one another. In this study, we aimed to determine if decreased fluid intelligence was associated with ADHD, and was mediated by deficits in working memory and processing speed. This study tested 142 young adults from the general population on a range of working memory, processing speed, and fluid intelligence tasks, and an ADHD self-report symptoms questionnaire. Results showed that total and hyperactive ADHD symptoms correlated significantly and negatively with fluid intelligence, but this association was fully mediated by working memory. However, inattentive symptoms were not associated with fluid intelligence. Additionally, processing speed was not associated with ADHD symptoms at all, and was not uniquely predictive of fluid intelligence. The results provide implications for working memory training programs for ADHD patients, and highlight potential differences between the neuropsychological profiles of ADHD subtypes. © 2015 The British Psychological Society.

The role of speed versus working memory in predicting learning new information in multiple sclerosis.

PubMed

Chiaravalloti, Nancy D; Stojanovic-Radic, Jelena; DeLuca, John

2013-01-01

The most common cognitive impairments in multiple sclerosis (MS) have been documented in specific domains, including new learning and memory, working memory, and information processing speed. However, little attempt has been made to increase our understanding of their relationship to one another. While recent studies have shown that processing speed impacts new learning and memory abilities in MS, the role of working memory in this relationship has received less attention. The present study examines the relative contribution of impaired working memory versus processing speed in new learning and memory functions in MS. Participants consisted of 51 individuals with clinically definite MS. Participants completed two measures of processing speed, two measures of working memory, and two measures of episodic memory. Data were analyzed via correlational and multiple regression analysis. Results indicate that the variance in new learning abilities in this sample was primarily associated with processing speed, with working memory exerting much less of an influence. Results are discussed in terms of the role of cognitive rehabilitation of new learning and memory abilities in persons with MS.

Statistical modelling of networked human-automation performance using working memory capacity.

PubMed

Ahmed, Nisar; de Visser, Ewart; Shaw, Tyler; Mohamed-Ameen, Amira; Campbell, Mark; Parasuraman, Raja

2014-01-01

This study examines the challenging problem of modelling the interaction between individual attentional limitations and decision-making performance in networked human-automation system tasks. Analysis of real experimental data from a task involving networked supervision of multiple unmanned aerial vehicles by human participants shows that both task load and network message quality affect performance, but that these effects are modulated by individual differences in working memory (WM) capacity. These insights were used to assess three statistical approaches for modelling and making predictions with real experimental networked supervisory performance data: classical linear regression, non-parametric Gaussian processes and probabilistic Bayesian networks. It is shown that each of these approaches can help designers of networked human-automated systems cope with various uncertainties in order to accommodate future users by linking expected operating conditions and performance from real experimental data to observable cognitive traits like WM capacity. Practitioner Summary: Working memory (WM) capacity helps account for inter-individual variability in operator performance in networked unmanned aerial vehicle supervisory tasks. This is useful for reliable performance prediction near experimental conditions via linear models; robust statistical prediction beyond experimental conditions via Gaussian process models and probabilistic inference about unknown task conditions/WM capacities via Bayesian network models.

Optimization of nonlinear, non-Gaussian Bayesian filtering for diagnosis and prognosis of monotonic degradation processes

NASA Astrophysics Data System (ADS)

Corbetta, Matteo; Sbarufatti, Claudio; Giglio, Marco; Todd, Michael D.

2018-05-01

The present work critically analyzes the probabilistic definition of dynamic state-space models subject to Bayesian filters used for monitoring and predicting monotonic degradation processes. The study focuses on the selection of the random process, often called process noise, which is a key perturbation source in the evolution equation of particle filtering. Despite the large number of applications of particle filtering predicting structural degradation, the adequacy of the picked process noise has not been investigated. This paper reviews existing process noise models that are typically embedded in particle filters dedicated to monitoring and predicting structural damage caused by fatigue, which is monotonic in nature. The analysis emphasizes that existing formulations of the process noise can jeopardize the performance of the filter in terms of state estimation and remaining life prediction (i.e., damage prognosis). This paper subsequently proposes an optimal and unbiased process noise model and a list of requirements that the stochastic model must satisfy to guarantee high prognostic performance. These requirements are useful for future and further implementations of particle filtering for monotonic system dynamics. The validity of the new process noise formulation is assessed against experimental fatigue crack growth data from a full-scale aeronautical structure using dedicated performance metrics.

A cyber physical system approach for composite part: From smart manufacturing to predictive maintenance

NASA Astrophysics Data System (ADS)

Quaranta, Giacomo; Abisset-Chavanne, Emmanuelle; Chinesta, Francisco; Duval, Jean-Louis

2018-05-01

In this work, a Cyber Physical System called Hybrid Twin is proposed for composite parts manufactured from RTM. This allows to introduce in the virtual twin of the parts the defect and the final properties induced by the real manufacturing process and to use on line data collection for predictive maintenance.

A dislocation-based, strain–gradient–plasticity strengthening model for deformation processed metal–metal composites

DOE PAGES

Tian, Liang; Russell, Alan; Anderson, Iver

2014-01-03

Deformation processed metal–metal composites (DMMCs) are high-strength, high-electrical conductivity composites developed by severe plastic deformation of two ductile metal phases. The extraordinarily high strength of DMMCs is underestimated using the rule of mixture (or volumetric weighted average) of conventionally work-hardened metals. A dislocation-density-based, strain–gradient–plasticity model is proposed to relate the strain-gradient effect with the geometrically necessary dislocations emanating from the interface to better predict the strength of DMMCs. The model prediction was compared with our experimental findings of Cu–Nb, Cu–Ta, and Al–Ti DMMC systems to verify the applicability of the new model. The results show that this model predicts themore » strength of DMMCs better than the rule-of-mixture model. The strain-gradient effect, responsible for the exceptionally high strength of heavily cold worked DMMCs, is dominant at large deformation strain since its characteristic microstructure length is comparable with the intrinsic material length.« less

Dynamic interactions between visual working memory and saccade target selection

PubMed Central

Schneegans, Sebastian; Spencer, John P.; Schöner, Gregor; Hwang, Seongmin; Hollingworth, Andrew

2014-01-01

Recent psychophysical experiments have shown that working memory for visual surface features interacts with saccadic motor planning, even in tasks where the saccade target is unambiguously specified by spatial cues. Specifically, a match between a memorized color and the color of either the designated target or a distractor stimulus influences saccade target selection, saccade amplitudes, and latencies in a systematic fashion. To elucidate these effects, we present a dynamic neural field model in combination with new experimental data. The model captures the neural processes underlying visual perception, working memory, and saccade planning relevant to the psychophysical experiment. It consists of a low-level visual sensory representation that interacts with two separate pathways: a spatial pathway implementing spatial attention and saccade generation, and a surface feature pathway implementing color working memory and feature attention. Due to bidirectional coupling between visual working memory and feature attention in the model, the working memory content can indirectly exert an effect on perceptual processing in the low-level sensory representation. This in turn biases saccadic movement planning in the spatial pathway, allowing the model to quantitatively reproduce the observed interaction effects. The continuous coupling between representations in the model also implies that modulation should be bidirectional, and model simulations provide specific predictions for complementary effects of saccade target selection on visual working memory. These predictions were empirically confirmed in a new experiment: Memory for a sample color was biased toward the color of a task-irrelevant saccade target object, demonstrating the bidirectional coupling between visual working memory and perceptual processing. PMID:25228628

I. WORKING MEMORY CAPACITY IN CONTEXT: MODELING DYNAMIC PROCESSES OF BEHAVIOR, MEMORY, AND DEVELOPMENT.

PubMed

Simmering, Vanessa R

2016-09-01

Working memory is a vital cognitive skill that underlies a broad range of behaviors. Higher cognitive functions are reliably predicted by working memory measures from two domains: children's performance on complex span tasks, and infants' performance in looking paradigms. Despite the similar predictive power across these research areas, theories of working memory development have not connected these different task types and developmental periods. The current project takes a first step toward bridging this gap by presenting a process-oriented theory, focusing on two tasks designed to assess visual working memory capacity in infants (the change-preference task) versus children and adults (the change detection task). Previous studies have shown inconsistent results, with capacity estimates increasing from one to four items during infancy, but only two to three items during early childhood. A probable source of this discrepancy is the different task structures used with each age group, but prior theories were not sufficiently specific to explain how performance relates across tasks. The current theory focuses on cognitive dynamics, that is, how memory representations are formed, maintained, and used within specific task contexts over development. This theory was formalized in a computational model to generate three predictions: 1) capacity estimates in the change-preference task should continue to increase beyond infancy; 2) capacity estimates should be higher in the change-preference versus change detection task when tested within individuals; and 3) performance should correlate across tasks because both rely on the same underlying memory system. I also tested a fourth prediction, that development across tasks could be explained through increasing real-time stability, realized computationally as strengthening connectivity within the model. Results confirmed these predictions, supporting the cognitive dynamics account of performance and developmental changes in real-time stability. The monograph concludes with implications for understanding memory, behavior, and development in a broader range of cognitive development. © 2016 The Society for Research in Child Development, Inc.

The Development of Real-Time Stability Supports Visual Working Memory Performance: Young Children's Feature Binding Can Be Improved through Perceptual Structure

ERIC Educational Resources Information Center

Simmering, Vanessa R.; Wood, Chelsey M.

2017-01-01

Working memory is a basic cognitive process that predicts higher-level skills. A central question in theories of working memory development is the generality of the mechanisms proposed to explain improvements in performance. Prior theories have been closely tied to particular tasks and/or age groups, limiting their generalizability. The cognitive…

Ballistic-Failure Mechanisms in Gas Metal Arc Welds of Mil A46100 Armor-Grade Steel: A Computational Investigation

NASA Astrophysics Data System (ADS)

Grujicic, M.; Snipes, J. S.; Galgalikar, R.; Ramaswami, S.; Yavari, R.; Yen, C.-F.; Cheeseman, B. A.

2014-09-01

In our recent work, a multi-physics computational model for the conventional gas metal arc welding (GMAW) joining process was introduced. The model is of a modular type and comprises five modules, each designed to handle a specific aspect of the GMAW process, i.e.: (i) electro-dynamics of the welding-gun; (ii) radiation-/convection-controlled heat transfer from the electric-arc to the workpiece and mass transfer from the filler-metal consumable electrode to the weld; (iii) prediction of the temporal evolution and the spatial distribution of thermal and mechanical fields within the weld region during the GMAW joining process; (iv) the resulting temporal evolution and spatial distribution of the material microstructure throughout the weld region; and (v) spatial distribution of the as-welded material mechanical properties. In the present work, the GMAW process model has been upgraded with respect to its predictive capabilities regarding the spatial distribution of the mechanical properties controlling the ballistic-limit (i.e., penetration-resistance) of the weld. The model is upgraded through the introduction of the sixth module in the present work in recognition of the fact that in thick steel GMAW weldments, the overall ballistic performance of the armor may become controlled by the (often inferior) ballistic limits of its weld (fusion and heat-affected) zones. To demonstrate the utility of the upgraded GMAW process model, it is next applied to the case of butt-welding of a prototypical high-hardness armor-grade martensitic steel, MIL A46100. The model predictions concerning the spatial distribution of the material microstructure and ballistic-limit-controlling mechanical properties within the MIL A46100 butt-weld are found to be consistent with prior observations and general expectations.

Prediction of Temperatures of Austenite Equilibrium Transformations in Steels During Thermomechanical Processing

NASA Astrophysics Data System (ADS)

Samadian, Pedram; Parsa, Mohammad Habibi; Ahmadabadi, M. Nili; Mirzadeh, Hamed

2014-10-01

Knowledge about the transformation temperatures is crucial in processing of steels especially in thermomechanical processes because microstructures and mechanical properties after processing are closely related to the extent and type of transformations. The experimental determination of critical temperatures is costly, and therefore, it is preferred to predict them by mathematical methods. In the current work, new thermodynamically based models were developed for computing the Ae3 and Acm temperatures in the equilibrium cooling conditions when austenite is deformed at elevated temperatures. The main advantage of the proposed models is their capability to predict the temperatures of austenite equilibrium transformations in steels with total alloying elements (Mn + Si + Ni + Cr + Mo + Cu) less than 5 wt.% and Si less than 1 wt.% under the deformation conditions just by using the chemical potential of constituents, without the need for determining the total Gibbs free energy of steel which requires many experiments and computations.

Individual Differences in Working Memory Capacity Predict Sleep-Dependent Memory Consolidation

ERIC Educational Resources Information Center

Fenn, Kimberly M.; Hambrick, David Z.

2012-01-01

Decades of research have established that "online" cognitive processes, which operate during conscious encoding and retrieval of information, contribute substantially to individual differences in memory. Furthermore, it is widely accepted that "offline" processes during sleep also contribute to memory performance. However, the question of whether…

Wraparound Retrospective: Factors Predicting Positive Outcomes

ERIC Educational Resources Information Center

Cox, Kathy; Baker, Dawniel; Wong, Mary Ann

2010-01-01

While research regarding the effectiveness of the wraparound process is steadily mounting, little is known about how this service delivery model works and for whom. Using data gathered on 176 youth who participated in the wraparound process, the authors examine client and service factors associated with outcomes. Bivariate logistic regression…

Wanted: Gerontological Social Workers--Factors Related to Interest in the Field

ERIC Educational Resources Information Center

Ferguson, Alishia

2012-01-01

This study attempted to build a predictive model of factors related to social work students' interest in gerontological social work. Bachelor's and Master's students from universities around Texas were surveyed to determine if knowledge about the aging process and related job opportunities, attitudes toward aging and professional or personal…

Working Memory Facilitates Insight Instead of Hindering It: Comment on Decaro, Van Stockum, and Wieth (2016)

ERIC Educational Resources Information Center

Chuderski, Adam; Jastrzebski, Jan

2017-01-01

The "nothing-special" account of insight predicts positive correlations of insight problem solving and working memory capacity (WMC), whereas the "special-process" account expects no, or even negative, correlations. In the latter vein, DeCaro, Van Stockum Jr., and Wieth (2016) have recently reported weak negative WMC…

When Simple Things Are Meaningful: Working Memory Strength Predicts Children's Cognitive Flexibility

ERIC Educational Resources Information Center

Blackwell, Katharine A.; Cepeda, Nicholas J.; Munakata, Yuko

2009-01-01

People often perseverate, repeating outdated behaviors despite correctly answering questions about rules they should be following. Children who perseverate are slower to respond to such questions than children who successfully switch to new rules, even after controlling for age and processing speed. Thus, switchers may have stronger working memory…

Working Memory Components as Predictors of Children's Mathematical Word Problem Solving

ERIC Educational Resources Information Center

Zheng, Xinhua; Swanson, H. Lee; Marcoulides, George A.

2011-01-01

This study determined the working memory (WM) components (executive, phonological loop, and visual-spatial sketchpad) that best predicted mathematical word problem-solving accuracy of elementary school children in Grades 2, 3, and 4 (N = 310). A battery of tests was administered to assess problem-solving accuracy, problem-solving processes, WM,…

On the Validity of Continuum Computational Fluid Dynamics Approach Under Very Low-Pressure Plasma Spray Conditions

NASA Astrophysics Data System (ADS)

Ivchenko, Dmitrii; Zhang, Tao; Mariaux, Gilles; Vardelle, Armelle; Goutier, Simon; Itina, Tatiana E.

2018-01-01

Plasma spray physical vapor deposition aims to substantially evaporate powders in order to produce coatings with various microstructures. This is achieved by powder vapor condensation onto the substrate and/or by deposition of fine melted powder particles and nanoclusters. The deposition process typically operates at pressures ranging between 10 and 200 Pa. In addition to the experimental works, numerical simulations are performed to better understand the process and optimize the experimental conditions. However, the combination of high temperatures and low pressure with shock waves initiated by supersonic expansion of the hot gas in the low-pressure medium makes doubtful the applicability of the continuum approach for the simulation of such a process. This work investigates (1) effects of the pressure dependence of thermodynamic and transport properties on computational fluid dynamics (CFD) predictions and (2) the validity of the continuum approach for thermal plasma flow simulation under very low-pressure conditions. The study compares the flow fields predicted with a continuum approach using CFD software with those obtained by a kinetic-based approach using a direct simulation Monte Carlo method (DSMC). It also shows how the presence of high gradients can contribute to prediction errors for typical PS-PVD conditions.

Membrane-assisted extraction of monoterpenes: from in silico solvent screening towards biotechnological process application

PubMed Central

2018-01-01

This work focuses on the process development of membrane-assisted solvent extraction of hydrophobic compounds such as monoterpenes. Beginning with the choice of suitable solvents, quantum chemical calculations with the simulation tool COSMO-RS were carried out to predict the partition coefficient (logP) of (S)-(+)-carvone and terpinen-4-ol in various solvent–water systems and validated afterwards with experimental data. COSMO-RS results show good prediction accuracy for non-polar solvents such as n-hexane, ethyl acetate and n-heptane even in the presence of salts and glycerol in an aqueous medium. Based on the high logP value, n-heptane was chosen for the extraction of (S)-(+)-carvone in a lab-scale hollow-fibre membrane contactor. Two operation modes are investigated where experimental and theoretical mass transfer values, based on their related partition coefficients, were compared. In addition, the process is evaluated in terms of extraction efficiency and overall product recovery, and its biotechnological application potential is discussed. Our work demonstrates that the combination of in silico prediction by COSMO-RS with membrane-assisted extraction is a promising approach for the recovery of hydrophobic compounds from aqueous solutions. PMID:29765654

Sensitivity to Referential Ambiguity in Discourse: The Role of Attention, Working Memory, and Verbal Ability

PubMed Central

Boudewyn, Megan A.; Long, Debra L.; Traxler, Matthew J.; Lesh, Tyler A.; Dave, Shruti; Mangun, George R.; Carter, Cameron S.; Swaab, Tamara Y.

2016-01-01

The establishment of reference is essential to language comprehension. The goal of this study was to examine listeners’ sensitivity to referential ambiguity as a function of individual variation in attention, working memory capacity, and verbal ability. Participants listened to stories in which two entities were introduced that were either very similar (e.g., two oaks) or less similar (e.g., one oak and one elm). The manipulation rendered an anaphor in a subsequent sentence (e.g., oak) ambiguous or unambiguous. EEG was recorded as listeners comprehended the story, after which participants completed tasks to assess working memory, verbal ability, and the ability to use context in task performance. Power in the alpha and theta frequency bands when listeners received critical information about the discourse entities (e.g., oaks) was used to index attention and the involvement of the working memory system in processing the entities. These measures were then used to predict an ERP component that is sensitive to referential ambiguity, the Nref, which was recorded when listeners received the anaphor. Nref amplitude at the anaphor was predicted by alpha power during the earlier critical sentence: Individuals with increased alpha power in ambiguous compared with unambiguous stories were less sensitive to the anaphor's ambiguity. Verbal ability was also predictive of greater sensitivity to referential ambiguity. Finally, increased theta power in the ambiguous compared with unambiguous condition was associated with higher working-memory span. These results highlight the role of attention and working memory in referential processing during listening comprehension. PMID:26401815

Sensitivity to Referential Ambiguity in Discourse: The Role of Attention, Working Memory, and Verbal Ability.

PubMed

Boudewyn, Megan A; Long, Debra L; Traxler, Matthew J; Lesh, Tyler A; Dave, Shruti; Mangun, George R; Carter, Cameron S; Swaab, Tamara Y

2015-12-01

The establishment of reference is essential to language comprehension. The goal of this study was to examine listeners' sensitivity to referential ambiguity as a function of individual variation in attention, working memory capacity, and verbal ability. Participants listened to stories in which two entities were introduced that were either very similar (e.g., two oaks) or less similar (e.g., one oak and one elm). The manipulation rendered an anaphor in a subsequent sentence (e.g., oak) ambiguous or unambiguous. EEG was recorded as listeners comprehended the story, after which participants completed tasks to assess working memory, verbal ability, and the ability to use context in task performance. Power in the alpha and theta frequency bands when listeners received critical information about the discourse entities (e.g., oaks) was used to index attention and the involvement of the working memory system in processing the entities. These measures were then used to predict an ERP component that is sensitive to referential ambiguity, the Nref, which was recorded when listeners received the anaphor. Nref amplitude at the anaphor was predicted by alpha power during the earlier critical sentence: Individuals with increased alpha power in ambiguous compared with unambiguous stories were less sensitive to the anaphor's ambiguity. Verbal ability was also predictive of greater sensitivity to referential ambiguity. Finally, increased theta power in the ambiguous compared with unambiguous condition was associated with higher working-memory span. These results highlight the role of attention and working memory in referential processing during listening comprehension.

Predicting Survey Responses: How and Why Semantics Shape Survey Statistics on Organizational Behaviour

PubMed Central

Arnulf, Jan Ketil; Larsen, Kai Rune; Martinsen, Øyvind Lund; Bong, Chih How

2014-01-01

Some disciplines in the social sciences rely heavily on collecting survey responses to detect empirical relationships among variables. We explored whether these relationships were a priori predictable from the semantic properties of the survey items, using language processing algorithms which are now available as new research methods. Language processing algorithms were used to calculate the semantic similarity among all items in state-of-the-art surveys from Organisational Behaviour research. These surveys covered areas such as transformational leadership, work motivation and work outcomes. This information was used to explain and predict the response patterns from real subjects. Semantic algorithms explained 60–86% of the variance in the response patterns and allowed remarkably precise prediction of survey responses from humans, except in a personality test. Even the relationships between independent and their purported dependent variables were accurately predicted. This raises concern about the empirical nature of data collected through some surveys if results are already given a priori through the way subjects are being asked. Survey response patterns seem heavily determined by semantics. Language algorithms may suggest these prior to administering a survey. This study suggests that semantic algorithms are becoming new tools for the social sciences, opening perspectives on survey responses that prevalent psychometric theory cannot explain. PMID:25184672

Predicting survey responses: how and why semantics shape survey statistics on organizational behaviour.

PubMed

Arnulf, Jan Ketil; Larsen, Kai Rune; Martinsen, Øyvind Lund; Bong, Chih How

2014-01-01

Some disciplines in the social sciences rely heavily on collecting survey responses to detect empirical relationships among variables. We explored whether these relationships were a priori predictable from the semantic properties of the survey items, using language processing algorithms which are now available as new research methods. Language processing algorithms were used to calculate the semantic similarity among all items in state-of-the-art surveys from Organisational Behaviour research. These surveys covered areas such as transformational leadership, work motivation and work outcomes. This information was used to explain and predict the response patterns from real subjects. Semantic algorithms explained 60-86% of the variance in the response patterns and allowed remarkably precise prediction of survey responses from humans, except in a personality test. Even the relationships between independent and their purported dependent variables were accurately predicted. This raises concern about the empirical nature of data collected through some surveys if results are already given a priori through the way subjects are being asked. Survey response patterns seem heavily determined by semantics. Language algorithms may suggest these prior to administering a survey. This study suggests that semantic algorithms are becoming new tools for the social sciences, opening perspectives on survey responses that prevalent psychometric theory cannot explain.

Commander’s Decision Aid for Predictive Battlespace Awareness (CDA4PBA)

DTIC Science & Technology

2006-12-01

defining how PBA is used in the AOC. Defining user requirements via the WDAR ensured a solid starting point for PBA system specifications, e.g...there was a brief mention of a concept being concerned with a certain element of information or certain process, it was not automatically included in...maker’s work context; and • Gain a solid understanding of the actual work that is required to conduct and maintain the PBA process. Initial

Toward a better understanding on the role of prediction error on memory processes: From bench to clinic.

PubMed

Krawczyk, María C; Fernández, Rodrigo S; Pedreira, María E; Boccia, Mariano M

2017-07-01

Experimental psychology defines Prediction Error (PE) as a mismatch between expected and current events. It represents a unifier concept within the memory field, as it is the driving force of memory acquisition and updating. Prediction error induces updating of consolidated memories in strength or content by memory reconsolidation. This process has two different neurobiological phases, which involves the destabilization (labilization) of a consolidated memory followed by its restabilization. The aim of this work is to emphasize the functional role of PE on the neurobiology of learning and memory, integrating and discussing different research areas: behavioral, neurobiological, computational and clinical psychiatry. Copyright © 2016 Elsevier Inc. All rights reserved.

Theoretical test of Jarzynski's equality for reversible volume-switching processes of an ideal gas system.

PubMed

Sung, Jaeyoung

2007-07-01

We present an exact theoretical test of Jarzynski's equality (JE) for reversible volume-switching processes of an ideal gas system. The exact analysis shows that the prediction of JE for the free energy difference is the same as the work done on the gas system during the reversible process that is dependent on the shape of path of the reversible volume-switching process.

Virtual milk for modelling and simulation of dairy processes.

PubMed

Munir, M T; Zhang, Y; Yu, W; Wilson, D I; Young, B R

2016-05-01

The modeling of dairy processing using a generic process simulator suffers from shortcomings, given that many simulators do not contain milk components in their component libraries. Recently, pseudo-milk components for a commercial process simulator were proposed for simulation and the current work extends this pseudo-milk concept by studying the effect of both total milk solids and temperature on key physical properties such as thermal conductivity, density, viscosity, and heat capacity. This paper also uses expanded fluid and power law models to predict milk viscosity over the temperature range from 4 to 75°C and develops a succinct regressed model for heat capacity as a function of temperature and fat composition. The pseudo-milk was validated by comparing the simulated and actual values of the physical properties of milk. The milk thermal conductivity, density, viscosity, and heat capacity showed differences of less than 2, 4, 3, and 1.5%, respectively, between the simulated results and actual values. This work extends the capabilities of the previously proposed pseudo-milk and of a process simulator to model dairy processes, processing different types of milk (e.g., whole milk, skim milk, and concentrated milk) with different intrinsic compositions, and to predict correct material and energy balances for dairy processes. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Toward a New Predictive Model of Student Retention in Higher Education: An Application of Classical Sociological Theory

ERIC Educational Resources Information Center

Kerby, Molly B.

2015-01-01

Theoretical models designed to predict whether students will persist or not have been valuable tools for retention efforts relative to the creation of services in academic and student affairs. Some of the early models attempted to explain and measure factors in the "college dropout process." For example, in his seminal work, Tinto…

Comparison of adaptive neuro-fuzzy inference system (ANFIS) and Gaussian processes for machine learning (GPML) algorithms for the prediction of skin temperature in lower limb prostheses.

PubMed

Mathur, Neha; Glesk, Ivan; Buis, Arjan

2016-10-01

Monitoring of the interface temperature at skin level in lower-limb prosthesis is notoriously complicated. This is due to the flexible nature of the interface liners used impeding the required consistent positioning of the temperature sensors during donning and doffing. Predicting the in-socket residual limb temperature by monitoring the temperature between socket and liner rather than skin and liner could be an important step in alleviating complaints on increased temperature and perspiration in prosthetic sockets. In this work, we propose to implement an adaptive neuro fuzzy inference strategy (ANFIS) to predict the in-socket residual limb temperature. ANFIS belongs to the family of fused neuro fuzzy system in which the fuzzy system is incorporated in a framework which is adaptive in nature. The proposed method is compared to our earlier work using Gaussian processes for machine learning. By comparing the predicted and actual data, results indicate that both the modeling techniques have comparable performance metrics and can be efficiently used for non-invasive temperature monitoring. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Prediction of ttt curves of cold working tool steels using support vector machine model

NASA Astrophysics Data System (ADS)

Pillai, Nandakumar; Karthikeyan, R., Dr.

2018-04-01

The cold working tool steels are of high carbon steels with metallic alloy additions which impart higher hardenability, abrasion resistance and less distortion in quenching. The microstructure changes occurring in tool steel during heat treatment is of very much importance as the final properties of the steel depends upon these changes occurred during the process. In order to obtain the desired performance the alloy constituents and its ratio plays a vital role as the steel transformation itself is complex in nature and depends very much upon the time and temperature. The proper treatment can deliver satisfactory results, at the same time process deviation can completely spoil the results. So knowing time temperature transformation (TTT) of phases is very critical which varies for each type depending upon its constituents and proportion range. To obtain adequate post heat treatment properties the percentage of retained austenite should be lower and metallic carbides obtained should be fine in nature. Support vector machine is a computational model which can learn from the observed data and use these to predict or solve using mathematical model. Back propagation feedback network will be created and trained for further solutions. The points on the TTT curve for the known transformations curves are used to plot the curves for different materials. These data will be trained to predict TTT curves for other steels having similar alloying constituents but with different proportion range. The proposed methodology can be used for prediction of TTT curves for cold working steels and can be used for prediction of phases for different heat treatment methods.

Hyperfocusing in Schizophrenia: Evidence from Interactions Between Working Memory and Eye Movements

PubMed Central

Luck, Steven J.; McClenon, Clara; Beck, Valerie M.; Hollingworth, Andrew; Leonard, Carly J.; Hahn, Britta; Robinson, Benjamin M.; Gold, James M.

2014-01-01

Recent research suggests that processing resources are focused more narrowly but more intensely in people with schizophrenia (PSZ) than in healthy control subjects (HCS), possibly reflecting local cortical circuit abnormalities. This hyperfocusing hypothesis leads to the counterintuitive prediction that, although PSZ cannot store as much information in working memory as HCS, the working memory representations that are present in PSZ may be more intense than those in HCS. To test this hypothesis, we used a task in which participants make a saccadic eye movement to a peripheral target and avoid a parafoveal nontarget while they are holding a color in working memory. Previous research with this task has shown that the parafoveal nontarget is more distracting when it matches the color being held in working memory. This effect should be enhanced in PSZ if their working memory representations are more intense. Consistent with this prediction, we found that the effect of a match between the distractor color and the memory color was larger in PSZ than in HCS. We also observed evidence that PSZ hyperfocused spatially on the region surrounding the fixation point. These results provide further evidence that some aspects of cognitive dysfunction in schizophrenia may be a result of a narrower and more intense focusing of processing resources. PMID:25089655

Hyperfocusing in schizophrenia: Evidence from interactions between working memory and eye movements.

PubMed

Luck, Steven J; McClenon, Clara; Beck, Valerie M; Hollingworth, Andrew; Leonard, Carly J; Hahn, Britta; Robinson, Benjamin M; Gold, James M

2014-11-01

Recent research suggests that processing resources are focused more narrowly but more intensely in people with schizophrenia (PSZ) than in healthy control subjects (HCS), possibly reflecting local cortical circuit abnormalities. This hyperfocusing hypothesis leads to the counterintuitive prediction that, although PSZ cannot store as much information in working memory as HCS, the working memory representations that are present in PSZ may be more intense than those in HCS. To test this hypothesis, we used a task in which participants make a saccadic eye movement to a peripheral target and avoid a parafoveal nontarget while they are holding a color in working memory. Previous research with this task has shown that the parafoveal nontarget is more distracting when it matches the color being held in working memory. This effect should be enhanced in PSZ if their working memory representations are more intense. Consistent with this prediction, we found that the effect of a match between the distractor color and the memory color was larger in PSZ than in HCS. We also observed evidence that PSZ hyperfocused spatially on the region surrounding the fixation point. These results provide further evidence that some aspects of cognitive dysfunction in schizophrenia may be a result of a narrower and more intense focusing of processing resources.

Changes in automatic threat processing precede and predict clinical changes with exposure-based cognitive-behavior therapy for panic disorder.

PubMed

Reinecke, Andrea; Waldenmaier, Lara; Cooper, Myra J; Harmer, Catherine J

2013-06-01

Cognitive behavioral therapy (CBT) is an effective treatment for emotional disorders such as anxiety or depression, but the mechanisms underlying successful intervention are far from understood. Although it has been a long-held view that psychopharmacological approaches work by directly targeting automatic emotional information processing in the brain, it is usually postulated that psychological treatments affect these processes only over time, through changes in more conscious thought cycles. This study explored the role of early changes in emotional information processing in CBT action. Twenty-eight untreated patients with panic disorder were randomized to a single session of exposure-based CBT or waiting group. Emotional information processing was measured on the day after intervention with an attentional visual probe task, and clinical symptoms were assessed on the day after intervention and at 4-week follow-up. Vigilance for threat information was decreased in the treated group, compared with the waiting group, the day after intervention, before reductions in clinical symptoms. The magnitude of this early effect on threat vigilance predicted therapeutic response after 4 weeks. Cognitive behavioral therapy rapidly affects automatic processing, and these early effects are predictive of later therapeutic change. Such results suggest very fast action on automatic processes mediating threat sensitivity, and they provide an early marker of treatment response. Furthermore, these findings challenge the notion that psychological treatments work directly on conscious thought processes before automatic information processing and imply a greater similarity between early effects of pharmacological and psychological treatments for anxiety than previously thought. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

GASP: Gapped Ancestral Sequence Prediction for proteins

PubMed Central

Edwards, Richard J; Shields, Denis C

2004-01-01

Background The prediction of ancestral protein sequences from multiple sequence alignments is useful for many bioinformatics analyses. Predicting ancestral sequences is not a simple procedure and relies on accurate alignments and phylogenies. Several algorithms exist based on Maximum Parsimony or Maximum Likelihood methods but many current implementations are unable to process residues with gaps, which may represent insertion/deletion (indel) events or sequence fragments. Results Here we present a new algorithm, GASP (Gapped Ancestral Sequence Prediction), for predicting ancestral sequences from phylogenetic trees and the corresponding multiple sequence alignments. Alignments may be of any size and contain gaps. GASP first assigns the positions of gaps in the phylogeny before using a likelihood-based approach centred on amino acid substitution matrices to assign ancestral amino acids. Important outgroup information is used by first working down from the tips of the tree to the root, using descendant data only to assign probabilities, and then working back up from the root to the tips using descendant and outgroup data to make predictions. GASP was tested on a number of simulated datasets based on real phylogenies. Prediction accuracy for ungapped data was similar to three alternative algorithms tested, with GASP performing better in some cases and worse in others. Adding simple insertions and deletions to the simulated data did not have a detrimental effect on GASP accuracy. Conclusions GASP (Gapped Ancestral Sequence Prediction) will predict ancestral sequences from multiple protein alignments of any size. Although not as accurate in all cases as some of the more sophisticated maximum likelihood approaches, it can process a wide range of input phylogenies and will predict ancestral sequences for gapped and ungapped residues alike. PMID:15350199

Do the Contents of Visual Working Memory Automatically Influence Attentional Selection During Visual Search?

PubMed Central

Woodman, Geoffrey F.; Luck, Steven J.

2007-01-01

In many theories of cognition, researchers propose that working memory and perception operate interactively. For example, in previous studies researchers have suggested that sensory inputs matching the contents of working memory will have an automatic advantage in the competition for processing resources. The authors tested this hypothesis by requiring observers to perform a visual search task while concurrently maintaining object representations in visual working memory. The hypothesis that working memory activation produces a simple but uncontrollable bias signal leads to the prediction that items matching the contents of working memory will automatically capture attention. However, no evidence for automatic attentional capture was obtained; instead, the participants avoided attending to these items. Thus, the contents of working memory can be used in a flexible manner for facilitation or inhibition of processing. PMID:17469973

Do the contents of visual working memory automatically influence attentional selection during visual search?

PubMed

Woodman, Geoffrey F; Luck, Steven J

2007-04-01

In many theories of cognition, researchers propose that working memory and perception operate interactively. For example, in previous studies researchers have suggested that sensory inputs matching the contents of working memory will have an automatic advantage in the competition for processing resources. The authors tested this hypothesis by requiring observers to perform a visual search task while concurrently maintaining object representations in visual working memory. The hypothesis that working memory activation produces a simple but uncontrollable bias signal leads to the prediction that items matching the contents of working memory will automatically capture attention. However, no evidence for automatic attentional capture was obtained; instead, the participants avoided attending to these items. Thus, the contents of working memory can be used in a flexible manner for facilitation or inhibition of processing.

Prediction of Proper Temperatures for the Hot Stamping Process Based on the Kinetics Models

NASA Astrophysics Data System (ADS)

Samadian, P.; Parsa, M. H.; Mirzadeh, H.

2015-02-01

Nowadays, the application of kinetics models for predicting microstructures of steels subjected to thermo-mechanical treatments has increased to minimize direct experimentation, which is costly and time consuming. In the current work, the final microstructures of AISI 4140 steel sheets after the hot stamping process were predicted using the Kirkaldy and Li kinetics models combined with new thermodynamically based models in order for the determination of the appropriate process temperatures. In this way, the effect of deformation during hot stamping on the Ae3, Acm, and Ae1 temperatures was considered, and then the equilibrium volume fractions of phases at different temperatures were calculated. Moreover, the ferrite transformation rate equations of the Kirkaldy and Li models were modified by a term proposed by Åkerström to consider the influence of plastic deformation. Results showed that the modified Kirkaldy model is satisfactory for the determination of appropriate austenitization temperatures for the hot stamping process of AISI 4140 steel sheets because of agreeable microstructure predictions in comparison with the experimental observations.

Harsh Parenting and Fearfulness in Toddlerhood Interact to Predict Amplitudes of Preschool Error-Related Negativity

PubMed Central

Brooker, Rebecca J.; Buss, Kristin A.

2014-01-01

Temperamentally fearful children are at increased risk for the development of anxiety problems relative to less-fearful children. This risk is even greater when early environments include high levels of harsh parenting behaviors. However, the mechanisms by which harsh parenting may impact fearful children’s risk for anxiety problems are largely unknown. Recent neuroscience work has suggested that punishment is associated with exaggerated error-related negativity (ERN), an event-related potential linked to performance monitoring, even after the threat of punishment is removed. In the current study, we examined the possibility that harsh parenting interacts with fearfulness, impacting anxiety risk via neural processes of performance monitoring. We found that greater fearfulness and harsher parenting at 2 years of age predicted greater fearfulness and greater ERN amplitudes at age 4. Supporting the role of cognitive processes in this association, greater fearfulness and harsher parenting also predicted less efficient neural processing during preschool. This study provides initial evidence that performance monitoring may be a candidate process by which early parenting interacts with fearfulness to predict risk for anxiety problems. PMID:24721466

Projection methods

Treesearch

Michael E. Goerndt; W. Keith Moser; Patrick D. Miles; Dave Wear; Ryan D. DeSantis; Robert J. Huggett; Stephen R. Shifley; Francisco X. Aguilar; Kenneth E. Skog

2016-01-01

One purpose of the Northern Forest Futures Project is to predict change in future forest attributes across the 20 States in the U.S. North for the period that extends from 2010 to 2060. The forest attributes of primary interest are the 54 indicators of forest sustainability identified in the Montreal Process Criteria and Indicators (Montreal Process Working Group, n.d...

Assessing the Driver’s Current Level of Working Memory Load with High Density Functional Near-infrared Spectroscopy: A Realistic Driving Simulator Study

PubMed Central

Unni, Anirudh; Ihme, Klas; Jipp, Meike; Rieger, Jochem W.

2017-01-01

Cognitive overload or underload results in a decrease in human performance which may result in fatal incidents while driving. We envision that driver assistive systems which adapt their functionality to the driver’s cognitive state could be a promising approach to reduce road accidents due to human errors. This research attempts to predict variations of cognitive working memory load levels in a natural driving scenario with multiple parallel tasks and to reveal predictive brain areas. We used a modified version of the n-back task to induce five different working memory load levels (from 0-back up to 4-back) forcing the participants to continuously update, memorize, and recall the previous ‘n’ speed sequences and adjust their speed accordingly while they drove for approximately 60 min on a highway with concurrent traffic in a virtual reality driving simulator. We measured brain activation using multichannel whole head, high density functional near-infrared spectroscopy (fNIRS) and predicted working memory load level from the fNIRS data by combining multivariate lasso regression and cross-validation. This allowed us to predict variations in working memory load in a continuous time-resolved manner with mean Pearson correlations between induced and predicted working memory load over 15 participants of 0.61 [standard error (SE) 0.04] and a maximum of 0.8. Restricting the analysis to prefrontal sensors placed over the forehead reduced the mean correlation to 0.38 (SE 0.04), indicating additional information gained through whole head coverage. Moreover, working memory load predictions derived from peripheral heart rate parameters achieved much lower correlations (mean 0.21, SE 0.1). Importantly, whole head fNIRS sampling revealed increasing brain activation in bilateral inferior frontal and bilateral temporo-occipital brain areas with increasing working memory load levels suggesting that these areas are specifically involved in workload-related processing. PMID:28424602

Assessing the Driver's Current Level of Working Memory Load with High Density Functional Near-infrared Spectroscopy: A Realistic Driving Simulator Study.

PubMed

Unni, Anirudh; Ihme, Klas; Jipp, Meike; Rieger, Jochem W

2017-01-01

Cognitive overload or underload results in a decrease in human performance which may result in fatal incidents while driving. We envision that driver assistive systems which adapt their functionality to the driver's cognitive state could be a promising approach to reduce road accidents due to human errors. This research attempts to predict variations of cognitive working memory load levels in a natural driving scenario with multiple parallel tasks and to reveal predictive brain areas. We used a modified version of the n-back task to induce five different working memory load levels (from 0-back up to 4-back) forcing the participants to continuously update, memorize, and recall the previous 'n' speed sequences and adjust their speed accordingly while they drove for approximately 60 min on a highway with concurrent traffic in a virtual reality driving simulator. We measured brain activation using multichannel whole head, high density functional near-infrared spectroscopy (fNIRS) and predicted working memory load level from the fNIRS data by combining multivariate lasso regression and cross-validation. This allowed us to predict variations in working memory load in a continuous time-resolved manner with mean Pearson correlations between induced and predicted working memory load over 15 participants of 0.61 [standard error (SE) 0.04] and a maximum of 0.8. Restricting the analysis to prefrontal sensors placed over the forehead reduced the mean correlation to 0.38 (SE 0.04), indicating additional information gained through whole head coverage. Moreover, working memory load predictions derived from peripheral heart rate parameters achieved much lower correlations (mean 0.21, SE 0.1). Importantly, whole head fNIRS sampling revealed increasing brain activation in bilateral inferior frontal and bilateral temporo-occipital brain areas with increasing working memory load levels suggesting that these areas are specifically involved in workload-related processing.

Squared exponential covariance function for prediction of hydrocarbon in seabed logging application

NASA Astrophysics Data System (ADS)

Mukhtar, Siti Mariam; Daud, Hanita; Dass, Sarat Chandra

2016-11-01

Seabed Logging technology (SBL) has progressively emerged as one of the demanding technologies in Exploration and Production (E&P) industry. Hydrocarbon prediction in deep water areas is crucial task for a driller in any oil and gas company as drilling cost is very expensive. Simulation data generated by Computer Software Technology (CST) is used to predict the presence of hydrocarbon where the models replicate real SBL environment. These models indicate that the hydrocarbon filled reservoirs are more resistive than surrounding water filled sediments. Then, as hydrocarbon depth is increased, it is more challenging to differentiate data with and without hydrocarbon. MATLAB is used for data extractions for curve fitting process using Gaussian process (GP). GP can be classified into regression and classification problems, where this work only focuses on Gaussian process regression (GPR) problem. Most popular choice to supervise GPR is squared exponential (SE), as it provides stability and probabilistic prediction in huge amounts of data. Hence, SE is used to predict the presence or absence of hydrocarbon in the reservoir from the data generated.

Software sensors for biomass concentration in a SSC process using artificial neural networks and support vector machine.

PubMed

Acuña, Gonzalo; Ramirez, Cristian; Curilem, Millaray

2014-01-01

The lack of sensors for some relevant state variables in fermentation processes can be coped by developing appropriate software sensors. In this work, NARX-ANN, NARMAX-ANN, NARX-SVM and NARMAX-SVM models are compared when acting as software sensors of biomass concentration for a solid substrate cultivation (SSC) process. Results show that NARMAX-SVM outperforms the other models with an SMAPE index under 9 for a 20 % amplitude noise. In addition, NARMAX models perform better than NARX models under the same noise conditions because of their better predictive capabilities as they include prediction errors as inputs. In the case of perturbation of initial conditions of the autoregressive variable, NARX models exhibited better convergence capabilities. This work also confirms that a difficult to measure variable, like biomass concentration, can be estimated on-line from easy to measure variables like CO₂ and O₂ using an adequate software sensor based on computational intelligence techniques.

Prediction of mass transfer coefficient in rotating bed contactor (Higee) using artificial neural network

NASA Astrophysics Data System (ADS)

Saha, Dipendu

2009-02-01

The feasibility of drastically reducing the contactor size in mass transfer processes utilizing centrifugal field has generated a lot of interest in rotating packed bed (Higee). Various investigators have proposed correlations to predict mass transfer coefficients in Higee, but, none of the correlations was more than 20-30% accurate. In this work, artificial neural network (ANN) is employed for predicting mass transfer coefficient data. Results show that ANN provides better estimation of mass transfer coefficient with accuracy 5-15%.

Dopamine reward prediction-error signalling: a two-component response

PubMed Central

Schultz, Wolfram

2017-01-01

Environmental stimuli and objects, including rewards, are often processed sequentially in the brain. Recent work suggests that the phasic dopamine reward prediction-error response follows a similar sequential pattern. An initial brief, unselective and highly sensitive increase in activity unspecifically detects a wide range of environmental stimuli, then quickly evolves into the main response component, which reflects subjective reward value and utility. This temporal evolution allows the dopamine reward prediction-error signal to optimally combine speed and accuracy. PMID:26865020

Predictability decomposition detects the impairment of brain-heart dynamical networks during sleep disorders and their recovery with treatment

NASA Astrophysics Data System (ADS)

Faes, Luca; Marinazzo, Daniele; Stramaglia, Sebastiano; Jurysta, Fabrice; Porta, Alberto; Giandomenico, Nollo

2016-05-01

This work introduces a framework to study the network formed by the autonomic component of heart rate variability (cardiac process η) and the amplitude of the different electroencephalographic waves (brain processes δ, θ, α, σ, β) during sleep. The framework exploits multivariate linear models to decompose the predictability of any given target process into measures of self-, causal and interaction predictability reflecting respectively the information retained in the process and related to its physiological complexity, the information transferred from the other source processes, and the information modified during the transfer according to redundant or synergistic interaction between the sources. The framework is here applied to the η, δ, θ, α, σ, β time series measured from the sleep recordings of eight severe sleep apnoea-hypopnoea syndrome (SAHS) patients studied before and after long-term treatment with continuous positive airway pressure (CPAP) therapy, and 14 healthy controls. Results show that the full and self-predictability of η, δ and θ decreased significantly in SAHS compared with controls, and were restored with CPAP for δ and θ but not for η. The causal predictability of η and δ occurred through significantly redundant source interaction during healthy sleep, which was lost in SAHS and recovered after CPAP. These results indicate that predictability analysis is a viable tool to assess the modifications of complexity and causality of the cerebral and cardiac processes induced by sleep disorders, and to monitor the restoration of the neuroautonomic control of these processes during long-term treatment.

Salience and Attention in Surprisal-Based Accounts of Language Processing.

PubMed

Zarcone, Alessandra; van Schijndel, Marten; Vogels, Jorrig; Demberg, Vera

2016-01-01

The notion of salience has been singled out as the explanatory factor for a diverse range of linguistic phenomena. In particular, perceptual salience (e.g., visual salience of objects in the world, acoustic prominence of linguistic sounds) and semantic-pragmatic salience (e.g., prominence of recently mentioned or topical referents) have been shown to influence language comprehension and production. A different line of research has sought to account for behavioral correlates of cognitive load during comprehension as well as for certain patterns in language usage using information-theoretic notions, such as surprisal. Surprisal and salience both affect language processing at different levels, but the relationship between the two has not been adequately elucidated, and the question of whether salience can be reduced to surprisal / predictability is still open. Our review identifies two main challenges in addressing this question: terminological inconsistency and lack of integration between high and low levels of representations in salience-based accounts and surprisal-based accounts. We capitalize upon work in visual cognition in order to orient ourselves in surveying the different facets of the notion of salience in linguistics and their relation with models of surprisal. We find that work on salience highlights aspects of linguistic communication that models of surprisal tend to overlook, namely the role of attention and relevance to current goals, and we argue that the Predictive Coding framework provides a unified view which can account for the role played by attention and predictability at different levels of processing and which can clarify the interplay between low and high levels of processes and between predictability-driven expectation and attention-driven focus.

Syntactic Recursion Facilitates and Working Memory Predicts Recursive Theory of Mind

PubMed Central

Arslan, Burcu; Hohenberger, Annette; Verbrugge, Rineke

2017-01-01

In this study, we focus on the possible roles of second-order syntactic recursion and working memory in terms of simple and complex span tasks in the development of second-order false belief reasoning. We tested 89 Turkish children in two age groups, one younger (4;6–6;5 years) and one older (6;7–8;10 years). Although second-order syntactic recursion is significantly correlated with the second-order false belief task, results of ordinal logistic regressions revealed that the main predictor of second-order false belief reasoning is complex working memory span. Unlike simple working memory and second-order syntactic recursion tasks, the complex working memory task required processing information serially with additional reasoning demands that require complex working memory strategies. Based on our results, we propose that children’s second-order theory of mind develops when they have efficient reasoning rules to process embedded beliefs serially, thus overcoming a possible serial processing bottleneck. PMID:28072823

On the calibration process of film dosimetry: OLS inverse regression versus WLS inverse prediction.

PubMed

Crop, F; Van Rompaye, B; Paelinck, L; Vakaet, L; Thierens, H; De Wagter, C

2008-07-21

The purpose of this study was both putting forward a statistically correct model for film calibration and the optimization of this process. A reliable calibration is needed in order to perform accurate reference dosimetry with radiographic (Gafchromic) film. Sometimes, an ordinary least squares simple linear (in the parameters) regression is applied to the dose-optical-density (OD) curve with the dose as a function of OD (inverse regression) or sometimes OD as a function of dose (inverse prediction). The application of a simple linear regression fit is an invalid method because heteroscedasticity of the data is not taken into account. This could lead to erroneous results originating from the calibration process itself and thus to a lower accuracy. In this work, we compare the ordinary least squares (OLS) inverse regression method with the correct weighted least squares (WLS) inverse prediction method to create calibration curves. We found that the OLS inverse regression method could lead to a prediction bias of up to 7.3 cGy at 300 cGy and total prediction errors of 3% or more for Gafchromic EBT film. Application of the WLS inverse prediction method resulted in a maximum prediction bias of 1.4 cGy and total prediction errors below 2% in a 0-400 cGy range. We developed a Monte-Carlo-based process to optimize calibrations, depending on the needs of the experiment. This type of thorough analysis can lead to a higher accuracy for film dosimetry.

Drift-Scale Coupled Processes (DST and THC Seepage) Models

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

E. Gonnenthal; N. Spyoher

The purpose of this Analysis/Model Report (AMR) is to document the Near-Field Environment (NFE) and Unsaturated Zone (UZ) models used to evaluate the potential effects of coupled thermal-hydrologic-chemical (THC) processes on unsaturated zone flow and transport. This is in accordance with the ''Technical Work Plan (TWP) for Unsaturated Zone Flow and Transport Process Model Report'', Addendum D, Attachment D-4 (Civilian Radioactive Waste Management System (CRWMS) Management and Operating Contractor (M and O) 2000 [153447]) and ''Technical Work Plan for Nearfield Environment Thermal Analyses and Testing'' (CRWMS M and O 2000 [153309]). These models include the Drift Scale Test (DST) THCmore » Model and several THC seepage models. These models provide the framework to evaluate THC coupled processes at the drift scale, predict flow and transport behavior for specified thermal loading conditions, and predict the chemistry of waters and gases entering potential waste-emplacement drifts. The intended use of this AMR is to provide input for the following: (1) Performance Assessment (PA); (2) Abstraction of Drift-Scale Coupled Processes AMR (ANL-NBS-HS-000029); (3) UZ Flow and Transport Process Model Report (PMR); and (4) Near-Field Environment (NFE) PMR. The work scope for this activity is presented in the TWPs cited above, and summarized as follows: continue development of the repository drift-scale THC seepage model used in support of the TSPA in-drift geochemical model; incorporate heterogeneous fracture property realizations; study sensitivity of results to changes in input data and mineral assemblage; validate the DST model by comparison with field data; perform simulations to predict mineral dissolution and precipitation and their effects on fracture properties and chemistry of water (but not flow rates) that may seep into drifts; submit modeling results to the TDMS and document the models. The model development, input data, sensitivity and validation studies described in this AMR are required to fully document and address the requirements of the TWPs.« less

Drift-Scale Coupled Processes (DST and THC Seepage) Models

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

E. Sonnenthale

The purpose of this Analysis/Model Report (AMR) is to document the Near-Field Environment (NFE) and Unsaturated Zone (UZ) models used to evaluate the potential effects of coupled thermal-hydrologic-chemical (THC) processes on unsaturated zone flow and transport. This is in accordance with the ''Technical Work Plan (TWP) for Unsaturated Zone Flow and Transport Process Model Report'', Addendum D, Attachment D-4 (Civilian Radioactive Waste Management System (CRWMS) Management and Operating Contractor (M&O) 2000 [1534471]) and ''Technical Work Plan for Nearfield Environment Thermal Analyses and Testing'' (CRWMS M&O 2000 [153309]). These models include the Drift Scale Test (DST) THC Model and several THCmore » seepage models. These models provide the framework to evaluate THC coupled processes at the drift scale, predict flow and transport behavior for specified thermal loading conditions, and predict the chemistry of waters and gases entering potential waste-emplacement drifts. The intended use of this AMR is to provide input for the following: Performance Assessment (PA); Near-Field Environment (NFE) PMR; Abstraction of Drift-Scale Coupled Processes AMR (ANL-NBS-HS-000029); and UZ Flow and Transport Process Model Report (PMR). The work scope for this activity is presented in the TWPs cited above, and summarized as follows: Continue development of the repository drift-scale THC seepage model used in support of the TSPA in-drift geochemical model; incorporate heterogeneous fracture property realizations; study sensitivity of results to changes in input data and mineral assemblage; validate the DST model by comparison with field data; perform simulations to predict mineral dissolution and precipitation and their effects on fracture properties and chemistry of water (but not flow rates) that may seep into drifts; submit modeling results to the TDMS and document the models. The model development, input data, sensitivity and validation studies described in this AMR are required to fully document and address the requirements of the TWPs.« less

Individual differences in physiological flexibility predict spontaneous avoidance.

PubMed

Aldao, Amelia; Dixon-Gordon, Katherine L; De Los Reyes, Andres

2016-08-01

People often regulate their emotions by resorting to avoidance, a putatively maladaptive strategy. Prior work suggests that increased psychopathology symptoms predict greater spontaneous utilisation of this strategy. Extending this work, we examined whether heightened resting cardiac vagal tone (which reflects a general ability to regulate emotions in line with contextual demands) predicts decreased spontaneous avoidance. In Study 1, greater resting vagal tone was associated with reduced spontaneous avoidance in response to disgust-eliciting pictures, beyond anxiety and depression symptoms and emotional reactivity. In Study 2, resting vagal tone interacted with anxiety and depression symptoms to predict spontaneous avoidance in response to disgust-eliciting film clips. The positive association between symptoms and spontaneous avoidance was more pronounced among participants with reduced resting vagal tone. Thus, increased resting vagal tone might protect against the use of avoidance. Our findings highlight the importance of assessing both subjective and biological processes when studying individual differences in emotion regulation.

Assessing working memory in children with ADHD: Minor administration and scoring changes may improve digit span backward's construct validity.

PubMed

Wells, Erica L; Kofler, Michael J; Soto, Elia F; Schaefer, Hillary S; Sarver, Dustin E

2018-01-01

Pediatric ADHD is associated with impairments in working memory, but these deficits often go undetected when using clinic-based tests such as digit span backward. The current study pilot-tested minor administration/scoring modifications to improve digit span backward's construct and predictive validities in a well-characterized sample of children with ADHD. WISC-IV digit span was modified to administer all trials (i.e., ignore discontinue rule) and count digits rather than trials correct. Traditional and modified scores were compared to a battery of criterion working memory (construct validity) and academic achievement tests (predictive validity) for 34 children with ADHD ages 8-13 (M=10.41; 11 girls). Traditional digit span backward scores failed to predict working memory or KTEA-2 achievement (allns). Alternate administration/scoring of digit span backward significantly improved its associations with working memory reordering (r=.58), working memory dual-processing (r=.53), working memory updating (r=.28), and KTEA-2 achievement (r=.49). Consistent with prior work, these findings urge caution when interpreting digit span performance. Minor test modifications may address test validity concerns, and should be considered in future test revisions. Digit span backward becomes a valid measure of working memory at exactly the point that testing is traditionally discontinued. Copyright © 2017 Elsevier Ltd. All rights reserved.

Homeostatic Regulation of Memory Systems and Adaptive Decisions

PubMed Central

Mizumori, Sheri JY; Jo, Yong Sang

2013-01-01

While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The “multiple memory systems of the brain” have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in rigid and suboptimal decision making and memory as seen in addiction and neurological disease. © 2013 The Authors. Hippocampus Published by Wiley Periodicals, Inc. PMID:23929788

Homeostatic regulation of memory systems and adaptive decisions.

PubMed

Mizumori, Sheri J Y; Jo, Yong Sang

2013-11-01

While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The "multiple memory systems of the brain" have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in rigid and suboptimal decision making and memory as seen in addiction and neurological disease. Copyright © 2013 Wiley Periodicals, Inc.

Post-processing of global model output to forecast point rainfall

NASA Astrophysics Data System (ADS)

Hewson, Tim; Pillosu, Fatima

2016-04-01

ECMWF (the European Centre for Medium range Weather Forecasts) has recently embarked upon a new project to post-process gridbox rainfall forecasts from its ensemble prediction system, to provide probabilistic forecasts of point rainfall. The new post-processing strategy relies on understanding how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals. We use a number of simple global model parameters, such as the convective rainfall fraction, to anticipate the sub-grid variability, and then post-process each ensemble forecast into a pdf (probability density function) for a point-rainfall total. The final forecast will comprise the sum of the different pdfs from all ensemble members. The post-processing is essentially a re-calibration exercise, which needs only rainfall totals from standard global reporting stations (and forecasts) to train it. High density observations are not needed. This presentation will describe results from the initial 'proof of concept' study, which has been remarkably successful. Reference will also be made to other useful outcomes of the work, such as gaining insights into systematic model biases in different synoptic settings. The special case of orographic rainfall will also be discussed. Work ongoing this year will also be described. This involves further investigations of which model parameters can provide predictive skill, and will then move on to development of an operational system for predicting point rainfall across the globe. The main practical benefit of this system will be a greatly improved capacity to predict extreme point rainfall, and thereby provide early warnings, for the whole world, of flash flood potential for lead times that extend beyond day 5. This will be incorporated into the suite of products output by GLOFAS (the GLObal Flood Awareness System) which is hosted at ECMWF. As such this work offers a very cost-effective approach to satisfying user needs right around the world. This field has hitherto relied on using very expensive high-resolution ensembles; by their very nature these can only run over small regions, and only for lead times up to about 2 days.

Drift-Scale Coupled Processes (DST and THC Seepage) Models

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

P. Dixon

The purpose of this Model Report (REV02) is to document the unsaturated zone (UZ) models used to evaluate the potential effects of coupled thermal-hydrological-chemical (THC) processes on UZ flow and transport. This Model Report has been developed in accordance with the ''Technical Work Plan for: Performance Assessment Unsaturated Zone'' (Bechtel SAIC Company, LLC (BSC) 2002 [160819]). The technical work plan (TWP) describes planning information pertaining to the technical scope, content, and management of this Model Report in Section 1.12, Work Package AUZM08, ''Coupled Effects on Flow and Seepage''. The plan for validation of the models documented in this Model Reportmore » is given in Attachment I, Model Validation Plans, Section I-3-4, of the TWP. Except for variations in acceptance criteria (Section 4.2), there were no deviations from this TWP. This report was developed in accordance with AP-SIII.10Q, ''Models''. This Model Report documents the THC Seepage Model and the Drift Scale Test (DST) THC Model. The THC Seepage Model is a drift-scale process model for predicting the composition of gas and water that could enter waste emplacement drifts and the effects of mineral alteration on flow in rocks surrounding drifts. The DST THC model is a drift-scale process model relying on the same conceptual model and much of the same input data (i.e., physical, hydrological, thermodynamic, and kinetic) as the THC Seepage Model. The DST THC Model is the primary method for validating the THC Seepage Model. The DST THC Model compares predicted water and gas compositions, as well as mineral alteration patterns, with observed data from the DST. These models provide the framework to evaluate THC coupled processes at the drift scale, predict flow and transport behavior for specified thermal-loading conditions, and predict the evolution of mineral alteration and fluid chemistry around potential waste emplacement drifts. The DST THC Model is used solely for the validation of the THC Seepage Model and is not used for calibration to measured data.« less

Working Memory Load Strengthens Reward Prediction Errors.

PubMed

Collins, Anne G E; Ciullo, Brittany; Frank, Michael J; Badre, David

2017-04-19

Reinforcement learning (RL) in simple instrumental tasks is usually modeled as a monolithic process in which reward prediction errors (RPEs) are used to update expected values of choice options. This modeling ignores the different contributions of different memory and decision-making systems thought to contribute even to simple learning. In an fMRI experiment, we investigated how working memory (WM) and incremental RL processes interact to guide human learning. WM load was manipulated by varying the number of stimuli to be learned across blocks. Behavioral results and computational modeling confirmed that learning was best explained as a mixture of two mechanisms: a fast, capacity-limited, and delay-sensitive WM process together with slower RL. Model-based analysis of fMRI data showed that striatum and lateral prefrontal cortex were sensitive to RPE, as shown previously, but, critically, these signals were reduced when the learning problem was within capacity of WM. The degree of this neural interaction related to individual differences in the use of WM to guide behavioral learning. These results indicate that the two systems do not process information independently, but rather interact during learning. SIGNIFICANCE STATEMENT Reinforcement learning (RL) theory has been remarkably productive at improving our understanding of instrumental learning as well as dopaminergic and striatal network function across many mammalian species. However, this neural network is only one contributor to human learning and other mechanisms such as prefrontal cortex working memory also play a key role. Our results also show that these other players interact with the dopaminergic RL system, interfering with its key computation of reward prediction errors. Copyright © 2017 the authors 0270-6474/17/374332-11$15.00/0.

Longevity and ageing: appraising the evolutionary consequences of growing old

PubMed Central

Bonsall, Michael B

2005-01-01

Senescence or ageing is an increase in mortality and/or decline in fertility with increasing age. Evolutionary theories predict that ageing or longevity evolves in response to patterns of extrinsic mortality or intrinsic damage. If ageing is viewed as the outcome of the processes of behaviour, growth and reproduction then it should be possible to predict mortality rate. Recent developments have shown that it is now possible to integrate these ecological and physiological processes and predict the shape of mortality trajectories. By drawing on the key exciting developments in the cellular, physiological and ecological process of longevity the evolutionary consequences of ageing are reviewed. In presenting these ideas an evolutionary demographic framework is used to argue how trade-offs in life-history strategies are important in the maintenance of variation in longevity within and between species. Evolutionary processes associated with longevity have an important role in explaining levels of biological diversity and speciation. In particular, the effects of life-history trait trade-offs in maintaining and promoting species diversity are explored. Such trade-offs can alleviate the effects of intense competition between species and promote species coexistence and diversification. These results have important implications for understanding a number of core ecological processes such as how species are divided among niches, how closely related species co-occur and the rules by which species assemble into food-webs. Theoretical work reveals that the proximate physiological processes are as important as the ecological factors in explaining the variation in the evolution of longevity. Possible future research challenges integrating work on the evolution and mechanisms of growing old are briefly discussed. PMID:16553312

Electronic Nose Based on Independent Component Analysis Combined with Partial Least Squares and Artificial Neural Networks for Wine Prediction

PubMed Central

Aguilera, Teodoro; Lozano, Jesús; Paredes, José A.; Álvarez, Fernando J.; Suárez, José I.

2012-01-01

The aim of this work is to propose an alternative way for wine classification and prediction based on an electronic nose (e-nose) combined with Independent Component Analysis (ICA) as a dimensionality reduction technique, Partial Least Squares (PLS) to predict sensorial descriptors and Artificial Neural Networks (ANNs) for classification purpose. A total of 26 wines from different regions, varieties and elaboration processes have been analyzed with an e-nose and tasted by a sensory panel. Successful results have been obtained in most cases for prediction and classification. PMID:22969387

An Integrated Approach Linking Process to Structural Modeling With Microstructural Characterization for Injections-Molded Long-Fiber Thermoplastics

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

Nguyen, Ba Nghiep; Bapanapalli, Satish K.; Smith, Mark T.

2008-09-01

The objective of our work is to enable the optimum design of lightweight automotive structural components using injection-molded long fiber thermoplastics (LFTs). To this end, an integrated approach that links process modeling to structural analysis with experimental microstructural characterization and validation is developed. First, process models for LFTs are developed and implemented into processing codes (e.g. ORIENT, Moldflow) to predict the microstructure of the as-formed composite (i.e. fiber length and orientation distributions). In parallel, characterization and testing methods are developed to obtain necessary microstructural data to validate process modeling predictions. Second, the predicted LFT composite microstructure is imported into amore » structural finite element analysis by ABAQUS to determine the response of the as-formed composite to given boundary conditions. At this stage, constitutive models accounting for the composite microstructure are developed to predict various types of behaviors (i.e. thermoelastic, viscoelastic, elastic-plastic, damage, fatigue, and impact) of LFTs. Experimental methods are also developed to determine material parameters and to validate constitutive models. Such a process-linked-structural modeling approach allows an LFT composite structure to be designed with confidence through numerical simulations. Some recent results of our collaborative research will be illustrated to show the usefulness and applications of this integrated approach.« less

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

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

Allen, C.A.W.; Watts, K.C.

Engine results using biofuels have varied considerably in the reported literature. This article addresses two potential sources of this variation, atomization differences and impurities due to lack of quality control during production. Atomization is the first process encountered during the combustion of fuels in a compression ignition engine and is largely determined by the fuel's viscosity and surface tension. Previous work using five experimentally produced methyl ester biodiesel fuels showed that the viscosity and surface tension could be predicted from their fatty acid ester composition, and the atomization characteristics in turn could be predicted from their viscosity and surface tension.more » This article utilizes the results of that work to give a quantitative comparison of the atomization characteristics of fifteen biodiesel fuel types using the fuel's viscosity and surface tension, predicted directly from the fatty acid composition of the fuels. Except for coconut and rapeseed biodiesel fuels, all of the rest of the 15 biodiesel fuels had similar atomization characteristics. Since the most likely contaminant in the fuel from the processing was residual glycerides, their effect on viscosity and surface tension was studied experimentally and their effect on the atomization characteristics was computed.« less

Individual reactions to high involvement work processes: investigating the role of empowerment and perceived organizational support.

PubMed

Butts, Marcus M; Vandenberg, Robert J; DeJoy, David M; Schaffer, Bryan S; Wilson, Mark G

2009-04-01

This study sought to understand how high involvement work processes (HIWP) are processed at the employee level. Using structural equation modeling techniques, the authors tested and supported a model in which psychological empowerment mediated the effects of HIWP on job satisfaction, organizational commitment, job performance, and job stress. Furthermore, perceived organizational support (POS) was hypothesized to moderate the relationships between empowerment and these outcomes. With exception for the empowerment-job satisfaction association, support was found for our predictions. Future directions for research and the practical implications of our findings for both employees and organizations are discussed.

Tire Changes, Fresh Air, and Yellow Flags: Challenges in Predictive Analytics for Professional Racing.

PubMed

Tulabandhula, Theja; Rudin, Cynthia

2014-06-01

Our goal is to design a prediction and decision system for real-time use during a professional car race. In designing a knowledge discovery process for racing, we faced several challenges that were overcome only when domain knowledge of racing was carefully infused within statistical modeling techniques. In this article, we describe how we leveraged expert knowledge of the domain to produce a real-time decision system for tire changes within a race. Our forecasts have the potential to impact how racing teams can optimize strategy by making tire-change decisions to benefit their rank position. Our work significantly expands previous research on sports analytics, as it is the only work on analytical methods for within-race prediction and decision making for professional car racing.

The effects of limited bandwidth and noise on verbal processing time and word recall in normal-hearing children.

PubMed

McCreery, Ryan W; Stelmachowicz, Patricia G

2013-09-01

Understanding speech in acoustically degraded environments can place significant cognitive demands on school-age children who are developing the cognitive and linguistic skills needed to support this process. Previous studies suggest the speech understanding, word learning, and academic performance can be negatively impacted by background noise, but the effect of limited audibility on cognitive processes in children has not been directly studied. The aim of the present study was to evaluate the impact of limited audibility on speech understanding and working memory tasks in school-age children with normal hearing. Seventeen children with normal hearing between 6 and 12 years of age participated in the present study. Repetition of nonword consonant-vowel-consonant stimuli was measured under conditions with combinations of two different signal to noise ratios (SNRs; 3 and 9 dB) and two low-pass filter settings (3.2 and 5.6 kHz). Verbal processing time was calculated based on the time from the onset of the stimulus to the onset of the child's response. Monosyllabic word repetition and recall were also measured in conditions with a full bandwidth and 5.6 kHz low-pass cutoff. Nonword repetition scores decreased as audibility decreased. Verbal processing time increased as audibility decreased, consistent with predictions based on increased listening effort. Although monosyllabic word repetition did not vary between the full bandwidth and 5.6 kHz low-pass filter condition, recall was significantly poorer in the condition with limited bandwidth (low pass at 5.6 kHz). Age and expressive language scores predicted performance on word recall tasks, but did not predict nonword repetition accuracy or verbal processing time. Decreased audibility was associated with reduced accuracy for nonword repetition and increased verbal processing time in children with normal hearing. Deficits in free recall were observed even under conditions where word repetition was not affected. The negative effects of reduced audibility may occur even under conditions where speech repetition is not impacted. Limited stimulus audibility may result in greater cognitive effort for verbal rehearsal in working memory and may limit the availability of cognitive resources to allocate to working memory and other processes.

Psychodynamic theory and counseling in predictive testing for Huntington's disease.

PubMed

Tassicker, Roslyn J

2005-04-01

This paper revisits psychodynamic theory, which can be applied in predictive testing counseling for Huntington's Disease (HD). Psychodynamic theory has developed from the work of Freud and places importance on early parent-child experiences. The nature of these relationships, or attachments are reflected in adult expectations and relationships. Two significant concepts, identification and fear of abandonment, have been developed and expounded by the psychodynamic theorist, Melanie Klein. The processes of identification and fear of abandonment can become evident in predictive testing counseling and are colored by the client's experience of growing up with a parent affected by Huntington's Disease. In reflecting on family-of-origin experiences, clients can also express implied expectations of the future, and future relationships. Case examples are given to illustrate the dynamic processes of identification and fear of abandonment which may present in the clinical setting. Counselor recognition of these processes can illuminate and inform counseling practice.

The Importance of Encoding-Related Neural Dynamics in the Prediction of Inter-Individual Differences in Verbal Working Memory Performance

PubMed Central

Majerus, Steve; Salmon, Eric; Attout, Lucie

2013-01-01

Studies of brain-behaviour interactions in the field of working memory (WM) have associated WM success with activation of a fronto-parietal network during the maintenance stage, and this mainly for visuo-spatial WM. Using an inter-individual differences approach, we demonstrate here the equal importance of neural dynamics during the encoding stage, and this in the context of verbal WM tasks which are characterized by encoding phases of long duration and sustained attentional demands. Participants encoded and maintained 5-word lists, half of them containing an unexpected word intended to disturb WM encoding and associated task-related attention processes. We observed that inter-individual differences in WM performance for lists containing disturbing stimuli were related to activation levels in a region previously associated with task-related attentional processing, the left intraparietal sulcus (IPS), and this during stimulus encoding but not maintenance; functional connectivity strength between the left IPS and lateral prefrontal cortex (PFC) further predicted WM performance. This study highlights the critical role, during WM encoding, of neural substrates involved in task-related attentional processes for predicting inter-individual differences in verbal WM performance, and, more generally, provides support for attention-based models of WM. PMID:23874935

Carving Executive Control at Its Joints: Working Memory Capacity Predicts Stimulus-Stimulus, but Not Stimulus-Response, Conflict

ERIC Educational Resources Information Center

Meier, Matt E.; Kane, Michael J.

2015-01-01

Three experiments examined the relation between working memory capacity (WMC) and 2 different forms of cognitive conflict: stimulus-stimulus (S-S) and stimulus-response (S-R) interference. Our goal was to test whether WMC's relation to conflict-task performance is mediated by stimulus-identification processes (captured by S-S conflict),…

Teacher Professionalism: Subverting the Society of Control

ERIC Educational Resources Information Center

Wood, Phil

2014-01-01

The past 30 years have seen a series of major shifts in English education. Central to these changes has been the growth of data systems which now measure and control the work of teachers to a huge degree. This form of data-led surveillance was predicted in the work of Gilles Deleuze, a totalising process where data become more important than the…

Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster.

PubMed

Wan, Cen; Lees, Jonathan G; Minneci, Federico; Orengo, Christine A; Jones, David T

2017-10-01

Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.

Predictors of change in life skills in schizophrenia after cognitive remediation.

PubMed

Kurtz, Matthew M; Seltzer, James C; Fujimoto, Marco; Shagan, Dana S; Wexler, Bruce E

2009-02-01

Few studies have investigated predictors of response to cognitive remediation interventions in patients with schizophrenia. Predictor studies to date have selected treatment outcome measures that were either part of the remediation intervention itself or closely linked to the intervention with few studies investigating factors that predict generalization to measures of everyday life-skills as an index of treatment-related improvement. In the current study we investigated the relationship between four measures of neurocognitive function, crystallized verbal ability, auditory sustained attention and working memory, verbal learning and memory, and problem-solving, two measures of symptoms, total positive and negative symptoms, and the process variables of treatment intensity and duration, to change on a performance-based measure of everyday life-skills after a year of computer-assisted cognitive remediation offered as part of intensive outpatient rehabilitation treatment. Thirty-six patients with schizophrenia or schizoaffective disorder were studied. Results of a linear regression model revealed that auditory attention and working memory predicted a significant amount of the variance in change in performance-based measures of everyday life skills after cognitive remediation, even when variance for all other neurocognitive variables in the model was controlled. Stepwise regression revealed that auditory attention and working memory predicted change in everyday life-skills across the trial even when baseline life-skill scores, symptoms and treatment process variables were controlled. These findings emphasize the importance of sustained auditory attention and working memory for benefiting from extended programs of cognitive remediation.

Passion for work and emotional exhaustion: the mediating role of rumination and recovery.

PubMed

Donahue, Eric G; Forest, Jacques; Vallerand, Robert J; Lemyre, Pierre-Nicolas; Crevier-Braud, Laurence; Bergeron, Eliane

2012-11-01

The purpose of the present research is to present a model pertaining to the mediating roles of rumination and recovery experiences in the relationship between a harmonious and an obsessive passion (Vallerand et al., 2003) for work and workers' emotional exhaustion. Two populations were measured in the present research: namely elite coaches and nurses. Study 1's model posits that obsessive passion positively predicts rumination about one's work when being physically away from work, while harmonious passion negatively predicts ruminative thoughts. In turn, rumination is expected to positively contribute to emotional exhaustion. The results of Study 1 were replicated in Study 2. In addition, in the model of Study 2, obsessive passion was expected to undermine recovery experiences, while harmonious passion was expected to predict recovery experiences. In turn, recovery experiences were expected to protect workers from emotional exhaustion. Results of both studies provided support for the proposed model. The present findings demonstrate that passion for work may lead to some adaptive and maladaptive psychological processes depending on the type of passion that is prevalent. © 2012 The Authors. Applied Psychology: Health and Well-Being © 2012 The International Association of Applied Psychology.

Predicting the magnetic vectors within coronal mass ejections arriving at Earth: 1. Initial architecture

NASA Astrophysics Data System (ADS)

Savani, N. P.; Vourlidas, A.; Szabo, A.; Mays, M. L.; Richardson, I. G.; Thompson, B. J.; Pulkkinen, A.; Evans, R.; Nieves-Chinchilla, T.

2015-06-01

The process by which the Sun affects the terrestrial environment on short timescales is predominately driven by the amount of magnetic reconnection between the solar wind and Earth's magnetosphere. Reconnection occurs most efficiently when the solar wind magnetic field has a southward component. The most severe impacts are during the arrival of a coronal mass ejection (CME) when the magnetosphere is both compressed and magnetically connected to the heliospheric environment. Unfortunately, forecasting magnetic vectors within coronal mass ejections remain elusive. Here we report how, by combining a statistically robust helicity rule for a CME's solar origin with a simplified flux rope topology, the magnetic vectors within the Earth-directed segment of a CME can be predicted. In order to test the validity of this proof-of-concept architecture for estimating the magnetic vectors within CMEs, a total of eight CME events (between 2010 and 2014) have been investigated. With a focus on the large false alarm of January 2014, this work highlights the importance of including the early evolutionary effects of a CME for forecasting purposes. The angular rotation in the predicted magnetic field closely follows the broad rotational structure seen within the in situ data. This time-varying field estimate is implemented into a process to quantitatively predict a time-varying Kp index that is described in detail in paper II. Future statistical work, quantifying the uncertainties in this process, may improve the more heuristic approach used by early forecasting systems.

Relationship Among Signal Fidelity, Hearing Loss, and Working Memory for Digital Noise Suppression.

PubMed

Arehart, Kathryn; Souza, Pamela; Kates, James; Lunner, Thomas; Pedersen, Michael Syskind

2015-01-01

This study considered speech modified by additive babble combined with noise-suppression processing. The purpose was to determine the relative importance of the signal modifications, individual peripheral hearing loss, and individual cognitive capacity on speech intelligibility and speech quality. The participant group consisted of 31 individuals with moderate high-frequency hearing loss ranging in age from 51 to 89 years (mean = 69.6 years). Speech intelligibility and speech quality were measured using low-context sentences presented in babble at several signal-to-noise ratios. Speech stimuli were processed with a binary mask noise-suppression strategy with systematic manipulations of two parameters (error rate and attenuation values). The cumulative effects of signal modification produced by babble and signal processing were quantified using an envelope-distortion metric. Working memory capacity was assessed with a reading span test. Analysis of variance was used to determine the effects of signal processing parameters on perceptual scores. Hierarchical linear modeling was used to determine the role of degree of hearing loss and working memory capacity in individual listener response to the processed noisy speech. The model also considered improvements in envelope fidelity caused by the binary mask and the degradations to envelope caused by error and noise. The participants showed significant benefits in terms of intelligibility scores and quality ratings for noisy speech processed by the ideal binary mask noise-suppression strategy. This benefit was observed across a range of signal-to-noise ratios and persisted when up to a 30% error rate was introduced into the processing. Average intelligibility scores and average quality ratings were well predicted by an objective metric of envelope fidelity. Degree of hearing loss and working memory capacity were significant factors in explaining individual listener's intelligibility scores for binary mask processing applied to speech in babble. Degree of hearing loss and working memory capacity did not predict listeners' quality ratings. The results indicate that envelope fidelity is a primary factor in determining the combined effects of noise and binary mask processing for intelligibility and quality of speech presented in babble noise. Degree of hearing loss and working memory capacity are significant factors in explaining variability in listeners' speech intelligibility scores but not in quality ratings.

Cognitive components of a mathematical processing network in 9-year-old children.

PubMed

Szűcs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

2014-07-01

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular 'number sense'. We suggest an 'executive memory function centric' model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors.

Cognitive components of a mathematical processing network in 9-year-old children

PubMed Central

Szűcs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

2014-01-01

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular ‘number sense’. We suggest an ‘executive memory function centric’ model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors. PMID:25089322

Evaluating High-Degree-and-Order Gravitational Harmonics and its Application to the State Predictions of a Lunar Orbiting Satellite

NASA Astrophysics Data System (ADS)

Song, Young-Joo; Kim, Bang-Yeop

2015-09-01

In this work, an efficient method with which to evaluate the high-degree-and-order gravitational harmonics of the nonsphericity of a central body is described and applied to state predictions of a lunar orbiter. Unlike the work of Song et al. (2010), which used a conventional computation method to process gravitational harmonic coefficients, the current work adapted a well-known recursion formula that directly uses fully normalized associated Legendre functions to compute the acceleration due to the non-sphericity of the moon. With the formulated algorithms, the states of a lunar orbiting satellite are predicted and its performance is validated in comparisons with solutions obtained from STK/Astrogator. The predicted differences in the orbital states between STK/Astrogator and the current work all remain at a position of less than 1 m with velocity accuracy levels of less than 1 mm/s, even with different orbital inclinations. The effectiveness of the current algorithm, in terms of both the computation time and the degree of accuracy degradation, is also shown in comparisons with results obtained from earlier work. It is expected that the proposed algorithm can be used as a foundation for the development of an operational flight dynamics subsystem for future lunar exploration missions by Korea. It can also be used to analyze missions which require very close operations to the moon.

How personal resources predict work engagement and self-rated performance among construction workers: a social cognitive perspective.

PubMed

Lorente, Laura; Salanova, Marisa; Martínez, Isabel M; Vera, María

2014-06-01

Traditionally, research focussing on psychosocial factors in the construction industry has focused mainly on the negative aspects of health and on results such as occupational accidents. This study, however, focuses on the specific relationships among the different positive psychosocial factors shared by construction workers that could be responsible for occupational well-being and outcomes such as performance. The main objective of this study was to test whether personal resources predict self-rated job performance through job resources and work engagement. Following the predictions of Bandura's Social Cognitive Theory and the motivational process of the Job Demands-Resources Model, we expect that the relationship between personal resources and performance will be fully mediated by job resources and work engagement. The sample consists of 228 construction workers. Structural equation modelling supports the research model. Personal resources (i.e. self-efficacy, mental and emotional competences) play a predicting role in the perception of job resources (i.e. job control and supervisor social support), which in turn leads to work engagement and self-rated performance. This study emphasises the crucial role that personal resources play in determining how people perceive job resources by determining the levels of work engagement and, hence, their self-rated job performance. Theoretical and practical implications are discussed. © 2014 International Union of Psychological Science.

New Computer Simulation Procedure of Heading Face Mining Process with Transverse Cutting Heads for Roadheader Automation

NASA Astrophysics Data System (ADS)

Dolipski, Marian; Cheluszka, Piotr; Sobota, Piotr; Remiorz, Eryk

2017-03-01

The key working process carried out by roadheaders is rock mining. For this reason, the mathematical modelling of the mining process is underlying the prediction of a dynamic load on the main components of a roadheader, the prediction of power demand for rock cutting with given properties or the prediction of energy consumption of this process. The theoretical and experimental investigations conducted point out - especially in relation to the technical parameters of roadheaders used these days in underground mining and their operating conditions - that the mathematical models of the process employed to date have many limitations, and in many cases the results obtained using such models deviate largely from the reality. This is due to the fact that certain factors strongly influencing cutting process progress have not been considered at the modelling stage, or have been approached in an oversimplified fashion. The article presents a new model of a rock cutting process using conical picks of cutting heads of boom-type roadheaders. An important novelty with respect to the models applied to date is, firstly, that the actual shape of cuts has been modelled with such shape resulting from the geometry of the currently used conical picks, and, secondly, variations in the depth of cuts in the cutting path of individual picks have been considered with such variations resulting from the picks' kinematics during the advancement of transverse cutting heads parallel to the floor surface. The work presents examples of simulation results for mining with a roadheader's transverse head equipped with 80 conical picks and compares them with the outcomes obtained using the existing model.

Predicting on-site environmental impacts of municipal engineering works

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

Gangolells, Marta, E-mail: marta.gangolells@upc.edu; Casals, Miquel, E-mail: miquel.casals@upc.edu; Forcada, Núria, E-mail: nuria.forcada@upc.edu

2014-01-15

The research findings fill a gap in the body of knowledge by presenting an effective way to evaluate the significance of on-site environmental impacts of municipal engineering works prior to the construction stage. First, 42 on-site environmental impacts of municipal engineering works were identified by means of a process-oriented approach. Then, 46 indicators and their corresponding significance limits were determined on the basis of a statistical analysis of 25 new-build and remodelling municipal engineering projects. In order to ensure the objectivity of the assessment process, direct and indirect indicators were always based on quantitative data from the municipal engineering projectmore » documents. Finally, two case studies were analysed and found to illustrate the practical use of the proposed model. The model highlights the significant environmental impacts of a particular municipal engineering project prior to the construction stage. Consequently, preventive actions can be planned and implemented during on-site activities. The results of the model also allow a comparison of proposed municipal engineering projects and alternatives with respect to the overall on-site environmental impact and the absolute importance of a particular environmental aspect. These findings are useful within the framework of the environmental impact assessment process, as they help to improve the identification and evaluation of on-site environmental aspects of municipal engineering works. The findings may also be of use to construction companies that are willing to implement an environmental management system or simply wish to improve on-site environmental performance in municipal engineering projects. -- Highlights: • We present a model to predict the environmental impacts of municipal engineering works. • It highlights significant on-site environmental impacts prior to the construction stage. • Findings are useful within the environmental impact assessment process. • They also help contractors to implement environmental management systems.« less

Spatial-Sequential Working Memory in Younger and Older Adults: Age Predicts Backward Recall Performance within Both Age Groups

PubMed Central

Brown, Louise A.

2016-01-01

Working memory is vulnerable to age-related decline, but there is debate regarding the age-sensitivity of different forms of spatial-sequential working memory task, depending on their passive or active nature. The functional architecture of spatial working memory was therefore explored in younger (18–40 years) and older (64–85 years) adults, using passive and active recall tasks. Spatial working memory was assessed using a modified version of the Spatial Span subtest of the Wechsler Memory Scale – Third Edition (WMS-III; Wechsler, 1998). Across both age groups, the effects of interference (control, visual, or spatial), and recall type (forward and backward), were investigated. There was a clear effect of age group, with younger adults demonstrating a larger spatial working memory capacity than the older adults overall. There was also a specific effect of interference, with the spatial interference task (spatial tapping) reliably reducing performance relative to both the control and visual interference (dynamic visual noise) conditions in both age groups and both recall types. This suggests that younger and older adults have similar dependence upon active spatial rehearsal, and that both forward and backward recall require this processing capacity. Linear regression analyses were then carried out within each age group, to assess the predictors of performance in each recall format (forward and backward). Specifically the backward recall task was significantly predicted by age, within both the younger and older adult groups. This finding supports previous literature showing lifespan linear declines in spatial-sequential working memory, and in working memory tasks from other domains, but contrasts with previous evidence that backward spatial span is no more sensitive to aging than forward span. The study suggests that backward spatial span is indeed more processing-intensive than forward span, even when both tasks include a retention period, and that age predicts backward spatial span performance across the adult lifespan, within both younger and older adulthood. PMID:27757096

Spatial-Sequential Working Memory in Younger and Older Adults: Age Predicts Backward Recall Performance within Both Age Groups.

PubMed

Brown, Louise A

2016-01-01

Working memory is vulnerable to age-related decline, but there is debate regarding the age-sensitivity of different forms of spatial-sequential working memory task, depending on their passive or active nature. The functional architecture of spatial working memory was therefore explored in younger (18-40 years) and older (64-85 years) adults, using passive and active recall tasks. Spatial working memory was assessed using a modified version of the Spatial Span subtest of the Wechsler Memory Scale - Third Edition (WMS-III; Wechsler, 1998). Across both age groups, the effects of interference (control, visual, or spatial), and recall type (forward and backward), were investigated. There was a clear effect of age group, with younger adults demonstrating a larger spatial working memory capacity than the older adults overall. There was also a specific effect of interference, with the spatial interference task (spatial tapping) reliably reducing performance relative to both the control and visual interference (dynamic visual noise) conditions in both age groups and both recall types. This suggests that younger and older adults have similar dependence upon active spatial rehearsal, and that both forward and backward recall require this processing capacity. Linear regression analyses were then carried out within each age group, to assess the predictors of performance in each recall format (forward and backward). Specifically the backward recall task was significantly predicted by age, within both the younger and older adult groups. This finding supports previous literature showing lifespan linear declines in spatial-sequential working memory, and in working memory tasks from other domains, but contrasts with previous evidence that backward spatial span is no more sensitive to aging than forward span. The study suggests that backward spatial span is indeed more processing-intensive than forward span, even when both tasks include a retention period, and that age predicts backward spatial span performance across the adult lifespan, within both younger and older adulthood.

Investigation into the influence of build parameters on failure of 3D printed parts

NASA Astrophysics Data System (ADS)

Fornasini, Giacomo

Additive manufacturing, including fused deposition modeling (FDM), is transforming the built world and engineering education. Deep understanding of parts created through FDM technology has lagged behind its adoption in home, work, and academic environments. Properties of parts created from bulk materials through traditional manufacturing are understood well enough to accurately predict their behavior through analytical models. Unfortunately, Additive Manufacturing (AM) process parameters create anisotropy on a scale that fundamentally affects the part properties. Understanding AM process parameters (implemented by program algorithms called slicers) is necessary to predict part behavior. Investigating algorithms controlling print parameters (slicers) revealed stark differences between the generation of part layers. In this work, tensile testing experiments, including a full factorial design, determined that three key factors, width, thickness, infill density, and their interactions, significantly affect the tensile properties of 3D printed test samples.

Quality status display for a vibration welding process

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

Spicer, John Patrick; Abell, Jeffrey A.; Wincek, Michael Anthony

A method includes receiving, during a vibration welding process, a set of sensory signals from a collection of sensors positioned with respect to a work piece during formation of a weld on or within the work piece. The method also includes receiving control signals from a welding controller during the process, with the control signals causing the welding horn to vibrate at a calibrated frequency, and processing the received sensory and control signals using a host machine. Additionally, the method includes displaying a predicted weld quality status on a surface of the work piece using a status projector. The methodmore » may include identifying and display a quality status of a suspect weld. The laser projector may project a laser beam directly onto or immediately adjacent to the suspect welds, e.g., as a red, green, blue laser or a gas laser having a switched color filter.« less

Predicting drug side-effect profiles: a chemical fragment-based approach

PubMed Central

2011-01-01

Background Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes of failure in the process of drug development, and of drug withdrawal once they have reached the market. Therefore, in silico prediction of potential side-effects early in the drug discovery process, before reaching the clinical stages, is of great interest to improve this long and expensive process and to provide new efficient and safe therapies for patients. Results In the present work, we propose a new method to predict potential side-effects of drug candidate molecules based on their chemical structures, applicable on large molecular databanks. A unique feature of the proposed method is its ability to extract correlated sets of chemical substructures (or chemical fragments) and side-effects. This is made possible using sparse canonical correlation analysis (SCCA). In the results, we show the usefulness of the proposed method by predicting 1385 side-effects in the SIDER database from the chemical structures of 888 approved drugs. These predictions are performed with simultaneous extraction of correlated ensembles formed by a set of chemical substructures shared by drugs that are likely to have a set of side-effects. We also conduct a comprehensive side-effect prediction for many uncharacterized drug molecules stored in DrugBank, and were able to confirm interesting predictions using independent source of information. Conclusions The proposed method is expected to be useful in various stages of the drug development process. PMID:21586169

The relation between working memory and language comprehension in signers and speakers.

PubMed

Emmorey, Karen; Giezen, Marcel R; Petrich, Jennifer A F; Spurgeon, Erin; O'Grady Farnady, Lucinda

2017-06-01

This study investigated the relation between linguistic and spatial working memory (WM) resources and language comprehension for signed compared to spoken language. Sign languages are both linguistic and visual-spatial, and therefore provide a unique window on modality-specific versus modality-independent contributions of WM resources to language processing. Deaf users of American Sign Language (ASL), hearing monolingual English speakers, and hearing ASL-English bilinguals completed several spatial and linguistic serial recall tasks. Additionally, their comprehension of spatial and non-spatial information in ASL and spoken English narratives was assessed. Results from the linguistic serial recall tasks revealed that the often reported advantage for speakers on linguistic short-term memory tasks does not extend to complex WM tasks with a serial recall component. For English, linguistic WM predicted retention of non-spatial information, and both linguistic and spatial WM predicted retention of spatial information. For ASL, spatial WM predicted retention of spatial (but not non-spatial) information, and linguistic WM did not predict retention of either spatial or non-spatial information. Overall, our findings argue against strong assumptions of independent domain-specific subsystems for the storage and processing of linguistic and spatial information and furthermore suggest a less important role for serial encoding in signed than spoken language comprehension. Copyright © 2017 Elsevier B.V. All rights reserved.

Pillars of judgment: how memory abilities affect performance in rule-based and exemplar-based judgments.

PubMed

Hoffmann, Janina A; von Helversen, Bettina; Rieskamp, Jörg

2014-12-01

Making accurate judgments is an essential skill in everyday life. Although how different memory abilities relate to categorization and judgment processes has been hotly debated, the question is far from resolved. We contribute to the solution by investigating how individual differences in memory abilities affect judgment performance in 2 tasks that induced rule-based or exemplar-based judgment strategies. In a study with 279 participants, we investigated how working memory and episodic memory affect judgment accuracy and strategy use. As predicted, participants switched strategies between tasks. Furthermore, structural equation modeling showed that the ability to solve rule-based tasks was predicted by working memory, whereas episodic memory predicted judgment accuracy in the exemplar-based task. Last, the probability of choosing an exemplar-based strategy was related to better episodic memory, but strategy selection was unrelated to working memory capacity. In sum, our results suggest that different memory abilities are essential for successfully adopting different judgment strategies. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Predictive modeling of multicellular structure formation by using Cellular Particle Dynamics simulations

NASA Astrophysics Data System (ADS)

McCune, Matthew; Shafiee, Ashkan; Forgacs, Gabor; Kosztin, Ioan

2014-03-01

Cellular Particle Dynamics (CPD) is an effective computational method for describing and predicting the time evolution of biomechanical relaxation processes of multicellular systems. A typical example is the fusion of spheroidal bioink particles during post bioprinting structure formation. In CPD cells are modeled as an ensemble of cellular particles (CPs) that interact via short-range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through integration of their equations of motion. CPD was successfully applied to describe and predict the fusion of 3D tissue construct involving identical spherical aggregates. Here, we demonstrate that CPD can also predict tissue formation involving uneven spherical aggregates whose volumes decrease during the fusion process. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.

Gas Metal Arc Welding Process Modeling and Prediction of Weld Microstructure in MIL A46100 Armor-Grade Martensitic Steel

NASA Astrophysics Data System (ADS)

Grujicic, M.; Arakere, A.; Ramaswami, S.; Snipes, J. S.; Yavari, R.; Yen, C.-F.; Cheeseman, B. A.; Montgomery, J. S.

2013-06-01

A conventional gas metal arc welding (GMAW) butt-joining process has been modeled using a two-way fully coupled, transient, thermal-mechanical finite-element procedure. To achieve two-way thermal-mechanical coupling, the work of plastic deformation resulting from potentially high thermal stresses is allowed to be dissipated in the form of heat, and the mechanical material model of the workpiece and the weld is made temperature dependent. Heat losses from the deposited filler-metal are accounted for by considering conduction to the adjoining workpieces as well as natural convection and radiation to the surroundings. The newly constructed GMAW process model is then applied, in conjunction with the basic material physical-metallurgy, to a prototypical high-hardness armor martensitic steel (MIL A46100). The main outcome of this procedure is the prediction of the spatial distribution of various crystalline phases within the weld and the heat-affected zone regions, as a function of the GMAW process parameters. The newly developed GMAW process model is validated by comparing its predictions with available open-literature experimental and computational data.

Weight and See: Loading Working Memory Improves Incidental Identification of Irrelevant Faces

PubMed Central

Carmel, David; Fairnie, Jake; Lavie, Nilli

2012-01-01

Are task-irrelevant stimuli processed to a level enabling individual identification? This question is central both for perceptual processing models and for applied settings (e.g., eye-witness testimony). Lavie’s load theory proposes that working memory actively maintains attentional prioritization of relevant over irrelevant information. Loading working memory thus impairs attentional prioritization, leading to increased processing of task-irrelevant stimuli. Previous research has shown that increased working memory load leads to greater interference effects from response-competing distractors. Here we test the novel prediction that increased processing of irrelevant stimuli under high working memory load should lead to a greater likelihood of incidental identification of entirely irrelevant stimuli. To test this, we asked participants to perform a word-categorization task while ignoring task-irrelevant images. The categorization task was performed during the retention interval of a working memory task with either low or high load (defined by memory set size). Following the final experimental trial, a surprise question assessed incidental identification of the irrelevant image. Loading working memory was found to improve identification of task-irrelevant faces, but not of building stimuli (shown in a separate experiment to be less distracting). These findings suggest that working memory plays a critical role in determining whether distracting stimuli will be subsequently identified. PMID:22912623

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

Kervick, R.; Blue, C. A.; Kadolkar, P. B.

Forging is a manufacturing process in which metal is pressed, pounded or squeezed under great pressure and, often, under high strain rates into high-strength parts known as forgings. The process is typically performed hot by preheating the metal to a desired temperature before it is worked. The forging process can create parts that are stronger than those manufactured by any other metal working process. Forgings are almost always used where reliability and human safety are critical. Forgings are normally component parts contained inside assembled items such airplanes, automobiles, tractors, ships, oil drilling equipment, engines missiles, and all kinds of capitalmore » equipment Forgings are stronger than castings and surpass them in predictable strength properties, producing superior strength that is assured, part to part.« less

Isothermal separation processes

NASA Technical Reports Server (NTRS)

England, C.

1982-01-01

The isothermal processes of membrane separation, supercritical extraction and chromatography were examined using availability analysis. The general approach was to derive equations that identified where energy is consumed in these processes and how they compare with conventional separation methods. These separation methods are characterized by pure work inputs, chiefly in the form of a pressure drop which supplies the required energy. Equations were derived for the energy requirement in terms of regular solution theory. This approach is believed to accurately predict the work of separation in terms of the heat of solution and the entropy of mixing. It can form the basis of a convenient calculation method for optimizing membrane and solvent properties for particular applications. Calculations were made on the energy requirements for a membrane process separating air into its components.

CFE-2 Experiment Run

NASA Image and Video Library

2013-11-11

View of Flight Engineer (FE) Mike Hopkins initiating a CFE-2 (Capillary Flow Experiment - 2) Interior Corner Flow - 5 (ICF-5) test run. Liquids behave differently in space than they do on Earth, so containers that can process, hold or transport them must be designed carefully to work in microgravity. The Capillary Flow Experiment-2 furthers research on wetting, which is a liquid's ability to spread across a surface, and its impact over large length scales in strange container shapes in microgravity environments. This work will improve our capabilities to quickly and accurately predict how related processes occur, and allow us to design better systems to process liquids aboard spacecraft (i.e., liquid fuel tanks, thermals fluids, and water processing for life support). Image was released by astronaut on Twitter.

Tests of the Dynamic Field Theory and the Spatial Precision Hypothesis: Capturing a Qualitative Developmental Transition in Spatial Working Memory

PubMed Central

Schutte, Anne R.; Spencer, John P.

2009-01-01

This study tested a dynamic field theory (DFT) of spatial working memory and an associated spatial precision hypothesis (SPH). Between three and six years of age there is a qualitative shift in how children use reference axes to remember locations: 3-year-olds’ spatial recall responses are biased toward reference axes after short memory delays, whereas 6-year-olds’ responses are biased away from reference axes. According to the DFT and the SPH, quantitative improvements over development in the precision of excitatory and inhibitory working memory processes lead to this qualitative shift. Simulations of the DFT in Experiment 1 predict that improvements in precision should cause the spatial range of targets attracted toward a reference axis to narrow gradually over development with repulsion emerging and gradually increasing until responses to most targets show biases away from the axis. Results from Experiment 2 with 3- to 5-year-olds support these predictions. Simulations of the DFT in Experiment 3 quantitatively fit the empirical results and offer insights into the neural processes underlying this developmental change. PMID:19968430

Automatic knowledge extraction from chemical structures: the case of mutagenicity prediction.

PubMed

Ferrari, T; Cattaneo, D; Gini, G; Golbamaki Bakhtyari, N; Manganaro, A; Benfenati, E

2013-01-01

This work proposes a new structure-activity relationship (SAR) approach to mine molecular fragments that act as structural alerts for biological activity. The entire process is designed to fit with human reasoning, not only to make the predictions more reliable but also to permit clear control by the user in order to meet customized requirements. This approach has been tested on the mutagenicity endpoint, showing marked prediction skills and, more interestingly, bringing to the surface much of the knowledge already collected in the literature as well as new evidence.

Creating pharmacy staffing-to-demand models: predictive tools used at two institutions.

PubMed

Krogh, Paul; Ernster, Jason; Knoer, Scott

2012-09-15

The creation and implementation of data-driven staffing-to-demand models at two institutions are described. Predictive workload tools provide a guideline for pharmacy managers to adjust staffing needs based on hospital volume metrics. At Abbott Northwestern Hospital, management worked with the department's staff and labor management committee to clearly outline the productivity monitoring system and the process for reducing hours. Reference charts describing the process for reducing hours and a form to track the hours of involuntary reductions for each employee were created to further enhance communication, explain the rationale behind the new process, and promote transparency. The University of Minnesota Medical Center-Fairview, found a strong correlation between measured pharmacy workload and an adjusted census formula. If the daily census and admission report indicate that the adjusted census will provide enough workload for the fully staffed department, no further action is needed. If the census report indicates the adjusted census is less than the breakeven point, staff members are asked to leave work, either voluntarily or involuntarily. The opposite holds true for days when the adjusted census is higher than the breakeven point, at which time additional staff are required to synchronize worked hours with predicted workload. Successful staffing-to- demand models were implemented in two hospital pharmacies. Financial savings, as indicated by decreased labor costs secondary to reduction of staffed shifts, were approximately $42,000 and $45,500 over a three-month period for Abbott Northwestern Hospital and the University of Minnesota Medical Center-Fairview, respectively. Maintenance of 100% productively allowed the departments to continue to replace vacant positions and avoid permanent staff reductions.

Salience and Attention in Surprisal-Based Accounts of Language Processing

PubMed Central

Zarcone, Alessandra; van Schijndel, Marten; Vogels, Jorrig; Demberg, Vera

2016-01-01

The notion of salience has been singled out as the explanatory factor for a diverse range of linguistic phenomena. In particular, perceptual salience (e.g., visual salience of objects in the world, acoustic prominence of linguistic sounds) and semantic-pragmatic salience (e.g., prominence of recently mentioned or topical referents) have been shown to influence language comprehension and production. A different line of research has sought to account for behavioral correlates of cognitive load during comprehension as well as for certain patterns in language usage using information-theoretic notions, such as surprisal. Surprisal and salience both affect language processing at different levels, but the relationship between the two has not been adequately elucidated, and the question of whether salience can be reduced to surprisal / predictability is still open. Our review identifies two main challenges in addressing this question: terminological inconsistency and lack of integration between high and low levels of representations in salience-based accounts and surprisal-based accounts. We capitalize upon work in visual cognition in order to orient ourselves in surveying the different facets of the notion of salience in linguistics and their relation with models of surprisal. We find that work on salience highlights aspects of linguistic communication that models of surprisal tend to overlook, namely the role of attention and relevance to current goals, and we argue that the Predictive Coding framework provides a unified view which can account for the role played by attention and predictability at different levels of processing and which can clarify the interplay between low and high levels of processes and between predictability-driven expectation and attention-driven focus. PMID:27375525

Wafer hot spot identification through advanced photomask characterization techniques: part 2

NASA Astrophysics Data System (ADS)

Choi, Yohan; Green, Michael; Cho, Young; Ham, Young; Lin, Howard; Lan, Andy; Yang, Richer; Lung, Mike

2017-03-01

Historically, 1D metrics such as Mean to Target (MTT) and CD Uniformity (CDU) have been adequate for mask end users to evaluate and predict the mask impact on the wafer process. However, the wafer lithographer's process margin is shrinking at advanced nodes to a point that classical mask CD metrics are no longer adequate to gauge the mask contribution to wafer process error. For example, wafer CDU error at advanced nodes is impacted by mask factors such as 3-dimensional (3D) effects and mask pattern fidelity on sub-resolution assist features (SRAFs) used in Optical Proximity Correction (OPC) models of ever-increasing complexity. To overcome the limitation of 1D metrics, there are numerous on-going industry efforts to better define wafer-predictive metrics through both standard mask metrology and aerial CD methods. Even with these improvements, the industry continues to struggle to define useful correlative metrics that link the mask to final device performance. In part 1 of this work, we utilized advanced mask pattern characterization techniques to extract potential hot spots on the mask and link them, theoretically, to issues with final wafer performance. In this paper, part 2, we complete the work by verifying these techniques at wafer level. The test vehicle (TV) that was used for hot spot detection on the mask in part 1 will be used to expose wafers. The results will be used to verify the mask-level predictions. Finally, wafer performance with predicted and verified mask/wafer condition will be shown as the result of advanced mask characterization. The goal is to maximize mask end user yield through mask-wafer technology harmonization. This harmonization will provide the necessary feedback to determine optimum design, mask specifications, and mask-making conditions for optimal wafer process margin.

Elevated depressive symptoms enhance reflexive but not reflective auditory category learning.

PubMed

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.

Carving Executive Control At Its Joints: Working Memory Capacity Predicts Stimulus-Stimulus, But Not Stimulus-Response, Conflict

PubMed Central

Meier, Matt E.; Kane, Michael J.

2015-01-01

Three experiments examined the relation between working memory capacity (WMC) and two different forms of cognitive conflict: stimulus-stimulus (S-S) and stimulus-response (SR) interference. Our goal was to test whether WMC’s relation to conflict-task performance is mediated by stimulus-identification processes (captured by S-S conflict), response-selection processes (captured by S-R conflict), or both. In Experiment 1, subjects completed a single task presenting both S-S and S-R conflict trials, plus trials that combined the two conflict types. We limited ostensible goal-maintenance contributions to performance by requiring the same goal for all trial types and by presenting frequent conflict trials that reinforced the goal. WMC predicted resolution of S-S conflict as expected: Higher-WMC subjects showed reduced response time interference. Although WMC also predicted S-R interference, here, higher-WMC subjects showed increased error interference. Experiment 2A replicated these results in a version of the conflict task without combined S-S/S-R trials. Experiment 2B increased the proportion of congruent (non-conflict) trials to promote reliance on goal-maintenance processes. Here, higher-WMC subjects resolved both S-S and S-R conflict more successfully than did lower-WMC subjects. The results were consistent with Kane and Engle’s (2003) two-factor theory of cognitive control, according to which WMC predicts executive-task performance through goal-maintenance and conflict-resolution processes. However, the present results add specificity to the account by suggesting that higher-WMC subjects better resolve cognitive conflict because they more efficiently select relevant stimulus features against irrelevant, distracting ones. PMID:26120774

Carving executive control at its joints: Working memory capacity predicts stimulus-stimulus, but not stimulus-response, conflict.

PubMed

Meier, Matt E; Kane, Michael J

2015-11-01

Three experiments examined the relation between working memory capacity (WMC) and 2 different forms of cognitive conflict: stimulus-stimulus (S-S) and stimulus-response (S-R) interference. Our goal was to test whether WMC's relation to conflict-task performance is mediated by stimulus-identification processes (captured by S-S conflict), response-selection processes (captured by S-R conflict), or both. In Experiment 1, subjects completed a single task presenting both S-S and S-R conflict trials, plus trials that combined the 2 conflict types. We limited ostensible goal-maintenance contributions to performance by requiring the same goal for all trial types and by presenting frequent conflict trials that reinforced the goal. WMC predicted resolution of S-S conflict as expected: Higher WMC subjects showed reduced response time interference. Although WMC also predicted S-R interference, here, higher WMC subjects showed increased error interference. Experiment 2A replicated these results in a version of the conflict task without combined S-S/S-R trials. Experiment 2B increased the proportion of congruent (nonconflict) trials to promote reliance on goal-maintenance processes. Here, higher WMC subjects resolved both S-S and S-R conflict more successfully than did lower WMC subjects. The results were consistent with Kane and Engle's (2003) 2-factor theory of cognitive control, according to which WMC predicts executive-task performance through goal-maintenance and conflict-resolution processes. However, the present results add specificity to the account by suggesting that higher WMC subjects better resolve cognitive conflict because they more efficiently select relevant stimulus features against irrelevant, distracting ones. (c) 2015 APA, all rights reserved).

Elevated Depressive Symptoms Enhance Reflexive but not Reflective Auditory Category Learning

PubMed Central

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

Predicting Word Reading and Comprehension with Executive Function and Speed Measures Across Development: A Latent Variable Analysis

PubMed Central

Christopher, Micaela E.; Miyake, Akira; Keenan, Janice M.; Pennington, Bruce; DeFries, John C.; Wadsworth, Sally J.; Willcutt, Erik; Olson, Richard K.

2012-01-01

The present study explored whether different executive control and speed measures (working memory, inhibition, processing speed, and naming speed) independently predict individual differences in word reading and reading comprehension. Although previous studies suggest these cognitive constructs are important for reading, we analyze the constructs simultaneously to test whether each is a unique predictor. We used latent variables from 483 participants (ages 8 to 16) to portion each cognitive and reading construct into its unique and shared variance. In these models we address two specific issues: (a) given that our wide age range may span the theoretical transition from “learning to read” to “reading to learn,” we first test whether the relation between word reading and reading comprehension is stable across two age groups (ages 8 to 10 and 11 to 16); and (b) the main theoretical question of interest: whether what is shared and what is separable for word reading and reading comprehension are associated with individual differences in working memory, inhibition, and measures of processing and naming speed. The results indicated that: (a) the relation between word reading and reading comprehension is largely invariant across the age groups; (b) working memory and general processing speed, but not inhibition or the speeded naming of non-alphanumeric stimuli, are unique predictors of both word reading and comprehension, with working memory equally important for both reading abilities and processing speed more important for word reading. These results have implications for understanding why reading comprehension and word reading are highly correlated yet separable. PMID:22352396

A review of supervised machine learning applied to ageing research.

PubMed

Fabris, Fabio; Magalhães, João Pedro de; Freitas, Alex A

2017-04-01

Broadly speaking, supervised machine learning is the computational task of learning correlations between variables in annotated data (the training set), and using this information to create a predictive model capable of inferring annotations for new data, whose annotations are not known. Ageing is a complex process that affects nearly all animal species. This process can be studied at several levels of abstraction, in different organisms and with different objectives in mind. Not surprisingly, the diversity of the supervised machine learning algorithms applied to answer biological questions reflects the complexities of the underlying ageing processes being studied. Many works using supervised machine learning to study the ageing process have been recently published, so it is timely to review these works, to discuss their main findings and weaknesses. In summary, the main findings of the reviewed papers are: the link between specific types of DNA repair and ageing; ageing-related proteins tend to be highly connected and seem to play a central role in molecular pathways; ageing/longevity is linked with autophagy and apoptosis, nutrient receptor genes, and copper and iron ion transport. Additionally, several biomarkers of ageing were found by machine learning. Despite some interesting machine learning results, we also identified a weakness of current works on this topic: only one of the reviewed papers has corroborated the computational results of machine learning algorithms through wet-lab experiments. In conclusion, supervised machine learning has contributed to advance our knowledge and has provided novel insights on ageing, yet future work should have a greater emphasis in validating the predictions.

Solar irradiance dictates settlement timing and intensity of marine mussels

PubMed Central

Fuentes-Santos, Isabel; Labarta, Uxío; Álvarez-Salgado, X. Antón; Fernández-Reiriz, Mª José

2016-01-01

Identifying the environmental factors driving larval settlement processes is crucial to understand the population dynamics of marine invertebrates. This work aims to go a step ahead and predict larval presence and intensity. For this purpose we consider the influence of solar irradiance, wind regime and continental runoff on the settlement processes. For the first time, we conducted a 5-years weekly monitoring of Mytilus galloprovincialis settlement on artificial suspended substrates, which allowed us to search for interannual variability in the settlement patterns. Comparison between the seasonal pattern of larval settlement and solar irradiance, as well as the well-known effect of solar irradiance on water temperature and food availability, suggest that solar irradiance indirectly influences the settlement process, and support the use of this meteorological variable to predict settlement occurrence. Our results show that solar irradiance allows predicting the beginning and end of the settlement cycle a month in advance: Particularly we have observed that solar irradiance during late winter indirectly drives the timing and intensity of the settlement onset, Finally, a functional generalise additive model, which considers the influence of solar irradiance and continental runoff on the settlement process, provides an accurate prediction of settlement intensity a fortnight in advance. PMID:27384527

Solar irradiance dictates settlement timing and intensity of marine mussels

NASA Astrophysics Data System (ADS)

Fuentes-Santos, Isabel; Labarta, Uxío; Álvarez-Salgado, X. Antón; Fernández-Reiriz, Mª José

2016-07-01

Identifying the environmental factors driving larval settlement processes is crucial to understand the population dynamics of marine invertebrates. This work aims to go a step ahead and predict larval presence and intensity. For this purpose we consider the influence of solar irradiance, wind regime and continental runoff on the settlement processes. For the first time, we conducted a 5-years weekly monitoring of Mytilus galloprovincialis settlement on artificial suspended substrates, which allowed us to search for interannual variability in the settlement patterns. Comparison between the seasonal pattern of larval settlement and solar irradiance, as well as the well-known effect of solar irradiance on water temperature and food availability, suggest that solar irradiance indirectly influences the settlement process, and support the use of this meteorological variable to predict settlement occurrence. Our results show that solar irradiance allows predicting the beginning and end of the settlement cycle a month in advance: Particularly we have observed that solar irradiance during late winter indirectly drives the timing and intensity of the settlement onset, Finally, a functional generalise additive model, which considers the influence of solar irradiance and continental runoff on the settlement process, provides an accurate prediction of settlement intensity a fortnight in advance.

Predicting cotton yield of small field plots in a cotton breeding program using UAV imagery data

NASA Astrophysics Data System (ADS)

Maja, Joe Mari J.; Campbell, Todd; Camargo Neto, Joao; Astillo, Philip

2016-05-01

One of the major criteria used for advancing experimental lines in a breeding program is yield performance. Obtaining yield performance data requires machine picking each plot with a cotton picker, modified to weigh individual plots. Harvesting thousands of small field plots requires a great deal of time and resources. The efficiency of cotton breeding could be increased significantly while the cost could be decreased with the availability of accurate methods to predict yield performance. This work is investigating the feasibility of using an image processing technique using a commercial off-the-shelf (COTS) camera mounted on a small Unmanned Aerial Vehicle (sUAV) to collect normal RGB images in predicting cotton yield on small plot. An orthonormal image was generated from multiple images and used to process multiple, segmented plots. A Gaussian blur was used to eliminate the high frequency component of the images, which corresponds to the cotton pixels, and used image subtraction technique to generate high frequency pixel images. The cotton pixels were then separated using k-means cluster with 5 classes. Based on the current work, the calculated percentage cotton area was computed using the generated high frequency image (cotton pixels) divided by the total area of the plot. Preliminary results showed (five flights, 3 altitudes) that cotton cover on multiple pre-selected 227 sq. m. plots produce an average of 8% which translate to approximately 22.3 kgs. of cotton. The yield prediction equation generated from the test site was then use on a separate validation site and produced a prediction error of less than 10%. In summary, the results indicate that a COTS camera with an appropriate image processing technique can produce results that are comparable to expensive sensors.

Prediction of Shrinkage Porosity Defect in Sand Casting Process of LM25

NASA Astrophysics Data System (ADS)

Rathod, Hardik; Dhulia, Jay K.; Maniar, Nirav P.

2017-08-01

In the present worldwide and aggressive environment, foundry commercial enterprises need to perform productively with least number of rejections and create casting parts in shortest lead time. It has become extremely difficult for foundry industries to meet demands of defects free casting and meet strict delivery schedules. The process of casting solidification is complex in nature. Prediction of shrinkage defect in metal casting is one of the critical concern in foundries and is one of the potential research areas in casting. Due to increasing pressure to improve quality and to reduce cost, it is very essential to upgrade the level of current methodology used in foundries. In the present research work, prediction methodology of shrinkage porosity defect in sand casting process of LM25 using experimentation and ANSYS is proposed. The objectives successfully achieved are prediction of shrinkage porosity distribution in Al-Si casting and determining effectiveness of investigated function for predicting shrinkage porosity by correlating results of simulating studies to those obtained experimentally. The real-time application of the research reflects from the fact that experimentation is performed on 9 different Y junctions at foundry industry and practical data obtained from experimentation are used for simulation.

Performance and Reliability Optimization for Aerospace Systems subject to Uncertainty and Degradation

NASA Technical Reports Server (NTRS)

Miller, David W.; Uebelhart, Scott A.; Blaurock, Carl

2004-01-01

This report summarizes work performed by the Space Systems Laboratory (SSL) for NASA Langley Research Center in the field of performance optimization for systems subject to uncertainty. The objective of the research is to develop design methods and tools to the aerospace vehicle design process which take into account lifecycle uncertainties. It recognizes that uncertainty between the predictions of integrated models and data collected from the system in its operational environment is unavoidable. Given the presence of uncertainty, the goal of this work is to develop means of identifying critical sources of uncertainty, and to combine these with the analytical tools used with integrated modeling. In this manner, system uncertainty analysis becomes part of the design process, and can motivate redesign. The specific program objectives were: 1. To incorporate uncertainty modeling, propagation and analysis into the integrated (controls, structures, payloads, disturbances, etc.) design process to derive the error bars associated with performance predictions. 2. To apply modern optimization tools to guide in the expenditure of funds in a way that most cost-effectively improves the lifecycle productivity of the system by enhancing the subsystem reliability and redundancy. The results from the second program objective are described. This report describes the work and results for the first objective: uncertainty modeling, propagation, and synthesis with integrated modeling.

The Role of Graphlets in Viral Processes on Networks

NASA Astrophysics Data System (ADS)

Khorshidi, Samira; Al Hasan, Mohammad; Mohler, George; Short, Martin B.

2018-05-01

Predicting the evolution of viral processes on networks is an important problem with applications arising in biology, the social sciences, and the study of the Internet. In existing works, mean-field analysis based upon degree distribution is used for the prediction of viral spreading across networks of different types. However, it has been shown that degree distribution alone fails to predict the behavior of viruses on some real-world networks and recent attempts have been made to use assortativity to address this shortcoming. In this paper, we show that adding assortativity does not fully explain the variance in the spread of viruses for a number of real-world networks. We propose using the graphlet frequency distribution in combination with assortativity to explain variations in the evolution of viral processes across networks with identical degree distribution. Using a data-driven approach by coupling predictive modeling with viral process simulation on real-world networks, we show that simple regression models based on graphlet frequency distribution can explain over 95% of the variance in virality on networks with the same degree distribution but different network topologies. Our results not only highlight the importance of graphlets but also identify a small collection of graphlets which may have the highest influence over the viral processes on a network.

Influence of the pressure dependent coefficient of friction on deep drawing springback predictions

NASA Astrophysics Data System (ADS)

Gil, Imanol; Galdos, Lander; Mendiguren, Joseba; Mugarra, Endika; Sáenz de Argandoña, Eneko

2016-10-01

This research studies the effect of considering an advanced variable friction coefficient on the springback prediction of stamping processes. Traditional constant coefficient of friction considerations are being replaced by more advanced friction coefficient definitions. The aim of this work is to show the influence of defining a pressure dependent friction coefficient on numerical springback predictions of a DX54D mild steel, a HSLA380 and a DP780 high strength steel. The pressure dependent friction model of each material was fitted to the experimental data obtained by Strip Drawing tests. Then, these friction models were implemented in a numerical simulation of a drawing process of an industrial automotive part. The results showed important differences between defining a pressure dependent friction coefficient or a constant friction coefficient.

Modeling and prediction of human word search behavior in interactive machine translation

NASA Astrophysics Data System (ADS)

Ji, Duo; Yu, Bai; Ma, Bin; Ye, Na

2017-12-01

As a kind of computer aided translation method, Interactive Machine Translation technology reduced manual translation repetitive and mechanical operation through a variety of methods, so as to get the translation efficiency, and played an important role in the practical application of the translation work. In this paper, we regarded the behavior of users' frequently searching for words in the translation process as the research object, and transformed the behavior to the translation selection problem under the current translation. The paper presented a prediction model, which is a comprehensive utilization of alignment model, translation model and language model of the searching words behavior. It achieved a highly accurate prediction of searching words behavior, and reduced the switching of mouse and keyboard operations in the users' translation process.

Mathematical modelling and numerical simulation of forces in milling process

NASA Astrophysics Data System (ADS)

Turai, Bhanu Murthy; Satish, Cherukuvada; Prakash Marimuthu, K.

2018-04-01

Machining of the material by milling induces forces, which act on the work piece material, tool and which in turn act on the machining tool. The forces involved in milling process can be quantified, mathematical models help to predict these forces. A lot of research has been carried out in this area in the past few decades. The current research aims at developing a mathematical model to predict forces at different levels which arise machining of Aluminium6061 alloy. Finite element analysis was used to develop a FE model to predict the cutting forces. Simulation was done for varying cutting conditions. Different experiments was designed using Taguchi method. A L9 orthogonal array was designed and the output was measure for the different experiments. The same was used to develop the mathematical model.

Knowing a Lot for One's Age: Vocabulary Skill and Not Age Is Associated with Anticipatory Incremental Sentence Interpretation in Children and Adults

ERIC Educational Resources Information Center

Borovsky, Arielle; Elman, Jeffrey L.; Fernald, Anne

2012-01-01

Adults can incrementally combine information from speech with astonishing speed to anticipate future words. Concurrently, a growing body of work suggests that vocabulary ability is crucially related to lexical processing skills in children. However, little is known about this relationship with predictive sentence processing in children or adults.…

Hybrid Vapor Stripping-Vapor Permeation Process for Recovery and Dehydration of 1-Butanol and Acetone/Butanol/Ethanol from Dilute Aqueous Solutions. Part 2. Experimental Validation with Simple Mixtures and Actual Fermentation Broth

EPA Science Inventory

BACKGROUND: In Part1 of this work, a process integrating vapor stripping, vapor compression, and a vapor permeation membrane separation step, Membrane Assisted Vapor Stripping (MAVS), was predicted to produce energy savings compared to traditional distillation systems for separat...

Numerical Order Processing in Children: From Reversing the Distance-Effect to Predicting Arithmetic

ERIC Educational Resources Information Center

Lyons, Ian M.; Ansari, Daniel

2015-01-01

Recent work has demonstrated that how we process the relative order--ordinality--of numbers may be key to understanding how we represent numbers symbolically, and has proven to be a robust predictor of more sophisticated math skills in both children and adults. However, it remains unclear whether numerical ordinality is primarily a by-product of…

A Cluster-Randomised, Controlled Trial of the Impact of Cogmed Working Memory Training on Both Academic Performance and Regulation of Social, Emotional and Behavioural Challenges

ERIC Educational Resources Information Center

Hitchcock, Caitlin; Westwell, Martin S.

2017-01-01

Background: We explored whether school-based Cogmed Working Memory Training (CWMT) may optimise both academic and psychological outcomes at school. Training of executive control skills may form a novel approach to enhancing processes that predict academic achievement, such as task-related attention, and thereby academic performance, but also has…

Shallow Water Reverberation Measurement and Prediction

DTIC Science & Technology

1994-06-01

tool . The temporal signal processing consisted of a short-time Fourier transform spectral estimation method applied to data from a single hydrophone...The three-dimensional Hamiltonian Acoustic Ray-tracing Program for the Ocean (HARPO) was used as the primary propagation modeling tool . The temporal...summarizes the work completed and discusses lessons learned . Advice regarding future work to refine the present study will be provided. 6 our poiut source

Assessment of motor and process skills: assessing client work performance in Belgium.

PubMed

Vandamme, Dirk

2010-01-01

The aim of this study is to establish whether the Assessment of Motor and Process Skills (AMPS) is an appropriate tool to evaluate the quality of work performance by comparing clients' results on the AMPS with the quality of the skills that they demonstrate on the shop floor. A convenience sample of chronically unemployed (vocationally disabled) participants (N=139) with no formal training who were seeking unskilled work through Jobcentrum West-Vlaanderen (West Flanders Job Centre, Belgium) was used. Results demonstrated that in 75.2% of cases the prediction of employment outcome was correct; it is suggested that an AMPS motor score < 2.5 and a process score < 1.2 is insufficient for regular employment, while a motor score > 3.1 and process score > 1.5 indicates that regular employment is a realistic goal. The quality of the motor skills measured by the AMPS and measured on the shop floor are comparable, but little similarity was found in the measurement of process skills.

Latent change models of adult cognition: are changes in processing speed and working memory associated with changes in episodic memory?

PubMed

Hertzog, Christopher; Dixon, Roger A; Hultsch, David F; MacDonald, Stuart W S

2003-12-01

The authors used 6-year longitudinal data from the Victoria Longitudinal Study (VLS) to investigate individual differences in amount of episodic memory change. Latent change models revealed reliable individual differences in cognitive change. Changes in episodic memory were significantly correlated with changes in other cognitive variables, including speed and working memory. A structural equation model for the latent change scores showed that changes in speed and working memory predicted changes in episodic memory, as expected by processing resource theory. However, these effects were best modeled as being mediated by changes in induction and fact retrieval. Dissociations were detected between cross-sectional ability correlations and longitudinal changes. Shuffling the tasks used to define the Working Memory latent variable altered patterns of change correlations.

Age differences in cognitive performance in later life: relationships to self-reported health and activity life style.

PubMed

Hultsch, D F; Hammer, M; Small, B J

1993-01-01

The predictive relationships among individual differences in self-reported physical health and activity life style and performance on an array of information processing and intellectual ability measures were examined. A sample of 484 men and women aged 55 to 86 years completed a battery of cognitive tasks measuring verbal processing time, working memory, vocabulary, verbal fluency, world knowledge, word recall, and text recall. Hierarchical regression was used to predict performance on these tasks from measures of self-reported physical health, alcohol and tobacco use, and level of participation in everyday activities. The results indicated: (a) individual differences in self-reported health and activity predicted performance on multiple cognitive measures; (b) self-reported health was more predictive of processing resource variables than knowledge-based abilities; (c) interaction effects indicated that participation in cognitively demanding activities was more highly related to performance on some measures for older adults than for middle-aged adults; and (d) age-related differences in performance on multiple measures were attenuated by partialing individual differences in self-reported health and activity.

T. rex, the Crater of Doom, and the Nature of Scientific Discovery

NASA Astrophysics Data System (ADS)

Lawson, Antone

Working from the 1970s to the early 1990s, Walter Alvarez and his research team sought the cause of the mass extinction that claimed the dinosaurs 65 million years ago. The present paper discusses that research in terms of eight puzzling observations, eight episodes of hypothetico-predictive reasoning, enumerative induction, and Jung's interrogative theory of scientific discovery. The Alvarez case history paints scientific discovery as a process in which causal questions are raised and answered through the creative use of analogical reasoning followed by an equally creative process of hypothesis testing in which predicted and observed results are compared. According to this account, puzzling observations, causal hypotheses, and imagined tests drive investigations and the search for evidence. Two implications follow. The first concerns the education of new scientists and science education researchers and the need to more clearly differentiate hypotheses from predictions in the research process. The second concerns standard science classroom instruction that should more frequently engage students in open inquiries that raise causal questions and encourage the generation of alternative causal hypotheses, which can then be explicitly tested in a hypothetico-predictive fashion.

Improving personalized link prediction by hybrid diffusion

NASA Astrophysics Data System (ADS)

Liu, Jin-Hu; Zhu, Yu-Xiao; Zhou, Tao

2016-04-01

Inspired by traditional link prediction and to solve the problem of recommending friends in social networks, we introduce the personalized link prediction in this paper, in which each individual will get equal number of diversiform predictions. While the performances of many classical algorithms are not satisfactory under this framework, thus new algorithms are in urgent need. Motivated by previous researches in other fields, we generalize heat conduction process to the framework of personalized link prediction and find that this method outperforms many classical similarity-based algorithms, especially in the performance of diversity. In addition, we demonstrate that adding one ground node that is supposed to connect all the nodes in the system will greatly benefit the performance of heat conduction. Finally, better hybrid algorithms composed of local random walk and heat conduction have been proposed. Numerical results show that the hybrid algorithms can outperform other algorithms simultaneously in all four adopted metrics: AUC, precision, recall and hamming distance. In a word, this work may shed some light on the in-depth understanding of the effect of physical processes in personalized link prediction.

When hard times take a toll: the distressing consequences of economic hardship and life events within the family-work interface.

PubMed

Young, Marisa; Schieman, Scott

2012-03-01

Using two waves of data from a national survey of working Americans (N = 1,122), we examine the associations among economic hardship, negative life events, and psychological distress in the context of the family-work interface. Our findings demonstrate that family-to-work conflict mediates the effects of economic hardship and negative events to significant others on distress (net of baseline distress and hardship). Moreover, economic hardship and negative events to significant others moderate the association between family-to-work conflict and distress. While negative events to others exacerbate the positive effect of family-to-work conflict on distress, we find the opposite for economic hardship: The positive association between hardship and distress is weaker at higher levels of family-to-work conflict. These patterns hold across an array of family, work, and sociodemographic conditions. We discuss how these findings refine and extend ideas of the stress process model, including complex predictions related to processes of stress-buffering, resource substitution, and role multiplication.

Work-family conflict: experiences and health implications among immigrant Latinos.

PubMed

Grzywacz, Joseph G; Arcury, Thomas A; Márin, Antonio; Carrillo, Lourdes; Burke, Bless; Coates, Michael L; Quandt, Sara A

2007-07-01

Work-family conflict research has focused almost exclusively on professional, White adults. The goal of this article was to expand the understanding of culture and industry in shaping experiences and consequences of work-family conflict. Using in-depth interview data (n = 26) and structured survey data (n = 200) from immigrant Latinos employed in the poultry processing industry, the authors evaluated predictions drawn from emerging models emphasizing the influence of cultural characteristics such as collectivism and gender ideology on work-family conflict. Results indicated that immigrant Latinos in poultry processing experienced infrequent work-to-family conflict; both the level and the antecedents of work-to-family conflict differed by gender, with physical demands contributing to greater conflict for women but not men. In addition, there was little evidence that work-family conflict was associated with health in this population. These results demonstrate how traditional models of work-family conflict need to be modified to reflect the needs and circumstances of diverse workers in the new global economy.

Journey to the Edges: Social Structures and Neural Maps of Intergroup Processes

PubMed Central

Fiske, Susan T.

2013-01-01

This article explores boundaries of the intellectual map of intergroup processes, going to the macro (social structure) boundary and the micro (neural systems) boundary. Both are illustrated by with my own and others’ work on social structures and on neural structures related to intergroup processes. Analyzing the impact of social structures on intergroup processes led to insights about distinct forms of sexism and underlies current work on forms of ageism. The stereotype content model also starts with the social structure of intergroup relations (interdependence and status) and predicts images, emotions, and behaviors. Social structure has much to offer the social psychology of intergroup processes. At the other, less explored boundary, social neuroscience addresses the effects of social contexts on neural systems relevant to intergroup processes. Both social structural and neural analyses circle back to traditional social psychology as converging indicators of intergroup processes. PMID:22435843

Optimisation Of Cutting Parameters Of Composite Material Laser Cutting Process By Taguchi Method

NASA Astrophysics Data System (ADS)

Lokesh, S.; Niresh, J.; Neelakrishnan, S.; Rahul, S. P. Deepak

2018-03-01

The aim of this work is to develop a laser cutting process model that can predict the relationship between the process input parameters and resultant surface roughness, kerf width characteristics. The research conduct is based on the Design of Experiment (DOE) analysis. Response Surface Methodology (RSM) is used in this work. It is one of the most practical and most effective techniques to develop a process model. Even though RSM has been used for the optimization of the laser process, this research investigates laser cutting of materials like Composite wood (veneer)to be best circumstances of laser cutting using RSM process. The input parameters evaluated are focal length, power supply and cutting speed, the output responses being kerf width, surface roughness, temperature. To efficiently optimize and customize the kerf width and surface roughness characteristics, a machine laser cutting process model using Taguchi L9 orthogonal methodology was proposed.

The development of real-time stability supports visual working memory performance: Young children's feature binding can be improved through perceptual structure.

PubMed

Simmering, Vanessa R; Wood, Chelsey M

2017-08-01

Working memory is a basic cognitive process that predicts higher-level skills. A central question in theories of working memory development is the generality of the mechanisms proposed to explain improvements in performance. Prior theories have been closely tied to particular tasks and/or age groups, limiting their generalizability. The cognitive dynamics theory of visual working memory development has been proposed to overcome this limitation. From this perspective, developmental improvements arise through the coordination of cognitive processes to meet demands of different behavioral tasks. This notion is described as real-time stability, and can be probed through experiments that assess how changing task demands impact children's performance. The current studies test this account by probing visual working memory for colors and shapes in a change detection task that compares detection of changes to new features versus swaps in color-shape binding. In Experiment 1, 3- to 4-year-old children showed impairments specific to binding swaps, as predicted by decreased real-time stability early in development; 5- to 6-year-old children showed a slight advantage on binding swaps, but 7- to 8-year-old children and adults showed no difference across trial types. Experiment 2 tested the proposed explanation of young children's binding impairment through added perceptual structure, which supported the stability and precision of feature localization in memory-a process key to detecting binding swaps. This additional structure improved young children's binding swap detection, but not new-feature detection or adults' performance. These results provide further evidence for the cognitive dynamics and real-time stability explanation of visual working memory development. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Software reliability studies

NASA Technical Reports Server (NTRS)

Hoppa, Mary Ann; Wilson, Larry W.

1994-01-01

There are many software reliability models which try to predict future performance of software based on data generated by the debugging process. Our research has shown that by improving the quality of the data one can greatly improve the predictions. We are working on methodologies which control some of the randomness inherent in the standard data generation processes in order to improve the accuracy of predictions. Our contribution is twofold in that we describe an experimental methodology using a data structure called the debugging graph and apply this methodology to assess the robustness of existing models. The debugging graph is used to analyze the effects of various fault recovery orders on the predictive accuracy of several well-known software reliability algorithms. We found that, along a particular debugging path in the graph, the predictive performance of different models can vary greatly. Similarly, just because a model 'fits' a given path's data well does not guarantee that the model would perform well on a different path. Further we observed bug interactions and noted their potential effects on the predictive process. We saw that not only do different faults fail at different rates, but that those rates can be affected by the particular debugging stage at which the rates are evaluated. Based on our experiment, we conjecture that the accuracy of a reliability prediction is affected by the fault recovery order as well as by fault interaction.

Analysis and Prediction of Sea Ice Evolution using Koopman Mode Decomposition Techniques

DTIC Science & Technology

2018-04-30

Title: Analysis and Prediction of Sea Ice Evolution using Koopman Mode Decomposition Techniques Subject: Monthly Progress Report Period of...Resources: N/A TOTAL: $18,687 2 TECHNICAL STATUS REPORT Abstract The program goal is analysis of sea ice dynamical behavior using Koopman Mode Decompo...sition (KMD) techniques. The work in the program’s first month consisted of improvements to data processing code, inclusion of additional arctic sea ice

Symbolic Number Comparison Is Not Processed by the Analog Number System: Different Symbolic and Non-symbolic Numerical Distance and Size Effects

PubMed Central

Krajcsi, Attila; Lengyel, Gábor; Kojouharova, Petia

2018-01-01

HIGHLIGHTS We test whether symbolic number comparison is handled by an analog noisy system.Analog system model has systematic biases in describing symbolic number comparison.This suggests that symbolic and non-symbolic numbers are processed by different systems. Dominant numerical cognition models suppose that both symbolic and non-symbolic numbers are processed by the Analog Number System (ANS) working according to Weber's law. It was proposed that in a number comparison task the numerical distance and size effects reflect a ratio-based performance which is the sign of the ANS activation. However, increasing number of findings and alternative models propose that symbolic and non-symbolic numbers might be processed by different representations. Importantly, alternative explanations may offer similar predictions to the ANS prediction, therefore, former evidence usually utilizing only the goodness of fit of the ANS prediction is not sufficient to support the ANS account. To test the ANS model more rigorously, a more extensive test is offered here. Several properties of the ANS predictions for the error rates, reaction times, and diffusion model drift rates were systematically analyzed in both non-symbolic dot comparison and symbolic Indo-Arabic comparison tasks. It was consistently found that while the ANS model's prediction is relatively good for the non-symbolic dot comparison, its prediction is poorer and systematically biased for the symbolic Indo-Arabic comparison. We conclude that only non-symbolic comparison is supported by the ANS, and symbolic number comparisons are processed by other representation. PMID:29491845

Capillary Rise: Validity of the Dynamic Contact Angle Models.

PubMed

Wu, Pingkeng; Nikolov, Alex D; Wasan, Darsh T

2017-08-15

The classical Lucas-Washburn-Rideal (LWR) equation, using the equilibrium contact angle, predicts a faster capillary rise process than experiments in many cases. The major contributor to the faster prediction is believed to be the velocity dependent dynamic contact angle. In this work, we investigated the dynamic contact angle models for their ability to correct the dynamic contact angle effect in the capillary rise process. We conducted capillary rise experiments of various wetting liquids in borosilicate glass capillaries and compared the model predictions with our experimental data. The results show that the LWR equations modified by the molecular kinetic theory and hydrodynamic model provide good predictions on the capillary rise of all the testing liquids with fitting parameters, while the one modified by Joos' empirical equation works for specific liquids, such as silicone oils. The LWR equation modified by molecular self-layering model predicts well the capillary rise of carbon tetrachloride, octamethylcyclotetrasiloxane, and n-alkanes with the molecular diameter or measured solvation force data. The molecular self-layering model modified LWR equation also has good predictions on the capillary rise of silicone oils covering a wide range of bulk viscosities with the same key parameter W(0), which results from the molecular self-layering. The advantage of the molecular self-layering model over the other models reveals the importance of the layered molecularly thin wetting film ahead of the main meniscus in the energy dissipation associated with dynamic contact angle. The analysis of the capillary rise of silicone oils with a wide range of bulk viscosities provides new insights into the capillary dynamics of polymer melts.

Seismic and Infrasound Location

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

Arrowsmith, Stephen J.; Begnaud, Michael L.

2014-03-19

This presentation includes slides on Signal Propagation Through the Earth/Atmosphere Varies at Different Scales; 3D Seismic Models: RSTT; Ray Coverage (Pn); Source-Specific Station Corrections (SSSCs); RSTT Conclusions; SALSA3D (SAndia LoS Alamos) Global 3D Earth Model for Travel Time; Comparison of IDC SSSCs to RSTT Predictions; SALSA3D; Validation and Model Comparison; DSS Lines in the Siberian Platform; DSS Line CRA-4 Comparison; Travel Time Δak135; Travel Time Prediction Uncertainty; SALSA3D Conclusions; Infrasound Data Processing: An example event; Infrasound Data Processing: An example event; Infrasound Location; How does BISL work?; BISL: Application to the 2013 DPRK Test; and BISL: Ongoing Research.

The Collective Benefits of Feeling Good and Letting Go: Positive Emotion and (dis)Inhibition Interact to Predict Cooperative Behavior

PubMed Central

Rand, David G.; Kraft-Todd, Gordon; Gruber, June

2015-01-01

Cooperation is central to human existence, forming the bedrock of everyday social relationships and larger societal structures. Thus, understanding the psychological underpinnings of cooperation is of both scientific and practical importance. Recent work using a dual-process framework suggests that intuitive processing can promote cooperation while deliberative processing can undermine it. Here we add to this line of research by more specifically identifying deliberative and intuitive processes that affect cooperation. To do so, we applied automated text analysis using the Linguistic Inquiry and Word Count (LIWC) software to investigate the association between behavior in one-shot anonymous economic cooperation games and the presence inhibition (a deliberative process) and positive emotion (an intuitive process) in free-response narratives written after (Study 1, N = 4,218) or during (Study 2, N = 236) the decision-making process. Consistent with previous results, across both studies inhibition predicted reduced cooperation while positive emotion predicted increased cooperation (even when controlling for negative emotion). Importantly, there was a significant interaction between positive emotion and inhibition, such that the most cooperative individuals had high positive emotion and low inhibition. This suggests that inhibition (i.e., reflective or deliberative processing) may undermine cooperative behavior by suppressing the prosocial effects of positive emotion. PMID:25625722

The collective benefits of feeling good and letting go: positive emotion and (dis)inhibition interact to predict cooperative behavior.

PubMed

Rand, David G; Kraft-Todd, Gordon; Gruber, June

2015-01-01

Cooperation is central to human existence, forming the bedrock of everyday social relationships and larger societal structures. Thus, understanding the psychological underpinnings of cooperation is of both scientific and practical importance. Recent work using a dual-process framework suggests that intuitive processing can promote cooperation while deliberative processing can undermine it. Here we add to this line of research by more specifically identifying deliberative and intuitive processes that affect cooperation. To do so, we applied automated text analysis using the Linguistic Inquiry and Word Count (LIWC) software to investigate the association between behavior in one-shot anonymous economic cooperation games and the presence inhibition (a deliberative process) and positive emotion (an intuitive process) in free-response narratives written after (Study 1, N = 4,218) or during (Study 2, N = 236) the decision-making process. Consistent with previous results, across both studies inhibition predicted reduced cooperation while positive emotion predicted increased cooperation (even when controlling for negative emotion). Importantly, there was a significant interaction between positive emotion and inhibition, such that the most cooperative individuals had high positive emotion and low inhibition. This suggests that inhibition (i.e., reflective or deliberative processing) may undermine cooperative behavior by suppressing the prosocial effects of positive emotion.

Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement

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

Bibby, Jaclyn; Keegan, Ronan M.; Mayans, Olga

2013-11-01

Processing of NMR structures for molecular replacement by AMPLE works well. AMPLE is a program developed for clustering and truncating ab initio protein structure predictions into search models for molecular replacement. Here, it is shown that its core cluster-and-truncate methods also work well for processing NMR ensembles into search models. Rosetta remodelling helps to extend success to NMR structures bearing low sequence identity or high structural divergence from the target protein. Potential future routes to improved performance are considered and practical, general guidelines on using AMPLE are provided.

Comparative Risk Predictions of Second Cancers After Carbon-Ion Therapy Versus Proton Therapy

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

Eley, John G., E-mail: jeley@som.umaryland.edu; University of Texas Graduate School of Biomedical Sciences, Houston, Texas; Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland

Purpose: This work proposes a theoretical framework that enables comparative risk predictions for second cancer incidence after particle beam therapy for different ion species for individual patients, accounting for differences in relative biological effectiveness (RBE) for the competing processes of tumor initiation and cell inactivation. Our working hypothesis was that use of carbon-ion therapy instead of proton therapy would show a difference in the predicted risk of second cancer incidence in the breast for a sample of Hodgkin lymphoma (HL) patients. Methods and Materials: We generated biologic treatment plans and calculated relative predicted risks of second cancer in the breastmore » by using two proposed methods: a full model derived from the linear quadratic model and a simpler linear-no-threshold model. Results: For our reference calculation, we found the predicted risk of breast cancer incidence for carbon-ion plans-to-proton plan ratio, , to be 0.75 ± 0.07 but not significantly smaller than 1 (P=.180). Conclusions: Our findings suggest that second cancer risks are, on average, comparable between proton therapy and carbon-ion therapy.« less

Comparative Risk Predictions of Second Cancers After Carbon-Ion Therapy Versus Proton Therapy.

PubMed

Eley, John G; Friedrich, Thomas; Homann, Kenneth L; Howell, Rebecca M; Scholz, Michael; Durante, Marco; Newhauser, Wayne D

2016-05-01

This work proposes a theoretical framework that enables comparative risk predictions for second cancer incidence after particle beam therapy for different ion species for individual patients, accounting for differences in relative biological effectiveness (RBE) for the competing processes of tumor initiation and cell inactivation. Our working hypothesis was that use of carbon-ion therapy instead of proton therapy would show a difference in the predicted risk of second cancer incidence in the breast for a sample of Hodgkin lymphoma (HL) patients. We generated biologic treatment plans and calculated relative predicted risks of second cancer in the breast by using two proposed methods: a full model derived from the linear quadratic model and a simpler linear-no-threshold model. For our reference calculation, we found the predicted risk of breast cancer incidence for carbon-ion plans-to-proton plan ratio, , to be 0.75 ± 0.07 but not significantly smaller than 1 (P=.180). Our findings suggest that second cancer risks are, on average, comparable between proton therapy and carbon-ion therapy. Copyright © 2016 Elsevier Inc. All rights reserved.

Improving Fermi Orbit Determination and Prediction in an Uncertain Atmospheric Drag Environment

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Newman, Clark P.; Slojkowski, Steven E.; Carpenter, J. Russell

2014-01-01

Orbit determination and prediction of the Fermi Gamma-ray Space Telescope trajectory is strongly impacted by the unpredictability and variability of atmospheric density and the spacecraft's ballistic coefficient. Operationally, Global Positioning System point solutions are processed with an extended Kalman filter for orbit determination, and predictions are generated for conjunction assessment with secondary objects. When these predictions are compared to Joint Space Operations Center radar-based solutions, the close approach distance between the two predictions can greatly differ ahead of the conjunction. This work explores strategies for improving prediction accuracy and helps to explain the prediction disparities. Namely, a tuning analysis is performed to determine atmospheric drag modeling and filter parameters that can improve orbit determination as well as prediction accuracy. A 45% improvement in three-day prediction accuracy is realized by tuning the ballistic coefficient and atmospheric density stochastic models, measurement frequency, and other modeling and filter parameters.

A study on the applicability of in-line measurements in the monitoring of the pellet coating process.

PubMed

Hudovornik, Grega; Korasa, Klemen; Vrečer, Franc

2015-07-30

Special populations including paediatric and elderly patients often need advanced approaches in treatment, such as one-a-day dosing, which is achieved with modified release formulations or alternative routes of applications such as nasogastric route. Pellets are a dosage form that is frequently used in such formulations. The aim of the present work was to study the applicability of two in-line techniques, namely, Near Infrared Spectroscopy (NIR) and Spatial Filtering Technique (SFT) in the pellet coating process. The first objective of our work was to develop a prediction model for moisture content determination with the in-line NIR and to test its robustness in terms of sensitivity to changes in composition of the pellets and performance in wide range of moisture content. Secondly, the in-line SFT measurement was correlated with different off-line particle size methods. The third objective was to evaluate the ability of both in-line techniques for the detection of undesired deviations during the process, such as pellet attrition and agglomeration. Finally, the ability to predict coating thickness with the in-line NIR probe was evaluated. Results suggested that NIR prediction model for moisture content was less robust outside the calibration range and was also sensitive to changes in composition of the film coating. Nevertheless, satisfactory prediction was achieved in the case when coating composition was partially altered and adequate calibration range was used. The SFT probe results were in good correlation with off-line particle size measurement methods and proved to be an effective tool for coating thickness determination during the coating, however, the probe failed to accurately show the actual amount of the agglomerates formed during the process. In experiment when pellet attrition was initiated, both probes successfully detected abrasion of the pellet surface in real time. Furthermore, a predictive NIR model for coating thickness was made and showed a good potential to measure coating thickness in-line, suggesting that the NIR probe can be used as a single tool to monitor water content, coating thickness, and deviations in the coating process. Copyright © 2015 Elsevier B.V. All rights reserved.

Stress, burnout and doctors' attitudes to work are determined by personality and learning style: a twelve year longitudinal study of UK medical graduates.

PubMed

McManus, I C; Keeling, A; Paice, E

2004-08-18

The study investigated the extent to which approaches to work, workplace climate, stress, burnout and satisfaction with medicine as a career in doctors aged about thirty are predicted by measures of learning style and personality measured five to twelve years earlier when the doctors were applicants to medical school or were medical students. Prospective study of a large cohort of doctors. The participants were first studied when they applied to any of five UK medical schools in 1990. Postal questionnaires were sent to all doctors with a traceable address on the current or a previous Medical Register. The current questionnaire included measures of Approaches to Work, Workplace Climate, stress (General Health Questionnaire), burnout (Maslach Burnout Inventory), and satisfaction with medicine as a career and personality (Big Five). Previous questionnaires had included measures of learning style (Study Process Questionnaire) and personality. Doctors' approaches to work were predicted by study habits and learning styles, both at application to medical school and in the final year. How doctors perceive their workplace climate and workload is predicted both by approaches to work and by measures of stress, burnout and satisfaction with medicine. These characteristics are partially predicted by trait measures of personality taken five years earlier. Stress, burnout and satisfaction also correlate with trait measures of personality taken five years earlier. Differences in approach to work and perceived workplace climate seem mainly to reflect stable, long-term individual differences in doctors themselves, reflected in measures of personality and learning style.

Stress, burnout and doctors' attitudes to work are determined by personality and learning style: A twelve year longitudinal study of UK medical graduates

PubMed Central

McManus, IC; Keeling, A; Paice, E

2004-01-01

Background The study investigated the extent to which approaches to work, workplace climate, stress, burnout and satisfaction with medicine as a career in doctors aged about thirty are predicted by measures of learning style and personality measured five to twelve years earlier when the doctors were applicants to medical school or were medical students. Methods Prospective study of a large cohort of doctors. The participants were first studied when they applied to any of five UK medical schools in 1990. Postal questionnaires were sent to all doctors with a traceable address on the current or a previous Medical Register. The current questionnaire included measures of Approaches to Work, Workplace Climate, stress (General Health Questionnaire), burnout (Maslach Burnout Inventory), and satisfaction with medicine as a career and personality (Big Five). Previous questionnaires had included measures of learning style (Study Process Questionnaire) and personality. Results Doctors' approaches to work were predicted by study habits and learning styles, both at application to medical school and in the final year. How doctors perceive their workplace climate and workload is predicted both by approaches to work and by measures of stress, burnout and satisfaction with medicine. These characteristics are partially predicted by trait measures of personality taken five years earlier. Stress, burnout and satisfaction also correlate with trait measures of personality taken five years earlier. Conclusions Differences in approach to work and perceived workplace climate seem mainly to reflect stable, long-term individual differences in doctors themselves, reflected in measures of personality and learning style. PMID:15317650

Effects of Early Life Stress on Depression, Cognitive Performance, and Brain Morphology

PubMed Central

Saleh, Ayman; Potter, Guy G.; McQuoid, Douglas R.; Boyd, Brian; Turner, Rachel; MacFall, James R; Taylor, Warren D.

2016-01-01

Background Childhood early life stress (ELS) increases risk of adulthood Major Depressive Disorder (MDD) and is associated with altered brain structure and function. It is unclear whether specific ELSs affect depression risk, cognitive function and brain structure. Methods This cross-sectional study included 64 antidepressant-free depressed and 65 never depressed individuals. Both groups reported a range of ELSs on the Early Life Stress Questionnaire, completed neuropsychological testing and 3T MRI. Neuropsychological testing assessed domains of episodic memory, working memory, processing speed and executive function. MRI measures included cortical thickness and regional gray matter volumes, with a priori focus on cingulate cortex, orbitofrontal cortex (OFC), amygdala, caudate and hippocampus. Results Of 19 ELSs, only emotional abuse, sexual abuse and severe family conflict independently predicted adulthood MDD diagnosis. The effect of total ELS score differed between groups. Greater ELS exposure was associated with slower processing speed and smaller OFC volumes in depressed subjects, but faster speed and larger volumes in nondepressed subjects. In contrast, exposure to ELSs predictive of depression had similar effects in both diagnostic groups. Individuals reporting predictive ELSs exhibited poorer processing speed and working memory performance, smaller volumes of the lateral OFC and caudate, and decreased cortical thickness in multiple areas including the insula bilaterally. Predictive ELS exposure was also associated with smaller left hippocampal volume in depressed subjects. Conclusion Findings suggest an association between childhood trauma exposure and adulthood cognitive function and brain structure. These relationships appear to differ between individuals who do and do not develop depression. PMID:27682320

Syntactic Constraints and Individual Differences in Native and Non-Native Processing of Wh-Movement

PubMed Central

Johnson, Adrienne; Fiorentino, Robert; Gabriele, Alison

2016-01-01

There is a debate as to whether second language (L2) learners show qualitatively similar processing profiles as native speakers or whether L2 learners are restricted in their ability to use syntactic information during online processing. In the realm of wh-dependency resolution, research has examined whether learners, similar to native speakers, attempt to resolve wh-dependencies in grammatically licensed contexts but avoid positing gaps in illicit contexts such as islands. Also at issue is whether the avoidance of gap filling in islands is due to adherence to syntactic constraints or whether islands simply present processing bottlenecks. One approach has been to examine the relationship between processing abilities and the establishment of wh-dependencies in islands. Grammatical accounts of islands do not predict such a relationship as the parser should simply not predict gaps in illicit contexts. In contrast, a pattern of results showing that individuals with more processing resources are better able to establish wh-dependencies in islands could conceivably be compatible with certain processing accounts. In a self-paced reading experiment which examines the processing of wh-dependencies, we address both questions, examining whether native English speakers and Korean learners of English show qualitatively similar patterns and whether there is a relationship between working memory, as measured by counting span and reading span, and processing in both island and non-island contexts. The results of the self-paced reading experiment suggest that learners can use syntactic information on the same timecourse as native speakers, showing qualitative similarity between the two groups. Results of regression analyses did not reveal a significant relationship between working memory and the establishment of wh-dependencies in islands but we did observe significant relationships between working memory and the processing of licit wh-dependencies. As the contexts in which these relationships emerged differed for learners and native speakers, our results call for further research examining individual differences in dependency resolution in both populations. PMID:27148152

Syntactic Constraints and Individual Differences in Native and Non-Native Processing of Wh-Movement.

PubMed

Johnson, Adrienne; Fiorentino, Robert; Gabriele, Alison

2016-01-01

There is a debate as to whether second language (L2) learners show qualitatively similar processing profiles as native speakers or whether L2 learners are restricted in their ability to use syntactic information during online processing. In the realm of wh-dependency resolution, research has examined whether learners, similar to native speakers, attempt to resolve wh-dependencies in grammatically licensed contexts but avoid positing gaps in illicit contexts such as islands. Also at issue is whether the avoidance of gap filling in islands is due to adherence to syntactic constraints or whether islands simply present processing bottlenecks. One approach has been to examine the relationship between processing abilities and the establishment of wh-dependencies in islands. Grammatical accounts of islands do not predict such a relationship as the parser should simply not predict gaps in illicit contexts. In contrast, a pattern of results showing that individuals with more processing resources are better able to establish wh-dependencies in islands could conceivably be compatible with certain processing accounts. In a self-paced reading experiment which examines the processing of wh-dependencies, we address both questions, examining whether native English speakers and Korean learners of English show qualitatively similar patterns and whether there is a relationship between working memory, as measured by counting span and reading span, and processing in both island and non-island contexts. The results of the self-paced reading experiment suggest that learners can use syntactic information on the same timecourse as native speakers, showing qualitative similarity between the two groups. Results of regression analyses did not reveal a significant relationship between working memory and the establishment of wh-dependencies in islands but we did observe significant relationships between working memory and the processing of licit wh-dependencies. As the contexts in which these relationships emerged differed for learners and native speakers, our results call for further research examining individual differences in dependency resolution in both populations.

Multimethod Prediction of Physical Parent-Child Aggression Risk in Expectant Mothers and Fathers with Social Information Processing Theory

PubMed Central

Rodriguez, Christina M.; Smith, Tamika L.; Silvia, Paul J.

2015-01-01

The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants’ own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. PMID:26631420

Prediction model for the return to work of workers with injuries in Hong Kong.

PubMed

Xu, Yanwen; Chan, Chetwyn C H; Lo, Karen Hui Yu-Ling; Tang, Dan

2008-01-01

This study attempts to formulate a prediction model of return to work for a group of workers who have been suffering from chronic pain and physical injury while also being out of work in Hong Kong. The study used Case-based Reasoning (CBR) method, and compared the result with the statistical method of logistic regression model. The database of the algorithm of CBR was composed of 67 cases who were also used in the logistic regression model. The testing cases were 32 participants who had a similar background and characteristics to those in the database. The methods of setting constraints and Euclidean distance metric were used in CBR to search the closest cases to the trial case based on the matrix. The usefulness of the algorithm was tested on 32 new participants, and the accuracy of predicting return to work outcomes was 62.5%, which was no better than the 71.2% accuracy derived from the logistic regression model. The results of the study would enable us to have a better understanding of the CBR applied in the field of occupational rehabilitation by comparing with the conventional regression analysis. The findings would also shed light on the development of relevant interventions for the return-to-work process of these workers.

Prediction in the Processing of Repair Disfluencies

PubMed Central

Lowder, Matthew W.; Ferreira, Fernanda

2015-01-01

Imagine a speaker who says "Turn left, uh I mean…" Before hearing the repair, the listener is likely to anticipate the word "right" based on the context, including the reparandum "left." Thus, even though the reparandum is not intended as part of the utterance, the listener uses it as information to predict the repair. The issue we explore in this article is how prediction operates in disfluency contexts. We begin by describing the Overlay model of disfluency comprehension, which assumes that the listener identifies a reparandum as such only after a repair is encountered which creates a local ungrammaticality. The Overlay model also allows the reparandum to influence subsequent processing, because the reparandum is not deleted from the final representation of the sentence. A somewhat different model can be developed which assumes a more active, anticipatory process for resolving repair disfluencies. On this model, the listener might predict the likely repair when the speaker becomes disfluent, or even identify a reparandum if the word or word string seems inconsistent with the speaker's intention. Our proposal is that the prediction can be made using the same mechanism involved in the processing of contrast, in which a listener uses contrastive prominence to generate likely alternates (the contrast set). We suggest that these two approaches to disfluency processing are not inconsistent: Successful repair processing requires listeners to use statistical and linguistic evidence to identify a reparandum and to integrate the repair, and the lingering of the reparandum is due to the coexistence in working memory of the reparandum, the repair, and unselected members of the contrast set. PMID:26878026

Application of agent-based system for bioprocess description and process improvement.

PubMed

Gao, Ying; Kipling, Katie; Glassey, Jarka; Willis, Mark; Montague, Gary; Zhou, Yuhong; Titchener-Hooker, Nigel J

2010-01-01

Modeling plays an important role in bioprocess development for design and scale-up. Predictive models can also be used in biopharmaceutical manufacturing to assist decision-making either to maintain process consistency or to identify optimal operating conditions. To predict the whole bioprocess performance, the strong interactions present in a processing sequence must be adequately modeled. Traditionally, bioprocess modeling considers process units separately, which makes it difficult to capture the interactions between units. In this work, a systematic framework is developed to analyze the bioprocesses based on a whole process understanding and considering the interactions between process operations. An agent-based approach is adopted to provide a flexible infrastructure for the necessary integration of process models. This enables the prediction of overall process behavior, which can then be applied during process development or once manufacturing has commenced, in both cases leading to the capacity for fast evaluation of process improvement options. The multi-agent system comprises a process knowledge base, process models, and a group of functional agents. In this system, agent components co-operate with each other in performing their tasks. These include the description of the whole process behavior, evaluating process operating conditions, monitoring of the operating processes, predicting critical process performance, and providing guidance to decision-making when coping with process deviations. During process development, the system can be used to evaluate the design space for process operation. During manufacture, the system can be applied to identify abnormal process operation events and then to provide suggestions as to how best to cope with the deviations. In all cases, the function of the system is to ensure an efficient manufacturing process. The implementation of the agent-based approach is illustrated via selected application scenarios, which demonstrate how such a framework may enable the better integration of process operations by providing a plant-wide process description to facilitate process improvement. Copyright 2009 American Institute of Chemical Engineers

CFE-2 Experiment Run

NASA Image and Video Library

2013-11-21

View of Flight Engineer (FE) Koichi Wakata posing for a photo during a CFE-2 (Capillary Flow Experiment - 2) Interior Corner Flow - 8 (ICF-8) test run. Liquids behave differently in space than they do on Earth, so containers that can process, hold or transport them must be designed carefully to work in microgravity. The Capillary Flow Experiment-2 furthers research on wetting, which is a liquid's ability to spread across a surface, and its impact over large length scales in strange container shapes in microgravity environments. This work will improve capabilities to quickly and accurately predict how related processes occur, and allow us to design better systems to process liquids aboard spacecraft (i.e., liquid fuel tanks, thermals fluids, and water processing for life support). Image was released by astronaut on Twitter.

Empowering leaders optimize working conditions for engagement: a multilevel study.

PubMed

Tuckey, Michelle R; Bakker, Arnold B; Dollard, Maureen F

2012-01-01

Using a multilevel framework, this study examined the role of empowering leadership at the group level by fire brigade captains in facilitating the individual level motivational processes that underpin work engagement in volunteer firefighters. Anonymous mail surveys were completed by 540 volunteer firefighters from 68 fire brigades and, separately, by 68 brigade captains. As predicted on the basis of the Job Demands-Resources model, increased levels of cognitive demands and cognitive resources partially mediated the relationship between empowering leadership and work engagement. In a three-way Leadership × Demands × Resources interaction, empowering leadership also had the effect of optimizing working conditions for engagement by strengthening the positive effect of a work context in which both cognitive demands and cognitive resources were high. Our findings shed light on a process through which leaders can empower workers and enhance well-being: via their influence on and interaction with the work environment. They also underscore the need to examine work engagement from a multilevel theoretical perspective.

Working in the sky: a diary study on work engagement among flight attendants.

PubMed

Xanthopoulou, Despoina; Bakker, Arnold B; Heuven, Ellen; Demerouti, Evangelia; Schaufeli, Wilmar B

2008-10-01

This study aims to gain insight in the motivational process of the Job Demands-Resources (JD-R) model by examining whether daily fluctuations in colleague support (i.e., a typical job resource) predict day-levels of job performance through self-efficacy and work engagement. Forty-four flight attendants filled in a questionnaire and a diary booklet before and after consecutive flights to three intercontinental destinations. Results of multilevel analyses revealed that colleague support had unique positive effects on self-efficacy and work engagement. Self-efficacy did not mediate the relationship between support and engagement, but work engagement mediated the relationship between self-efficacy and (in-role and extra-role) performance. In addition, colleague support had an indirect effect on in-role performance through work engagement. These findings shed light on the motivational process as outlined in the JD-R model, and suggest that colleague support is an important job resource for flight attendants helping them reach their work-related goals.

Dopamine and the Management of Attentional Resources: Genetic Markers of Striatal D2 Dopamine Predict Individual Differences in the Attentional Blink

ERIC Educational Resources Information Center

Colzato, Lorenza S.; Slagter, Heleen A.; de Rover, Mischa; Hommel, Bernhard

2011-01-01

The attentional blink (AB)--a deficit in reporting the second of two target stimuli presented in close succession in a rapid sequence of distracters--has been related to processing limitations in working memory. Given that dopamine (DA) plays a crucial role working memory, the present study tested whether individual differences in the size of the…

The two-process theory of face processing: modifications based on two decades of data from infants and adults.

PubMed

Johnson, Mark H; Senju, Atsushi; Tomalski, Przemyslaw

2015-03-01

Johnson and Morton (1991. Biology and Cognitive Development: The Case of Face Recognition. Blackwell, Oxford) used Gabriel Horn's work on the filial imprinting model to inspire a two-process theory of the development of face processing in humans. In this paper we review evidence accrued over the past two decades from infants and adults, and from other primates, that informs this two-process model. While work with newborns and infants has been broadly consistent with predictions from the model, further refinements and questions have been raised. With regard to adults, we discuss more recent evidence on the extension of the model to eye contact detection, and to subcortical face processing, reviewing functional imaging and patient studies. We conclude with discussion of outstanding caveats and future directions of research in this field. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

DEVELOPMENT OF THE VIRTUAL BEACH MODEL, PHASE 1: AN EMPIRICAL MODEL

EPA Science Inventory

With increasing attention focused on the use of multiple linear regression (MLR) modeling of beach fecal bacteria concentration, the validity of the entire statistical process should be carefully evaluated to assure satisfactory predictions. This work aims to identify pitfalls an...

The fate of memory: Reconsolidation and the case of Prediction Error.

PubMed

Fernández, Rodrigo S; Boccia, Mariano M; Pedreira, María E

2016-09-01

The ability to make predictions based on stored information is a general coding strategy. A Prediction-Error (PE) is a mismatch between expected and current events. It was proposed as the process by which memories are acquired. But, our memories like ourselves are subject to change. Thus, an acquired memory can become active and update its content or strength by a labilization-reconsolidation process. Within the reconsolidation framework, PE drives the updating of consolidated memories. Moreover, memory features, such as strength and age, are crucial boundary conditions that limit the initiation of the reconsolidation process. In order to disentangle these boundary conditions, we review the role of surprise, classical models of conditioning, and their neural correlates. Several forms of PE were found to be capable of inducing memory labilization-reconsolidation. Notably, many of the PE findings mirror those of memory-reconsolidation, suggesting a strong link between these signals and memory process. Altogether, the aim of the present work is to integrate a psychological and neuroscientific analysis of PE into a general framework for memory-reconsolidation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Working alliance, real relationship, session quality, and client improvement in psychodynamic psychotherapy: A longitudinal actor partner interdependence model.

PubMed

Kivlighan, Dennis M; Hill, Clara E; Gelso, Charles J; Baumann, Ellen

2016-03-01

We used the Actor Partner Interdependence Model (APIM; Kashy & Kenny, 2000) to examine the dyadic associations of 74 clients and 23 therapists in their evaluations of working alliance, real relationship, session quality, and client improvement over time in ongoing psychodynamic or interpersonal psychotherapy. There were significant actor effects for both therapists and clients, with the participant's own ratings of working alliance and real relationship independently predicting their own evaluations of session quality. There were significant client partner effects, with clients' working alliance and real relationship independently predicting their therapists' evaluations of session quality. The client partner real relationship effect was stronger in later sessions than in earlier sessions. Therapists' real relationship ratings (partner effect) were a stronger predictor of clients' session quality ratings in later sessions than in earlier sessions. Therapists' working alliance ratings (partner effect) were a stronger predictor of clients' session quality ratings when clients made greater improvement than when clients made lesser improvement. For clients' session outcome ratings, there were complex three-way interactions, such that both Client real relationship and working alliance interacted with client improvement and time in treatment to predict clients' session quality. These findings strongly suggest both individual and partner effects when clients and therapists evaluate psychotherapy process and outcome. Implications for research and practice are discussed. (c) 2016 APA, all rights reserved).

Rolling Process Modeling Report: Finite-Element Prediction of Roll Separating Force and Rolling Defects

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

Soulami, Ayoub; Lavender, Curt A.; Paxton, Dean M.

2014-04-23

Pacific Northwest National Laboratory (PNNL) has been investigating manufacturing processes for the uranium-10% molybdenum (U-10Mo) alloy plate-type fuel for the U.S. high-performance research reactors. This work supports the Convert Program of the U.S. Department of Energy’s National Nuclear Security Administration (DOE/NNSA) Global Threat Reduction Initiative. This report documents modeling results of PNNL’s efforts to perform finite-element simulations to predict roll separating forces and rolling defects. Simulations were performed using a finite-element model developed using the commercial code LS-Dyna. Simulations of the hot rolling of U-10Mo coupons encapsulated in low-carbon steel have been conducted following two different schedules. Model predictions ofmore » the roll-separation force and roll-pack thicknesses at different stages of the rolling process were compared with experimental measurements. This report discusses various attributes of the rolled coupons revealed by the model (e.g., dog-boning and thickness non-uniformity).« less

Delta-Isobar Production in the Hard Photodisintegration of a Deuteron

NASA Astrophysics Data System (ADS)

Granados, Carlos; Sargsian, Misak

2010-02-01

Hard photodisintegration of the deuteron in delta-isobar production channels is proposed as a useful process in identifying the quark structure of hadrons and of hadronic interactions at large momentum and energy transfer. The reactions are modeled using the hard re scattering model, HRM, following previous works on hard breakup of a nucleon nucleon (NN) system in light nuclei. Here,quantitative predictions through the HRM require the numerical input of fits of experimental NN hard elastic scattering cross sections. Because of the lack of data in hard NN scattering into δ-isobar channels, the cross section of the corresponding photodisintegration processes cannot be predicted in the same way. Instead, the corresponding NN scattering process is modeled through the quark interchange mechanism, QIM, leaving an unknown normalization parameter. The observables of interest are ratios of differential cross sections of δ-isobar production channels to NN breakup in deuteron photodisintegration. Both entries in these ratios are derived through the HRM and QIM so that normalization parameters cancel out and numerical predictions can be obtained. )

Factors affecting medication-order processing time.

PubMed

Beaman, M A; Kotzan, J A

1982-11-01

The factors affecting medication-order processing time at one hospital were studied. The order processing time was determined by directly observing the time to process randomly selected new drug orders on all three work shifts during two one-week periods. An order could list more than one drug for an individual patient. The observer recorded the nature, location, and cost of the drugs ordered, as well as the time to process the order. The time and type of interruptions also were noted. The time to process a drug order was classified as six dependent variables: (1) total time, (2) work time, (3) check time, (4) waiting time I--time from arrival on the dumbwaiter until work was initiated, (5) waiting time II--time between completion of the work and initiation of checking, and (6) waiting time III--time after the check was completed until the order left on the dumbwaiter. The significant predictors of each of the six dependent variables were determined using stepwise multiple regression. The total time to process a prescription order was 58.33 +/- 48.72 minutes; the urgency status of the order was the only significant determinant of total time. Urgency status also significantly predicted the three waiting-time variables. Interruptions and the number of drugs on the order were significant determinants of work time and check time. Each telephone interruption increased the work time by 1.72 minutes. While the results of this study cannot be generalized to other institutions, pharmacy managers can use the method of determining factors that affect medication-order processing time to identify problem areas in their institutions.

Isoscalar-isovector mass splittings in excited mesons

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

Geiger, P.

1994-06-01

Mass splittings between the isovector and isoscalar members of meson nonets arise in part from hadronic loop diagrams which violate the Okubo-Zweig-Iizuka rule. Using a model for these loop processes which works qualitatively well in the established nonets, I tabulate predictions for the splittings and associated isoscalar mixing angles in the remaining nonets below about 2 GeV, and explain some of their systematic features. The model predicts significant deviations from ideal mixing in the excited vector nonets.

The calcium binding properties and structure prediction of the Hax-1 protein.

PubMed

Balcerak, Anna; Rowinski, Sebastian; Szafron, Lukasz M; Grzybowska, Ewa A

2017-01-01

Hax-1 is a protein involved in regulation of different cellular processes, but its properties and exact mechanisms of action remain unknown. In this work, using purified, recombinant Hax-1 and by applying an in vitro autoradiography assay we have shown that this protein binds Ca 2+ . Additionally, we performed structure prediction analysis which shows that Hax-1 displays definitive structural features, such as two α-helices, short β-strands and four disordered segments.

The Predictive Brain State: Asynchrony in Disorders of Attention?

PubMed Central

Ghajar, Jamshid; Ivry, Richard B.

2015-01-01

It is postulated that a key function of attention in goal-oriented behavior is to reduce performance variability by generating anticipatory neural activity that can be synchronized with expected sensory information. A network encompassing the prefrontal cortex, parietal lobe, and cerebellum may be critical in the maintenance and timing of such predictive neural activity. Dysfunction of this temporal process may constitute a fundamental defect in attention, causing working memory problems, distractibility, and decreased awareness. PMID:19074688

Optimization and Prediction of Ultimate Tensile Strength in Metal Active Gas Welding.

PubMed

Ampaiboon, Anusit; Lasunon, On-Uma; Bubphachot, Bopit

2015-01-01

We investigated the effect of welding parameters on ultimate tensile strength of structural steel, ST37-2, welded by Metal Active Gas welding. A fractional factorial design was used for determining the significance of six parameters: wire feed rate, welding voltage, welding speed, travel angle, tip-to-work distance, and shielded gas flow rate. A regression model to predict ultimate tensile strength was developed. Finally, we verified optimization of the process parameters experimentally. We achieved an optimum tensile strength (558 MPa) and wire feed rate, 19 m/min, had the greatest effect, followed by tip-to-work distance, 7 mm, welding speed, 200 mm/min, welding voltage, 30 V, and travel angle, 60°. Shield gas flow rate, 10 L/min, was slightly better but had little effect in the 10-20 L/min range. Tests showed that our regression model was able to predict the ultimate tensile strength within 4%.

Electrochemistry-based Battery Modeling for Prognostics

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Kulkarni, Chetan Shrikant

2013-01-01

Batteries are used in a wide variety of applications. In recent years, they have become popular as a source of power for electric vehicles such as cars, unmanned aerial vehicles, and commericial passenger aircraft. In such application domains, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. To implement such technologies, it is crucial to understand how batteries work and to capture that knowledge in the form of models that can be used by monitoring, diagnosis, and prognosis algorithms. In this work, we develop electrochemistry-based models of lithium-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles. This paper reports on the progress of such a model, with results demonstrating the model validity and accurate EOD predictions.

Enhancing the Performance of LibSVM Classifier by Kernel F-Score Feature Selection

NASA Astrophysics Data System (ADS)

Sarojini, Balakrishnan; Ramaraj, Narayanasamy; Nickolas, Savarimuthu

Medical Data mining is the search for relationships and patterns within the medical datasets that could provide useful knowledge for effective clinical decisions. The inclusion of irrelevant, redundant and noisy features in the process model results in poor predictive accuracy. Much research work in data mining has gone into improving the predictive accuracy of the classifiers by applying the techniques of feature selection. Feature selection in medical data mining is appreciable as the diagnosis of the disease could be done in this patient-care activity with minimum number of significant features. The objective of this work is to show that selecting the more significant features would improve the performance of the classifier. We empirically evaluate the classification effectiveness of LibSVM classifier on the reduced feature subset of diabetes dataset. The evaluations suggest that the feature subset selected improves the predictive accuracy of the classifier and reduce false negatives and false positives.

Working memory capacity and the spacing effect in cued recall.

PubMed

Delaney, Peter F; Godbole, Namrata R; Holden, Latasha R; Chang, Yoojin

2018-07-01

Spacing repetitions typically improves memory (the spacing effect). In three cued recall experiments, we explored the relationship between working memory capacity and the spacing effect. People with higher working memory capacity are more accurate on memory tasks that require retrieval relative to people with lower working memory capacity. The experiments used different retention intervals and lags between repetitions, but were otherwise similar. Working memory capacity and spacing of repetitions both improved memory in most of conditions, but they did not interact, suggesting additive effects. The results are consistent with the ACT-R model's predictions, and with a study-phase recognition process underpinning the spacing effect in cued recall.

Simple, empirical approach to predict neutron capture cross sections from nuclear masses

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

Couture, Aaron Joseph; Casten, Richard F.; Cakirli, R. B.

Here, neutron capture cross sections are essential to understanding the astrophysical s and r processes, the modeling of nuclear reactor design and performance, and for a wide variety of nuclear forensics applications. Often, cross sections are needed for nuclei where experimental measurements are difficult. Enormous effort, over many decades, has gone into attempting to develop sophisticated statistical reaction models to predict these cross sections. Such work has met with some success but is often unable to reproduce measured cross sections to better than 40%, and has limited predictive power, with predictions from different models rapidly differing by an order ofmore » magnitude a few nucleons from the last measurement.« less

Simple, empirical approach to predict neutron capture cross sections from nuclear masses

DOE PAGES

Couture, Aaron Joseph; Casten, Richard F.; Cakirli, R. B.

2017-12-20

Here, neutron capture cross sections are essential to understanding the astrophysical s and r processes, the modeling of nuclear reactor design and performance, and for a wide variety of nuclear forensics applications. Often, cross sections are needed for nuclei where experimental measurements are difficult. Enormous effort, over many decades, has gone into attempting to develop sophisticated statistical reaction models to predict these cross sections. Such work has met with some success but is often unable to reproduce measured cross sections to better than 40%, and has limited predictive power, with predictions from different models rapidly differing by an order ofmore » magnitude a few nucleons from the last measurement.« less

Calculation of electromagnetic force in electromagnetic forming process of metal sheet

NASA Astrophysics Data System (ADS)

Xu, Da; Liu, Xuesong; Fang, Kun; Fang, Hongyuan

2010-06-01

Electromagnetic forming (EMF) is a forming process that relies on the inductive electromagnetic force to deform metallic workpiece at high speed. Calculation of the electromagnetic force is essential to understand the EMF process. However, accurate calculation requires complex numerical solution, in which the coupling between the electromagnetic process and the deformation of workpiece needs be considered. In this paper, an appropriate formula has been developed to calculate the electromagnetic force in metal work-piece in the sheet EMF process. The effects of the geometric size of coil, the material properties, and the parameters of discharge circuit on electromagnetic force are taken into consideration. Through the formula, the electromagnetic force at different time and in different positions of the workpiece can be predicted. The calculated electromagnetic force and magnetic field are in good agreement with the numerical and experimental results. The accurate prediction of the electromagnetic force provides an insight into the physical process of the EMF and a powerful tool to design optimum EMF systems.

Determination of melt pool dimensions using DOE-FEM and RSM with process window during SLM of Ti6Al4V powder

NASA Astrophysics Data System (ADS)

Zhuang, Jyun-Rong; Lee, Yee-Ting; Hsieh, Wen-Hsin; Yang, An-Shik

2018-07-01

Selective laser melting (SLM) shows a positive prospect as an additive manufacturing (AM) technique for fabrication of 3D parts with complicated structures. A transient thermal model was developed by the finite element method (FEM) to simulate the thermal behavior for predicting the time evolution of temperature field and melt pool dimensions of Ti6Al4V powder during SLM. The FEM predictions were then compared with published experimental measurements and calculation results for model validation. This study applied the design of experiment (DOE) scheme together with the response surface method (RSM) to conduct the regression analysis based on four processing parameters (exactly, the laser power, scanning speed, preheating temperature and hatch space) for predicting the dimensions of the melt pool in SLM. The preliminary RSM results were used to quantify the effects of those parameters on the melt pool size. The process window was further implemented via two criteria of the width and depth of the molten pool to screen impractical conditions of four parameters for including the practical ranges of processing parameters. The FEM simulations confirmed the good accuracy of the critical RSM models in the predictions of melt pool dimensions for three typical SLM working scenarios.

Individual Differences in Working Memory Capacity Predict Retrieval-Induced Forgetting

ERIC Educational Resources Information Center

Aslan, Alp; Bauml, Karl-Heinz T.

2011-01-01

Selectively retrieving a subset of previously studied information enhances memory for the retrieved information but causes forgetting of related, nonretrieved information. Such retrieval-induced forgetting (RIF) has often been attributed to inhibitory executive-control processes that supposedly suppress the nonretrieved items' memory…

What's in a New Name? Collaborative Learning and Shakespeare.

ERIC Educational Resources Information Center

Jaccarino, Victor

1993-01-01

Considers ways of implementing collaborative learning techniques into the teaching of William Shakespeare in the high school English curriculum. Argues for allowing students to predict the action after viewing only one act of a play. Shows how group work enhanced students' thinking processes. (HB)

"Obesity is a disease": examining the self-regulatory impact of this public-health message.

PubMed

Hoyt, Crystal L; Burnette, Jeni L; Auster-Gussman, Lisa

2014-04-01

In the current work, we examined the impact of the American Medical Association's recent classification of obesity as a disease on weight-management processes. Across three experimental studies, we highlighted the potential hidden costs associated with labeling obesity as a disease, showing that this message, presented in an actual New York Times article, undermined beneficial weight-loss self-regulatory processes. A disease-based, relative to an information-based, weight-management message weakened the importance placed on health-focused dieting and reduced concerns about weight among obese individuals--the very people whom such public-health messages are targeting. Further, the decreased concern about weight predicted higher-calorie food choices. In addition, the disease message, relative to a message that obesity is not a disease, lowered body-image dissatisfaction, but this too predicted higher-calorie food choices. Thus, although defining obesity as a disease may be beneficial for body image, results from the current work emphasize the negative implications of this message for self-regulation.

Numerical simulation of mushrooms during freezing using the FEM and an enthalpy: Kirchhoff formulation

NASA Astrophysics Data System (ADS)

Santos, M. V.; Lespinard, A. R.

2011-12-01

The shelf life of mushrooms is very limited since they are susceptible to physical and microbial attack; therefore they are usually blanched and immediately frozen for commercial purposes. The aim of this work was to develop a numerical model using the finite element technique to predict freezing times of mushrooms considering the actual shape of the product. The original heat transfer equation was reformulated using a combined enthalpy-Kirchhoff formulation, therefore an own computational program using Matlab 6.5 (MathWorks, Natick, Massachusetts) was developed, considering the difficulties encountered when simulating this non-linear problem in commercial softwares. Digital images were used to generate the irregular contour and the domain discretization. The numerical predictions agreed with the experimental time-temperature curves during freezing of mushrooms (maximum absolute error <3.2°C) obtaining accurate results and minimum computer processing times. The codes were then applied to determine required processing times for different operating conditions (external fluid temperatures and surface heat transfer coefficients).

Mechatronics technology in predictive maintenance method

NASA Astrophysics Data System (ADS)

Majid, Nurul Afiqah A.; Muthalif, Asan G. A.

2017-11-01

This paper presents recent mechatronics technology that can help to implement predictive maintenance by combining intelligent and predictive maintenance instrument. Vibration Fault Simulation System (VFSS) is an example of mechatronics system. The focus of this study is the prediction on the use of critical machines to detect vibration. Vibration measurement is often used as the key indicator of the state of the machine. This paper shows the choice of the appropriate strategy in the vibration of diagnostic process of the mechanical system, especially rotating machines, in recognition of the failure during the working process. In this paper, the vibration signature analysis is implemented to detect faults in rotary machining that includes imbalance, mechanical looseness, bent shaft, misalignment, missing blade bearing fault, balancing mass and critical speed. In order to perform vibration signature analysis for rotating machinery faults, studies have been made on how mechatronics technology is used as predictive maintenance methods. Vibration Faults Simulation Rig (VFSR) is designed to simulate and understand faults signatures. These techniques are based on the processing of vibrational data in frequency-domain. The LabVIEW-based spectrum analyzer software is developed to acquire and extract frequency contents of faults signals. This system is successfully tested based on the unique vibration fault signatures that always occur in a rotating machinery.

Comparison of RF spectrum prediction methods for dynamic spectrum access

NASA Astrophysics Data System (ADS)

Kovarskiy, Jacob A.; Martone, Anthony F.; Gallagher, Kyle A.; Sherbondy, Kelly D.; Narayanan, Ram M.

2017-05-01

Dynamic spectrum access (DSA) refers to the adaptive utilization of today's busy electromagnetic spectrum. Cognitive radio/radar technologies require DSA to intelligently transmit and receive information in changing environments. Predicting radio frequency (RF) activity reduces sensing time and energy consumption for identifying usable spectrum. Typical spectrum prediction methods involve modeling spectral statistics with Hidden Markov Models (HMM) or various neural network structures. HMMs describe the time-varying state probabilities of Markov processes as a dynamic Bayesian network. Neural Networks model biological brain neuron connections to perform a wide range of complex and often non-linear computations. This work compares HMM, Multilayer Perceptron (MLP), and Recurrent Neural Network (RNN) algorithms and their ability to perform RF channel state prediction. Monte Carlo simulations on both measured and simulated spectrum data evaluate the performance of these algorithms. Generalizing spectrum occupancy as an alternating renewal process allows Poisson random variables to generate simulated data while energy detection determines the occupancy state of measured RF spectrum data for testing. The results suggest that neural networks achieve better prediction accuracy and prove more adaptable to changing spectral statistics than HMMs given sufficient training data.

GALACTIC CHEMICAL EVOLUTION: THE IMPACT OF THE {sup 13}C-POCKET STRUCTURE ON THE s -PROCESS DISTRIBUTION

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

Bisterzo, S.; Travaglio, C.; Wiescher, M.

2017-01-20

The solar s -process abundances have been analyzed in the framework of a Galactic Chemical Evolution (GCE) model. The aim of this work is to implement the study by Bisterzo et al., who investigated the effect of one of the major uncertainties of asymptotic giant branch (AGB) yields, the internal structure of the {sup 13}C pocket. We present GCE predictions of s -process elements computed with additional tests in the light of suggestions provided in recent publications. The analysis is extended to different metallicities, by comparing GCE results and updated spectroscopic observations of unevolved field stars. We verify that themore » GCE predictions obtained with different tests may represent, on average, the evolution of selected neutron-capture elements in the Galaxy. The impact of an additional weak s -process contribution from fast-rotating massive stars is also explored.« less

Comprehensive Model of Single Particle Pulverized Coal Combustion Extended to Oxy-Coal Conditions

DOE PAGES

Holland, Troy; Fletcher, Thomas H.

2017-02-22

Oxy-fired coal combustion is a promising potential carbon capture technology. Predictive CFD simulations are valuable tools in evaluating and deploying oxy-fuel and other carbon capture technologies either as retrofit technologies or for new construction. But, accurate predictive simulations require physically realistic submodels with low computational requirements. In particular, comprehensive char oxidation and gasification models have been developed that describe multiple reaction and diffusion processes. Our work extends a comprehensive char conversion code (CCK), which treats surface oxidation and gasification reactions as well as processes such as film diffusion, pore diffusion, ash encapsulation, and annealing. In this work several submodels inmore » the CCK code were updated with more realistic physics or otherwise extended to function in oxy-coal conditions. Improved submodels include the annealing model, the swelling model, the mode of burning parameter, and the kinetic model, as well as the addition of the chemical percolation devolatilization (CPD) model. We compare our results of the char combustion model to oxy-coal data, and further compared to parallel data sets near conventional conditions. A potential method to apply the detailed code in CFD work is given.« less

Comprehensive Model of Single Particle Pulverized Coal Combustion Extended to Oxy-Coal Conditions

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

Holland, Troy; Fletcher, Thomas H.

Oxy-fired coal combustion is a promising potential carbon capture technology. Predictive CFD simulations are valuable tools in evaluating and deploying oxy-fuel and other carbon capture technologies either as retrofit technologies or for new construction. But, accurate predictive simulations require physically realistic submodels with low computational requirements. In particular, comprehensive char oxidation and gasification models have been developed that describe multiple reaction and diffusion processes. Our work extends a comprehensive char conversion code (CCK), which treats surface oxidation and gasification reactions as well as processes such as film diffusion, pore diffusion, ash encapsulation, and annealing. In this work several submodels inmore » the CCK code were updated with more realistic physics or otherwise extended to function in oxy-coal conditions. Improved submodels include the annealing model, the swelling model, the mode of burning parameter, and the kinetic model, as well as the addition of the chemical percolation devolatilization (CPD) model. We compare our results of the char combustion model to oxy-coal data, and further compared to parallel data sets near conventional conditions. A potential method to apply the detailed code in CFD work is given.« less

Validating and Extending the Three Process Model of Alertness in Airline Operations

PubMed Central

Ingre, Michael; Van Leeuwen, Wessel; Klemets, Tomas; Ullvetter, Christer; Hough, Stephen; Kecklund, Göran; Karlsson, David; Åkerstedt, Torbjörn

2014-01-01

Sleepiness and fatigue are important risk factors in the transport sector and bio-mathematical sleepiness, sleep and fatigue modeling is increasingly becoming a valuable tool for assessing safety of work schedules and rosters in Fatigue Risk Management Systems (FRMS). The present study sought to validate the inner workings of one such model, Three Process Model (TPM), on aircrews and extend the model with functions to model jetlag and to directly assess the risk of any sleepiness level in any shift schedule or roster with and without knowledge of sleep timings. We collected sleep and sleepiness data from 136 aircrews in a real life situation by means of an application running on a handheld touch screen computer device (iPhone, iPod or iPad) and used the TPM to predict sleepiness with varying level of complexity of model equations and data. The results based on multilevel linear and non-linear mixed effects models showed that the TPM predictions correlated with observed ratings of sleepiness, but explorative analyses suggest that the default model can be improved and reduced to include only two-processes (S+C), with adjusted phases of the circadian process based on a single question of circadian type. We also extended the model with a function to model jetlag acclimatization and with estimates of individual differences including reference limits accounting for 50%, 75% and 90% of the population as well as functions for predicting the probability of any level of sleepiness for ecological assessment of absolute and relative risk of sleepiness in shift systems for safety applications. PMID:25329575

Carboxylator: incorporating solvent-accessible surface area for identifying protein carboxylation sites

NASA Astrophysics Data System (ADS)

Lu, Cheng-Tsung; Chen, Shu-An; Bretaña, Neil Arvin; Cheng, Tzu-Hsiu; Lee, Tzong-Yi

2011-10-01

In proteins, glutamate (Glu) residues are transformed into γ-carboxyglutamate (Gla) residues in a process called carboxylation. The process of protein carboxylation catalyzed by γ-glutamyl carboxylase is deemed to be important due to its involvement in biological processes such as blood clotting cascade and bone growth. There is an increasing interest within the scientific community to identify protein carboxylation sites. However, experimental identification of carboxylation sites via mass spectrometry-based methods is observed to be expensive, time-consuming, and labor-intensive. Thus, we were motivated to design a computational method for identifying protein carboxylation sites. This work aims to investigate the protein carboxylation by considering the composition of amino acids that surround modification sites. With the implication of a modified residue prefers to be accessible on the surface of a protein, the solvent-accessible surface area (ASA) around carboxylation sites is also investigated. Radial basis function network is then employed to build a predictive model using various features for identifying carboxylation sites. Based on a five-fold cross-validation evaluation, a predictive model trained using the combined features of amino acid sequence (AA20D), amino acid composition, and ASA, yields the highest accuracy at 0.874. Furthermore, an independent test done involving data not included in the cross-validation process indicates that in silico identification is a feasible means of preliminary analysis. Additionally, the predictive method presented in this work is implemented as Carboxylator (http://csb.cse.yzu.edu.tw/Carboxylator/), a web-based tool for identifying carboxylated proteins with modification sites in order to help users in investigating γ-glutamyl carboxylation.

Maximum Likelihood Time-of-Arrival Estimation of Optical Pulses via Photon-Counting Photodetectors

NASA Technical Reports Server (NTRS)

Erkmen, Baris I.; Moision, Bruce E.

2010-01-01

Many optical imaging, ranging, and communications systems rely on the estimation of the arrival time of an optical pulse. Recently, such systems have been increasingly employing photon-counting photodetector technology, which changes the statistics of the observed photocurrent. This requires time-of-arrival estimators to be developed and their performances characterized. The statistics of the output of an ideal photodetector, which are well modeled as a Poisson point process, were considered. An analytical model was developed for the mean-square error of the maximum likelihood (ML) estimator, demonstrating two phenomena that cause deviations from the minimum achievable error at low signal power. An approximation was derived to the threshold at which the ML estimator essentially fails to provide better than a random guess of the pulse arrival time. Comparing the analytic model performance predictions to those obtained via simulations, it was verified that the model accurately predicts the ML performance over all regimes considered. There is little prior art that attempts to understand the fundamental limitations to time-of-arrival estimation from Poisson statistics. This work establishes both a simple mathematical description of the error behavior, and the associated physical processes that yield this behavior. Previous work on mean-square error characterization for ML estimators has predominantly focused on additive Gaussian noise. This work demonstrates that the discrete nature of the Poisson noise process leads to a distinctly different error behavior.

1987 Robert E. Horton Award to Thomas Dunne

NASA Astrophysics Data System (ADS)

Dunne, Thomas

Robert Horton demonstrated in his seminal 1945 paper that physically based quantitative models for landscape evolution can be constructed by using predicted overland flow in a sediment transport equation for sheetwash. He envisioned drainage network evolution by infiltration-limited overland flow as a process of channel incision, network growth, and then abstraction to a stable channel network fed by hillslopes too short for channel initiation. Not until the work of Tom Dunne in the late 1960s in the Sleepers River watershed, Vermont, was it realized that overland flow, and consequently hillslope evolution, could occur by an entirely different mechanism than that proposed by Horton. Dunne showed that in certain predictable zones of the landscape, exfiltration from saturated grounds adds to precipitation on the soil surface to form what he later called saturation overland flow. Many researchers have since found that this form of overland flow occurs in humid and semiarid landscapes throughout the world. So clear is Dunne's contribution to defining this process that some refer to it as the “Dunne mechanism” to distinguish it from “Horton overland flow.” His work also documented unquestionably the applicability of the partial area concept in explaining runoff generation. Because of this work, his research in snowmelt runoff, and his subsequent authorship with Luna Leopold of the widely used book entitled Water in Environmental Planning, Dunne has established himself as a leader of process hydrology.

System Theory and Physiological Processes.

PubMed

Jones, R W

1963-05-03

Engineers and physiologists working together in experimental and theoretical studies predict that the application of system analysis to biological processes will increase understanding of these processes and broaden the base of system theory. Richard W. Jones, professor of electrical engineering at Northwestern University, Evanston, Illinois, and John S. Gray, professor of physiology at Northwestern's Medical School, discuss these developments. Their articles are adapted from addresses delivered in Chicago in November 1962 at the 15th Annual Conference on Engineering in Medicine and Biology.

Mathematical modeling in biological populations through branching processes. Application to salmonid populations.

PubMed

Molina, Manuel; Mota, Manuel; Ramos, Alfonso

2015-01-01

This work deals with mathematical modeling through branching processes. We consider sexually reproducing animal populations where, in each generation, the number of progenitor couples is determined in a non-predictable environment. By using a class of two-sex branching processes, we describe their demographic dynamics and provide several probabilistic and inferential contributions. They include results about the extinction of the population and the estimation of the offspring distribution and its main moments. We also present an application to salmonid populations.

Object selection costs in visual working memory: A diffusion model analysis of the focus of attention.

PubMed

Sewell, David K; Lilburn, Simon D; Smith, Philip L

2016-11-01

A central question in working memory research concerns the degree to which information in working memory is accessible to other cognitive processes (e.g., decision-making). Theories assuming that the focus of attention can only store a single object at a time require the focus to orient to a target representation before further processing can occur. The need to orient the focus of attention implies that single-object accounts typically predict response time costs associated with object selection even when working memory is not full (i.e., memory load is less than 4 items). For other theories that assume storage of multiple items in the focus of attention, predictions depend on specific assumptions about the way resources are allocated among items held in the focus, and how this affects the time course of retrieval of items from the focus. These broad theoretical accounts have been difficult to distinguish because conventional analyses fail to separate components of empirical response times related to decision-making from components related to selection and retrieval processes associated with accessing information in working memory. To better distinguish these response time components from one another, we analyze data from a probed visual working memory task using extensions of the diffusion decision model. Analysis of model parameters revealed that increases in memory load resulted in (a) reductions in the quality of the underlying stimulus representations in a manner consistent with a sample size model of visual working memory capacity and (b) systematic increases in the time needed to selectively access a probed representation in memory. The results are consistent with single-object theories of the focus of attention. The results are also consistent with a subset of theories that assume a multiobject focus of attention in which resource allocation diminishes both the quality and accessibility of the underlying representations. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Statistical prediction with Kanerva's sparse distributed memory

NASA Technical Reports Server (NTRS)

Rogers, David

1989-01-01

A new viewpoint of the processing performed by Kanerva's sparse distributed memory (SDM) is presented. In conditions of near- or over-capacity, where the associative-memory behavior of the model breaks down, the processing performed by the model can be interpreted as that of a statistical predictor. Mathematical results are presented which serve as the framework for a new statistical viewpoint of sparse distributed memory and for which the standard formulation of SDM is a special case. This viewpoint suggests possible enhancements to the SDM model, including a procedure for improving the predictiveness of the system based on Holland's work with genetic algorithms, and a method for improving the capacity of SDM even when used as an associative memory.

The commerce and crossover of resources: resource conservation in the service of resilience.

PubMed

Chen, Shoshi; Westman, Mina; Hobfoll, Stevan E

2015-04-01

Conservation of resources (COR) theory was originally introduced as a framework for understanding and predicting the consequences of major and traumatic stress, but following the work of Hobfoll and Shirom (1993), COR theory has been adopted to understanding and predicting work-related stress and both the stress and resilience that occur within work settings and work culture. COR theory underscores the critical role of resource possession, lack, loss and gain and depicts personal, social and material resources co-travelling in resource caravans, rather than piecemeal. We briefly review the principles of COR theory and integrate it in the crossover model, which provides a key mechanism for multi-person exchange of emotions, experiences and resources. Understanding the impact of resource reservoirs, resource passageways and crossover provides a framework for research and intervention promoting resilience to employees as well as to organizations. It emphasizes that the creation and maintenance of resource caravan passageways promote resource gain climates through resource crossover processes. Copyright © 2014 John Wiley & Sons, Ltd.

A work-family conflict/subjective well-being process model: a test of competing theories of longitudinal effects.

PubMed

Matthews, Russell A; Wayne, Julie Holliday; Ford, Michael T

2014-11-01

In the present study, we examine competing predictions of stress reaction models and adaptation theories regarding the longitudinal relationship between work-family conflict and subjective well-being. Based on data from 432 participants over 3 time points with 2 lags of varying lengths (i.e., 1 month, 6 months), our findings suggest that in the short term, consistent with prior theory and research, work-family conflict is associated with poorer subjective well-being. Counter to traditional work-family predictions but consistent with adaptation theories, after accounting for concurrent levels of work-family conflict as well as past levels of subjective well-being, past exposure to work-family conflict was associated with higher levels of subjective well-being over time. Moreover, evidence was found for reverse causation in that greater subjective well-being at 1 point in time was associated with reduced work-family conflict at a subsequent point in time. Finally, the pattern of results did not vary as a function of using different temporal lags. We discuss the theoretical, research, and practical implications of our findings. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Distinguishing values from science in decision making: Setting harvest quotas for mountain lions in Montana

USGS Publications Warehouse

Mitchell, Michael S.; Cooley, Hilary; Gude, Justin A.; Kolbe, Jay; Nowak, J. Joshua; Proffitt, Kelly M.; Sells, Sarah N.; Thompson, Mike

2018-01-01

The relative roles of science and human values can be difficult to distinguish when informal processes are used to make complex and contentious decisions in wildlife management. Structured Decision Making (SDM) offers a formal process for making such decisions, where scientific results and concepts can be disentangled from the values of differing stakeholders. We used SDM to formally integrate science and human values for a citizen working group of ungulate hunting advocates, lion hunting advocates, and outfitters convened to address the contentious allocation of harvest quotas for mountain lions (Puma concolor) in west‐central Montana, USA, during 2014. A science team consisting of mountain lion biologists and population ecologists convened to support the working group. The science team used integrated population models that incorporated 4 estimates of mountain lion density to estimate population trajectories for 5 alternative harvest quotas developed by the working group. Results of the modeling predicted that effects of each harvest quota were consistent across the 4 density estimates; harvest quotas affected predicted population trajectories for 5 years after implementation but differences were not strong. Based on these results, the focus of the working group changed to differences in values among stakeholders that were the true impediment to allocating harvest quotas. By distinguishing roles of science and human values in this process, the working group was able to collaboratively recommend a compromise solution. This solution differed little from the status quo that had been the focus of debate, but the SDM process produced understanding and buy‐in among stakeholders involved, reducing disagreements, misunderstanding, and unproductive arguments founded on informal application of scientific data and concepts. Whereas investments involved in conducting SDM may be unnecessary for many decisions in wildlife management, the investment may be beneficial for complex, contentious, and multiobjective decisions that integrate science and human values.

Adapting hierarchical bidirectional inter prediction on a GPU-based platform for 2D and 3D H.264 video coding

NASA Astrophysics Data System (ADS)

Rodríguez-Sánchez, Rafael; Martínez, José Luis; Cock, Jan De; Fernández-Escribano, Gerardo; Pieters, Bart; Sánchez, José L.; Claver, José M.; de Walle, Rik Van

2013-12-01

The H.264/AVC video coding standard introduces some improved tools in order to increase compression efficiency. Moreover, the multi-view extension of H.264/AVC, called H.264/MVC, adopts many of them. Among the new features, variable block-size motion estimation is one which contributes to high coding efficiency. Furthermore, it defines a different prediction structure that includes hierarchical bidirectional pictures, outperforming traditional Group of Pictures patterns in both scenarios: single-view and multi-view. However, these video coding techniques have high computational complexity. Several techniques have been proposed in the literature over the last few years which are aimed at accelerating the inter prediction process, but there are no works focusing on bidirectional prediction or hierarchical prediction. In this article, with the emergence of many-core processors or accelerators, a step forward is taken towards an implementation of an H.264/AVC and H.264/MVC inter prediction algorithm on a graphics processing unit. The results show a negligible rate distortion drop with a time reduction of up to 98% for the complete H.264/AVC encoder.

Neuroanatomical and Cognitive Mediators of Age-Related Differences in Episodic Memory

PubMed Central

Head, Denise; Rodrigue, Karen M.; Kennedy, Kristen M.; Raz, Naftali

2009-01-01

Aging is associated with declines in episodic memory. In this study, the authors used a path analysis framework to explore the mediating role of differences in brain structure, executive functions, and processing speed in age-related differences in episodic memory. Measures of regional brain volume (prefrontal gray and white matter, caudate, hippocampus, visual cortex), executive functions (working memory, inhibitory control, task switching, temporal processing), processing speed, and episodic memory were obtained in a sample of young and older adults. As expected, age was linked to reduction in regional brain volumes and cognitive performance. Moreover, neural and cognitive factors completely mediated age differences in episodic memory. Whereas hippocampal shrinkage directly affected episodic memory, prefrontal volumetric reductions influenced episodic memory via limitations in working memory and inhibitory control. Age-related slowing predicted reduced efficiency in temporal processing, working memory, and inhibitory control. Lastly, poorer temporal processing directly affected episodic memory. No direct effects of age on episodic memory remained once these factors were taken into account. These analyses highlight the value of a multivariate approach with the understanding of complex relationships in cognitive and brain aging. PMID:18590361

Different personal propensities among scientists relate to deeper vs. broader knowledge contributions

PubMed Central

Bateman, Thomas S.; Hess, Andrew M.

2015-01-01

Scientific journal publications, and their contributions to knowledge, can be described by their depth (specialized, domain-specific knowledge extensions) and breadth (topical scope, including spanning multiple knowledge domains). Toward generating hypotheses about how scientists’ personal dispositions would uniquely predict deeper vs. broader contributions to the literature, we assumed that conducting broader studies is generally viewed as less attractive (e.g., riskier) than conducting deeper studies. Study 1 then supported our assumptions: the scientists surveyed considered a hypothetical broader study, compared with an otherwise-comparable deeper study, to be riskier, a less-significant opportunity, and of lower potential importance; they further reported being less likely to pursue it and, in a forced choice, most chose to work on the deeper study. In Study 2, questionnaire measures of medical researchers’ personal dispositions and 10 y of PubMed data indicating their publications’ topical coverage revealed how dispositions differentially predict depth vs. breadth. Competitiveness predicted depth positively, whereas conscientiousness predicted breadth negatively. Performance goal orientation predicted depth but not breadth, and learning goal orientation contrastingly predicted breadth but not depth. Openness to experience positively predicted both depth and breadth. Exploratory work behavior (the converse of applying and exploiting one’s current knowledge) predicted breadth positively and depth negatively. Thus, this research distinguishes depth and breadth of published knowledge contributions, and provides new insights into how scientists’ personal dispositions influence research processes and products. PMID:25733900

Different personal propensities among scientists relate to deeper vs. broader knowledge contributions.

PubMed

Bateman, Thomas S; Hess, Andrew M

2015-03-24

Scientific journal publications, and their contributions to knowledge, can be described by their depth (specialized, domain-specific knowledge extensions) and breadth (topical scope, including spanning multiple knowledge domains). Toward generating hypotheses about how scientists' personal dispositions would uniquely predict deeper vs. broader contributions to the literature, we assumed that conducting broader studies is generally viewed as less attractive (e.g., riskier) than conducting deeper studies. Study 1 then supported our assumptions: the scientists surveyed considered a hypothetical broader study, compared with an otherwise-comparable deeper study, to be riskier, a less-significant opportunity, and of lower potential importance; they further reported being less likely to pursue it and, in a forced choice, most chose to work on the deeper study. In Study 2, questionnaire measures of medical researchers' personal dispositions and 10 y of PubMed data indicating their publications' topical coverage revealed how dispositions differentially predict depth vs. breadth. Competitiveness predicted depth positively, whereas conscientiousness predicted breadth negatively. Performance goal orientation predicted depth but not breadth, and learning goal orientation contrastingly predicted breadth but not depth. Openness to experience positively predicted both depth and breadth. Exploratory work behavior (the converse of applying and exploiting one's current knowledge) predicted breadth positively and depth negatively. Thus, this research distinguishes depth and breadth of published knowledge contributions, and provides new insights into how scientists' personal dispositions influence research processes and products.

Further Development and Assessment of a Broadband Liner Optimization Process

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Jones, Michael G.; Sutliff, Daniel L.

2016-01-01

The utilization of advanced fan designs (including higher bypass ratios) and shorter engine nacelles has highlighted a need for increased fan noise reduction over a broader frequency range. Thus, improved broadband liner designs must account for these constraints and, where applicable, take advantage of advanced manufacturing techniques that have opened new possibilities for novel configurations. This work focuses on the use of an established broadband acoustic liner optimization process to design a variable-depth, multi-degree of freedom liner for a high speed fan. Specifically, in-duct attenuation predictions with a statistical source model are used to obtain optimum impedance spectra over the conditions of interest. The predicted optimum impedance information is then used with acoustic liner modeling tools to design a liner aimed at producing impedance spectra that most closely match the predicted optimum values. The multi-degree of freedom design is carried through design, fabrication, and testing. In-duct attenuation predictions compare well with measured data and the multi-degree of freedom liner is shown to outperform a more conventional liner over a range of flow conditions. These promising results provide further confidence in the design tool, as well as the enhancements made to the overall design process.

Cross-Modal Decoding of Neural Patterns Associated with Working Memory: Evidence for Attention-Based Accounts of Working Memory

PubMed Central

Majerus, Steve; Cowan, Nelson; Péters, Frédéric; Van Calster, Laurens; Phillips, Christophe; Schrouff, Jessica

2016-01-01

Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine-learning approach to determine more directly the extent to which common neural patterns characterize retention in verbal WM and visual WM. Verbal WM was assessed via a standard delayed probe recognition task for letter sequences of variable length. Visual WM was assessed via a visual array WM task involving the maintenance of variable amounts of visual information in the focus of attention. We trained a classifier to distinguish neural activation patterns associated with high- and low-visual WM load and tested the ability of this classifier to predict verbal WM load (high–low) from their associated neural activation patterns, and vice versa. We observed significant between-task prediction of load effects during WM maintenance, in posterior parietal and superior frontal regions of the dorsal attention network; in contrast, between-task prediction in sensory processing cortices was restricted to the encoding stage. Furthermore, between-task prediction of load effects was strongest in those participants presenting the highest capacity for the visual WM task. This study provides novel evidence for common, attention-based neural patterns supporting verbal and visual WM. PMID:25146374

Memory and Processing Limits in Decision-Making.

ERIC Educational Resources Information Center

Klapp, Stuart T.

According to the classical working memory perspective, tasks such as command and control decision-making should be performed less effectively if extraneous material must be retained in short-term memory. Only marginal support for this prediction was obtained for a simulation involving scheduling trucking and transportation missions, although…

Predicted effects of climate change on northern Gulf of Mexico hypoxia

EPA Science Inventory

U.S. state and federal partners are working cooperatively to develop nutrient management strategies to reduce hypoxia (O2 < 63 mmol m-3) in the northern Gulf of Mexico. Numerical models that represent eutrophication and hypoxia development processes have been an important too...

41 CFR 60-3.16 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... substantially different rate of selection in hiring, promotion, or other employment decision which works to the... showing that the selection procedure is predictive of or significantly correlated with important elements... process or the issuance of right to sue letters under title VII or under Executive Order 11246 where such...

Thermal analysis of friction riveting of dissimilar materials

NASA Astrophysics Data System (ADS)

Vignesh, N. J.; Hynes, N. Rajesh Jesudoss

2018-05-01

Friction riveting is a new technique which finds its applications in a variety of domains, where there is a need to join dissimilar materials for the sake of achieving weight reduction of the components produced especially in the fields of aerospace and automobile. In this present work, a numerical simulation on the heat transfer analysis has been done to predict the variation of temperature on the surface of the components being joined. Owing to the applications, Aluminum rivet is chosen for friction riveting on Poly Methyl Metha Acrylate base material. Abaqus explicit version 6.14 has been used to simulate the results of the process. Heat flux at the joint interface has been computed and thermal distribution at the work material is predicted.

Assessment of Process Capability: the case of Soft Drinks Processing Unit

NASA Astrophysics Data System (ADS)

Sri Yogi, Kottala

2018-03-01

The process capability studies have significant impact in investigating process variation which is important in achieving product quality characteristics. Its indices are to measure the inherent variability of a process and thus to improve the process performance radically. The main objective of this paper is to understand capability of the process being produced within specification of the soft drinks processing unit, a premier brands being marketed in India. A few selected critical parameters in soft drinks processing: concentration of gas volume, concentration of brix, torque of crock has been considered for this study. Assessed some relevant statistical parameters: short term capability, long term capability as a process capability indices perspective. For assessment we have used real time data of soft drinks bottling company which is located in state of Chhattisgarh, India. As our research output suggested reasons for variations in the process which is validated using ANOVA and also predicted Taguchi cost function, assessed also predicted waste monetarily this shall be used by organization for improving process parameters. This research work has substantially benefitted the organization in understanding the various variations of selected critical parameters for achieving zero rejection.

Cortical and Hippocampal Correlates of Deliberation during Model-Based Decisions for Rewards in Humans

PubMed Central

Bornstein, Aaron M.; Daw, Nathaniel D.

2013-01-01

How do we use our memories of the past to guide decisions we've never had to make before? Although extensive work describes how the brain learns to repeat rewarded actions, decisions can also be influenced by associations between stimuli or events not directly involving reward — such as when planning routes using a cognitive map or chess moves using predicted countermoves — and these sorts of associations are critical when deciding among novel options. This process is known as model-based decision making. While the learning of environmental relations that might support model-based decisions is well studied, and separately this sort of information has been inferred to impact decisions, there is little evidence concerning the full cycle by which such associations are acquired and drive choices. Of particular interest is whether decisions are directly supported by the same mnemonic systems characterized for relational learning more generally, or instead rely on other, specialized representations. Here, building on our previous work, which isolated dual representations underlying sequential predictive learning, we directly demonstrate that one such representation, encoded by the hippocampal memory system and adjacent cortical structures, supports goal-directed decisions. Using interleaved learning and decision tasks, we monitor predictive learning directly and also trace its influence on decisions for reward. We quantitatively compare the learning processes underlying multiple behavioral and fMRI observables using computational model fits. Across both tasks, a quantitatively consistent learning process explains reaction times, choices, and both expectation- and surprise-related neural activity. The same hippocampal and ventral stream regions engaged in anticipating stimuli during learning are also engaged in proportion to the difficulty of decisions. These results support a role for predictive associations learned by the hippocampal memory system to be recalled during choice formation. PMID:24339770

The Impeller Exit Flow Coefficient As a Performance Map Variable for Predicting Centrifugal Compressor Off-Design Operation Applied to a Supercritical CO 2 Working Fluid

DOE PAGES

Liese, Eric; Zitney, Stephen E.

2017-06-26

A multi-stage centrifugal compressor model is presented with emphasis on analyzing use of an exit flow coefficient vs. an inlet flow coefficient performance parameter to predict off-design conditions in the critical region of a supercritical carbon dioxide (CO 2) power cycle. A description of the performance parameters is given along with their implementation in a design model (number of stages, basic sizing, etc.) and a dynamic model (for use in transient studies). A design case is shown for two compressors, a bypass compressor and a main compressor, as defined in a process simulation of a 10 megawatt (MW) supercritical COmore » 2 recompression Brayton cycle. Simulation results are presented for a simple open cycle and closed cycle process with changes to the inlet temperature of the main compressor which operates near the CO 2 critical point. Results showed some difference in results using the exit vs. inlet flow coefficient correction, however, it was not significant for the range of conditions examined. Here, this paper also serves as a reference for future works, including a full process simulation of the 10 MW recompression Brayton cycle.« less

Interactive effects of aging parameters of AA6056

NASA Astrophysics Data System (ADS)

Dehghani, Kamran; Nekahi, Atiye

2012-10-01

The effect of thermomechanical treatment on the aging behavior of AA6056 aluminum alloy was modeled using response surface methodology (RSM). Two models were developed to predict the final yield stress (FYS) and elongation amounts as well as the optimum conditions of aging process. These were done based on the interactive effects of applied thermomechanical parameters. The optimum condition predicted by the model to attain the maximum strength was pre-aging at 80 °C for 15 h, followed by 70% cold work and subsequent final aging at 165 °C for 4 h, which resulted in the FYS of about 480 MPa. As for the elongation, the optimum condition was pre-aging at 80 °C for 15 h, followed by 30% cold work and final-aging at 165 °C for 4 h, which led to 21% elongation. To verify the suggested optimum conditions, the tests were carried out confirming the high accuracy (above 94%) of the RSM technique as well as the developed models. It is shown that the RSM can be used successfully to optimize the aging process, to determine the significance of aging parameters and to model the combination effect of process variables on the aging behavior of AA6056.

The Impeller Exit Flow Coefficient As a Performance Map Variable for Predicting Centrifugal Compressor Off-Design Operation Applied to a Supercritical CO 2 Working Fluid

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

Liese, Eric; Zitney, Stephen E.

A multi-stage centrifugal compressor model is presented with emphasis on analyzing use of an exit flow coefficient vs. an inlet flow coefficient performance parameter to predict off-design conditions in the critical region of a supercritical carbon dioxide (CO 2) power cycle. A description of the performance parameters is given along with their implementation in a design model (number of stages, basic sizing, etc.) and a dynamic model (for use in transient studies). A design case is shown for two compressors, a bypass compressor and a main compressor, as defined in a process simulation of a 10 megawatt (MW) supercritical COmore » 2 recompression Brayton cycle. Simulation results are presented for a simple open cycle and closed cycle process with changes to the inlet temperature of the main compressor which operates near the CO 2 critical point. Results showed some difference in results using the exit vs. inlet flow coefficient correction, however, it was not significant for the range of conditions examined. Here, this paper also serves as a reference for future works, including a full process simulation of the 10 MW recompression Brayton cycle.« less

Dissociable Roles of Different Types of Working Memory Load in Visual Detection

PubMed Central

Konstantinou, Nikos; Lavie, Nilli

2013-01-01

We contrasted the effects of different types of working memory (WM) load on detection. Considering the sensory-recruitment hypothesis of visual short-term memory (VSTM) within load theory (e.g., Lavie, 2010) led us to predict that VSTM load would reduce visual-representation capacity, thus leading to reduced detection sensitivity during maintenance, whereas load on WM cognitive control processes would reduce priority-based control, thus leading to enhanced detection sensitivity for a low-priority stimulus. During the retention interval of a WM task, participants performed a visual-search task while also asked to detect a masked stimulus in the periphery. Loading WM cognitive control processes (with the demand to maintain a random digit order [vs. fixed in conditions of low load]) led to enhanced detection sensitivity. In contrast, loading VSTM (with the demand to maintain the color and positions of six squares [vs. one in conditions of low load]) reduced detection sensitivity, an effect comparable with that found for manipulating perceptual load in the search task. The results confirmed our predictions and established a new functional dissociation between the roles of different types of WM load in the fundamental visual perception process of detection. PMID:23713796

Deficits in oculomotor performance in pediatric epilepsy

PubMed Central

Asato, Miya R.; Nawarawong, Natalie; Hermann, Bruce; Crumrine, Patricia; Luna, Beatriz

2010-01-01

Summary Purpose Given evidence of limitations in neuropsychological performance in epilepsy, we probed the integrity of components of cognition, including speed of processing, response inhibition, and spatial working memory supporting executive function in pediatric epilepsy patients and matched controls. Methods A total of 44 pairs of controls and medically treated pediatric epilepsy patients with no known brain pathology completed cognitive oculomotor tasks, computerized neuropsychological testing, and psychiatric assessment. Results Patients showed slower reaction time to initiate a saccadic response compared to controls but had intact saccade accuracy. Cognitively driven responses including response inhibition were impaired in the patient group. Patients had increased incidence of comorbid psychopathology but comorbidity did not predict worse functioning compared to patients with no ADHD. Epilepsy type and medication status were not predictive of outcome. More complex neuropsychological performance was impaired in tasks requiring visual memory and sequential processing which was correlated with inhibitory control and antisaccade accuracy. Discussion Pediatric epilepsy may be associated with vulnerabilities that specifically undermine speed of processing and response inhibition but not working memory and may underlie known neuropsychological performance limitations. This particular profile of abnormalities may be associated with seizure-mediated compromises in brain maturation early in development. PMID:21087246

Design and Optimization of an Austenitic TRIP Steel for Blast and Fragment Protection

NASA Astrophysics Data System (ADS)

Feinberg, Zechariah Daniel

In light of the pervasive nature of terrorist attacks, there is a pressing need for the design and optimization of next generation materials for blast and fragment protection applications. Sadhukhan used computational tools and a systems-based approach to design TRIP-120---a fully austenitic transformation-induced plasticity (TRIP) steel. Current work more completely evaluates the mechanical properties of the prototype, optimizes the processing for high performance in tension and shear, and builds models for more predictive power of the mechanical behavior and austenite stability. Under quasi-static and dynamic tension and shear, the design exhibits high strength and high uniform ductility as a result of a strain hardening effect that arises with martensitic transformation. Significantly more martensitic transformation occurred under quasi-static loading conditions (69% in tension and 52% in shear) compared to dynamic loading conditions (13% tension and 5% in shear). Nonetheless, significant transformation occurs at high-strain rates which increases strain hardening, delays the onset of necking instability, and increases total energy absorption under adiabatic conditions. Although TRIP-120 effectively utilizes a TRIP effect to delay necking instability, a common trend of abrupt failure with limited fracture ductility was observed in tension and shear at all strain rates. Further characterization of the structure of TRIP-120 showed that an undesired grain boundary cellular reaction (η phase formation) consumed the fine dispersion of the metastable gamma' phase and limited the fracture ductility. A warm working procedure was added to the processing of TRIP-120 in order to eliminate the grain boundary cellular reaction from the structure. By eliminating η formation at the grain boundaries, warm-worked TRIP-120 exhibits a drastic improvement in the mechanical properties in tension and shear. In quasi-static tension, the optimized warm-worked TRIP-120 with an Mssigma( u.t.) of -13°C has a yield strength of 180 ksi (1241 MPa), uniform ductility of 0.303, and fracture ductility of 0.95, which corresponds to a 48% increase in yield strength, a 43% increase in uniform ductility, and a 254% increase in fracture ductility relative to the designed processing of TRIP-120. The highest performing condition of warm-worked TRIP-120 in quasi-static shear with an Mssigma( sh) of 58°C exhibits a shear yield strength of 95.1 ksi (656 MPa), shear fracture strain of 144%, and energy dissipation density of 1099 MJ/m3, which corresponds to a shear yield strength increase of 61%, a shear fracture strain increase of 55%, and an energy dissipation density increase of 76%. A wide range of austenite stabilities can be achieved by altering the heat treatment times and temperatures, which significantly alters the mechanical properties. Although performance cannot be optimized for tension and shear simultaneously, different heat treatments can be applied to warm-worked TRIP-120 to achieve high performance in tension or shear. Parametric models calibrated with three-dimensional atom probe data played a crucial role in guiding the predictive process optimization of TRIP-120. Such models have been built to provide the predictive capability of inputting warm working and aging conditions and outputting the resulting structure, austenite stability, and mechanical properties. The predictive power of computational models has helped identify processing conditions that have improved the performance of TRIP-120 in tension and shear and can be applied to future designs that optimize for adiabatic conditions.

SVM-Based System for Prediction of Epileptic Seizures from iEEG Signal

PubMed Central

Cherkassky, Vladimir; Lee, Jieun; Veber, Brandon; Patterson, Edward E.; Brinkmann, Benjamin H.; Worrell, Gregory A.

2017-01-01

Objective This paper describes a data-analytic modeling approach for prediction of epileptic seizures from intracranial electroencephalogram (iEEG) recording of brain activity. Even though it is widely accepted that statistical characteristics of iEEG signal change prior to seizures, robust seizure prediction remains a challenging problem due to subject-specific nature of data-analytic modeling. Methods Our work emphasizes understanding of clinical considerations important for iEEG-based seizure prediction, and proper translation of these clinical considerations into data-analytic modeling assumptions. Several design choices during pre-processing and post-processing are considered and investigated for their effect on seizure prediction accuracy. Results Our empirical results show that the proposed SVM-based seizure prediction system can achieve robust prediction of preictal and interictal iEEG segments from dogs with epilepsy. The sensitivity is about 90–100%, and the false-positive rate is about 0–0.3 times per day. The results also suggest good prediction is subject-specific (dog or human), in agreement with earlier studies. Conclusion Good prediction performance is possible only if the training data contain sufficiently many seizure episodes, i.e., at least 5–7 seizures. Significance The proposed system uses subject-specific modeling and unbalanced training data. This system also utilizes three different time scales during training and testing stages. PMID:27362758

Remembering the time: a continuous clock.

PubMed

Lewis, Penelope A; Miall, R Chris

2006-09-01

The neural mechanisms for time measurement are currently a subject of much debate. This article argues that our brains can measure time using the same dorsolateral prefrontal cells that are known to be involved in working memory. Evidence for this is: (1) the dorsolateral prefrontal cortex is integral to both cognitive timing and working memory; (2) both behavioural processes are modulated by dopamine and disrupted by manipulation of dopaminergic projections to the dorsolateral prefrontal cortex; (3) the neurons in question ramp their activity in a temporally predictable way during both types of processing; and (4) this ramping activity is modulated by dopamine. The dual involvement of these prefrontal neurons in working memory and cognitive timing supports a view of the prefrontal cortex as a multipurpose processor recruited by a wide variety of tasks.

Modeling methods for merging computational and experimental aerodynamic pressure data

NASA Astrophysics Data System (ADS)

Haderlie, Jacob C.

This research describes a process to model surface pressure data sets as a function of wing geometry from computational and wind tunnel sources and then merge them into a single predicted value. The described merging process will enable engineers to integrate these data sets with the goal of utilizing the advantages of each data source while overcoming the limitations of both; this provides a single, combined data set to support analysis and design. The main challenge with this process is accurately representing each data source everywhere on the wing. Additionally, this effort demonstrates methods to model wind tunnel pressure data as a function of angle of attack as an initial step towards a merging process that uses both location on the wing and flow conditions (e.g., angle of attack, flow velocity or Reynold's number) as independent variables. This surrogate model of pressure as a function of angle of attack can be useful for engineers that need to predict the location of zero-order discontinuities, e.g., flow separation or normal shocks. Because, to the author's best knowledge, there is no published, well-established merging method for aerodynamic pressure data (here, the coefficient of pressure Cp), this work identifies promising modeling and merging methods, and then makes a critical comparison of these methods. Surrogate models represent the pressure data for both data sets. Cubic B-spline surrogate models represent the computational simulation results. Machine learning and multi-fidelity surrogate models represent the experimental data. This research compares three surrogates for the experimental data (sequential--a.k.a. online--Gaussian processes, batch Gaussian processes, and multi-fidelity additive corrector) on the merits of accuracy and computational cost. The Gaussian process (GP) methods employ cubic B-spline CFD surrogates as a model basis function to build a surrogate model of the WT data, and this usage of the CFD surrogate in building the WT data could serve as a "merging" because the resulting WT pressure prediction uses information from both sources. In the GP approach, this model basis function concept seems to place more "weight" on the Cp values from the wind tunnel (WT) because the GP surrogate uses the CFD to approximate the WT data values. Conversely, the computationally inexpensive additive corrector method uses the CFD B-spline surrogate to define the shape of the spanwise distribution of the Cp while minimizing prediction error at all spanwise locations for a given arc length position; this, too, combines information from both sources to make a prediction of the 2-D WT-based Cp distribution, but the additive corrector approach gives more weight to the CFD prediction than to the WT data. Three surrogate models of the experimental data as a function of angle of attack are also compared for accuracy and computational cost. These surrogates are a single Gaussian process model (a single "expert"), product of experts, and generalized product of experts. The merging approach provides a single pressure distribution that combines experimental and computational data. The batch Gaussian process method provides a relatively accurate surrogate that is computationally acceptable, and can receive wind tunnel data from port locations that are not necessarily parallel to a variable direction. On the other hand, the sequential Gaussian process and additive corrector methods must receive a sufficient number of data points aligned with one direction, e.g., from pressure port bands (tap rows) aligned with the freestream. The generalized product of experts best represents wind tunnel pressure as a function of angle of attack, but at higher computational cost than the single expert approach. The format of the application data from computational and experimental sources in this work precluded the merging process from including flow condition variables (e.g., angle of attack) in the independent variables, so the merging process is only conducted in the wing geometry variables of arc length and span. The merging process of Cp data allows a more "hands-off" approach to aircraft design and analysis, (i.e., not as many engineers needed to debate the Cp distribution shape) and generates Cp predictions at any location on the wing. However, the cost with these benefits are engineer time (learning how to build surrogates), computational time in constructing the surrogates, and surrogate accuracy (surrogates introduce error into data predictions). This dissertation effort used the Trap Wing / First AIAA CFD High-Lift Prediction Workshop as a relevant transonic wing with a multi-element high-lift system, and this work identified that the batch GP model for the WT data and the B-spline surrogate for the CFD might best be combined using expert belief weights to describe Cp as a function of location on the wing element surface. (Abstract shortened by ProQuest.).

Prediction of surface roughness and cutting force under MQL turning of AISI 4340 with nano fluid by using response surface methodology

NASA Astrophysics Data System (ADS)

Patole, Pralhad B.; Kulkarni, Vivek V.

2018-06-01

This paper presents an investigation into the minimum quantity lubrication mode with nano fluid during turning of alloy steel AISI 4340 work piece material with the objective of experimental model in order to predict surface roughness and cutting force and analyze effect of process parameters on machinability. Full factorial design matrix was used for experimental plan. According to design of experiment surface roughness and cutting force were measured. The relationship between the response variables and the process parameters is determined through the response surface methodology, using a quadratic regression model. Results show how much surface roughness is mainly influenced by feed rate and cutting speed. The depth of cut exhibits maximum influence on cutting force components as compared to the feed rate and cutting speed. The values predicted from the model and experimental values are very close to each other.

An approach to predict Sudden Cardiac Death (SCD) using time domain and bispectrum features from HRV signal.

PubMed

Houshyarifar, Vahid; Chehel Amirani, Mehdi

2016-08-12

In this paper we present a method to predict Sudden Cardiac Arrest (SCA) with higher order spectral (HOS) and linear (Time) features extracted from heart rate variability (HRV) signal. Predicting the occurrence of SCA is important in order to avoid the probability of Sudden Cardiac Death (SCD). This work is a challenge to predict five minutes before SCA onset. The method consists of four steps: pre-processing, feature extraction, feature reduction, and classification. In the first step, the QRS complexes are detected from the electrocardiogram (ECG) signal and then the HRV signal is extracted. In second step, bispectrum features of HRV signal and time-domain features are obtained. Six features are extracted from bispectrum and two features from time-domain. In the next step, these features are reduced to one feature by the linear discriminant analysis (LDA) technique. Finally, KNN and support vector machine-based classifiers are used to classify the HRV signals. We used two database named, MIT/BIH Sudden Cardiac Death (SCD) Database and Physiobank Normal Sinus Rhythm (NSR). In this work we achieved prediction of SCD occurrence for six minutes before the SCA with the accuracy over 91%.

Contextual predictability enhances reading performance in patients with schizophrenia.

PubMed

Fernández, Gerardo; Guinjoan, Salvador; Sapognikoff, Marcelo; Orozco, David; Agamennoni, Osvaldo

2016-07-30

In the present work we analyzed fixation duration in 40 healthy individuals and 18 patients with chronic, stable SZ during reading of regular sentences and proverbs. While they read, their eye movements were recorded. We used lineal mixed models to analyze fixation durations. The predictability of words N-1, N, and N+1 exerted a strong influence on controls and SZ patients. The influence of the predictabilities of preceding, current, and upcoming words on SZ was clearly reduced for proverbs in comparison to regular sentences. Both controls and SZ readers were able to use highly predictable fixated words for an easier reading. Our results suggest that SZ readers might compensate attentional and working memory deficiencies by using stored information of familiar texts for enhancing their reading performance. The predictabilities of words in proverbs serve as task-appropriate cues that are used by SZ readers. To the best of our knowledge, this is the first study using eyetracking for measuring how patients with SZ process well-defined words embedded in regular sentences and proverbs. Evaluation of the resulting changes in fixation durations might provide a useful tool for understanding how SZ patients could enhance their reading performance. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Modelling morphology evolution during solidification of IPP in processing conditions

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

Pantani, R., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it; De Santis, F., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it; Speranza, V., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it

During polymer processing, crystallization takes place during or soon after flow. In most of cases, the flow field dramatically influences both the crystallization kinetics and the crystal morphology. On their turn, crystallinity and morphology affect product properties. Consequently, in the last decade, researchers tried to identify the main parameters determining crystallinity and morphology evolution during solidification In processing conditions. In this work, we present an approach to model flow-induced crystallization with the aim of predicting the morphology after processing. The approach is based on: interpretation of the FIC as the effect of molecular stretch on the thermodynamic crystallization temperature; modelingmore » the molecular stretch evolution by means of a model simple and easy to be implemented in polymer processing simulation codes; identification of the effect of flow on nucleation density and spherulites growth rate by means of simple experiments; determination of the condition under which fibers form instead of spherulites. Model predictions reproduce most of the features of final morphology observed in the samples after solidification.« less

Multimethod prediction of physical parent-child aggression risk in expectant mothers and fathers with Social Information Processing theory.

PubMed

Rodriguez, Christina M; Smith, Tamika L; Silvia, Paul J

2016-01-01

The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants' own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Algorithms in the historical emergence of word senses.

PubMed

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.

NASA Earth Science Research Results for Improved Regional Crop Yield Prediction

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

Model-Based Fatigue Prognosis of Fiber-Reinforced Laminates Exhibiting Concurrent Damage Mechanisms

NASA Technical Reports Server (NTRS)

Corbetta, M.; Sbarufatti, C.; Saxena, A.; Giglio, M.; Goebel, K.

2016-01-01

Prognostics of large composite structures is a topic of increasing interest in the field of structural health monitoring for aerospace, civil, and mechanical systems. Along with recent advancements in real-time structural health data acquisition and processing for damage detection and characterization, model-based stochastic methods for life prediction are showing promising results in the literature. Among various model-based approaches, particle-filtering algorithms are particularly capable in coping with uncertainties associated with the process. These include uncertainties about information on the damage extent and the inherent uncertainties of the damage propagation process. Some efforts have shown successful applications of particle filtering-based frameworks for predicting the matrix crack evolution and structural stiffness degradation caused by repetitive fatigue loads. Effects of other damage modes such as delamination, however, are not incorporated in these works. It is well established that delamination and matrix cracks not only co-exist in most laminate structures during the fatigue degradation process but also affect each other's progression. Furthermore, delamination significantly alters the stress-state in the laminates and accelerates the material degradation leading to catastrophic failure. Therefore, the work presented herein proposes a particle filtering-based framework for predicting a structure's remaining useful life with consideration of multiple co-existing damage-mechanisms. The framework uses an energy-based model from the composite modeling literature. The multiple damage-mode model has been shown to suitably estimate the energy release rate of cross-ply laminates as affected by matrix cracks and delamination modes. The model is also able to estimate the reduction in stiffness of the damaged laminate. This information is then used in the algorithms for life prediction capabilities. First, a brief summary of the energy-based damage model is provided. Then, the paper describes how the model is embedded within the prognostic framework and how the prognostics performance is assessed using observations from run-to-failure experiments

Calculation of precise firing statistics in a neural network model

NASA Astrophysics Data System (ADS)

Cho, Myoung Won

2017-08-01

A precise prediction of neural firing dynamics is requisite to understand the function of and the learning process in a biological neural network which works depending on exact spike timings. Basically, the prediction of firing statistics is a delicate manybody problem because the firing probability of a neuron at a time is determined by the summation over all effects from past firing states. A neural network model with the Feynman path integral formulation is recently introduced. In this paper, we present several methods to calculate firing statistics in the model. We apply the methods to some cases and compare the theoretical predictions with simulation results.

Vocabulary learning in primary school children: working memory and long-term memory components.

PubMed

Morra, Sergio; Camba, Roberta

2009-10-01

The goal of this study was to investigate which working memory and long-term memory components predict vocabulary learning. We used a nonword learning paradigm in which 8- to 10-year-olds learned picture-nonword pairs. The nonwords varied in length (two vs. four syllables) and phonology (native sounding vs. including one Russian phoneme). Short, phonologically native nonwords were learned best, whereas learning long nonwords leveled off after a few presentation cycles. Linear structural equation analyses showed an influence of three constructs-phonological sensitivity, vocabulary knowledge, and central attentional resources (M capacity)-on nonword learning, but the extent of their contributions depended on specific characteristics of the nonwords to be learned. Phonological sensitivity predicted learning of all nonword types except short native nonwords, vocabulary predicted learning of only short native nonwords, and M capacity predicted learning of short nonwords but not long nonwords. The discussion considers three learning processes-effortful activation of phonological representations, lexical mediation, and passive associative learning-that use different cognitive resources and could be involved in learning different nonword types.

The role of working memory in inferential sentence comprehension.

PubMed

Pérez, Ana Isabel; Paolieri, Daniela; Macizo, Pedro; Bajo, Teresa

2014-08-01

Existing literature on inference making is large and varied. Trabasso and Magliano (Discourse Process 21(3):255-287, 1996) proposed the existence of three types of inferences: explicative, associative and predictive. In addition, the authors suggested that these inferences were related to working memory (WM). In the present experiment, we investigated whether WM capacity plays a role in our ability to answer comprehension sentences that require text information based on these types of inferences. Participants with high and low WM span read two narratives with four paragraphs each. After each paragraph was read, they were presented with four true/false comprehension sentences. One required verbatim information and the other three implied explicative, associative and predictive inferential information. Results demonstrated that only the explicative and predictive comprehension sentences required WM: participants with high verbal WM were more accurate in giving explanations and also faster at making predictions relative to participants with low verbal WM span; in contrast, no WM differences were found in the associative comprehension sentences. These results are interpreted in terms of the causal nature underlying these types of inferences.

Predictive Simulation of Process Windows for Powder Bed Fusion Additive Manufacturing: Influence of the Powder Bulk Density.

PubMed

Rausch, Alexander M; Küng, Vera E; Pobel, Christoph; Markl, Matthias; Körner, Carolin

2017-09-22

The resulting properties of parts fabricated by powder bed fusion additive manufacturing processes are determined by their porosity, local composition, and microstructure. The objective of this work is to examine the influence of the stochastic powder bed on the process window for dense parts by means of numerical simulation. The investigations demonstrate the unique capability of simulating macroscopic domains in the range of millimeters with a mesoscopic approach, which resolves the powder bed and the hydrodynamics of the melt pool. A simulated process window reveals the influence of the stochastic powder layer. The numerical results are verified with an experimental process window for selective electron beam-melted Ti-6Al-4V. Furthermore, the influence of the powder bulk density is investigated numerically. The simulations predict an increase in porosity and surface roughness for samples produced with lower powder bulk densities. Due to its higher probability for unfavorable powder arrangements, the process stability is also decreased. This shrinks the actual parameter range in a process window for producing dense parts.

Predictive Simulation of Process Windows for Powder Bed Fusion Additive Manufacturing: Influence of the Powder Bulk Density

PubMed Central

Rausch, Alexander M.; Küng, Vera E.; Pobel, Christoph; Körner, Carolin

2017-01-01

The resulting properties of parts fabricated by powder bed fusion additive manufacturing processes are determined by their porosity, local composition, and microstructure. The objective of this work is to examine the influence of the stochastic powder bed on the process window for dense parts by means of numerical simulation. The investigations demonstrate the unique capability of simulating macroscopic domains in the range of millimeters with a mesoscopic approach, which resolves the powder bed and the hydrodynamics of the melt pool. A simulated process window reveals the influence of the stochastic powder layer. The numerical results are verified with an experimental process window for selective electron beam-melted Ti-6Al-4V. Furthermore, the influence of the powder bulk density is investigated numerically. The simulations predict an increase in porosity and surface roughness for samples produced with lower powder bulk densities. Due to its higher probability for unfavorable powder arrangements, the process stability is also decreased. This shrinks the actual parameter range in a process window for producing dense parts. PMID:28937633

Systematic Characterization and Prediction of Human Hypertension Genes.

PubMed

Li, Yan-Hui; Zhang, Gai-Gai; Wang, Nanping

2017-02-01

Hypertension is a major cardiovascular risk factor and accounts for a large part of cardiovascular mortality. In this work, we analyzed the properties of hypertension genes and found that when compared with genes not yet known to be involved in hypertension regulation, known hypertension genes display distinguishing features: (1) hypertension genes tend to be located at network center; (2) hypertension genes tend to interact with each other; and (3) hypertension genes tend to enrich in certain biological processes and show certain phenotypes. Based on these features, we developed a machine-learning algorithm to predict new hypertension genes. One hundred and seventy-seven candidates were predicted with a posterior probability >0.9. Evidence supporting 17 of the predictions has been found. © 2016 American Heart Association, Inc.

Improving streamflow prediction using remotely-sensed soil moisture and snow depth

USDA-ARS?s Scientific Manuscript database

The monitoring of both cold and warm season hydrologic processes in headwater watersheds is critical for accurate water resource monitoring in many alpine regions. This work presents a new method that explores the simultaneous use of remotely sensed surface soil moisture (SM) and snow depth (SD) ret...

The Information Society: Fact or Charming Mythology?

ERIC Educational Resources Information Center

Ledingham, John A.

Today the majority of the United States work force is employed in the production, processing, and dissemination of information. However, the situation with regard to videotex, the medium that served as the basis for predicting an information society, is far from settled. The statistics concerning videotex are impressive, the technology…

No Negative Priming without Cognitive Control

ERIC Educational Resources Information Center

de Fockert, Jan W.; Mizon, Guy A.; D'Ubaldo, Mariangela

2010-01-01

There is evidence that the efficiency of selective attention depends on the availability of cognitive control mechanisms as distractor processing has been found to increase with high load on working memory or dual task coordination (Lavie, Hirst, de Fockert, & Viding, 2004). We tested the prediction that cognitive control load would also…

Reclamation of mined lands in the western coal region

USGS Publications Warehouse

Narten, Perry F.; Litner, S.F.; Allingham, J.W.; Foster, Lee; Larsen, D.M.; McWreath, H.C.

1983-01-01

In 1978, a group of scientists from several Federal agencies examined reclamation work at 22 coal mines in seven western States. The results of these examinations were not used to derive quantitative predictions of the outcome of reclamation work but rather to determine the general requirements for revegetation success. Locally, reclamation efforts are affected by climate, especially precipitation; the landform of the restored surface; the nature of the overburden material; the nature of the surface soil; and the natural ecological system. The goals of reclamation efforts are now broader than ever. Regulations call not only for reducing the steepness of the final surface and establishing a cover of mostly perennial native vegetation, but for restoring the land for specific land uses, achieving diversity both in types of plants and in number of species, and reintroduction of biological and ecological processes. If specific sites are monitored over a long enough period of time, quantitative predictions of success for individual mines may be possible, and such predictions can be included in environmental impact statements to help in the decision-making process. The results of this study indicate that current reclamation objectives can be met when the reclamation effort is designed on the basis of site-specific needs and when existing technology is used.

Predictors of Hearing-Aid Outcomes

PubMed Central

Johannesen, Peter T.; Pérez-González, Patricia; Blanco, José L.; Kalluri, Sridhar; Edwards, Brent

2017-01-01

Over 360 million people worldwide suffer from disabling hearing loss. Most of them can be treated with hearing aids. Unfortunately, performance with hearing aids and the benefit obtained from using them vary widely across users. Here, we investigate the reasons for such variability. Sixty-eight hearing-aid users or candidates were fitted bilaterally with nonlinear hearing aids using standard procedures. Treatment outcome was assessed by measuring aided speech intelligibility in a time-reversed two-talker background and self-reported improvement in hearing ability. Statistical predictive models of these outcomes were obtained using linear combinations of 19 predictors, including demographic and audiological data, indicators of cochlear mechanical dysfunction and auditory temporal processing skills, hearing-aid settings, working memory capacity, and pretreatment self-perceived hearing ability. Aided intelligibility tended to be better for younger hearing-aid users with good unaided intelligibility in quiet and with good temporal processing abilities. Intelligibility tended to improve by increasing amplification for low-intensity sounds and by using more linear amplification for high-intensity sounds. Self-reported improvement in hearing ability was hard to predict but tended to be smaller for users with better working memory capacity. Indicators of cochlear mechanical dysfunction, alone or in combination with hearing settings, did not affect outcome predictions. The results may be useful for improving hearing aids and setting patients’ expectations. PMID:28929903

Profiles of verbal working memory growth predict speech and language development in children with cochlear implants.

PubMed

Kronenberger, William G; Pisoni, David B; Harris, Michael S; Hoen, Helena M; Xu, Huiping; Miyamoto, Richard T

2013-06-01

Verbal short-term memory (STM) and working memory (WM) skills predict speech and language outcomes in children with cochlear implants (CIs) even after conventional demographic, device, and medical factors are taken into account. However, prior research has focused on single end point outcomes as opposed to the longitudinal process of development of verbal STM/WM and speech-language skills. In this study, the authors investigated relations between profiles of verbal STM/WM development and speech-language development over time. Profiles of verbal STM/WM development were identified through the use of group-based trajectory analysis of repeated digit span measures over at least a 2-year time period in a sample of 66 children (ages 6-16 years) with CIs. Subjects also completed repeated assessments of speech and language skills during the same time period. Clusters representing different patterns of development of verbal STM (digit span forward scores) were related to the growth rate of vocabulary and language comprehension skills over time. Clusters representing different patterns of development of verbal WM (digit span backward scores) were related to the growth rate of vocabulary and spoken word recognition skills over time. Different patterns of development of verbal STM/WM capacity predict the dynamic process of development of speech and language skills in this clinical population.

Optimization of Biomathematical Model Predictions for Cognitive Performance Impairment in Individuals: Accounting for Unknown Traits and Uncertain States in Homeostatic and Circadian Processes

PubMed Central

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

Mediating toxic emotions in the workplace--the impact of abusive supervision.

PubMed

Chu, Li-Chuan

2014-11-01

This study explores whether abusive supervision can effectively predict employees' counterproductive work behaviour (CWB) and organisational citizenship behaviour (OCB) and the role of toxic emotions at work as a potential mediator of these relationships in nursing settings. Workplace bullying is widespread in nursing. Despite the growing literature on abusive supervision and employees' counterproductive work behaviour and organisational citizenship behaviour, few studies have examined the relationships between abusive supervision and these work behaviours from the viewpoint of the victimed employee's emotion process. This study adopted a two-stage survey of 212 nurses, all of whom were employed by hospitals in Taiwan. Hypotheses were tested through the use of hierarchical multiple regression. The results showed that abusive supervision was positively associated with toxic emotions. Moreover, toxic emotions could effectively predict nurses' counterproductive work behaviour and organisational citizenship behaviour. Finally, it was found that toxic emotions partially mediated the negative effects of abusive supervision on both work behaviours. Toxic emotions at work are a critical mediating variable between abusive supervision and both counterproductive work behaviour and organisational citizenship behaviour. Hospital administrators can implement policies designed to manage events effectively that can spark toxic emotions in their employees. Work empowerment may be an effective way to reduce counterproductive work behaviour and to enhance organisational citizenship behaviour among nurses when supervisors do not promote a healthy work environment for them. © 2013 John Wiley & Sons Ltd.

Thermal Spray Maps: Material Genomics of Processing Technologies

NASA Astrophysics Data System (ADS)

Ang, Andrew Siao Ming; Sanpo, Noppakun; Sesso, Mitchell L.; Kim, Sun Yung; Berndt, Christopher C.

2013-10-01

There is currently no method whereby material properties of thermal spray coatings may be predicted from fundamental processing inputs such as temperature-velocity correlations. The first step in such an important understanding would involve establishing a foundation that consolidates the thermal spray literature so that known relationships could be documented and any trends identified. This paper presents a method to classify and reorder thermal spray data so that relationships and correlations between competing processes and materials can be identified. Extensive data mining of published experimental work was performed to create thermal spray property-performance maps, known as "TS maps" in this work. Six TS maps will be presented. The maps are based on coating characteristics of major importance; i.e., porosity, microhardness, adhesion strength, and the elastic modulus of thermal spray coatings.

Processing-microstructure models for short- and long-fiber thermoplastic composites

NASA Astrophysics Data System (ADS)

Phelps, Jay H.

The research for this thesis has explored the important microstructural variables for injection-molded thermoplastic composites with discontinuous fiber reinforcement. Two variables, the distributions of fiber orientation and fiber length after processing, have proven to be not only important for correct material property prediction but also difficult to predict using currently available modeling and simulation techniques. In this work, we develop new models for the prediction of these two microstructural variables. Previously, the Folgar-Tucker model has been widely used to predict fiber orientation in injection molded SFT composites. This model accounts for the effects of both hydrodynamics and fiber-fiber interactions in order to give a prediction for a tensorial measure of fiber orientation. However, when applied to at least some classes of LFTs, this model does not match all components of experimental fiber orientation tensor data. In order to address this shortcoming of the model, we hypothesize that Folgar and Tucker's phenomenological treatment of the effects of fiber-fiber interactions with an isotropic rotary diffusion contribution to the rate of change of orientation is insufficient for materials with longer fibers. Instead, this work develops a fiber orientation model that incorporates anisotropic rotary diffusion (ARD). From kinetic theory we derive a general family of evolution equations for the second-order orientation tensor, correcting errors in earlier treatments, and identify a specific equation that is useful for predicting orientation in LFTs. The amount of diffusivity in this model used to approximate the effect of fiber-fiber interactions in each direction is assumed to depend on a second-order space tensor, which is taken to be a function of the orientation state and the rate of deformation. Also, concentrated fiber suspensions align more slowly with respect to strain than the Folgar-Tucker model predicts. Here, we borrow the technique of Wang et al. (2008) to incorporate this behavior in an objective fashion in this new model. Model parameters are selected by matching the experimental steady-state orientation in simple shear flow, and by requiring stable steady states and physically realizable solutions. Utilizing two separate techniques, we identify model parameters for three different materials. We then show that once a set of parameters that meets all previously established criteria has been identified, the differences in model behavior are negligible within that set of parameters. The final model with the proper parameter set is suitable for use in mold filling and other flow simulations, and does give improved predictions of fiber orientation for injection molded LFTs. Although significant fiber length degradation in LFTs has been observed both in literature and in this work, there are no quantitative fiber breakage models to predict either fiber length distributions or average fiber length measures. This work reviews the suspected causes of fiber breakage during the processing of discontinuously-reinforced thermoplastics, specifically LFTs, and introduces a phenomenological fiber breakage model based on the buckling force in a hydrodynamically loaded fiber. This breakage model is incorporated into a conservation equation for total fiber length, and a phenomenological model for the evolution of the fiber length distribution is developed. From this model, we also develop separate, approximate models for the evolution of both the number-average and weight-average fiber length measures. By applying these models to both a simple numerical example and a more complex mold-filling simulation, a qualitative agreement between experiment and prediction is observed. Although these results are promising, the breakage models have only been applied to the mold cavity in injection molding simulation. Both a literature review and our experimental data strongly suggest that the majority of fiber length degradation occurs in the earlier stages of injection molding, in the screw nozzle, runners, and gate. A better understanding of the melting and flow conditions upstream of the mold cavity, the simulation of which is beyond the scope of this work, is needed before these breakage models can be properly applied to the entire injection molding process. (Abstract shortened by UMI.)

Variations in working memory capacity predict individual differences in general learning abilities among genetically diverse mice.

PubMed

Kolata, Stefan; Light, Kenneth; Townsend, David A; Hale, Gregory; Grossman, Henya C; Matzel, Louis D

2005-11-01

Up to 50% of an individuals' performance across a wide variety of distinct cognitive tests can be accounted for by a single factor (i.e., "general intelligence"). Despite its ubiquity, the processes or mechanisms regulating this factor are a matter of considerable debate. Although it has been hypothesized that working memory may impact cognitive performance across various domains, tests have been inconclusive due to the difficulty in isolating working memory from its overlapping operations, such as verbal ability. We address this problem using genetically diverse mice, which exhibit a trait analogous to general intelligence. The general cognitive abilities of CD-1 mice were found to covary with individuals' working memory capacity, but not with variations in long-term retention. These results provide evidence that independent of verbal abilities, variations in working memory are associated with general cognitive abilities, and further, suggest a conservation across species of mechanisms and/or processes that regulate cognitive abilities.

Variation in Dopamine D2 and Serotonin 5-HT2A Receptor Genes is Associated with Working Memory Processing and Response to Treatment with Antipsychotics

PubMed Central

Blasi, Giuseppe; Selvaggi, Pierluigi; Fazio, Leonardo; Antonucci, Linda Antonella; Taurisano, Paolo; Masellis, Rita; Romano, Raffaella; Mancini, Marina; Zhang, Fengyu; Caforio, Grazia; Popolizio, Teresa; Apud, Jose; Weinberger, Daniel R; Bertolino, Alessandro

2015-01-01

Dopamine D2 and serotonin 5-HT2A receptors contribute to modulate prefrontal cortical physiology and response to treatment with antipsychotics in schizophrenia. Similarly, functional variation in the genes encoding these receptors is also associated with these phenotypes. In particular, the DRD2 rs1076560 T allele predicts a lower ratio of expression of D2 short/long isoforms, suboptimal working memory processing, and better response to antipsychotic treatment compared with the G allele. Furthermore, the HTR2A T allele is associated with lower 5-HT2A expression, impaired working memory processing, and poorer response to antipsychotics compared with the C allele. Here, we investigated in healthy subjects whether these functional polymorphisms have a combined effect on prefrontal cortical physiology and related cognitive behavior linked to schizophrenia as well as on response to treatment with second-generation antipsychotics in patients with schizophrenia. In a total sample of 620 healthy subjects, we found that subjects with the rs1076560 T and rs6314 T alleles have greater fMRI prefrontal activity during working memory. Similar results were obtained within the attentional domain. Also, the concomitant presence of the rs1076560 T/rs6314 T alleles also predicted lower behavioral accuracy during working memory. Moreover, we found that rs1076560 T carrier/rs6314 CC individuals had better responses to antipsychotic treatment in two independent samples of patients with schizophrenia (n=63 and n=54, respectively), consistent with the previously reported separate effects of these genotypes. These results indicate that DRD2 and HTR2A genetic variants together modulate physiological prefrontal efficiency during working memory and also modulate the response to antipsychotics. Therefore, these results suggest that further exploration is needed to better understand the clinical consequences of these genotype–phenotype relationships. PMID:25563748

Variation in Dopamine D2 and Serotonin 5-HT2A Receptor Genes is Associated with Working Memory Processing and Response to Treatment with Antipsychotics.

PubMed

Blasi, Giuseppe; Selvaggi, Pierluigi; Fazio, Leonardo; Antonucci, Linda Antonella; Taurisano, Paolo; Masellis, Rita; Romano, Raffaella; Mancini, Marina; Zhang, Fengyu; Caforio, Grazia; Popolizio, Teresa; Apud, Jose; Weinberger, Daniel R; Bertolino, Alessandro

2015-06-01

Dopamine D2 and serotonin 5-HT2A receptors contribute to modulate prefrontal cortical physiology and response to treatment with antipsychotics in schizophrenia. Similarly, functional variation in the genes encoding these receptors is also associated with these phenotypes. In particular, the DRD2 rs1076560 T allele predicts a lower ratio of expression of D2 short/long isoforms, suboptimal working memory processing, and better response to antipsychotic treatment compared with the G allele. Furthermore, the HTR2A T allele is associated with lower 5-HT2A expression, impaired working memory processing, and poorer response to antipsychotics compared with the C allele. Here, we investigated in healthy subjects whether these functional polymorphisms have a combined effect on prefrontal cortical physiology and related cognitive behavior linked to schizophrenia as well as on response to treatment with second-generation antipsychotics in patients with schizophrenia. In a total sample of 620 healthy subjects, we found that subjects with the rs1076560 T and rs6314 T alleles have greater fMRI prefrontal activity during working memory. Similar results were obtained within the attentional domain. Also, the concomitant presence of the rs1076560 T/rs6314 T alleles also predicted lower behavioral accuracy during working memory. Moreover, we found that rs1076560 T carrier/rs6314 CC individuals had better responses to antipsychotic treatment in two independent samples of patients with schizophrenia (n=63 and n=54, respectively), consistent with the previously reported separate effects of these genotypes. These results indicate that DRD2 and HTR2A genetic variants together modulate physiological prefrontal efficiency during working memory and also modulate the response to antipsychotics. Therefore, these results suggest that further exploration is needed to better understand the clinical consequences of these genotype-phenotype relationships.

Burnout among psychosocial oncologists: an application and extension of the effort–reward imbalance model

PubMed Central

Rasmussen, Victoria; Turnell, Adrienne; Butow, Phyllis; Juraskova, Ilona; Kirsten, Laura; Wiener, Lori; Patenaude, Andrea; Hoekstra-Weebers, Josette; Grassi, Luigi

2016-01-01

Objectives Burnout is a significant problem among healthcare professionals working within the oncology setting. This study aimed to investigate predictors of emotional exhaustion (EE) and depersonalisation (DP) in psychosocial oncologists, through the application of the effort–reward imbalance (ERI) model with an additional focus on the role of meaningful work in the burnout process. Methods Psychosocial oncology clinicians (n = 417) in direct patient contact who were proficient in English were recruited from 10 international psychosocial oncology societies. Participants completed an online questionnaire, which included measures of demographic and work characteristics, EE and DP subscales of the Maslach Burnout Inventory-Human Services Survey, the Short Version ERI Questionnaire and the Work and Meaning Inventory. Results Higher effort and lower reward were both significantly associated with greater EE, although not DP. The interaction of higher effort and lower reward did not predict greater EE or DP. Overcommitment predicted both EE and DP but did not moderate the impact of effort and reward on burnout. Overall, the ERI model accounted for 33% of the variance in EE. Meaningful work significantly predicted both EE and DP but accounted for only 2% more of the variance in EE above and beyond the ERI model. Conclusions The ERI was only partially supported as a useful framework for investigating burnout in psychosocial oncology professionals. Meaningful work may be a viable extension of the ERI model. Burnout among health professionals may be reduced by interventions aimed at increasing self-efficacy and changes to the supportive work environment. PMID:26239424

Natural selection and the predictability of evolution in Timema stick insects.

PubMed

Nosil, Patrik; Villoutreix, Romain; de Carvalho, Clarissa F; Farkas, Timothy E; Soria-Carrasco, Víctor; Feder, Jeffrey L; Crespi, Bernard J; Gompert, Zach

2018-02-16

Predicting evolution remains difficult. We studied the evolution of cryptic body coloration and pattern in a stick insect using 25 years of field data, experiments, and genomics. We found that evolution is more difficult to predict when it involves a balance between multiple selective factors and uncertainty in environmental conditions than when it involves feedback loops that cause consistent back-and-forth fluctuations. Specifically, changes in color-morph frequencies are modestly predictable through time ( r 2 = 0.14) and driven by complex selective regimes and yearly fluctuations in climate. In contrast, temporal changes in pattern-morph frequencies are highly predictable due to negative frequency-dependent selection ( r 2 = 0.86). For both traits, however, natural selection drives evolution around a dynamic equilibrium, providing some predictability to the process. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Revisiting the Holy Grail: using plant functional traits to understand ecological processes.

PubMed

Funk, Jennifer L; Larson, Julie E; Ames, Gregory M; Butterfield, Bradley J; Cavender-Bares, Jeannine; Firn, Jennifer; Laughlin, Daniel C; Sutton-Grier, Ariana E; Williams, Laura; Wright, Justin

2017-05-01

One of ecology's grand challenges is developing general rules to explain and predict highly complex systems. Understanding and predicting ecological processes from species' traits has been considered a 'Holy Grail' in ecology. Plant functional traits are increasingly being used to develop mechanistic models that can predict how ecological communities will respond to abiotic and biotic perturbations and how species will affect ecosystem function and services in a rapidly changing world; however, significant challenges remain. In this review, we highlight recent work and outstanding questions in three areas: (i) selecting relevant traits; (ii) describing intraspecific trait variation and incorporating this variation into models; and (iii) scaling trait data to community- and ecosystem-level processes. Over the past decade, there have been significant advances in the characterization of plant strategies based on traits and trait relationships, and the integration of traits into multivariate indices and models of community and ecosystem function. However, the utility of trait-based approaches in ecology will benefit from efforts that demonstrate how these traits and indices influence organismal, community, and ecosystem processes across vegetation types, which may be achieved through meta-analysis and enhancement of trait databases. Additionally, intraspecific trait variation and species interactions need to be incorporated into predictive models using tools such as Bayesian hierarchical modelling. Finally, existing models linking traits to community and ecosystem processes need to be empirically tested for their applicability to be realized. © 2016 Cambridge Philosophical Society.

A Binaural Grouping Model for Predicting Speech Intelligibility in Multitalker Environments

PubMed Central

Colburn, H. Steven

2016-01-01

Spatially separating speech maskers from target speech often leads to a large intelligibility improvement. Modeling this phenomenon has long been of interest to binaural-hearing researchers for uncovering brain mechanisms and for improving signal-processing algorithms in hearing-assistive devices. Much of the previous binaural modeling work focused on the unmasking enabled by binaural cues at the periphery, and little quantitative modeling has been directed toward the grouping or source-separation benefits of binaural processing. In this article, we propose a binaural model that focuses on grouping, specifically on the selection of time-frequency units that are dominated by signals from the direction of the target. The proposed model uses Equalization-Cancellation (EC) processing with a binary decision rule to estimate a time-frequency binary mask. EC processing is carried out to cancel the target signal and the energy change between the EC input and output is used as a feature that reflects target dominance in each time-frequency unit. The processing in the proposed model requires little computational resources and is straightforward to implement. In combination with the Coherence-based Speech Intelligibility Index, the model is applied to predict the speech intelligibility data measured by Marrone et al. The predicted speech reception threshold matches the pattern of the measured data well, even though the predicted intelligibility improvements relative to the colocated condition are larger than some of the measured data, which may reflect the lack of internal noise in this initial version of the model. PMID:27698261

A Binaural Grouping Model for Predicting Speech Intelligibility in Multitalker Environments.

PubMed

Mi, Jing; Colburn, H Steven

2016-10-03

Spatially separating speech maskers from target speech often leads to a large intelligibility improvement. Modeling this phenomenon has long been of interest to binaural-hearing researchers for uncovering brain mechanisms and for improving signal-processing algorithms in hearing-assistive devices. Much of the previous binaural modeling work focused on the unmasking enabled by binaural cues at the periphery, and little quantitative modeling has been directed toward the grouping or source-separation benefits of binaural processing. In this article, we propose a binaural model that focuses on grouping, specifically on the selection of time-frequency units that are dominated by signals from the direction of the target. The proposed model uses Equalization-Cancellation (EC) processing with a binary decision rule to estimate a time-frequency binary mask. EC processing is carried out to cancel the target signal and the energy change between the EC input and output is used as a feature that reflects target dominance in each time-frequency unit. The processing in the proposed model requires little computational resources and is straightforward to implement. In combination with the Coherence-based Speech Intelligibility Index, the model is applied to predict the speech intelligibility data measured by Marrone et al. The predicted speech reception threshold matches the pattern of the measured data well, even though the predicted intelligibility improvements relative to the colocated condition are larger than some of the measured data, which may reflect the lack of internal noise in this initial version of the model. © The Author(s) 2016.

1/f neural noise and electrophysiological indices of contextual prediction in aging.

PubMed

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.

Improved Processes to Remove Naphthenic Acids

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

Aihua Zhang; Qisheng Ma; Kangshi Wang

2005-12-09

In the past three years, we followed the work plan as we suggested in the proposal and made every efforts to fulfill the project objectives. Based on our large amount of creative and productive work, including both of experimental and theoretic aspects, we received important technical breakthrough on naphthenic acid removal process and obtained deep insight on catalytic decarboxylation chemistry. In detail, we established an integrated methodology to serve for all of the experimental and theoretical work. Our experimental investigation results in discovery of four type effective catalysts to the reaction of decarboxylation of model carboxylic acid compounds. The adsorptionmore » experiment revealed the effectiveness of several solid materials to naphthenic acid adsorption and acidity reduction of crude oil, which can be either natural minerals or synthesized materials. The test with crude oil also received promising results, which can be potentially developed into a practical process for oil industry. The theoretical work predicted several possible catalytic decarboxylation mechanisms that would govern the decarboxylation pathways depending on the type of catalysts being used. The calculation for reaction activation energy was in good agreement with our experimental measurements.« less

Validation of a model for the cast-film process

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

Chambon, F.; Ohlsson, S.; Silagy, D.

1996-12-31

We have developed a model of the cast-film process and compared theoretical predictions against experiments on a pilot line. Three polyethylenes with a markedly different level of melt elasticity were used in this evaluation; namely, a high pressure low density polyethylene, LDPE, and two linear low density polyethylenes, LLDPE-1 and LLDPE-2. The final film dimensions of the LDPE were found to be in good agreement with 1-D viscoelastic stationary predictions. Flow field visualization experiments indicate, however, a 2-D velocity field in the airgap between the extrusion die and the chill roll. Taking this observation into account, evolutions of the freemore » surface of the web along the airgap were recorded with LLDPE-2, our least elastic melt. An excellent agreement is found between these measurements and predictions of neck-in and edge bead with 2-D Newtonian stationary simulations. The time-dependent solution, which is based on a linear stability analysis, allows to identify a zone of draw resonance within the working space of the process, defined by the draw ratio, the Deborah number, and the web aspect ratio. It is predicted that increasing this latter parameter stabilizes the process until an optimum value is reached. Experiments with LLDPE-1 are shown to validate this unique theoretical result, thus allowing to increase the draw ratio by about 75%.« less

Computer-aided analysis and design of the shape rolling process for producing turbine engine airfoils

NASA Technical Reports Server (NTRS)

Lahoti, G. D.; Akgerman, N.; Altan, T.

1978-01-01

Mild steel (AISI 1018) was selected as model cold-rolling material and Ti-6Al-4V and INCONEL 718 were selected as typical hot-rolling and cold-rolling alloys, respectively. The flow stress and workability of these alloys were characterized and friction factor at the roll/workpiece interface was determined at their respective working conditions by conducting ring tests. Computer-aided mathematical models for predicting metal flow and stresses, and for simulating the shape-rolling process were developed. These models utilize the upper-bound and the slab methods of analysis, and are capable of predicting the lateral spread, roll-separating force, roll torque and local stresses, strains and strain rates. This computer-aided design (CAD) system is also capable of simulating the actual rolling process and thereby designing roll-pass schedule in rolling of an airfoil or similar shape. The predictions from the CAD system were verified with respect to cold rolling of mild steel plates. The system is being applied to cold and hot isothermal rolling of an airfoil shape, and will be verified with respect to laboratory experiments under controlled conditions.

A Microstructure-Based Constitutive Model for Superplastic Forming

NASA Astrophysics Data System (ADS)

Jafari Nedoushan, Reza; Farzin, Mahmoud; Mashayekhi, Mohammad; Banabic, Dorel

2012-11-01

A constitutive model is proposed for simulations of hot metal forming processes. This model is constructed based on dominant mechanisms that take part in hot forming and includes intergranular deformation, grain boundary sliding, and grain boundary diffusion. A Taylor type polycrystalline model is used to predict intergranular deformation. Previous works on grain boundary sliding and grain boundary diffusion are extended to drive three-dimensional macro stress-strain rate relationships for each mechanism. In these relationships, the effect of grain size is also taken into account. The proposed model is first used to simulate step strain-rate tests and the results are compared with experimental data. It is shown that the model can be used to predict flow stresses for various grain sizes and strain rates. The yield locus is then predicted for multiaxial stress states, and it is observed that it is very close to the von Mises yield criterion. It is also shown that the proposed model can be directly used to simulate hot forming processes. Bulge forming process and gas pressure tray forming are simulated, and the results are compared with experimental data.

Discerning measures of conscious brain processes associated with superior early motor performance: Capacity, coactivation, and character.

PubMed

van Duijn, Tina; Buszard, Tim; Hoskens, Merel C J; Masters, Rich S W

2017-01-01

This study explored the relationship between working memory (WM) capacity, corticocortical communication (EEG coherence), and propensity for conscious control of movement during the performance of a complex far-aiming task. We were specifically interested in the role of these variables in predicting motor performance by novices. Forty-eight participants completed (a) an assessment of WM capacity (an adapted Rotation Span task), (b) a questionnaire that assessed the propensity to consciously control movement (the Movement Specific Reinvestment Scale), and (c) a hockey push-pass task. The hockey push-pass task was performed in a single task (movement only) condition and a combined task (movement plus decision) condition. Electroencephalography (EEG) was used to examine brain activity during the single task. WM capacity best predicted single task performance. WM capacity in combination with T8-Fz coherence (between the visuospatial and motor regions of the brain) best predicted combined task performance. We discuss the implied roles of visuospatial information processing capacity, neural coactivation, and propensity for conscious processing during performance of complex motor tasks. © 2017 Elsevier B.V. All rights reserved.

Gaussian Process Regression for Predictive But Interpretable Machine Learning Models: An Example of Predicting Mental Workload across Tasks

PubMed Central

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

A modified artificial neural network based prediction technique for tropospheric radio refractivity

PubMed Central

Javeed, Shumaila; Javed, Wajahat; Atif, M.; Uddin, Mueen

2018-01-01

Radio refractivity plays a significant role in the development and design of radio systems for attaining the best level of performance. Refractivity in the troposphere is one of the features affecting electromagnetic waves, and hence the communication system interrupts. In this work, a modified artificial neural network (ANN) based model is applied to predict the refractivity. The suggested ANN model comprises three modules: the data preparation module, the feature selection module, and the forecast module. The first module applies pre-processing to make the data compatible for the feature selection module. The second module discards irrelevant and redundant data from the input set. The third module uses ANN for prediction. The ANN model applies a sigmoid activation function and a multi-variate auto regressive model to update the weights during the training process. In this work, the refractivity is predicted and estimated based on ten years (2002–2011) of meteorological data, such as the temperature, pressure, and humidity, obtained from the Pakistan Meteorological Department (PMD), Islamabad. The refractivity is estimated using the method suggested by the International Telecommunication Union (ITU). The refractivity is predicted for the year 2012 using the database of the previous ten years, with the help of ANN. The ANN model is implemented in MATLAB. Next, the estimated and predicted refractivity levels are validated against each other. The predicted and actual values (PMD data) of the atmospheric parameters agree with each other well, and demonstrate the accuracy of the proposed ANN method. It was further found that all parameters have a strong relationship with refractivity, in particular the temperature and humidity. The refractivity values are higher during the rainy season owing to a strong association with the relative humidity. Therefore, it is important to properly cater the signal communication system during hot and humid weather. Based on the results, the proposed ANN method can be used to develop a refractivity database, which is highly important in a radio communication system. PMID:29494609

Rayleigh instability at small length scales.

PubMed

Gopan, Nandu; Sathian, Sarith P

2014-09-01

The Rayleigh instability (also called the Plateau-Rayleigh instability) of a nanosized liquid propane thread is investigated using molecular dynamics (MD). The validity of classical predictions at small length scales is verified by comparing the temporal evolution of liquid thread simulated by MD against classical predictions. Previous works have shown that thermal fluctuations become dominant at small length scales. The role and influence of the stochastic nature of thermal fluctuations in determining the instability at small length scale is also investigated. Thermal fluctuations are seen to dominate and accelerate the breakup process only during the last stages of breakup. The simulations also reveal that the breakup profile of nanoscale threads undergo modification due to reorganization of molecules by the evaporation-condensation process.

Drift of surface and near-bottom waters of the San Francisco Bay system, California March 1970 through April 1971

USGS Publications Warehouse

Conomos, T.J.; McCulloch, D.S.; Peterson, D.H.; Carlson, P.R.

1972-01-01

The San Francisco Bay system is a complex estuary in which there is an interplay between natural chemical and physical processes, and changes resulting from the works of man. The bay is used for recreation, water-borne commerce, fishing, domestic and industrial waste disposal, and esthetic pleasure. Because some of these uses are competitive, it is desirable to adequately predict the impact of man's activities on this natural system. The reliability of such predictions will be strengthened by long-term observations directed toward understanding the natural processes occurring in the bay. This study is a compilation of one aspect of the U.S. Geological Survey's continuing investigations of the San Francisco Bay system.

Bioethanol production optimization: a thermodynamic analysis.

PubMed

Alvarez, Víctor H; Rivera, Elmer Ccopa; Costa, Aline C; Filho, Rubens Maciel; Wolf Maciel, Maria Regina; Aznar, Martín

2008-03-01

In this work, the phase equilibrium of binary mixtures for bioethanol production by continuous extractive process was studied. The process is composed of four interlinked units: fermentor, centrifuge, cell treatment unit, and flash vessel (ethanol-congener separation unit). A proposal for modeling the vapor-liquid equilibrium in binary mixtures found in the flash vessel has been considered. This approach uses the Predictive Soave-Redlich-Kwong equation of state, with original and modified molecular parameters. The congeners considered were acetic acid, acetaldehyde, furfural, methanol, and 1-pentanol. The results show that the introduction of new molecular parameters r and q in the UNIFAC model gives more accurate predictions for the concentration of the congener in the gas phase for binary and ternary systems.

Detecting uber-operons in prokaryotic genomes.

PubMed

Che, Dongsheng; Li, Guojun; Mao, Fenglou; Wu, Hongwei; Xu, Ying

2006-01-01

We present a study on computational identification of uber-operons in a prokaryotic genome, each of which represents a group of operons that are evolutionarily or functionally associated through operons in other (reference) genomes. Uber-operons represent a rich set of footprints of operon evolution, whose full utilization could lead to new and more powerful tools for elucidation of biological pathways and networks than what operons have provided, and a better understanding of prokaryotic genome structures and evolution. Our prediction algorithm predicts uber-operons through identifying groups of functionally or transcriptionally related operons, whose gene sets are conserved across the target and multiple reference genomes. Using this algorithm, we have predicted uber-operons for each of a group of 91 genomes, using the other 90 genomes as references. In particular, we predicted 158 uber-operons in Escherichia coli K12 covering 1830 genes, and found that many of the uber-operons correspond to parts of known regulons or biological pathways or are involved in highly related biological processes based on their Gene Ontology (GO) assignments. For some of the predicted uber-operons that are not parts of known regulons or pathways, our analyses indicate that their genes are highly likely to work together in the same biological processes, suggesting the possibility of new regulons and pathways. We believe that our uber-operon prediction provides a highly useful capability and a rich information source for elucidation of complex biological processes, such as pathways in microbes. All the prediction results are available at our Uber-Operon Database: http://csbl.bmb.uga.edu/uber, the first of its kind.

Detecting uber-operons in prokaryotic genomes

PubMed Central

Che, Dongsheng; Li, Guojun; Mao, Fenglou; Wu, Hongwei; Xu, Ying

2006-01-01

We present a study on computational identification of uber-operons in a prokaryotic genome, each of which represents a group of operons that are evolutionarily or functionally associated through operons in other (reference) genomes. Uber-operons represent a rich set of footprints of operon evolution, whose full utilization could lead to new and more powerful tools for elucidation of biological pathways and networks than what operons have provided, and a better understanding of prokaryotic genome structures and evolution. Our prediction algorithm predicts uber-operons through identifying groups of functionally or transcriptionally related operons, whose gene sets are conserved across the target and multiple reference genomes. Using this algorithm, we have predicted uber-operons for each of a group of 91 genomes, using the other 90 genomes as references. In particular, we predicted 158 uber-operons in Escherichia coli K12 covering 1830 genes, and found that many of the uber-operons correspond to parts of known regulons or biological pathways or are involved in highly related biological processes based on their Gene Ontology (GO) assignments. For some of the predicted uber-operons that are not parts of known regulons or pathways, our analyses indicate that their genes are highly likely to work together in the same biological processes, suggesting the possibility of new regulons and pathways. We believe that our uber-operon prediction provides a highly useful capability and a rich information source for elucidation of complex biological processes, such as pathways in microbes. All the prediction results are available at our Uber-Operon Database: , the first of its kind. PMID:16682449

Denitrification in Agricultural Soils: Integrated control and Modelling at various scales (DASIM)

NASA Astrophysics Data System (ADS)

Müller, Christoph; Well, Reinhard; Böttcher, Jürgen; Butterbach-Bahl, Klaus; Dannenmann, Michael; Deppe, Marianna; Dittert, Klaus; Dörsch, Peter; Horn, Marcus; Ippisch, Olaf; Mikutta, Robert; Senbayram, Mehmet; Vogel, Hans-Jörg; Wrage-Mönnig, Nicole; Müller, Carsten

2016-04-01

The new research unit DASIM brings together the expertise of 11 working groups to study the process of denitrification at unprecedented spatial and temporal resolution. Based on state-of-the art analytical techniques our aim is to develop improved denitrification models ranging from the microscale to the field/plot scale. Denitrification, the process of nitrate reduction allowing microbes to sustain respiration under anaerobic conditions, is the key process returning reactive nitrogen as N2to the atmosphere. Actively denitrifying communities in soil show distinct regulatory phenotypes (DRP) with characteristic controls on the single reaction steps and end-products. It is unresolved whether DRPs are anchored in the taxonomic composition of denitrifier communities and how environmental conditions shape them. Despite being intensively studied for more than 100 years, denitrification rates and emissions of its gaseous products can still not be satisfactorily predicted. While the impact of single environmental parameters is well understood, the complexity of the process itself with its intricate cellular regulation in response to highly variable factors in the soil matrix prevents robust prediction of gaseous emissions. Key parameters in soil are pO2, organic matter content and quality, pH and the microbial community structure, which in turn are affected by the soil structure, chemistry and soil-plant interactions. In the DASIM research unit, we aim at the quantitative prediction of denitrification rates as a function of microscale soil structure, organic matter quality, DRPs and atmospheric boundary conditions via a combination of state-of-the-art experimental and analytical tools (X-ray μCT, 15N tracing, NanoSIMS, microsensors, advanced flux detection, NMR spectroscopy, and molecular methods including next generation sequencing of functional gene transcripts). We actively seek collaboration with researchers working in the field of denitrification.

Prediction of Weld Penetration in FCAW of HSLA steel using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Asl, Y. Dadgar; Mostafa, N. B.; Panahizadeh R., V.; Seyedkashi, S. M. H.

2011-01-01

Flux-cored arc welding (FCAW) is a semiautomatic or automatic arc welding process that requires a continuously-fed consumable tubular electrode containing a flux. The main FCAW process parameters affecting the depth of penetration are welding current, arc voltage, nozzle-to-work distance, torch angle and welding speed. Shallow depth of penetration may contribute to failure of a welded structure since penetration determines the stress-carrying capacity of a welded joint. To avoid such occurrences; the welding process parameters influencing the weld penetration must be properly selected to obtain an acceptable weld penetration and hence a high quality joint. Artificial neural networks (ANN), also called neural networks (NN), are computational models used to express complex non-linear relationships between input and output data. In this paper, artificial neural network (ANN) method is used to predict the effects of welding current, arc voltage, nozzle-to-work distance, torch angle and welding speed on weld penetration depth in gas shielded FCAW of a grade of high strength low alloy steel. 32 experimental runs were carried out using the bead-on-plate welding technique. Weld penetrations were measured and on the basis of these 32 sets of experimental data, a feed-forward back-propagation neural network was created. 28 sets of the experiments were used as the training data and the remaining 4 sets were used for the testing phase of the network. The ANN has one hidden layer with eight neurons and is trained after 840 iterations. The comparison between the experimental results and ANN results showed that the trained network could predict the effects of the FCAW process parameters on weld penetration adequately.

Rapid and non-destructive assessment of polyunsaturated fatty acids contents in Salmon using near-infrared hyperspectral imaging

NASA Astrophysics Data System (ADS)

Tao, Feifei; Mba, Ogan; Liu, Li; Ngadi, Michael

2017-04-01

Polyunsaturated fatty acids (PUFAs) are important nutrients present in Salmon. However, current methods for quantifying the fatty acids (FAs) contents in foods are generally based on gas chromatography (GC) technique, which is time-consuming, laborious and destructive to the tested samples. Therefore, the capability of near-infrared (NIR) hyperspectral imaging to predict the PUFAs contents of C20:2 n-6, C20:3 n-6, C20:5 n-3, C22:5 n-3 and C22:6 n-3 in Salmon fillets in a rapid and non-destructive way was investigated in this work. Mean reflectance spectra were first extracted from the region of interests (ROIs), and then the spectral pre-processing methods of 2nd derivative and Savitzky-Golay (SG) smoothing were performed on the original spectra. Based on the original and the pre-processed spectra, PLSR technique was employed to develop the quantitative models for predicting each PUFA content in Salmon fillets. The results showed that for all the studied PUFAs, the quantitative models developed using the pre-processed reflectance spectra by "2nd derivative + SG smoothing" could improve their modeling results. Good prediction results were achieved with RP and RMSEP of 0.91 and 0.75 mg/g dry weight, 0.86 and 1.44 mg/g dry weight, 0.82 and 3.01 mg/g dry weight for C20:3 n-6, C22:5 n-3 and C20:5 n-3, respectively after pre-processing by "2nd derivative + SG smoothing". The work demonstrated that NIR hyperspectral imaging could be a useful tool for rapid and non-destructive determination of the PUFA contents in fish fillets.

Ecotoxicological criteria for final storage quality: Possibilities and limits

NASA Astrophysics Data System (ADS)

Zeyer, Josef; Meyer, Joseph

Landfills are complex chemical and biological reactors whose internal processes are often beyond the immediate control of process engineers. Therefore, the concept of a "Final Storage Landfill" may be deceptive. Furthermore, traditional approaches to establishing discharge criteria and treatment requirements for industrial effluents may not work well for landfill emissions. Factories can often be treated as steady-state processes whose inputs and outputs are predictable; however, landfills are batch reactors whose contents and emissions may be unknown and will vary temporally and spatially. If the contents of a landfill are known, the sequence of chemical reactions can be predicted qualitatively. Even if that sequence is predictable, though, quantitative ecotoxicological criteria will be difficult to establish, and risk assessments based on chemical "laundry lists" will be questionable. The situation is not hopeless, though. New approaches can be developed to monitor and predict landfill emissions. We believe these will include (1) testing (biological and chemical) of internal components of landfills as well as emissions; (2) development of laboratory and/or field methods in which the chemical and biological evolution of landfills can be studied at accelerated rates, thus allowing better prediction of future emissions; and (3) flexible ecotoxicological criteria that are adaptable to the evolving nature of landfill emissions. These criteria should be based on complementary chemical analyses and biological tests that fit into a hierarchical (decision-tree) hazard assessment strategy.

Tobacco counter-advertising: a review of the literature and a conceptual model for understanding effects.

PubMed

Agostinelli, Gina; Grube, Joel W

2003-01-01

The tobacco counter-advertising literature is reviewed as it relates to basic process questions concerning what makes counter-advertisements effective. Limitations in addressing (a) counter-advertisement content and the psychological mediators targeted, (b) counter-advertisement style and the affective reactions targeted, (c) prior smoking experience, and (d) other audience factors are enumerated. A theoretical model based on alcohol advertising research is presented to address those limitations. The model addresses the practical research question of predicting when tobacco counter-advertising will work by examining the independent influence of each of these enumerated factors, as well as how these factors operate in concert, qualifying each other. The model also addresses the process question of explaining how counter-advertising works by identifying affective and cognitive processes as mediators. By understanding the processes that underlie the qualified findings, one can better advise the designers of tobacco counter-advertisements how to be more effective.

Working memory and decision processes in visual area v4.

PubMed

Hayden, Benjamin Y; Gallant, Jack L

2013-01-01

Recognizing and responding to a remembered stimulus requires the coordination of perception, working memory, and decision-making. To investigate the role of visual cortex in these processes, we recorded responses of single V4 neurons during performance of a delayed match-to-sample task that incorporates rapid serial visual presentation of natural images. We found that neuronal activity during the delay period after the cue but before the images depends on the identity of the remembered image and that this change persists while distractors appear. This persistent response modulation has been identified as a diagnostic criterion for putative working memory signals; our data thus suggest that working memory may involve reactivation of sensory neurons. When the remembered image reappears in the neuron's receptive field, visually evoked responses are enhanced; this match enhancement is a diagnostic criterion for decision. One model that predicts these data is the matched filter hypothesis, which holds that during search V4 neurons change their tuning so as to match the remembered cue, and thus become detectors for that image. More generally, these results suggest that V4 neurons participate in the perceptual, working memory, and decision processes that are needed to perform memory-guided decision-making.

A general software reliability process simulation technique

NASA Technical Reports Server (NTRS)

Tausworthe, Robert C.

1991-01-01

The structure and rationale of the generalized software reliability process, together with the design and implementation of a computer program that simulates this process are described. Given assumed parameters of a particular project, the users of this program are able to generate simulated status timelines of work products, numbers of injected anomalies, and the progress of testing, fault isolation, repair, validation, and retest. Such timelines are useful in comparison with actual timeline data, for validating the project input parameters, and for providing data for researchers in reliability prediction modeling.

Mapping geomorphic process domains to predict hillslope sediment size distribution using remotely-sensed data and field sampling, Inyo Creek, California

NASA Astrophysics Data System (ADS)

Leclere, S.; Sklar, L. S.; Genetti, J. R.

2014-12-01

The size distribution of sediments produced on hillslopes and supplied to channels depends on the geomorphic processes that weather, detach and transport rock fragments down slopes. Little in the way of theory or data is available to predict patterns in hillslope size distributions at the catchment scale from topographic and geologic maps. Here we use aerial imagery and a variety of remote sensing techniques to map and categorize geomorphic landscape units (GLUs) by inferred sediment production process regime, across the steep mountain catchment of Inyo Creek, eastern Sierra Nevada, California. We also use field measurements of particle size and local geomorphic attributes to test and refine GLU determinations. Across the 2 km of relief in this catchment, landcover varies from bare bedrock cliffs at higher elevations to vegetated, regolith-covered convex slopes at lower elevations. Hillslope gradient could provide a simple index of sediment production process, from rock spallation and landsliding at highest slopes, to tree-throw and other disturbance-driven soil production processes at lowest slopes. However, many other attributes are needed for a more robust predictive model, including elevation, curvature, aspect, drainage area, and color. We combine tools from ArcGIS, ERDAS Imagine and Envi with groundtruthing field work to find an optimal combination of attributes for defining sediment production GLUs. Key challenges include distinguishing: weathered from freshly eroded bedrock, boulders from intact bedrock, and landslide deposits from talus slopes. We take advantage of emerging technologies that provide new ways of conducting fieldwork and comparing field data to mapping solutions. In particular, cellphone GPS is approaching the accuracy of dedicated GPS systems and the ability to geo-reference photos simplifies field notes and increases accuracy of later map creation. However, the predictive power of the GLU mapping approach is limited by inherent uncertainty in remotely sensed data and aerial imagery. This work is a contribution toward the long-term goal of reliable and automated mapping of hillslope sediment size distributions for use in sediment budgets and hazard delineation, and for understanding the feedbacks between climate, erosion and topography that drive sediment production.

Modeling individual differences in working memory performance: a source activation account

PubMed Central

Daily, Larry Z.; Lovett, Marsha C.; Reder, Lynne M.

2008-01-01

Working memory resources are needed for processing and maintenance of information during cognitive tasks. Many models have been developed to capture the effects of limited working memory resources on performance. However, most of these models do not account for the finding that different individuals show different sensitivities to working memory demands, and none of the models predicts individual subjects' patterns of performance. We propose a computational model that accounts for differences in working memory capacity in terms of a quantity called source activation, which is used to maintain goal-relevant information in an available state. We apply this model to capture the working memory effects of individual subjects at a fine level of detail across two experiments. This, we argue, strengthens the interpretation of source activation as working memory capacity. PMID:19079561

Ceramic Technology Project semiannual progress report, October 1992--March 1993

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

Johnson, D.R.

1993-09-01

This project was developed to meet the ceramic technology requirements of the OTS`s automotive technology programs. Although progress has been made in developing reliable structural ceramics, further work is needed to reduce cost. The work described in this report is organized according to the following work breakdown structure project elements: Materials and processing (monolithics [Si nitride, carbide], ceramic composites, thermal and wear coatings, joining, cost effective ceramic machining), materials design methodology (contact interfaces, new concepts), data base and life prediction (structural qualification, time-dependent behavior, environmental effects, fracture mechanics, nondestructive evaluation development), and technology transfer.

A model for the evolution of CO2 on Mars

NASA Technical Reports Server (NTRS)

Haberle, Robert M.; Tyler, D.; Mckay, C. P.; Davis, W. L.

1993-01-01

Our MSATT work has focused on the evolution of CO2 on Mars. We have constructed a model that predicts the evolution of CO2 on Mars from a specified initial amount at the end of the heavy bombardment to the present. The model draws on published estimates of the main process believed to affect the fate of CO2 during this period: chemical weathering, regolith uptake, polar cap formation, and atmospheric escape. Except for escape, the rate at which these processes act is controlled by surface temperatures that we calculate using a modified version of the Gierasch and Toon energy balance model. Various aspects of this work are covered.

Issues of upscaling in space and time with soil erosion models

NASA Astrophysics Data System (ADS)

Brazier, R. E.; Parsons, A. J.; Wainwright, J.; Hutton, C.

2009-04-01

Soil erosion - the entrainment, transport and deposition of soil particles - is an important phenomenon to understand; the quantity of soil loss determines the long term on-site sustainability of agricultural production (Pimental et al., 1995), and has potentially important off-site impacts on water quality (Bilotta and Brazier, 2008). The fundamental mechanisms of the soil erosion process have been studied at the laboratory scale, plot scale (Wainwright et al., 2000), the small catchment scale (refs here) and river basin scale through sediment yield and budgeting work. Subsequently, soil erosion models have developed alongside and directly from this empirical work, from data-based models such as the USLE (Wischmeier and Smith, 1978), to ‘physics or process-based' models such as EUROSEM (Morgan et al., 1998) and WEPP (Nearing et al., 1989). Model development has helped to structure our understanding of the fundamental factors that control soil erosion process at the plot and field scale. Despite these advances, however, our understanding of and ability to predict erosion and sediment yield at the same plot, field and also larger catchment scales remains poor. Sediment yield has been shown to both increase and decrease as a function of drainage area (de Vente et al., 2006); the lack of a simple relationship demonstrates complex and scale-dependant process domination throughout a catchment, and emphasises our uncertainty and poor conceptual basis for predicting plot to catchment scale erosion rates and sediment yields (Parsons et al., 2006b). Therefore, this paper presents a review of the problems associated with modelling soil erosion across spatial and temporal scales and suggests some potential solutions to address these problems. The transport-distance approach to scaling erosion rates (Wainwright, et al., 2008) is assessed and discussed in light of alternative techniques to predict erosion across spatial and temporal scales. References Bilotta, G.S. and Brazier, R.E., 2008. Understanding the influence of suspended solids on water quality and aquatic biota. Water Research, 42(12): 2849-2861. de Vente, J., Poesen, J., Bazzoffi, P., Van Ropaey, A.V. and Verstraeten, G., 2006. Predicting catchment sediment yield in Mediterranean environments: the importance of sediment sources and connectivity in Italian drainage basins. Earth Surface Processes And Landforms, 31: 1017-1034. Morgan, R.P.C. et al., 1998. The European soil erosion model (EUROSEM): a dynamic approach for predicting sediment transport from fields to small catchments. Earth Surface Processes And Landforms, 23: 527-544. Nearing, M. A., G. R. Foster, L. J. Lane, and S. C. Finkner. 1989. A process-based soil erosion model for USDA Water Erosion Prediction Project technology. Trans. ASAE 32(5): 1587-1593. Parsons, A.J., Brazier, R.E., Wainwright, J. and Powell, D.M., 2006a. Scale relationships in hillslope runoff and erosion. Earth Surface Processes and Landforms, 31(11): 1384-1393. Parsons, A.J., Wainwright, J., Brazier, R.E. and Powell, D.M., 2006b. Is sediment delivery a fallacy? Earth Surface Processes and Landforms, 31(10): 1325-1328. Pimental, D. et al., 1995. Environmental and economic costs of soil erosion and conservation benefits. Science, 267:1117-1122. Wainwright, J., Parsons, A.J. and Abrahams, A.D., 2000. Plot-scale studies of vegetation, overland flow and erosion interactions: case studies from Arizona and New Mexico. Hydrological Processes, 14(16-17): 2921-2943. Wischmeier, W.H. and Smith, D.D., 1978. Predicting rainfall erosion losses - a guide for conservation planning., 537.

Does work pay psychologically as well as economically? The role of employment in predicting depressive symptoms and parenting among low-income families.

PubMed

Raver, C Cybele

2003-01-01

This longitudinal study examined quantity and quality of maternal employment as predictors of depressive symptoms and parenting style in a sample of 94 low-income mothers whose 4-year-old children were enrolled in Head Start at baseline. Results suggest that answers to the question of whether work "pays" are complex: Findings suggest some benefits of greater employment participation while also indicating that women holding lower prestige jobs experienced increases in their use of negative parenting style, net of baseline demographic and psychological characteristics. Sparse evidence for selection processes was found, with cohabitation and maternal depressive symptoms modestly predictive of subsequent maternal employment. Implications of these findings for welfare reform and educationally related policies for low-income families are discussed.

The interactional significance of formulas in autistic language.

PubMed

Dobbinson, Sushie; Perkins, Mick; Boucher, Jill

2003-01-01

The phenomenon of echolalia in autistic language is well documented. Whilst much early research dismissed echolalia as merely an indicator of cognitive limitation, later work identified particular discourse functions of echolalic utterances. The work reported here extends the study of the interactional significance of echolalia to formulaic utterances. Audio and video recordings of conversations between the first author and two research participants were transcribed and analysed according to a Conversation Analysis framework and a multi-layered linguistic framework. Formulaic language was found to have predictable interactional significance within the language of an individual with autism, and the generic phenomenon of formulaicity in company with predictable discourse function was seen to hold across the research participants, regardless of cognitive ability. The implications of formulaicity in autistic language for acquisition and processing mechanisms are discussed.

Phonological mismatch makes aided speech recognition in noise cognitively taxing.

PubMed

Rudner, Mary; Foo, Catharina; Rönnberg, Jerker; Lunner, Thomas

2007-12-01

The working memory framework for Ease of Language Understanding predicts that speech processing becomes more effortful, thus requiring more explicit cognitive resources, when there is mismatch between speech input and phonological representations in long-term memory. To test this prediction, we changed the compression release settings in the hearing instruments of experienced users and allowed them to train for 9 weeks with the new settings. After training, aided speech recognition in noise was tested with both the trained settings and orthogonal settings. We postulated that training would lead to acclimatization to the trained setting, which in turn would involve establishment of new phonological representations in long-term memory. Further, we postulated that after training, testing with orthogonal settings would give rise to phonological mismatch, associated with more explicit cognitive processing. Thirty-two participants (mean=70.3 years, SD=7.7) with bilateral sensorineural hearing loss (pure-tone average=46.0 dB HL, SD=6.5), bilaterally fitted for more than 1 year with digital, two-channel, nonlinear signal processing hearing instruments and chosen from the patient population at the Linköping University Hospital were randomly assigned to 9 weeks training with new, fast (40 ms) or slow (640 ms), compression release settings in both channels. Aided speech recognition in noise performance was tested according to a design with three within-group factors: test occasion (T1, T2), test setting (fast, slow), and type of noise (unmodulated, modulated) and one between-group factor: experience setting (fast, slow) for two types of speech materials-the highly constrained Hagerman sentences and the less-predictable Hearing in Noise Test (HINT). Complex cognitive capacity was measured using the reading span and letter monitoring tests. PREDICTION: We predicted that speech recognition in noise at T2 with mismatched experience and test settings would be associated with more explicit cognitive processing and thus stronger correlations with complex cognitive measures, as well as poorer performance if complex cognitive capacity was exceeded. Under mismatch conditions, stronger correlations were found between performance on speech recognition with the Hagerman sentences and reading span, along with poorer speech recognition for participants with low reading span scores. No consistent mismatch effect was found with HINT. The mismatch prediction generated by the working memory framework for Ease of Language Understanding is supported for speech recognition in noise with the highly constrained Hagerman sentences but not the less-predictable HINT.

Training Students’ Science Process Skills through Didactic Design on Work and Energy

NASA Astrophysics Data System (ADS)

Ramayanti, S.; Utari, S.; Saepuzaman, D.

2017-09-01

Science Process Skills (SPS) has not been optimally trained to the students in the learning activity. The aim of this research is finding the ways to train SPS on the subject of Work and Energy. One shot case study design is utilized in this research that conducted on 32 students in one of the High Schools in Bandung. The students’ SPS responses were analyzed by the development SPS based assessment portfolios. The results of this research showed the didactic design that had been designed to training the identifying variables skills, formulating hypotheses, and the experiment activity shows the development. But the didactic design to improve the students’ predicting skills shows that the development is still not optimal. Therefore, in the future studies need to be developed the didactic design on the subject Work and Energy that exercising these skills.

When High-Capacity Readers Slow Down and Low-Capacity Readers Speed Up: Working Memory and Locality Effects.

PubMed

Nicenboim, Bruno; Logačev, Pavel; Gattei, Carolina; Vasishth, Shravan

2016-01-01

We examined the effects of argument-head distance in SVO and SOV languages (Spanish and German), while taking into account readers' working memory capacity and controlling for expectation (Levy, 2008) and other factors. We predicted only locality effects, that is, a slowdown produced by increased dependency distance (Gibson, 2000; Lewis and Vasishth, 2005). Furthermore, we expected stronger locality effects for readers with low working memory capacity. Contrary to our predictions, low-capacity readers showed faster reading with increased distance, while high-capacity readers showed locality effects. We suggest that while the locality effects are compatible with memory-based explanations, the speedup of low-capacity readers can be explained by an increased probability of retrieval failure. We present a computational model based on ACT-R built under the previous assumptions, which is able to give a qualitative account for the present data and can be tested in future research. Our results suggest that in some cases, interpreting longer RTs as indexing increased processing difficulty and shorter RTs as facilitation may be too simplistic: The same increase in processing difficulty may lead to slowdowns in high-capacity readers and speedups in low-capacity ones. Ignoring individual level capacity differences when investigating locality effects may lead to misleading conclusions.

When High-Capacity Readers Slow Down and Low-Capacity Readers Speed Up: Working Memory and Locality Effects

PubMed Central

Nicenboim, Bruno; Logačev, Pavel; Gattei, Carolina; Vasishth, Shravan

2016-01-01

We examined the effects of argument-head distance in SVO and SOV languages (Spanish and German), while taking into account readers' working memory capacity and controlling for expectation (Levy, 2008) and other factors. We predicted only locality effects, that is, a slowdown produced by increased dependency distance (Gibson, 2000; Lewis and Vasishth, 2005). Furthermore, we expected stronger locality effects for readers with low working memory capacity. Contrary to our predictions, low-capacity readers showed faster reading with increased distance, while high-capacity readers showed locality effects. We suggest that while the locality effects are compatible with memory-based explanations, the speedup of low-capacity readers can be explained by an increased probability of retrieval failure. We present a computational model based on ACT-R built under the previous assumptions, which is able to give a qualitative account for the present data and can be tested in future research. Our results suggest that in some cases, interpreting longer RTs as indexing increased processing difficulty and shorter RTs as facilitation may be too simplistic: The same increase in processing difficulty may lead to slowdowns in high-capacity readers and speedups in low-capacity ones. Ignoring individual level capacity differences when investigating locality effects may lead to misleading conclusions. PMID:27014113

Top-Down Modulation of Auditory-Motor Integration during Speech Production: The Role of Working Memory.

PubMed

Guo, Zhiqiang; Wu, Xiuqin; Li, Weifeng; Jones, Jeffery A; Yan, Nan; Sheft, Stanley; Liu, Peng; Liu, Hanjun

2017-10-25

Although working memory (WM) is considered as an emergent property of the speech perception and production systems, the role of WM in sensorimotor integration during speech processing is largely unknown. We conducted two event-related potential experiments with female and male young adults to investigate the contribution of WM to the neurobehavioural processing of altered auditory feedback during vocal production. A delayed match-to-sample task that required participants to indicate whether the pitch feedback perturbations they heard during vocalizations in test and sample sequences matched, elicited significantly larger vocal compensations, larger N1 responses in the left middle and superior temporal gyrus, and smaller P2 responses in the left middle and superior temporal gyrus, inferior parietal lobule, somatosensory cortex, right inferior frontal gyrus, and insula compared with a control task that did not require memory retention of the sequence of pitch perturbations. On the other hand, participants who underwent extensive auditory WM training produced suppressed vocal compensations that were correlated with improved auditory WM capacity, and enhanced P2 responses in the left middle frontal gyrus, inferior parietal lobule, right inferior frontal gyrus, and insula that were predicted by pretraining auditory WM capacity. These findings indicate that WM can enhance the perception of voice auditory feedback errors while inhibiting compensatory vocal behavior to prevent voice control from being excessively influenced by auditory feedback. This study provides the first evidence that auditory-motor integration for voice control can be modulated by top-down influences arising from WM, rather than modulated exclusively by bottom-up and automatic processes. SIGNIFICANCE STATEMENT One outstanding question that remains unsolved in speech motor control is how the mismatch between predicted and actual voice auditory feedback is detected and corrected. The present study provides two lines of converging evidence, for the first time, that working memory cannot only enhance the perception of vocal feedback errors but also exert inhibitory control over vocal motor behavior. These findings represent a major advance in our understanding of the top-down modulatory mechanisms that support the detection and correction of prediction-feedback mismatches during sensorimotor control of speech production driven by working memory. Rather than being an exclusively bottom-up and automatic process, auditory-motor integration for voice control can be modulated by top-down influences arising from working memory. Copyright © 2017 the authors 0270-6474/17/3710324-11$15.00/0.

The perfect family: decision making in biparental care.

PubMed

Akçay, Erol; Roughgarden, Joan

2009-10-13

Previous theoretical work on parental decisions in biparental care has emphasized the role of the conflict between evolutionary interests of parents in these decisions. A prominent prediction from this work is that parents should compensate for decreases in each other's effort, but only partially so. However, experimental tests that manipulate parents and measure their responses fail to confirm this prediction. At the same time, the process of parental decision making has remained unexplored theoretically. We develop a model to address the discrepancy between experiments and the theoretical prediction, and explore how assuming different decision making processes changes the prediction from the theory. We assume that parents make decisions in behavioral time. They have a fixed time budget, and allocate it between two parental tasks: provisioning the offspring and defending the nest. The proximate determinant of the allocation decisions are parents' behavioral objectives. We assume both parents aim to maximize the offspring production from the nest. Experimental manipulations change the shape of the nest production function. We consider two different scenarios for how parents make decisions: one where parents communicate with each other and act together (the perfect family), and one where they do not communicate, and act independently (the almost perfect family). The perfect family model is able to generate all the types of responses seen in experimental studies. The kind of response predicted depends on the nest production function, i.e. how parents' allocations affect offspring production, and the type of experimental manipulation. In particular, we find that complementarity of parents' allocations promotes matching responses. In contrast, the relative responses do not depend on the type of manipulation in the almost perfect family model. These results highlight the importance of the interaction between nest production function and how parents make decisions, factors that have largely been overlooked in previous models.

Do Predictors of Career Success Differ between Swedish Women and Men? Data from the Swedish Longitudinal Occupational Survey of Health (SLOSH).

PubMed

Nyberg, Anna; Magnusson Hanson, Linda L; Leineweber, Constanze; Johansson, Gunn

2015-01-01

The aim of this prospective study was to explore predictors of objective career success among Swedish women and men, focussing on gender differences. Data were drawn from the 2008 and 2010 waves of the Swedish Longitudinal Occupational Survey of Health (SLOSH) with a total of 3670 female and 2773 male participants. Odds ratios and 95% confidence intervals for job promotion and an above-average salary increase between 2008 and 2010 were obtained through binary logistic regression analyses. Individual and organisational factors measured in 2008 were used as predictors in analyses stratified by sex. Mutual adjustment was performed for these variables, as well as for labour market sector and staff category at baseline. In both sexes, younger age predicted both job promotion and an above-average salary increase. Job promotion was also in both sexes predicted by being part of decision-making processes, having conflicts with superiors, and being eager to advance. Furthermore, promotion was predicted by, among men, being educated to post-graduate level and having an open coping strategy and, among women, working >60 hours/week. An above-average salary increase was predicted in both sexes by having a university education. Postgraduate education, having children living at home, and being very motivated to advance predicted an above-average salary increase among women, as did working 51-60 hours/week and being part of decision-making processes in men. Gender differences were seen in several predictors. In conclusion, the results support previous findings of gender differences in predictors of career success. A high level of education, motivation to advance, and procedural justice appear to be more important predictors of career success among women, while open coping was a more important predictor among men.

Do Predictors of Career Success Differ between Swedish Women and Men? Data from the Swedish Longitudinal Occupational Survey of Health (SLOSH)

PubMed Central

Nyberg, Anna; Johansson, Gunn

2015-01-01

The aim of this prospective study was to explore predictors of objective career success among Swedish women and men, focussing on gender differences. Data were drawn from the 2008 and 2010 waves of the Swedish Longitudinal Occupational Survey of Health (SLOSH) with a total of 3670 female and 2773 male participants. Odds ratios and 95% confidence intervals for job promotion and an above-average salary increase between 2008 and 2010 were obtained through binary logistic regression analyses. Individual and organisational factors measured in 2008 were used as predictors in analyses stratified by sex. Mutual adjustment was performed for these variables, as well as for labour market sector and staff category at baseline. In both sexes, younger age predicted both job promotion and an above-average salary increase. Job promotion was also in both sexes predicted by being part of decision-making processes, having conflicts with superiors, and being eager to advance. Furthermore, promotion was predicted by, among men, being educated to post-graduate level and having an open coping strategy and, among women, working >60 hours/week. An above-average salary increase was predicted in both sexes by having a university education. Postgraduate education, having children living at home, and being very motivated to advance predicted an above-average salary increase among women, as did working 51–60 hours/week and being part of decision-making processes in men. Gender differences were seen in several predictors. In conclusion, the results support previous findings of gender differences in predictors of career success. A high level of education, motivation to advance, and procedural justice appear to be more important predictors of career success among women, while open coping was a more important predictor among men. PMID:26501351

Modeling Interdependent and Periodic Real-World Action Sequences

PubMed Central

Kurashima, Takeshi; Althoff, Tim; Leskovec, Jure

2018-01-01

Mobile health applications, including those that track activities such as exercise, sleep, and diet, are becoming widely used. Accurately predicting human actions in the real world is essential for targeted recommendations that could improve our health and for personalization of these applications. However, making such predictions is extremely difficult due to the complexities of human behavior, which consists of a large number of potential actions that vary over time, depend on each other, and are periodic. Previous work has not jointly modeled these dynamics and has largely focused on item consumption patterns instead of broader types of behaviors such as eating, commuting or exercising. In this work, we develop a novel statistical model, called TIPAS, for Time-varying, Interdependent, and Periodic Action Sequences. Our approach is based on personalized, multivariate temporal point processes that model time-varying action propensities through a mixture of Gaussian intensities. Our model captures short-term and long-term periodic interdependencies between actions through Hawkes process-based self-excitations. We evaluate our approach on two activity logging datasets comprising 12 million real-world actions (e.g., eating, sleep, and exercise) taken by 20 thousand users over 17 months. We demonstrate that our approach allows us to make successful predictions of future user actions and their timing. Specifically, TIPAS improves predictions of actions, and their timing, over existing methods across multiple datasets by up to 156%, and up to 37%, respectively. Performance improvements are particularly large for relatively rare and periodic actions such as walking and biking, improving over baselines by up to 256%. This demonstrates that explicit modeling of dependencies and periodicities in real-world behavior enables successful predictions of future actions, with implications for modeling human behavior, app personalization, and targeting of health interventions. PMID:29780977

Physics-based process model approach for detecting discontinuity during friction stir welding

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

Shrivastava, Amber; Pfefferkorn, Frank E.; Duffie, Neil A.

2015-02-12

The goal of this work is to develop a method for detecting the creation of discontinuities during friction stir welding. This in situ weld monitoring method could significantly reduce the need for post-process inspection. A process force model and a discontinuity force model were created based on the state-of-the-art understanding of flow around an friction stir welding (FSW) tool. These models are used to predict the FSW forces and size of discontinuities formed in the weld. Friction stir welds with discontinuities and welds without discontinuities were created, and the differences in force dynamics were observed. In this paper, discontinuities weremore » generated by reducing the tool rotation frequency and increasing the tool traverse speed in order to create "cold" welds. Experimental force data for welds with discontinuities and welds without discontinuities compared favorably with the predicted forces. The model currently overpredicts the discontinuity size.« less

Computer-aided analysis and design of the shape rolling process for producing turbine engine airfoils

NASA Technical Reports Server (NTRS)

Lahoti, G. D.; Akgerman, N.; Altan, T.

1978-01-01

Mild steel (AISI 1018) was selected as model cold rolling material and Ti-6A1-4V and Inconel 718 were selected as typical hot rolling and cold rolling alloys, respectively. The flow stress and workability of these alloys were characterized and friction factor at the roll/workpiece interface was determined at their respective working conditions by conducting ring tests. Computer-aided mathematical models for predicting metal flow and stresses, and for simulating the shape rolling process were developed. These models utilized the upper bound and the slab methods of analysis, and were capable of predicting the lateral spread, roll separating force, roll torque, and local stresses, strains and strain rates. This computer-aided design system was also capable of simulating the actual rolling process, and thereby designing the roll pass schedule in rolling of an airfoil or a similar shape.

Multiple objects tracking with HOGs matching in circular windows

NASA Astrophysics Data System (ADS)

Miramontes-Jaramillo, Daniel; Kober, Vitaly; Díaz-Ramírez, Víctor H.

2014-09-01

In recent years tracking applications with development of new technologies like smart TVs, Kinect, Google Glass and Oculus Rift become very important. When tracking uses a matching algorithm, a good prediction algorithm is required to reduce the search area for each object to be tracked as well as processing time. In this work, we analyze the performance of different tracking algorithms based on prediction and matching for a real-time tracking multiple objects. The used matching algorithm utilizes histograms of oriented gradients. It carries out matching in circular windows, and possesses rotation invariance and tolerance to viewpoint and scale changes. The proposed algorithm is implemented in a personal computer with GPU, and its performance is analyzed in terms of processing time in real scenarios. Such implementation takes advantage of current technologies and helps to process video sequences in real-time for tracking several objects at the same time.

Modeling conductive heat transfer during high-pressure thawing processes: determination of latent heat as a function of pressure.

PubMed

Denys, S; Van Loey, A M; Hendrickx, M E

2000-01-01

A numerical heat transfer model for predicting product temperature profiles during high-pressure thawing processes was recently proposed by the authors. In the present work, the predictive capacity of the model was considerably improved by taking into account the pressure dependence of the latent heat of the product that was used (Tylose). The effect of pressure on the latent heat of Tylose was experimentally determined by a series of freezing experiments conducted at different pressure levels. By combining a numerical heat transfer model for freezing processes with a least sum of squares optimization procedure, the corresponding latent heat at each pressure level was estimated, and the obtained pressure relation was incorporated in the original high-pressure thawing model. Excellent agreement with the experimental temperature profiles for both high-pressure freezing and thawing was observed.

Multimodality Prediction of Chaotic Time Series with Sparse Hard-Cut EM Learning of the Gaussian Process Mixture Model

NASA Astrophysics Data System (ADS)

Zhou, Ya-Tong; Fan, Yu; Chen, Zi-Yi; Sun, Jian-Cheng

2017-05-01

The contribution of this work is twofold: (1) a multimodality prediction method of chaotic time series with the Gaussian process mixture (GPM) model is proposed, which employs a divide and conquer strategy. It automatically divides the chaotic time series into multiple modalities with different extrinsic patterns and intrinsic characteristics, and thus can more precisely fit the chaotic time series. (2) An effective sparse hard-cut expectation maximization (SHC-EM) learning algorithm for the GPM model is proposed to improve the prediction performance. SHC-EM replaces a large learning sample set with fewer pseudo inputs, accelerating model learning based on these pseudo inputs. Experiments on Lorenz and Chua time series demonstrate that the proposed method yields not only accurate multimodality prediction, but also the prediction confidence interval. SHC-EM outperforms the traditional variational learning in terms of both prediction accuracy and speed. In addition, SHC-EM is more robust and insusceptible to noise than variational learning. Supported by the National Natural Science Foundation of China under Grant No 60972106, the China Postdoctoral Science Foundation under Grant No 2014M561053, the Humanity and Social Science Foundation of Ministry of Education of China under Grant No 15YJA630108, and the Hebei Province Natural Science Foundation under Grant No E2016202341.

Trialability, observability and risk reduction accelerating individual innovation adoption decisions.

PubMed

Hayes, Kathryn J; Eljiz, Kathy; Dadich, Ann; Fitzgerald, Janna-Anneke; Sloan, Terry

2015-01-01

The purpose of this paper is to provide a retrospective analysis of computer simulation's role in accelerating individual innovation adoption decisions. The process innovation examined is Lean Systems Thinking, and the organizational context is the imaging department of an Australian public hospital. Intrinsic case study methods including observation, interviews with radiology and emergency personnel about scheduling procedures, mapping patient appointment processes and document analysis were used over three years and then complemented with retrospective interviews with key hospital staff. The multiple data sources and methods were combined in a pragmatic and reflexive manner to explore an extreme case that provides potential to act as an instructive template for effective change. Computer simulation of process change ideas offered by staff to improve patient-flow accelerated the adoption of the process changes, largely because animated computer simulation permitted experimentation (trialability), provided observable predictions of change results (observability) and minimized perceived risk. The difficulty of making accurate comparisons between time periods in a health care setting is acknowledged. This work has implications for policy, practice and theory, particularly for inducing the rapid diffusion of process innovations to address challenges facing health service organizations and national health systems. Originality/value - The research demonstrates the value of animated computer simulation in presenting the need for change, identifying options, and predicting change outcomes and is the first work to indicate the importance of trialability, observability and risk reduction in individual adoption decisions in health services.

Ares I-X Range Safety Trajectory Analyses Overview and Independent Validation and Verification

NASA Technical Reports Server (NTRS)

Tarpley, Ashley F.; Starr, Brett R.; Tartabini, Paul V.; Craig, A. Scott; Merry, Carl M.; Brewer, Joan D.; Davis, Jerel G.; Dulski, Matthew B.; Gimenez, Adrian; Barron, M. Kyle

2011-01-01

All Flight Analysis data products were successfully generated and delivered to the 45SW in time to support the launch. The IV&V effort allowed data generators to work through issues early. Data consistency proved through the IV&V process provided confidence that the delivered data was of high quality. Flight plan approval was granted for the launch. The test flight was successful and had no safety related issues. The flight occurred within the predicted flight envelopes. Post flight reconstruction results verified the simulations accurately predicted the FTV trajectory.

Examining the Prediction of Reading Comprehension on Different Multiple-Choice Tests

ERIC Educational Resources Information Center

Andreassen, Rune; Braten, Ivar

2010-01-01

In this study, 180 Norwegian fifth-grade students with a mean age of 10.5 years were administered measures of word recognition skills, strategic text processing, reading motivation and working memory. Six months later, the same students were given three different multiple-choice reading comprehension measures. Based on three forced-order…

Do Creativity Self-Beliefs Predict Literacy Achievement and Motivation?

ERIC Educational Resources Information Center

Putwain, David W.; Kearsley, Rebecca; Symes, Wendy

2012-01-01

Previous work has suggested that creativity self-beliefs show only small relations with academic achievement and may only be related to intrinsic, not extrinsic motivation. We set out to re-examine these relationships accounting for the multifaceted and process embedded nature of creativity self-beliefs and the full domain range of extrinsic…

Atmospheric Turbulence Relative to Aviation, Missile, and Space Programs

NASA Technical Reports Server (NTRS)

Camp, Dennis W. (Editor); Frost, Walter (Editor)

1987-01-01

The purpose of the workshop was to bring together various disciplines of the aviation, missile, and space programs involved in predicting, measuring, modeling, and understanding the processes of atmospheric turbulence. Working committees re-examined the current state of knowledge, identified present and future needs, and documented and prioritized integrated and cooperative research programs.

Lexicality and Frequency in Specific Language Impairment: Accuracy and Error Data from Two Nonword Repetition Tests

ERIC Educational Resources Information Center

Jones, Gary; Tamburelli, Marco; Watson, Sarah E.; Gobet, Fernand; Pine, Julian M.

2010-01-01

Purpose: Deficits in phonological working memory and deficits in phonological processing have both been considered potential explanatory factors in specific language impairment (SLI). Manipulations of the lexicality and phonotactic frequency of nonwords enable contrasting predictions to be derived from these hypotheses. Method: Eighteen typically…

The Stereotyped Task Engagement Process: The Role of Interest and Achievement Motivation

ERIC Educational Resources Information Center

Smith, Jessi L.; Sansone, Carol; White, Paul H.

2007-01-01

Competence-based stereotypes can negatively affect women's performance in math and science (referred to as stereotype threat), presumably leading to lower motivation. The authors examined the effects of stereotype threat on interest, a motivational path not necessarily mediated by performance. They predicted that working on a computer science task…

VLSI design of lossless frame recompression using multi-orientation prediction

NASA Astrophysics Data System (ADS)

Lee, Yu-Hsuan; You, Yi-Lun; Chen, Yi-Guo

2016-01-01

Pursuing an experience of high-end visual quality drives human to demand a higher display resolution and a higher frame rate. Hence, a lot of powerful coding tools are aggregated together in emerging video coding standards to improve coding efficiency. This also makes video coding standards suffer from two design challenges: heavy computation and tremendous memory bandwidth. The first issue can be properly solved by a careful hardware architecture design with advanced semiconductor processes. Nevertheless, the second one becomes a critical design bottleneck for a modern video coding system. In this article, a lossless frame recompression using multi-orientation prediction technique is proposed to overcome this bottleneck. This work is realised into a silicon chip with the technology of TSMC 0.18 µm CMOS process. Its encoding capability can reach full-HD (1920 × 1080)@48 fps. The chip power consumption is 17.31 mW@100 MHz. Core area and chip area are 0.83 × 0.83 mm2 and 1.20 × 1.20 mm2, respectively. Experiment results demonstrate that this work exhibits an outstanding performance on lossless compression ratio with a competitive hardware performance.

A modeling approach to direct interspecies electron transfer process in anaerobic transformation of ethanol to methane.

PubMed

Liu, Yiwen; Zhang, Yaobin; Zhao, Zhiqiang; Ngo, Huu Hao; Guo, Wenshan; Zhou, Junliang; Peng, Lai; Ni, Bing-Jie

2017-01-01

Recent studies have shown that direct interspecies electron transfer (DIET) plays an important part in contributing to methane production from anaerobic digestion. However, so far anaerobic digestion models that have been proposed only consider two pathways for methane production, namely, acetoclastic methanogenesis and hydrogenotrophic methanogenesis, via indirect interspecies hydrogen transfer, which lacks an effective way for incorporating DIET into this paradigm. In this work, a new mathematical model is specifically developed to describe DIET process in anaerobic digestion through introducing extracellular electron transfer as a new pathway for methane production, taking anaerobic transformation of ethanol to methane as an example. The developed model was able to successfully predict experimental data on methane dynamics under different experimental conditions, supporting the validity of the developed model. Modeling predictions clearly demonstrated that DIET plays an important role in contributing to overall methane production (up to 33 %) and conductive material (i.e., carbon cloth) addition would significantly promote DIET through increasing ethanol conversion rate and methane production rate. The model developed in this work will potentially enhance our current understanding on syntrophic metabolism via DIET.

Evolutionary Maps: A new model for the analysis of conceptual development, with application to the diurnal cycle

NASA Astrophysics Data System (ADS)

Navarro, Manuel

2014-05-01

This paper presents a model of how children generate concrete concepts from perception through processes of differentiation and integration. The model informs the design of a novel methodology (evolutionary maps or emaps), whose implementation on certain domains unfolds the web of itineraries that children may follow in the construction of concrete conceptual knowledge and pinpoints, for each conception, the architecture of the conceptual change that leads to the scientific concept. Remarkably, the generative character of its syntax yields conceptions that, if unknown, amount to predictions that can be tested experimentally. Its application to the diurnal cycle (including the sun's trajectory in the sky) indicates that the model is correct and the methodology works (in some domains). Specifically, said emap predicts a number of exotic trajectories of the sun in the sky that, in the experimental work, were drawn spontaneously both on paper and a dome. Additionally, the application of the emaps theoretical framework in clinical interviews has provided new insight into other cognitive processes. The field of validity of the methodology and its possible applications to science education are discussed.

Effect of Multipass TIG and Activated TIG Welding Process on the Thermo-Mechanical Behavior of 316LN Stainless Steel Weld Joints

NASA Astrophysics Data System (ADS)

Ganesh, K. C.; Balasubramanian, K. R.; Vasudevan, M.; Vasantharaja, P.; Chandrasekhar, N.

2016-04-01

The primary objective of this work was to develop a finite element model to predict the thermo-mechanical behavior of an activated tungsten inert gas (ATIG)-welded joint. The ATIG-welded joint was fabricated using 10 mm thickness of 316LN stainless steel plates in a single pass. To distinguish the merits of ATIG welding process, it was compared with manual multipass tungsten inert gas (MPTIG)-welded joint. The ATIG-welded joint was fabricated with square butt edge configuration using an activating flux developed in-house. The MPTIG-welded joint was fabricated in thirteen passes with V-groove edge configuration. The finite element model was developed to predict the transient temperature, residual stress, and distortion of the welded joints. Also, microhardness, impact toughness, tensile strength, ferrite measurement, and microstructure were characterized. Since most of the recent publications of ATIG-welded joint was focused on the molten weld pool dynamics, this research work gives an insight on the thermo-mechanical behavior of ATIG-welded joint over MPTIG-welded joint.

Cross-Modal Decoding of Neural Patterns Associated with Working Memory: Evidence for Attention-Based Accounts of Working Memory.

PubMed

Majerus, Steve; Cowan, Nelson; Péters, Frédéric; Van Calster, Laurens; Phillips, Christophe; Schrouff, Jessica

2016-01-01

Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine-learning approach to determine more directly the extent to which common neural patterns characterize retention in verbal WM and visual WM. Verbal WM was assessed via a standard delayed probe recognition task for letter sequences of variable length. Visual WM was assessed via a visual array WM task involving the maintenance of variable amounts of visual information in the focus of attention. We trained a classifier to distinguish neural activation patterns associated with high- and low-visual WM load and tested the ability of this classifier to predict verbal WM load (high-low) from their associated neural activation patterns, and vice versa. We observed significant between-task prediction of load effects during WM maintenance, in posterior parietal and superior frontal regions of the dorsal attention network; in contrast, between-task prediction in sensory processing cortices was restricted to the encoding stage. Furthermore, between-task prediction of load effects was strongest in those participants presenting the highest capacity for the visual WM task. This study provides novel evidence for common, attention-based neural patterns supporting verbal and visual WM. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Self-determination, control, and reactions to changes in workload: a work simulation.

PubMed

Parker, Stacey L; Jimmieson, Nerina L; Amiot, Catherine E

2013-04-01

The objective of this experimental study is to capture the dynamic temporal processes that occur in changing work settings and to test how work control and individuals' motivational predispositions interact to predict reactions to these changes. To this aim, we examine the moderating effects of global self-determined and non-self-determined motivation, at different levels of work control, on participants' adaptation and stress reactivity to changes in workload during four trials of an inbox activity. Workload was increased or decreased at Trial 3, and adaptation to this change was examined via fluctuations in anxiety, coping, motivation, and performance. In support of the hypotheses, results revealed that, for non-self-determined individuals, low work control was stress-buffering and high work control was stress-exacerbating when predicting anxiety and intrinsic motivation. In contrast, for self-determined individuals, high work control facilitated the adaptive use of planning coping in response to a change in workload. Overall, this pattern of results demonstrates that, while high work control was anxiety-provoking and demotivating for non-self-determined individuals, self-determined individuals used high work control to implement an adaptive antecedent-focused emotion regulation strategy (i.e., planning coping) to meet situational demands. Other interactive effects of global motivation emerged on anxiety, active coping, and task performance. These results and their practical implications are discussed.

Empathy-Related Responses to Depicted People in Art Works

PubMed Central

Kesner, Ladislav; Horáček, Jiří

2017-01-01

Existing theories of empathic response to visual art works postulate the primacy of automatic embodied reaction to images based on mirror neuron mechanisms. Arguing for a more inclusive concept of empathy-related response and integrating four distinct bodies of literature, we discuss contextual, and personal factors which modulate empathic response to depicted people. We then present an integrative model of empathy-related responses to depicted people in art works. The model assumes that a response to empathy-eliciting figural artworks engages the dynamic interaction of two mutually interlinked sets of processes: socio-affective/cognitive processing, related to the person perception, and esthetic processing, primarily concerned with esthetic appreciation and judgment and attention to non-social aspects of the image. The model predicts that the specific pattern of interaction between empathy-related and esthetic processing is co-determined by several sets of factors: (i) the viewer's individual characteristics, (ii) the context variables (which include various modes of priming by narratives and other images), (iii) multidimensional features of the image, and (iv) aspects of a viewer's response. Finally we propose that the model is implemented by the interaction of functionally connected brain networks involved in socio-cognitive and esthetic processing. PMID:28286487

Processing speed and visuospatial executive function predict visual working memory ability in older adults.

PubMed

Brown, Louise A; Brockmole, James R; Gow, Alan J; Deary, Ian J

2012-01-01

BACKGROUND/STUDY CONTEXT: Visual working memory (VWM) has been shown to be particularly age sensitive. Determining which measures share variance with this cognitive ability in older adults may help to elucidate the key factors underlying the effects of aging. Predictors of VWM (measured by a modified Visual Patterns Test) were investigated in a subsample (N = 44, mean age = 73) of older adults from the Lothian Birth Cohort 1936 (LBC1936; Deary et al., 2007 , BMC Geriatrics, 7, 28). Childhood intelligence (Moray House Test) and contemporaneous measures of processing speed (four-choice reaction time), executive function (verbal fluency; block design), and spatial working memory (backward spatial span), were assessed as potential predictors. All contemporaneous measures except verbal fluency were significantly associated with VWM, and processing speed had the largest effect size (r = -.53, p < .001). In linear regression analysis, even after adjusting for childhood intelligence, processing speed and the executive measure associated with visuospatial organization accounted for 35% of the variance in VWM. Processing speed may affect VWM performance in older adults via speed of encoding and/or rate of rehearsal, while executive resources specifically associated with visuospatial material are also important.

Influence of Solvent on the Drug-Loading Process of Amphiphilic Nanogel Star Polymers.

PubMed

Carr, Amber C; Piunova, Victoria A; Maarof, Hasmerya; Rice, Julia E; Swope, William C

2018-05-31

We present an all-atom molecular dynamics study of the effect of a range of organic solvents (dichloromethane, diethyl ether, toluene, methanol, dimethyl sulfoxide, and tetrahydrofuran) on the conformations of a nanogel star polymeric nanoparticle with solvophobic and solvophilic structural elements. These nanoparticles are of particular interest for drug delivery applications. As drug loading generally takes place in an organic solvent, this work serves to provide insight into the factors controlling the early steps of that process. Our work suggests that nanoparticle conformational structure is highly sensitive to the choice of solvent, providing avenues for further study as well as predictions for both computational and experimental explorations of the drug-loading process. Our findings suggest that when used in the drug-loading process, dichloromethane, tetrahydrofuran, and toluene allow for a more extensive and increased drug-loading into the interior of nanogel star polymers of the composition studied here. In contrast, methanol is more likely to support shallow or surface loading and, consequently, faster drug release rates. Finally, diethyl ether should not work in a formulation process since none of the regions of the nanogel star polymer appear to be sufficiently solvated by it.

Sensory processing patterns predict the integration of information held in visual working memory.

PubMed

Lowe, Matthew X; Stevenson, Ryan A; Wilson, Kristin E; Ouslis, Natasha E; Barense, Morgan D; Cant, Jonathan S; Ferber, Susanne

2016-02-01

Given the limited resources of visual working memory, multiple items may be remembered as an averaged group or ensemble. As a result, local information may be ill-defined, but these ensemble representations provide accurate diagnostics of the natural world by combining gist information with item-level information held in visual working memory. Some neurodevelopmental disorders are characterized by sensory processing profiles that predispose individuals to avoid or seek-out sensory stimulation, fundamentally altering their perceptual experience. Here, we report such processing styles will affect the computation of ensemble statistics in the general population. We identified stable adult sensory processing patterns to demonstrate that individuals with low sensory thresholds who show a greater proclivity to engage in active response strategies to prevent sensory overstimulation are less likely to integrate mean size information across a set of similar items and are therefore more likely to be biased away from the mean size representation of an ensemble display. We therefore propose the study of ensemble processing should extend beyond the statistics of the display, and should also consider the statistics of the observer. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Statistical Tools And Artificial Intelligence Approaches To Predict Fracture In Bulk Forming Processes

NASA Astrophysics Data System (ADS)

Di Lorenzo, R.; Ingarao, G.; Fonti, V.

2007-05-01

The crucial task in the prevention of ductile fracture is the availability of a tool for the prediction of such defect occurrence. The technical literature presents a wide investigation on this topic and many contributions have been given by many authors following different approaches. The main class of approaches regards the development of fracture criteria: generally, such criteria are expressed by determining a critical value of a damage function which depends on stress and strain paths: ductile fracture is assumed to occur when such critical value is reached during the analysed process. There is a relevant drawback related to the utilization of ductile fracture criteria; in fact each criterion usually has good performances in the prediction of fracture for particular stress - strain paths, i.e. it works very well for certain processes but may provide no good results for other processes. On the other hand, the approaches based on damage mechanics formulation are very effective from a theoretical point of view but they are very complex and their proper calibration is quite difficult. In this paper, two different approaches are investigated to predict fracture occurrence in cold forming operations. The final aim of the proposed method is the achievement of a tool which has a general reliability i.e. it is able to predict fracture for different forming processes. The proposed approach represents a step forward within a research project focused on the utilization of innovative predictive tools for ductile fracture. The paper presents a comparison between an artificial neural network design procedure and an approach based on statistical tools; both the approaches were aimed to predict fracture occurrence/absence basing on a set of stress and strain paths data. The proposed approach is based on the utilization of experimental data available, for a given material, on fracture occurrence in different processes. More in detail, the approach consists in the analysis of experimental tests in which fracture occurs followed by the numerical simulations of such processes in order to track the stress-strain paths in the workpiece region where fracture is expected. Such data are utilized to build up a proper data set which was utilized both to train an artificial neural network and to perform a statistical analysis aimed to predict fracture occurrence. The developed statistical tool is properly designed and optimized and is able to recognize the fracture occurrence. The reliability and predictive capability of the statistical method were compared with the ones obtained from an artificial neural network developed to predict fracture occurrence. Moreover, the approach is validated also in forming processes characterized by a complex fracture mechanics.

Approach/Avoidance Orientations Affect Self-Construal and Identification with In-group

PubMed Central

Nussinson, Ravit; Häfner, Michael; Seibt, Beate; Strack, Fritz; Trope, Yaacov

2011-01-01

Approach and avoidance are two basic motivational orientations. Their activation influences cognitive and perceptive processes: Previous work suggests that an approach orientation instigates a focus on larger units as compared to avoidance. Study 1 confirms this assumption using a paradigm that more directly taps a person’s tendency to represent objects as belonging to small or large units than prior studies. It was further predicted that the self should also be represented as belonging to larger units, and hence be more interdependent under approach than under avoidance. Study 2 supports this prediction. As a consequence of this focus on belonging to larger units, it was finally predicted that approach results in a stronger identification with one’s in-group than avoidance. Studies 3 and 4 support that prediction. PMID:22844229

Feed-Forward Neural Network Prediction of the Mechanical Properties of Sandcrete Materials

PubMed Central

Asteris, Panagiotis G.; Roussis, Panayiotis C.; Douvika, Maria G.

2017-01-01

This work presents a soft-sensor approach for estimating critical mechanical properties of sandcrete materials. Feed-forward (FF) artificial neural network (ANN) models are employed for building soft-sensors able to predict the 28-day compressive strength and the modulus of elasticity of sandcrete materials. To this end, a new normalization technique for the pre-processing of data is proposed. The comparison of the derived results with the available experimental data demonstrates the capability of FF ANNs to predict with pinpoint accuracy the mechanical properties of sandcrete materials. Furthermore, the proposed normalization technique has been proven effective and robust compared to other normalization techniques available in the literature. PMID:28598400

Leveraging LSTM for rapid intensifications prediction of tropical cyclones

NASA Astrophysics Data System (ADS)

Li, Y.; Yang, R.; Yang, C.; Yu, M.; Hu, F.; Jiang, Y.

2017-10-01

Tropical cyclones (TCs) usually cause severe damages and destructions. TC intensity forecasting helps people prepare for the extreme weather and could save lives and properties. Rapid Intensifications (RI) of TCs are the major error sources of TC intensity forecasting. A large number of factors, such as sea surface temperature and wind shear, affect the RI processes of TCs. Quite a lot of work have been done to identify the combination of conditions most favorable to RI. In this study, deep learning method is utilized to combine conditions for RI prediction of TCs. Experiments show that the long short-term memory (LSTM) network provides the ability to leverage past conditions to predict TC rapid intensifications.

Advanced modelling, monitoring, and process control of bioconversion systems

NASA Astrophysics Data System (ADS)

Schmitt, Elliott C.

Production of fuels and chemicals from lignocellulosic biomass is an increasingly important area of research and industrialization throughout the world. In order to be competitive with fossil-based fuels and chemicals, maintaining cost-effectiveness is critical. Advanced process control (APC) and optimization methods could significantly reduce operating costs in the biorefining industry. Two reasons APC has previously proven challenging to implement for bioprocesses include: lack of suitable online sensor technology of key system components, and strongly nonlinear first principal models required to predict bioconversion behavior. To overcome these challenges batch fermentations with the acetogen Moorella thermoacetica were monitored with Raman spectroscopy for the conversion of real lignocellulosic hydrolysates and a kinetic model for the conversion of synthetic sugars was developed. Raman spectroscopy was shown to be effective in monitoring the fermentation of sugarcane bagasse and sugarcane straw hydrolysate, where univariate models predicted acetate concentrations with a root mean square error of prediction (RMSEP) of 1.9 and 1.0 g L-1 for bagasse and straw, respectively. Multivariate partial least squares (PLS) models were employed to predict acetate, xylose, glucose, and total sugar concentrations for both hydrolysate fermentations. The PLS models were more robust than univariate models, and yielded a percent error of approximately 5% for both sugarcane bagasse and sugarcane straw. In addition, a screening technique was discussed for improving Raman spectra of hydrolysate samples prior to collecting fermentation data. Furthermore, a mechanistic model was developed to predict batch fermentation of synthetic glucose, xylose, and a mixture of the two sugars to acetate. The models accurately described the bioconversion process with an RMSEP of approximately 1 g L-1 for each model and provided insights into how kinetic parameters changed during dual substrate fermentation with diauxic growth. Model predictive control (MPC), an advanced process control strategy, is capable of utilizing nonlinear models and sensor feedback to provide optimal input while ensuring critical process constraints are met. Using the microorganism Saccharomyces cerevisiae, a commonly used microorganism for biofuel production, and work performed with M. thermoacetica, a nonlinear MPC was implemented on a continuous membrane cell-recycle bioreactor (MCRB) for the conversion of glucose to ethanol. The dilution rate was used to control the ethanol productivity of the system will maintaining total substrate conversion above the constraint of 98%. PLS multivariate models for glucose (RMSEP 1.5 g L-1) and ethanol (RMSEP 0.4 g L-1) were robust in predicting concentrations and a mechanistic kinetic model built accurately predicted continuous fermentation behavior. A setpoint trajectory, ranging from 2 - 4.5 g L-1 h-1 for productivity was closely tracked by the fermentation system using Raman measurements and an extended Kalman filter to estimate biomass concentrations. Overall, this work was able to demonstrate an effective approach for real-time monitoring and control of a complex fermentation system.

Subvocal articulatory rehearsal during verbal working memory in multiple sclerosis.

PubMed

Sweet, Lawrence H; Vanderhill, Susan D; Jerskey, Beth A; Gordon, Norman M; Paul, Robert H; Cohen, Ronald A

2010-10-01

This study was designed to examine verbal working memory (VWM) components among multiple sclerosis (MS) patients and determine the influence of information processing speed. Of two frequently studied VWM sub-components, subvocal rehearsal was expected to be more affected by MS than short-term memory buffering. Furthermore, worse subvocal rehearsal was predicted to be specifically related to slower cognitive processing. Fifteen MS patients were administered a neuropsychological battery assessing VWM, processing speed, mood, fatigue, and disability. Participants performed a 2-Back VWM task with modified nested conditions designed to increase subvocal rehearsal (via inter-stimulus interval) and short-term memory buffering demands (via phonological similarity). Performance during these 2-Back conditions did not significantly differ and both exhibited strong positive correlations with disability. However, only scores on the subvocal rehearsal 2-Back were significantly related to performance on the remaining test battery, including processing speed and depressive symptoms. Findings suggest that performance during increased subvocal rehearsal demands is specifically influenced by cognitive processing speed and depressive symptoms.

The 2004 Parkfield, CA Earthquake: A Teachable Moment for Exploring Earthquake Processes, Probability, and Earthquake Prediction

NASA Astrophysics Data System (ADS)

Kafka, A.; Barnett, M.; Ebel, J.; Bellegarde, H.; Campbell, L.

2004-12-01

The occurrence of the 2004 Parkfield earthquake provided a unique "teachable moment" for students in our science course for teacher education majors. The course uses seismology as a medium for teaching a wide variety of science topics appropriate for future teachers. The 2004 Parkfield earthquake occurred just 15 minutes after our students completed a lab on earthquake processes and earthquake prediction. That lab included a discussion of the Parkfield Earthquake Prediction Experiment as a motivation for the exercises they were working on that day. Furthermore, this earthquake was recorded on an AS1 seismograph right in their lab, just minutes after the students left. About an hour after we recorded the earthquake, the students were able to see their own seismogram of the event in the lecture part of the course, which provided an excellent teachable moment for a lecture/discussion on how the occurrence of the 2004 Parkfield earthquake might affect seismologists' ideas about earthquake prediction. The specific lab exercise that the students were working on just before we recorded this earthquake was a "sliding block" experiment that simulates earthquakes in the classroom. The experimental apparatus includes a flat board on top of which are blocks of wood attached to a bungee cord and a string wrapped around a hand crank. Plate motion is modeled by slowly turning the crank, and earthquakes are modeled as events in which the block slips ("blockquakes"). We scaled the earthquake data and the blockquake data (using how much the string moved as a proxy for time) so that we could compare blockquakes and earthquakes. This provided an opportunity to use interevent-time histograms to teach about earthquake processes, probability, and earthquake prediction, and to compare earthquake sequences with blockquake sequences. We were able to show the students, using data obtained directly from their own lab, how global earthquake data fit a Poisson exponential distribution better than do the blockquake and Parkfield data. This provided opportunities for discussing the difference between Poisson and normal distributions, how those differences affect our estimation of future earthquake probabilities, the importance of both the mean and the standard deviation in predicting future behavior from a sequence of events, and how conditional probability is used to help seismologists predict future earthquakes given a known or theoretical distribution of past earthquakes.

Runoff as a factor in USLE/RUSLE technology

NASA Astrophysics Data System (ADS)

Kinnell, Peter

2014-05-01

Modelling erosion for prediction purposes started with the development of the Universal Soil Loss Equation the focus of which was the prediction of long term (~20) average annul soil loss from field sized areas. That purpose has been maintained in the subsequent revision RUSLE, the most widely used erosion prediction model in the world. The lack of ability to predict short term soil loss saw the development of so-called process based models like WEPP and EUROSEM which focussed on predicting event erosion but failed to improve the prediction of long term erosion where the RUSLE worked well. One of the features of erosion recognised in the so-called process based modes is the fact that runoff is a primary factor in rainfall erosion and some modifications of USLE/RUSLE model have been proposed have included runoff as in independent factor in determining event erosivity. However, these models have ignored fundamental mathematical rules. The USLE-M which replaces the EI30 index by the product of the runoff ratio and EI30 was developed from the concept that soil loss is the product of runoff and sediment concentration and operates in a way that obeys the mathematical rules upon which the USLE/RUSLE model was based. In accounts for event soil loss better that the EI30 index where runoff values are known or predicted adequately. RUSLE2 now includes a capacity to model runoff driven erosion.

An automated process for building reliable and optimal in vitro/in vivo correlation models based on Monte Carlo simulations.

PubMed

Sutton, Steven C; Hu, Mingxiu

2006-05-05

Many mathematical models have been proposed for establishing an in vitro/in vivo correlation (IVIVC). The traditional IVIVC model building process consists of 5 steps: deconvolution, model fitting, convolution, prediction error evaluation, and cross-validation. This is a time-consuming process and typically a few models at most are tested for any given data set. The objectives of this work were to (1) propose a statistical tool to screen models for further development of an IVIVC, (2) evaluate the performance of each model under different circumstances, and (3) investigate the effectiveness of common statistical model selection criteria for choosing IVIVC models. A computer program was developed to explore which model(s) would be most likely to work well with a random variation from the original formulation. The process used Monte Carlo simulation techniques to build IVIVC models. Data-based model selection criteria (Akaike Information Criteria [AIC], R2) and the probability of passing the Food and Drug Administration "prediction error" requirement was calculated. To illustrate this approach, several real data sets representing a broad range of release profiles are used to illustrate the process and to demonstrate the advantages of this automated process over the traditional approach. The Hixson-Crowell and Weibull models were often preferred over the linear. When evaluating whether a Level A IVIVC model was possible, the model selection criteria AIC generally selected the best model. We believe that the approach we proposed may be a rapid tool to determine which IVIVC model (if any) is the most applicable.

The importance, measurement and practical implications of worker's expectations for return to work.

PubMed

Young, Amanda E; Besen, Elyssa; Choi, YoonSun

2015-01-01

Workers' own expectations for return to work consistently predict work status. To advance the understanding of the relationship between RTW expectations and outcomes, we reviewed existing measures to determine those which we felt were the most likely to capture the construct. A comprehensive search of the work-disability rehabilitation literature was undertaken. The review of the measures was conducted in three steps: first, a review of terminology; second, an examination of whether a time reference was included; third, an evaluation of ease of comprehension, and applicability across contexts. A total of 42 different measures were identified. One of the most striking findings was the inconsistency in terminology. Measures were also limited by not including a time reference. Problems were also identified with regards to ease of understanding, utility of response options, and applicability in a wide variety of research and applied settings. Most previously used measures contain elements that potentially limit utility. However, it would seem that further development can overcome these, resulting in a tool that provides risk prediction information, and an opportunity to start a conversation to help identify problems that might negatively impact a worker's movement through the RTW process and the outcomes achieved. Implications for Rehabilitation Return to work is an integral part of workplace injury management. The capture of RTW expectations affords a way to identify the potential for less than optimal RTW processes and outcomes. A mismatch between an injured worker's expectations and what other stakeholders might expect suggests that efforts could be made to determine what is causing the injured worker's concerns. Once underling issues are identified, work can be put into resolving these so that the worker's return to the workplace is not impeded.

Predictors of working beyond retirement in older workers with and without a chronic disease - results from data linkage of Dutch questionnaire and registry data.

PubMed

de Wind, Astrid; Scharn, Micky; Geuskens, Goedele A; van der Beek, Allard J; Boot, Cécile R L

2018-02-17

An increasing number of retirees continue to work beyond retirement despite being eligible to retire. As the prevalence of chronic disease increases with age, working beyond retirement may go along with having a chronic disease. Working beyond retirement may be different for retirees with and without chronic disease. We aim to investigate whether demographic, socioeconomic and work characteristics, health and social factors predict working beyond retirement, in workers with and without a chronic disease. Employees aged 56-64 years were selected from the Study on Transitions in Employment, Ability and Motivation (N = 1125). Questionnaire data on demographic and work characteristics, health, social factors, and working beyond retirement were linked to registry data from Statistics Netherlands on socioeconomic characteristics. Separate prediction models were built for retirees with and without chronic disease using multivariate logistic regression analyses. Workers without chronic disease were more likely to work beyond retirement compared to workers with chronic disease (27% vs 23%). In retirees with chronic disease, work and health factors predicted working beyond retirement, while in retirees without a chronic disease, work, health and social factors predicted working beyond retirement. In the final model for workers with chronic disease, healthcare work, better physical health, higher body height, lower physical load and no permanent contract were positively predictive of working beyond retirement. In the final model for workers without chronic disease, feeling full of life and being intensively physically active for > = 2 days per week were positively predictive of working beyond retirement; while manual labor, better recovery, and a partner who did not support working until the statutory retirement age, were negatively predictive of working beyond retirement. Work and health factors independently predicted working beyond retirement in workers with and without chronic disease, whereas social factors only did so among workers without chronic disease. Demographic and socioeconomic characteristics did not independently contribute to prediction of working beyond retirement in any group. As prediction of working beyond retirement was more difficult among workers with a chronic disease, future research is needed in this group.

Emotion, working memory task demands and individual differences predict behavior, cognitive effort and negative affect.

PubMed

Storbeck, Justin; Davidson, Nicole A; Dahl, Chelsea F; Blass, Sara; Yung, Edwin

2015-01-01

We examined whether positive and negative affect motivates verbal and spatial working memory processes, respectively, which have implications for the expenditure of mental effort. We argue that when emotion promotes cognitive tendencies that are goal incompatible with task demands, greater cognitive effort is required to perform well. We sought to investigate whether this increase in cognitive effort impairs behavioural control over a broad domain of self-control tasks. Moreover, we predicted that individuals with higher behavioural inhibition system (BIS) sensitivities would report more negative affect within the goal incompatible conditions because such individuals report higher negative affect during cognitive challenge. Positive or negative affective states were induced followed by completing a verbal or spatial 2-back working memory task. All participants then completed one of three self-control tasks. Overall, we observed that conditions of emotion and working memory incompatibility (positive/spatial and negative/verbal) performed worse on the self-control tasks, and within the incompatible conditions individuals with higher BIS sensitivities reported more negative affect at the end of the study. The combination of findings suggests that emotion and working memory compatibility reduces cognitive effort and impairs behavioural control.

Motor system contributions to verbal and non-verbal working memory.

PubMed

Liao, Diana A; Kronemer, Sharif I; Yau, Jeffrey M; Desmond, John E; Marvel, Cherie L

2014-01-01

Working memory (WM) involves the ability to maintain and manipulate information held in mind. Neuroimaging studies have shown that secondary motor areas activate during WM for verbal content (e.g., words or letters), in the absence of primary motor area activation. This activation pattern may reflect an inner speech mechanism supporting online phonological rehearsal. Here, we examined the causal relationship between motor system activity and WM processing by using transcranial magnetic stimulation (TMS) to manipulate motor system activity during WM rehearsal. We tested WM performance for verbalizable (words and pseudowords) and non-verbalizable (Chinese characters) visual information. We predicted that disruption of motor circuits would specifically affect WM processing of verbalizable information. We found that TMS targeting motor cortex slowed response times (RTs) on verbal WM trials with high (pseudoword) vs. low (real word) phonological load. However, non-verbal WM trials were also significantly slowed with motor TMS. WM performance was unaffected by sham stimulation or TMS over visual cortex (VC). Self-reported use of motor strategy predicted the degree of motor stimulation disruption on WM performance. These results provide evidence of the motor system's contributions to verbal and non-verbal WM processing. We speculate that the motor system supports WM by creating motor traces consistent with the type of information being rehearsed during maintenance.

Motor system contributions to verbal and non-verbal working memory

PubMed Central

Liao, Diana A.; Kronemer, Sharif I.; Yau, Jeffrey M.; Desmond, John E.; Marvel, Cherie L.

2014-01-01

Working memory (WM) involves the ability to maintain and manipulate information held in mind. Neuroimaging studies have shown that secondary motor areas activate during WM for verbal content (e.g., words or letters), in the absence of primary motor area activation. This activation pattern may reflect an inner speech mechanism supporting online phonological rehearsal. Here, we examined the causal relationship between motor system activity and WM processing by using transcranial magnetic stimulation (TMS) to manipulate motor system activity during WM rehearsal. We tested WM performance for verbalizable (words and pseudowords) and non-verbalizable (Chinese characters) visual information. We predicted that disruption of motor circuits would specifically affect WM processing of verbalizable information. We found that TMS targeting motor cortex slowed response times (RTs) on verbal WM trials with high (pseudoword) vs. low (real word) phonological load. However, non-verbal WM trials were also significantly slowed with motor TMS. WM performance was unaffected by sham stimulation or TMS over visual cortex (VC). Self-reported use of motor strategy predicted the degree of motor stimulation disruption on WM performance. These results provide evidence of the motor system’s contributions to verbal and non-verbal WM processing. We speculate that the motor system supports WM by creating motor traces consistent with the type of information being rehearsed during maintenance. PMID:25309402

Interactions of attention, emotion and motivation.

PubMed

Raymond, Jane

2009-01-01

Although successful visually guided action begins with sensory processes and ends with motor control, the intervening processes related to the appropriate selection of information for processing are especially critical because of the brain's limited capacity to handle information. Three important mechanisms--attention, emotion and motivation--contribute to the prioritization and selection of information. In this chapter, the interplay between these systems is discussed with emphasis placed on interactions between attention (or immediate task relevance of stimuli) and emotion (or affective evaluation of stimuli), and between attention and motivation (or the predicted value of stimuli). Although numerous studies have shown that emotional stimuli modulate mechanisms of selective attention in humans, little work has been directed at exploring whether such interactions can be reciprocal, that is, whether attention can influence emotional response. Recent work on this question (showing that distracting information is typically devalued upon later encounters) is reviewed in the first half of the chapter. In the second half, some recent experiments exploring how prior value-prediction learning (i.e., learning to associate potential outcomes, good or bad, with specific stimuli) plays a role in visual selection and conscious perception. The results indicate that some aspects of motivation act on selection independently of traditionally defined attention and other aspects interact with it.

The Relationships Between Microstructure, Tensile Properties and Fatigue Life in Ti-5Al-5V-5Mo-3Cr-0.4Fe (Ti-5553)

NASA Astrophysics Data System (ADS)

Foltz, John W., IV

beta-titanium alloys are being increasingly used in airframes as a way to decrease the weight of the aircraft. As a result of this movement, Ti-5Al-5V-5Mo-3Cr-0.4Fe (Timetal 555), a high-strength beta titanium alloy, is being used on the current generation of landing gear. This alloy features good combinations of strength, ductility, toughness and fatigue life in alpha+beta processed conditions, but little is known about beta-processed conditions. Recent work by the Center for the Accelerated Maturation of Materials (CAMM) research group at The Ohio State University has improved the tensile property knowledge base for beta-processed conditions in this alloy, and this thesis augments the aforementioned development with description of how microstructure affects fatigue life. In this work, beta-processed microstructures have been produced in a Gleeble(TM) thermomechanical simulator and subsequently characterized with a combination of electron and optical microscopy techniques. Four-point bending fatigue tests have been carried out on the material to characterize fatigue life. All the microstructural conditions have been fatigue tested with the maximum test stress equal to 90% of the measured yield strength. The subsequent results from tensile tests, fatigue tests, and microstructural quantification have been analyzed using Bayesian neural networks in an attempt to predict fatigue life using microstructural and tensile inputs. Good correlation has been developed between lifetime predictions and experimental results using microstructure and tensile inputs. Trained Bayesian neural networks have also been used in a predictive fashion to explore functional dependencies between these inputs and fatigue life. In this work, one section discusses the thermal treatments that led to the observed microstructures, and the possible sequence of precipitation that led to these microstructures. The thesis then describes the implications of microstructure on fatigue life and implications of tensile properties on fatigue life. Several additional experiments are then described that highlight possible causes for the observed dependence of microstructure on fatigue life, including fractographic evidence to provide support of microstructural dependencies.

Daily fluctuations in teachers' well-being: a diary study using the Job Demands-Resources model.

PubMed

Simbula, Silvia

2010-10-01

The study tests the dynamic nature of the Job Demands-Resources model with regard to both motivational and health impairment processes. It does so by examining whether daily fluctuations in co-workers' support (i.e., a typical job resource) and daily fluctuations in work/family conflict (i.e., a typical job demand) predict day-levels of job satisfaction and mental health through work engagement and exhaustion, respectively. A total of 61 schoolteachers completed a general questionnaire and a daily survey over a period of five consecutive work days. Multilevel analyses provided evidence for both the above processes. Consistently with the hypotheses, our results showed that day-level work engagement mediated the impact of day-level co-workers' support on day-level job satisfaction and day-level mental health, after general levels of work engagement and outcome variables had been controlled for. Moreover, day-level exhaustion mediated the relationship between day-level work/family conflict and day-level job satisfaction and day-level mental health after general levels of exhaustion and outcome variables had been controlled for. These findings provide new insights into the dynamic psychological processes that determine daily fluctuations in employee well-being. Such insights may be transformed into job redesign strategies and other interventions designed to enhance work-related psychological well-being on a daily level.

Predicting Levels of Reading and Writing Achievement in Typically Developing, English-Speaking 2nd and 5th Graders

PubMed Central

Jones, Jasmin Niedo; Abbott, Robert D.; Berninger, Virginia W.

2014-01-01

Human traits tend to fall along normal distributions. The aim of this research was to evaluate an evidence-based conceptual framework for predicting expected individual differences in reading and writing achievement outcomes for typically developing readers and writers in early and middle childhood from Verbal Reasoning with or without Working Memory Components (phonological, orthographic, and morphological word storage and processing units, phonological and orthographic loops, and rapid switching attention for cross-code integration). Verbal Reasoning (reconceptualized as Bidirectional Cognitive-Linguistic Translation) plus the Working Memory Components (reconceptualized as a language learning system) accounted for more variance than Verbal Reasoning alone, except for handwriting for which Working Memory Components alone were better predictors. Which predictors explained unique variance varied within and across reading (oral real word and pseudoword accuracy and rate, reading comprehension) and writing (handwriting, spelling, composing) skills and grade levels (second and fifth) in this longitudinal study. Educational applications are illustrated and theoretical and practical significance discussed. PMID:24948868

The Development of Cognitive Skills and Gains in Academic School Readiness for Children from Low-Income Families

PubMed Central

Welsh, Janet A.; Nix, Robert L.; Blair, Clancy; Bierman, Karen L.; Nelson, Keith E.

2010-01-01

This study examined developmental associations between growth in domain-general cognitive processes (working memory and attention control) and growth in domain-specific skills (emergent literacy and numeracy) across the pre-kindergarten year, and their relative contributions to kindergarten reading and math achievement. One hundred sixty-four Head Start children (44% African American or Latino; 57% female) were followed longitudinally. Path analyses revealed that working memory and attention control predicted growth in emergent literacy and numeracy skills during the pre-kindergarten year, and furthermore, that growth in these domain-general cognitive skills made unique contributions to the prediction of kindergarten math and reading achievement, controlling for growth in domain-specific skills. These findings extend research highlighting the importance of working memory and attention control for academic learning, demonstrating the effects in early childhood, prior to school entry. We discuss the implications of these findings for pre-kindergarten programs, particularly those designed to reduce the school readiness gaps associated with socio-economic disadvantage. PMID:20411025

Using attribute amnesia to test the limits of hyper-binding and associative deficits in working memory.

PubMed

McCormick-Huhn, John M; Chen, Hui; Wyble, Bradley P; Dennis, Nancy A

2018-02-01

Previous work has shown mixed evidence regarding age-related deficits for binding in working memory. The current study used the newly developed attribute amnesia effect (H. Chen & Wyble, 2015a) to test the associative-deficit hypothesis during working memory and to probe whether hyper-binding extends to include binding of de-selected information. In studies of attribute amnesia, participants use target attributes (e.g., identity, color) to demonstrate near ceiling levels of reporting of a second target attribute (e.g., location) across a series of trials (H. Chen & Wyble, 2015a, 2016). Yet, despite having just processed the target-defining attribute, they have difficulty reporting it on a surprise trial. This effect provides several predictions for associative binding in aging. The associative-deficit hypothesis predicts age-related decline on the surprise trial, whereas an extension of hyper-binding predicts age-related increase in performance in older adults. In Experiment 1, when working memory load was low, older adults demonstrated attribute amnesia equal to that found in younger adults. When load increased in Experiment 2, older adults again demonstrated attribute amnesia as well as an age deficit for reporting target attributes. In lieu of spontaneous binding, results suggest that expectancy plays a critical role in older adults' propensity to encode and bind target attributes in working memory. Results further suggest that expectancy alone is not enough for older adults to form bound representations when task demands are high. Taken together results revealed a boundary condition of hyper-binding and further provided conditional support for the associative-deficit hypothesis in working memory. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Temporal and Spatial Predictability of an Irrelevant Event Differently Affect Detection and Memory of Items in a Visual Sequence

PubMed Central

Ohyama, Junji; Watanabe, Katsumi

2016-01-01

We examined how the temporal and spatial predictability of a task-irrelevant visual event affects the detection and memory of a visual item embedded in a continuously changing sequence. Participants observed 11 sequentially presented letters, during which a task-irrelevant visual event was either present or absent. Predictabilities of spatial location and temporal position of the event were controlled in 2 × 2 conditions. In the spatially predictable conditions, the event occurred at the same location within the stimulus sequence or at another location, while, in the spatially unpredictable conditions, it occurred at random locations. In the temporally predictable conditions, the event timing was fixed relative to the order of the letters, while in the temporally unpredictable condition; it could not be predicted from the letter order. Participants performed a working memory task and a target detection reaction time (RT) task. Memory accuracy was higher for a letter simultaneously presented at the same location as the event in the temporally unpredictable conditions, irrespective of the spatial predictability of the event. On the other hand, the detection RTs were only faster for a letter simultaneously presented at the same location as the event when the event was both temporally and spatially predictable. Thus, to facilitate ongoing detection processes, an event must be predictable both in space and time, while memory processes are enhanced by temporally unpredictable (i.e., surprising) events. Evidently, temporal predictability has differential effects on detection and memory of a visual item embedded in a sequence of images. PMID:26869966

Temporal and Spatial Predictability of an Irrelevant Event Differently Affect Detection and Memory of Items in a Visual Sequence.

PubMed

Ohyama, Junji; Watanabe, Katsumi

2016-01-01

We examined how the temporal and spatial predictability of a task-irrelevant visual event affects the detection and memory of a visual item embedded in a continuously changing sequence. Participants observed 11 sequentially presented letters, during which a task-irrelevant visual event was either present or absent. Predictabilities of spatial location and temporal position of the event were controlled in 2 × 2 conditions. In the spatially predictable conditions, the event occurred at the same location within the stimulus sequence or at another location, while, in the spatially unpredictable conditions, it occurred at random locations. In the temporally predictable conditions, the event timing was fixed relative to the order of the letters, while in the temporally unpredictable condition; it could not be predicted from the letter order. Participants performed a working memory task and a target detection reaction time (RT) task. Memory accuracy was higher for a letter simultaneously presented at the same location as the event in the temporally unpredictable conditions, irrespective of the spatial predictability of the event. On the other hand, the detection RTs were only faster for a letter simultaneously presented at the same location as the event when the event was both temporally and spatially predictable. Thus, to facilitate ongoing detection processes, an event must be predictable both in space and time, while memory processes are enhanced by temporally unpredictable (i.e., surprising) events. Evidently, temporal predictability has differential effects on detection and memory of a visual item embedded in a sequence of images.

Investigating the intrinsic and extrinsic work values of 10th grade students in science-oriented charter schools

NASA Astrophysics Data System (ADS)

Ozer, Ozgur

The purpose of this study was to investigate to what extent gender, achievement level, and income level predict the intrinsic and extrinsic work values of 10th grade students. The study explored whether group differences were good predictors of scores in work values. The research was a descriptive, cross-sectional study conducted on 131 10th graders who attended science-oriented charter schools. Students took Super's Work Values Instrument, a Likert-type test that links to 15 work values, which can be categorized as intrinsic and extrinsic values (Super, 1970). Multiple regression analysis was employed as the main analysis followed by ANCOVA. Multiple regression analysis results indicated that there is evidence that 8.9% of the variance in intrinsic work values and 10.2% of the variance in extrinsic work values can be explained by the independent variables ( p < .05). Achievement Level and Income Level may help predict intrinsic work value scores; Achievement Level may also help predict extrinsic work values. Achievement Level was the covariate in ANCOVA. Results indicated that males (M = .174) in this sample have a higher mean of extrinsic work values than that of females (M = -.279). However, there was no statistically significant difference between the intrinsic work values by gender. One possible interpretation of this might be school choice; students in these science-oriented charter schools may have higher intrinsic work values regardless of gender. Results indicated that there was no statistically significant difference among the means of extrinsic work values by income level (p < .05). However, free lunch students (M = .268) have a higher mean of intrinsic work values than that of paid lunch students ( M = -.279). A possible interpretation of this might be that lower income students benefit greatly from the intrinsic work values in overcoming obstacles. Further research is needed in each of these areas. The study produced statistically significant results with little practical significance. Students, parents, teachers, and counselors may still be advised to consider the work value orientations of students during the career choice process.

The relationship between sustained inattentional blindness and working memory capacity.

PubMed

Beanland, Vanessa; Chan, Esther Hiu Chung

2016-04-01

Inattentional blindness, whereby observers fail to detect unexpected stimuli, has been robustly demonstrated in a range of situations. Originally research focused primarily on how stimulus characteristics and task demands affect inattentional blindness, but increasingly studies are exploring the influence of observer characteristics on the detection of unexpected stimuli. It has been proposed that individual differences in working memory capacity predict inattentional blindness, on the assumption that higher working memory capacity confers greater attentional capacity for processing unexpected stimuli. Unfortunately, empirical investigations of the association between inattentional blindness and working memory capacity have produced conflicting findings. To help clarify this relationship, we examined the relationship between inattentional blindness and working memory capacity in two samples (Ns = 195, 147) of young adults. We used three common variants of sustained inattentional blindness tasks, systematically manipulating the salience of the unexpected stimulus and primary task practice. Working memory capacity, measured by automated operation span (both Experiments 1 & 2) and N-back (Experiment 1 only) tasks, did not predict detection of the unexpected stimulus in any of the inattentional blindness tasks tested. Together with previous research, this undermines claims that there is a robust relationship between inattentional blindness and working memory capacity. Rather, it appears that any relationship between inattentional blindness and working memory is either too small to have practical significance or is moderated by other factors and consequently varies with attributes such as the sample characteristics within a given study.

Cerebrocerebellar networks during articulatory rehearsal and verbal working memory tasks.

PubMed

Chen, S H Annabel; Desmond, John E

2005-01-15

Converging evidence has implicated the cerebellum in verbal working memory. The current fMRI study sought to further characterize cerebrocerebellar participation in this cognitive process by revealing regions of activation common to a verbal working task and an articulatory control task, as well as regions that are uniquely activated by working memory. Consistent with our model's predictions, load-dependent activations were observed in Broca's area (BA 44/6) and the superior cerebellar hemisphere (VI/CrusI) for both working memory and motoric rehearsal. In contrast, activations unique to verbal working memory were found in the inferior parietal lobule (BA 40) and the right inferior cerebellum hemisphere (VIIB). These findings provide evidence for two cerebrocerebellar networks for verbal working memory: a frontal/superior cerebellar articulatory control system and a parietal/inferior cerebellar phonological storage system.

A model for prediction of profile and flatness of hot and cold rolled flat products in four-high mills

NASA Astrophysics Data System (ADS)

Overhagen, Christian; Mauk, Paul Josef

2018-05-01

For flat rolled products, the thickness profile in the transversal direction is one of the most important product properties. For further processing, a defined crown of the product is necessary. In the rolling process, several mechanical and thermal influences interact with each other to form the strip shape at the roll gap exit. In the present analysis, a process model for rolling of strip and sheet is presented. The core feature of the process model is a two-dimensional stress distribution model based on von Karman's differential equation. Sub models for the mechanical influences of work roll flattening as well as work and backup roll deflection and the thermal influence of work roll expansion have been developed or extended. The two-dimensional stress distribution serves as an input parameter for the roll deformation models. For work roll flattening, a three-dimensional model based on the Boussinesq problem is adopted, while the work and backup roll deflection, including contact flattening is calculated by means of finite beam elements. The thermal work roll crown is calculated with help of an axisymmetric numerical solution of the heat equation for the work roll, considering azimuthal averaging for the boundary conditions at the work roll surface. Results are presented for hot rolling of a strip in a seven-stand finishing train of a hot strip mill, showing the calculated evolution of the strip profile. A variation of the strip profile from the first to the 20th rolled strip is shown. This variation is addressed to the progressive increase of work roll temperature during the first 20 strips. It is shown that a CVC® system can lead to improvements in strip profile and therefore flatness.

Exposure and response prevention process predicts treatment outcome in youth with OCD.

PubMed

Kircanski, Katharina; Peris, Tara S

2015-04-01

Recent research on the treatment of adults with anxiety disorders suggests that aspects of the in-session exposure therapy process are relevant to clinical outcomes. However, few comprehensive studies have been conducted with children and adolescents. In the present study, 35 youth diagnosed with primary obsessive-compulsive disorder (OCD; M age = 12.9 years, 49% male, 63% Caucasian) completed 12 sessions of exposure and response prevention (ERP) in one of two treatment conditions as part of a pilot randomized controlled testing of a family focused intervention for OCD. Key exposure process variables, including youth self-reported distress during ERP and the quantity and quality of ERP completed, were computed. These variables were examined as predictors of treatment outcomes assessed at mid-treatment, post-treatment, and three-month follow-up, partialing treatment condition. In general, greater variability of distress during ERP and completing a greater proportion of combined exposures (i.e., exposures targeting more than one OC symptom at once) were predictive of better outcomes. Conversely, greater distress at the end of treatment was generally predictive of poorer outcomes. Finally, several variables, including within- and between-session decreases in distress during ERP, were not consistently predictive of outcomes. Findings signal potentially important facets of exposure for youth with OCD and have implications for treatment. A number of results also parallel recent findings in the adult literature, suggesting that there may be some continuity in exposure processes from child to adult development. Future work should examine additional measures of exposure process, such as psychophysiological arousal during exposure, in youth.

AISI/DOE Advanced Process Control Program Vol. 3 of 6 Microstructure Engineering in Hot Strip Mills, Part 1 of 2: Integrated Mathematical Model

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

J.K. Brimacombe; I.V. Samarasekera; E.B. Hawbolt

1999-07-31

This report describes the work of developing an integrated model used to predict the thermal history, deformation, roll forces, microstructural evolution and mechanical properties of steel strip in a hot-strip mill. This achievement results from a joint research effort that is part of the American Iron and Steel Institute's (AIS) Advanced Process Control Program, a collaboration between the U.S. DOE and fifteen North American Steelmakers.

Novel opportunities for computational biology and sociology in drug discovery☆

PubMed Central

Yao, Lixia; Evans, James A.; Rzhetsky, Andrey

2013-01-01

Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development, explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy–industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies. PMID:20349528

The impact of depuration on mussel hepatopancreas bacteriome composition and predicted metagenome.

PubMed

Rubiolo, J A; Lozano-Leon, A; Rodriguez-Souto, R; Fol Rodríguez, N; Vieytes, M R; Botana, L M

2018-07-01

Due to the rapid elimination of bacteria through normal behaviour of filter feeding and excretion, the decontamination of hazardous contaminating bacteria from shellfish is performed by depuration. This process, under conditions that maximize shellfish filtering activity, is a useful method to eliminate microorganisms from bivalves. The microbiota composition in bivalves reflects that of the environment of harvesting waters, so quite different bacteriomes would be expected in shellfish collected in different locations. Bacterial accumulation within molluscan shellfish occurs primarily in the hepatopancreas. In order to assess the effect of the depuration process on these different bacteriomes, in this work we used 16S RNA pyrosequencing and metagenome prediction to assess the impact of 15 h of depuration on the whole hepatopancreas bacteriome of mussels collected in three different locations.

Artificial neural network associated to UV/Vis spectroscopy for monitoring bioreactions in biopharmaceutical processes.

PubMed

Takahashi, Maria Beatriz; Leme, Jaci; Caricati, Celso Pereira; Tonso, Aldo; Fernández Núñez, Eutimio Gustavo; Rocha, José Celso

2015-06-01

Currently, mammalian cells are the most utilized hosts for biopharmaceutical production. The culture media for these cell lines include commonly in their composition a pH indicator. Spectroscopic techniques are used for biopharmaceutical process monitoring, among them, UV-Vis spectroscopy has found scarce applications. This work aimed to define artificial neural networks architecture and fit its parameters to predict some nutrients and metabolites, as well as viable cell concentration based on UV-Vis spectral data of mammalian cell bioprocess using phenol red in culture medium. The BHK-21 cell line was used as a mammalian cell model. Off-line spectra of supernatant samples taken from batches performed at different dissolved oxygen concentrations in two bioreactor configurations and with two pH control strategies were used to define two artificial neural networks. According to absolute errors, glutamine (0.13 ± 0.14 mM), glutamate (0.02 ± 0.02 mM), glucose (1.11 ± 1.70 mM), lactate (0.84 ± 0.68 mM) and viable cell concentrations (1.89 10(5) ± 1.90 10(5) cell/mL) were suitably predicted. The prediction error averages for monitored variables were lower than those previously reported using different spectroscopic techniques in combination with partial least squares or artificial neural network. The present work allows for UV-VIS sensor development, and decreases cost related to nutrients and metabolite quantifications.

Cognitive domains that predict time to diagnosis in prodromal Huntington disease.

PubMed

Harrington, Deborah Lynn; Smith, Megan M; Zhang, Ying; Carlozzi, Noelle E; Paulsen, Jane S

2012-06-01

Prodromal Huntington's disease (prHD) is associated with a myriad of cognitive changes but the domains that best predict time to clinical diagnosis have not been studied. This is a notable gap because some domains may be more sensitive to cognitive decline, which would inform clinical trials. The present study sought to characterise cognitive domains underlying a large test battery and for the first time, evaluate their ability to predict time to diagnosis. Participants included gene negative and gene positive prHD participants who were enrolled in the PREDICT-HD study. The CAG-age product (CAP) score was the measure of an individual's genetic signature. A factor analysis of 18 tests was performed to identify sets of measures or latent factors that elucidated core constructs of tests. Factor scores were then fit to a survival model to evaluate their ability to predict time to diagnosis. Six factors were identified: (1) speed/inhibition, (2) verbal working memory, (3) motor planning/speed, (4) attention-information integration, (5) sensory-perceptual processing and (6) verbal learning/memory. Factor scores were sensitive to worsening of cognitive functioning in prHD, typically more so than performances on individual tests comprising the factors. Only the motor planning/speed and sensory-perceptual processing factors predicted time to diagnosis, after controlling for CAP scores and motor symptoms. Conclusions The results suggest that motor planning/speed and sensory-perceptual processing are important markers of disease prognosis. The findings also have implications for using composite indices of cognition in preventive Huntington's disease trials where they may be more sensitive than individual tests.

A Novel Approach for Using Dielectric Spectroscopy to Predict Viable Cell Volume (VCV) in Early Process Development

PubMed Central

Downey, Brandon J; Graham, Lisa J; Breit, Jeffrey F; Glutting, Nathaniel K

2014-01-01

Online monitoring of viable cell volume (VCV) is essential to the development, monitoring, and control of bioprocesses. The commercial availability of steam-sterilizable dielectric-spectroscopy probes has enabled successful adoption of this technology as a key noninvasive method to measure VCV for cell-culture processes. Technological challenges still exist, however. For some cell lines, the technique's accuracy in predicting the VCV from probe-permittivity measurements declines as the viability of the cell culture decreases. To investigate the cause of this decrease in accuracy, divergences in predicted vs. actual VCV measurements were directly related to the shape of dielectric frequency scans collected during a cell culture. The changes in the shape of the beta dispersion, which are associated with changes in cell state, are quantified by applying a novel “area ratio” (AR) metric to frequency-scanning data from the dielectric-spectroscopy probes. The AR metric is then used to relate the shape of the beta dispersion to single-frequency permittivity measurements to accurately predict the offline VCV throughout an entire fed-batch run, regardless of cell state. This work demonstrates the possible feasibility of quantifying the shape of the beta dispersion, determined from frequency-scanning data, for enhanced measurement of VCV in mammalian cell cultures by applying a novel shape-characterization technique. In addition, this work demonstrates the utility of using changes in the shape of the beta dispersion to quantify cell health. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 30:479–487, 2014 PMID:24851255

Dorsolateral Prefrontal Cortex GABA Concentration in Humans Predicts Working Memory Load Processing Capacity.

PubMed

Yoon, Jong H; Grandelis, Anthony; Maddock, Richard J

2016-11-16

The discovery of neural mechanisms of working memory (WM) would significantly enhance our understanding of complex human behaviors and guide treatment development for WM-related impairments found in neuropsychiatric conditions and aging. Although the dorsolateral prefrontal cortex (DLPFC) has long been considered critical for WM, we still know little about the neural elements and pathways within the DLPFC that support WM in humans. In this study, we tested whether an individual's DLPFC gamma-aminobutryic acid (GABA) content predicts individual differences in WM task performance using a novel behavioral approach. Twenty-three healthy adults completed a task that measured the unique contribution of major WM components (memory load, maintenance, and distraction resistance) to performance. This was done to address the possibility that components have differing GABA dependencies and the failure to parse WM into components would lead to missing true associations with GABA. The subjects then had their DLPFC GABA content measured by single-voxel proton magnetic spectroscopy. We found that individuals with lower DLPFC GABA showed greater performance degradation with higher load, accounting for 31% of variance, p (corrected) = 0.015. This relationship was component, neurochemical, and brain region specific. DLPFC GABA content did not predict performance sensitivity to other components tested; DLPFC glutamate + glutamine and visual cortical GABA content did not predict load sensitivity. These results confirm the involvement of DLPFC GABA in WM load processing in humans and implicate factors controlling DLPFC GABA content in the neural mechanisms of WM and its impairments. This study demonstrated for the first time that the amount of gamma-aminobutryic acid (GABA), the major inhibitory neurotransmitter of the brain, in an individual's prefrontal cortex predicts working memory (WM) task performance. Given that WM is required for many of the most characteristic cognitive and behavioral capabilities in humans, this finding could have a significant impact on our understanding of the neural basis of complex human behavior. Furthermore, this finding suggests that efforts to preserve or increase brain GABA levels could be fruitful in remediating WM-related deficits associated with neuropsychiatric conditions. Copyright © 2016 the authors 0270-6474/16/3611788-07$15.00/0.

Clinical time series prediction: Toward a hierarchical dynamical system framework.

PubMed

Liu, Zitao; Hauskrecht, Milos

2015-09-01

Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

Transference interventions and the process between therapist and patient.

PubMed

Ulberg, Randi; Amlo, Svein; Critchfield, Kenneth L; Marble, Alice; Høglend, Per

2014-06-01

Interpreting the transference has been considered a core ingredient in psychodynamic psychotherapy. The effects of analyzing the transference are probably dependent on certain characteristics of the interventions themselves and the context in which transference interventions are given. The present study describes the development and use of a therapy process rating scale (Transference Work Scale; TWS) constructed to identify, categorize, and explore work with the transference. TWS has subscales that rate timing, content, and valence of the transference interventions, as well as response from the patient. Transcribed segments (10 min) from 51 different patients were scored with TWS by 2 independent raters. The interrater agreement on the TWS items was good to excellent. Clinical examples of transference work were also rated using the Structural Analysis of Social Behavior (SASB). TWS and SASB supplement each other. TWS might be a potentially useful tool to explore the interaction of timing, category, and valence of transference work in predicting in-session patient response as well as treatment outcome. (c) 2014 APA, all rights reserved.

Gender differences in working memory networks: A BrainMap meta-analysis

PubMed Central

Hill, Ashley C.; Laird, Angela R.; Robinson, Jennifer L.

2014-01-01

Gender differences in psychological processes have been of great interest in a variety of fields. While the majority of research in this area has focused on specific differences in relation to test performance, this study sought to determine the underlying neurofunctional differences observed during working memory, a pivotal cognitive process shown to be predictive of academic achievement and intelligence. Using the BrainMap database, we performed a meta-analysis and applied activation likelihood estimation to our search set. Our results demonstrate consistent working memory networks across genders, but also provide evidence for gender-specific networks whereby females consistently activate more limbic (e.g., amygdala and hippocampus) and prefrontal structures (e.g., right inferior frontal gyrus), and males activate a distributed network inclusive of more parietal regions. These data provide a framework for future investigation using functional or effective connectivity methods to elucidate the underpinnings of gender differences in neural network recruitment during working memory tasks. PMID:25042764

Gender differences in working memory networks: a BrainMap meta-analysis.

PubMed

Hill, Ashley C; Laird, Angela R; Robinson, Jennifer L

2014-10-01

Gender differences in psychological processes have been of great interest in a variety of fields. While the majority of research in this area has focused on specific differences in relation to test performance, this study sought to determine the underlying neurofunctional differences observed during working memory, a pivotal cognitive process shown to be predictive of academic achievement and intelligence. Using the BrainMap database, we performed a meta-analysis and applied activation likelihood estimation to our search set. Our results demonstrate consistent working memory networks across genders, but also provide evidence for gender-specific networks whereby females consistently activate more limbic (e.g., amygdala and hippocampus) and prefrontal structures (e.g., right inferior frontal gyrus), and males activate a distributed network inclusive of more parietal regions. These data provide a framework for future investigations using functional or effective connectivity methods to elucidate the underpinnings of gender differences in neural network recruitment during working memory tasks. Copyright © 2014 Elsevier B.V. All rights reserved.

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

USGS Publications Warehouse

Plant, Nathaniel G.

2016-01-01

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

Preliminary Empirical Models for Predicting Shrinkage, Part Geometry and Metallurgical Aspects of Ti-6Al-4V Shaped Metal Deposition Builds

NASA Astrophysics Data System (ADS)

Escobar-Palafox, Gustavo; Gault, Rosemary; Ridgway, Keith

2011-12-01

Shaped Metal Deposition (SMD) is an additive manufacturing process which creates parts layer by layer by weld depositions. In this work, empirical models that predict part geometry (wall thickness and outer diameter) and some metallurgical aspects (i.e. surface texture, portion of finer Widmanstätten microstructure) for the SMD process were developed. The models are based on an orthogonal fractional factorial design of experiments with four factors at two levels. The factors considered were energy level (a relationship between heat source power and the rate of raw material input.), step size, programmed diameter and travel speed. The models were validated using previous builds; the prediction error for part geometry was under 11%. Several relationships between the factors and responses were identified. Current had a significant effect on wall thickness; thickness increases with increasing current. Programmed diameter had a significant effect on percentage of shrinkage; this decreased with increasing component size. Surface finish decreased with decreasing step size and current.

Prediction Of Tensile And Shear Strength Of Friction Surfaced Tool Steel Deposit By Using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Manzoor Hussain, M.; Pitchi Raju, V.; Kandasamy, J.; Govardhan, D.

2018-04-01

Friction surface treatment is well-established solid technology and is used for deposition, abrasion and corrosion protection coatings on rigid materials. This novel process has wide range of industrial applications, particularly in the field of reclamation and repair of damaged and worn engineering components. In this paper, we present the prediction of tensile and shear strength of friction surface treated tool steel using ANN for simulated results of friction surface treatment. This experiment was carried out to obtain tool steel coatings of low carbon steel parts by changing contribution process parameters essentially friction pressure, rotational speed and welding speed. The simulation is performed by a 33-factor design that takes into account the maximum and least limits of the experimental work performed with the 23-factor design. Neural network structures, such as the Feed Forward Neural Network (FFNN), were used to predict tensile and shear strength of tool steel sediments caused by friction.

A Tribute to Charlie Chaplin: Induced Positive Affect Improves Reward-Based Decision-Learning in Parkinson’s Disease

PubMed Central

Ridderinkhof, K. Richard; van Wouwe, Nelleke C.; Band, Guido P. H.; Wylie, Scott A.; Van der Stigchel, Stefan; van Hees, Pieter; Buitenweg, Jessika; van de Vijver, Irene; van den Wildenberg, Wery P. M.

2012-01-01

Reward-based decision-learning refers to the process of learning to select those actions that lead to rewards while avoiding actions that lead to punishments. This process, known to rely on dopaminergic activity in striatal brain regions, is compromised in Parkinson’s disease (PD). We hypothesized that such decision-learning deficits are alleviated by induced positive affect, which is thought to incur transient boosts in midbrain and striatal dopaminergic activity. Computational measures of probabilistic reward-based decision-learning were determined for 51 patients diagnosed with PD. Previous work has shown these measures to rely on the nucleus caudatus (outcome evaluation during the early phases of learning) and the putamen (reward prediction during later phases of learning). We observed that induced positive affect facilitated learning, through its effects on reward prediction rather than outcome evaluation. Viewing a few minutes of comedy clips served to remedy dopamine-related problems associated with frontostriatal circuitry and, consequently, learning to predict which actions will yield reward. PMID:22707944

A Theoretical Model for Predicting Residual Stress Generation in Fabrication Process of Double-Ceramic-Layer Thermal Barrier Coating System.

PubMed

Song, Yan; Wu, Weijie; Xie, Feng; Liu, Yilun; Wang, Tiejun

2017-01-01

Residual stress arisen in fabrication process of Double-Ceramic-Layer Thermal Barrier Coating System (DCL-TBCs) has a significant effect on its quality and reliability. In this work, based on the practical fabrication process of DCL-TBCs and the force and moment equilibrium, a theoretical model was proposed at first to predict residual stress generation in its fabrication process, in which the temperature dependent material properties of DCL-TBCs were incorporated. Then, a Finite Element method (FEM) has been carried out to verify our theoretical model. Afterwards, some important geometric parameters for DCL-TBCs, such as the thickness ratio of stabilized Zirconia (YSZ, ZrO2-8%Y2O3) layer to Lanthanum Zirconate (LZ, La2Zr2O7) layer, which is adjustable in a wide range in the fabrication process, have a remarkable effect on its performance, therefore, the effect of this thickness ratio on residual stress generation in the fabrication process of DCL-TBCs has been systematically studied. In addition, some thermal spray treatment, such as the pre-heating treatment, its effect on residual stress generation has also been studied in this work. It is found that, the final residual stress mainly comes from the cooling down process in the fabrication of DCL-TBCs. Increasing the pre-heating temperature can obviously decrease the magnitude of residual stresses in LZ layer, YSZ layer and substrate. With the increase of the thickness ratio of YSZ layer to LZ layer, magnitudes of residual stresses arisen in LZ layer and YSZ layer will increase while residual stress in substrate will decrease.

A Theoretical Model for Predicting Residual Stress Generation in Fabrication Process of Double-Ceramic-Layer Thermal Barrier Coating System

PubMed Central

Song, Yan; Wu, Weijie; Xie, Feng; Liu, Yilun; Wang, Tiejun

2017-01-01

Residual stress arisen in fabrication process of Double-Ceramic-Layer Thermal Barrier Coating System (DCL-TBCs) has a significant effect on its quality and reliability. In this work, based on the practical fabrication process of DCL-TBCs and the force and moment equilibrium, a theoretical model was proposed at first to predict residual stress generation in its fabrication process, in which the temperature dependent material properties of DCL-TBCs were incorporated. Then, a Finite Element method (FEM) has been carried out to verify our theoretical model. Afterwards, some important geometric parameters for DCL-TBCs, such as the thickness ratio of stabilized Zirconia (YSZ, ZrO2-8%Y2O3) layer to Lanthanum Zirconate (LZ, La2Zr2O7) layer, which is adjustable in a wide range in the fabrication process, have a remarkable effect on its performance, therefore, the effect of this thickness ratio on residual stress generation in the fabrication process of DCL-TBCs has been systematically studied. In addition, some thermal spray treatment, such as the pre-heating treatment, its effect on residual stress generation has also been studied in this work. It is found that, the final residual stress mainly comes from the cooling down process in the fabrication of DCL-TBCs. Increasing the pre-heating temperature can obviously decrease the magnitude of residual stresses in LZ layer, YSZ layer and substrate. With the increase of the thickness ratio of YSZ layer to LZ layer, magnitudes of residual stresses arisen in LZ layer and YSZ layer will increase while residual stress in substrate will decrease. PMID:28103275

Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia.

PubMed

Cassidy, Clifford M; Van Snellenberg, Jared X; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa; Horga, Guillermo

2016-04-13

Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during ann-back working-memory task) and positron emission tomography using the radiotracer [(11)C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. It is unclear how communication between brain networks responds to changing environmental demands during complex cognitive processes. Also, unknown in regard to these network dynamics is the role of neuromodulators, such as dopamine, and whether their dysregulation could underlie cognitive deficits in neuropsychiatric illness. We found that connectivity between brain networks changes with working-memory load and greater increases predict better working memory performance; however, it was not related to capacity for dopamine release in the cortex. Patients with schizophrenia did show dynamic internetwork connectivity; however, this was more weakly associated with successful performance in patients compared with healthy individuals. Our findings indicate that dynamic interactions between brain networks may support the type of flexible adaptations essential to goal-directed behavior. Copyright © 2016 the authors 0270-6474/16/364378-12$15.00/0.

Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia

PubMed Central

Van Snellenberg, Jared X.; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa

2016-01-01

Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during an n-back working-memory task) and positron emission tomography using the radiotracer [11C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. SIGNIFICANCE STATEMENT It is unclear how communication between brain networks responds to changing environmental demands during complex cognitive processes. Also, unknown in regard to these network dynamics is the role of neuromodulators, such as dopamine, and whether their dysregulation could underlie cognitive deficits in neuropsychiatric illness. We found that connectivity between brain networks changes with working-memory load and greater increases predict better working memory performance; however, it was not related to capacity for dopamine release in the cortex. Patients with schizophrenia did show dynamic internetwork connectivity; however, this was more weakly associated with successful performance in patients compared with healthy individuals. Our findings indicate that dynamic interactions between brain networks may support the type of flexible adaptations essential to goal-directed behavior. PMID:27076432

Near-infrared chemical imaging (NIR-CI) as a process monitoring solution for a production line of roll compaction and tableting.

PubMed

Khorasani, Milad; Amigo, José M; Sun, Changquan Calvin; Bertelsen, Poul; Rantanen, Jukka

2015-06-01

In the present study the application of near-infrared chemical imaging (NIR-CI) supported by chemometric modeling as non-destructive tool for monitoring and assessing the roller compaction and tableting processes was investigated. Based on preliminary risk-assessment, discussion with experts and current work from the literature the critical process parameter (roll pressure and roll speed) and critical quality attributes (ribbon porosity, granule size, amount of fines, tablet tensile strength) were identified and a design space was established. Five experimental runs with different process settings were carried out which revealed intermediates (ribbons, granules) and final products (tablets) with different properties. Principal component analysis (PCA) based model of NIR images was applied to map the ribbon porosity distribution. The ribbon porosity distribution gained from the PCA based NIR-CI was used to develop predictive models for granule size fractions. Predictive methods with acceptable R(2) values could be used to predict the granule particle size. Partial least squares regression (PLS-R) based model of the NIR-CI was used to map and predict the chemical distribution and content of active compound for both roller compacted ribbons and corresponding tablets. In order to select the optimal process, setting the standard deviation of tablet tensile strength and tablet weight for each tablet batch was considered. Strong linear correlation between tablet tensile strength and amount of fines and granule size was established, respectively. These approaches are considered to have a potentially large impact on quality monitoring and control of continuously operating manufacturing lines, such as roller compaction and tableting processes. Copyright © 2015 Elsevier B.V. All rights reserved.

PARAMO: A Parallel Predictive Modeling Platform for Healthcare Analytic Research using Electronic Health Records

PubMed Central

Ng, Kenney; Ghoting, Amol; Steinhubl, Steven R.; Stewart, Walter F.; Malin, Bradley; Sun, Jimeng

2014-01-01

Objective Healthcare analytics research increasingly involves the construction of predictive models for disease targets across varying patient cohorts using electronic health records (EHRs). To facilitate this process, it is critical to support a pipeline of tasks: 1) cohort construction, 2) feature construction, 3) cross-validation, 4) feature selection, and 5) classification. To develop an appropriate model, it is necessary to compare and refine models derived from a diversity of cohorts, patient-specific features, and statistical frameworks. The goal of this work is to develop and evaluate a predictive modeling platform that can be used to simplify and expedite this process for health data. Methods To support this goal, we developed a PARAllel predictive MOdeling (PARAMO) platform which 1) constructs a dependency graph of tasks from specifications of predictive modeling pipelines, 2) schedules the tasks in a topological ordering of the graph, and 3) executes those tasks in parallel. We implemented this platform using Map-Reduce to enable independent tasks to run in parallel in a cluster computing environment. Different task scheduling preferences are also supported. Results We assess the performance of PARAMO on various workloads using three datasets derived from the EHR systems in place at Geisinger Health System and Vanderbilt University Medical Center and an anonymous longitudinal claims database. We demonstrate significant gains in computational efficiency against a standard approach. In particular, PARAMO can build 800 different models on a 300,000 patient data set in 3 hours in parallel compared to 9 days if running sequentially. Conclusion This work demonstrates that an efficient parallel predictive modeling platform can be developed for EHR data. This platform can facilitate large-scale modeling endeavors and speed-up the research workflow and reuse of health information. This platform is only a first step and provides the foundation for our ultimate goal of building analytic pipelines that are specialized for health data researchers. PMID:24370496

PARAMO: a PARAllel predictive MOdeling platform for healthcare analytic research using electronic health records.

PubMed

Ng, Kenney; Ghoting, Amol; Steinhubl, Steven R; Stewart, Walter F; Malin, Bradley; Sun, Jimeng

2014-04-01

Healthcare analytics research increasingly involves the construction of predictive models for disease targets across varying patient cohorts using electronic health records (EHRs). To facilitate this process, it is critical to support a pipeline of tasks: (1) cohort construction, (2) feature construction, (3) cross-validation, (4) feature selection, and (5) classification. To develop an appropriate model, it is necessary to compare and refine models derived from a diversity of cohorts, patient-specific features, and statistical frameworks. The goal of this work is to develop and evaluate a predictive modeling platform that can be used to simplify and expedite this process for health data. To support this goal, we developed a PARAllel predictive MOdeling (PARAMO) platform which (1) constructs a dependency graph of tasks from specifications of predictive modeling pipelines, (2) schedules the tasks in a topological ordering of the graph, and (3) executes those tasks in parallel. We implemented this platform using Map-Reduce to enable independent tasks to run in parallel in a cluster computing environment. Different task scheduling preferences are also supported. We assess the performance of PARAMO on various workloads using three datasets derived from the EHR systems in place at Geisinger Health System and Vanderbilt University Medical Center and an anonymous longitudinal claims database. We demonstrate significant gains in computational efficiency against a standard approach. In particular, PARAMO can build 800 different models on a 300,000 patient data set in 3h in parallel compared to 9days if running sequentially. This work demonstrates that an efficient parallel predictive modeling platform can be developed for EHR data. This platform can facilitate large-scale modeling endeavors and speed-up the research workflow and reuse of health information. This platform is only a first step and provides the foundation for our ultimate goal of building analytic pipelines that are specialized for health data researchers. Copyright © 2013 Elsevier Inc. All rights reserved.

Impact of polymer film thickness and cavity size on polymer flow during embossing : towards process design rules for nanoimprint lithography.

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

Schunk, Peter Randall; King, William P.; Sun, Amy Cha-Tien

2006-08-01

This paper presents continuum simulations of polymer flow during nanoimprint lithography (NIL). The simulations capture the underlying physics of polymer flow from the nanometer to millimeter length scale and examine geometry and thermophysical process quantities affecting cavity filling. Variations in embossing tool geometry and polymer film thickness during viscous flow distinguish different flow driving mechanisms. Three parameters can predict polymer deformation mode: cavity width to polymer thickness ratio, polymer supply ratio, and Capillary number. The ratio of cavity width to initial polymer film thickness determines vertically or laterally dominant deformation. The ratio of indenter width to residual film thickness measuresmore » polymer supply beneath the indenter which determines Stokes or squeeze flow. The local geometry ratios can predict a fill time based on laminar flow between plates, Stokes flow, or squeeze flow. Characteristic NIL capillary number based on geometry-dependent fill time distinguishes between capillary or viscous driven flows. The three parameters predict filling modes observed in published studies of NIL deformation over nanometer to millimeter length scales. The work seeks to establish process design rules for NIL and to provide tools for the rational design of NIL master templates, resist polymers, and process parameters.« less

Motivation, working memory, and decision making: a cognitive-motivational theory of personality vulnerability to alcoholism.

PubMed

Finn, Peter R

2002-09-01

This article presents a cognitive-motivational theory (CMT) of the mechanisms associated with three basic dimensions of personality vulnerability to alcoholism, impulsivity/novelty seeking, harm avoidance, and excitement seeking. CMT describes the interrelationships between activity in basic motivational systems and attentional, decision-making and working memory processes as the mechanisms associated with variation in each personality trait. Impulsivity/novelty seeking reflects activity in both appetitive and inhibitory motivational systems, greater attention to reward cues, and increased emotional reactivity to reward and frustration. Harm avoidance reflects individual differences in fearfulness and activity in specific inhibitory systems. Excitement seeking reflects the need to engage in appetitive behaviors in less predictable environments to experience positive affect. CMT also describes the impact of working memory and the specific motivational processes underlying each trait dimension on the dynamics of decision making from the perspective of decision field theory.

Stress, Psychosocial Mediators, and Cognitive Mediators in Parents of Child Cancer Patients and Cancer Survivors: Attention and Working Memory Pathway Perspectives.

PubMed

Vander Haegen, Marie; Luminet, Olivier

2015-01-01

This review examines stress and its consequences on attention and working memory, stress symptoms in parents of child cancer patients and survivors and long-term consequences of stress on cognitive processing in parents of child cancer survivors. Eligible studies were experimental, meta-analyses, and qualitative (2000-2013) from Pubmed, Medline, the Cochrane Library, PsycArticles, and Google Scholar. We identified 92 eligible papers. They showed that elevated stress can impede performances on tasks requiring attention and memory patterns. In pediatric oncology, parental stress increased shortly after diagnosis involving depression and anxiety. Consequences of stress on cognitive performances were observed mainly among depressed individuals. As regards parents of child cancer survivors, female gender, low Socioeconomic Status (SES), and innate traits of anxiety/anger predicted the development of PTSS. Evidence of stress on attention and working memory processes in parents of child cancer survivors is insufficiently developed.

Central Executive Dysfunction and Deferred Prefrontal Processing in Veterans with Gulf War Illness.

PubMed

Hubbard, Nicholas A; Hutchison, Joanna L; Motes, Michael A; Shokri-Kojori, Ehsan; Bennett, Ilana J; Brigante, Ryan M; Haley, Robert W; Rypma, Bart

2014-05-01

Gulf War Illness is associated with toxic exposure to cholinergic disruptive chemicals. The cholinergic system has been shown to mediate the central executive of working memory (WM). The current work proposes that impairment of the cholinergic system in Gulf War Illness patients (GWIPs) leads to behavioral and neural deficits of the central executive of WM. A large sample of GWIPs and matched controls (MCs) underwent functional magnetic resonance imaging during a varied-load working memory task. Compared to MCs, GWIPs showed a greater decline in performance as WM-demand increased. Functional imaging suggested that GWIPs evinced separate processing strategies, deferring prefrontal cortex activity from encoding to retrieval for high demand conditions. Greater activity during high-demand encoding predicted greater WM performance. Behavioral data suggest that WM executive strategies are impaired in GWIPs. Functional data further support this hypothesis and suggest that GWIPs utilize less effective strategies during high-demand WM.

Central Executive Dysfunction and Deferred Prefrontal Processing in Veterans with Gulf War Illness

PubMed Central

Hubbard, Nicholas A.; Hutchison, Joanna L.; Motes, Michael A.; Shokri-Kojori, Ehsan; Bennett, Ilana J.; Brigante, Ryan M.; Haley, Robert W.; Rypma, Bart

2015-01-01

Gulf War Illness is associated with toxic exposure to cholinergic disruptive chemicals. The cholinergic system has been shown to mediate the central executive of working memory (WM). The current work proposes that impairment of the cholinergic system in Gulf War Illness patients (GWIPs) leads to behavioral and neural deficits of the central executive of WM. A large sample of GWIPs and matched controls (MCs) underwent functional magnetic resonance imaging during a varied-load working memory task. Compared to MCs, GWIPs showed a greater decline in performance as WM-demand increased. Functional imaging suggested that GWIPs evinced separate processing strategies, deferring prefrontal cortex activity from encoding to retrieval for high demand conditions. Greater activity during high-demand encoding predicted greater WM performance. Behavioral data suggest that WM executive strategies are impaired in GWIPs. Functional data further support this hypothesis and suggest that GWIPs utilize less effective strategies during high-demand WM. PMID:25767746

Time and interference: Effects on working memory.

PubMed

Botto, Marta; Palladino, Paola

2016-05-01

This study tested predictions from the time-based resource-sharing (TBRS) model with a classical verbal working memory (WM) task, where target and non-target information interfere strongly with each other. Different predictions can be formulated according to the dominant perspectives (TBRS and interference hypothesis) on the role of inhibitory control in WM task performance. Here, we aimed to trace the activation of irrelevant information, examining priming effects in a lexical decision task immediately following WM recall. Results indicate the roles of both time and interference constraints in determining task performance. In particular, the role of time available seemed crucial at the highest WM loads (i.e., 3 and 4 memoranda). These were also associated with a higher activation of no-longer-relevant information but, in this case, independently from time available for processing. © 2015 The British Psychological Society.

Prediction of Business Jet Airloads Using The Overflow Navier-Stokes Code

NASA Technical Reports Server (NTRS)

Bounajem, Elias; Buning, Pieter G.

2001-01-01

The objective of this work is to evaluate the application of Navier-Stokes computational fluid dynamics technology, for the purpose of predicting off-design condition airloads on a business jet configuration in the transonic regime. The NASA Navier-Stokes flow solver OVERFLOW with Chimera overset grid capability, availability of several numerical schemes and convergence acceleration techniques was selected for this work. A set of scripts which have been compiled to reduce the time required for the grid generation process are described. Several turbulence models are evaluated in the presence of separated flow regions on the wing. Computed results are compared to available wind tunnel data for two Mach numbers and a range of angles-of-attack. Comparisons of wing surface pressure from numerical simulation and wind tunnel measurements show good agreement up to fairly high angles-of-attack.

Hydrological response of a subhumid watershed after a greening-up process, an example in South East Spain

NASA Astrophysics Data System (ADS)

Zema, Demetrio Antonio; Cataldo, Maria Francesca; Denisi, Pietro; Martino, Domenico; de Vente, Joris; Boix-Fayos, Carolina

2016-04-01

Many watersheds in the Mediterranean are subject to land use changes and hydrological control works that can have important effects on their hydrological and geomorphological response. In such contexts, a better understanding of the hydrological processes and their linkage to the geomorphic evolutionary trends would help territory planners and other stakeholders to face off soil and water body degradation, optimising efficiency and cheapness of planned interventions. This study focuses on a catchment in SE Spain, Upper Taibilla (320 km2, Segura basin), which suffered an important greening-up process with increase of forest cover, decrease of agriculture activities and installation of hydrological control works during the second half of XX century. The objective was to characterize the changes in the hydrological response of the catchment in relation to the changes in their drainage area. Firstly, the actual hydrological response to precipitation was analysed at aggregated (i.e. monthly, seasonal and annual) scale, using 15 years of the most recent runoff observations collected at the outlet of Upper Taibilla river (specifically at the inlet of Taibilla reservoir). Based on the actual distribution of soil land use and texture, the studied sub-basins were discretised by a GIS software in a system of homogenous hydrological units, in order to identify the most critical areas producing surface runoff. This actual aptitude to produce runoff was compared to the sub-basin hydrological response of 1930-1940s (that is before reforestation works and check-dam installation), in order to analyse the eventual presence of evolutionary trends in basin hydrology and the whole efficiency of these works in mitigating runoff impacts. Furthermore, considering that computer prediction models are important tools for planning land use changes and other management works in basins, the applicability of two hydrological models for predicting surface runoff in the studied sub-basins was evaluated. To this aim, the continuous simulation AnnAGNPS and HEC-HMS models were applied at aggregated and event scales respectively. Their reliability in predicting surface runoff was measured by quantitative indexes (e.g. coefficient of determination and efficiency, main statistics, summary and difference measures), using the available hydrological databases. The models were then calibrated by adjusting the initial Curve Number values (the empiric parameter to which the model is very sensitive), which allowed the improvement of their runoff prediction capacity. Finally, the calibrated AnnAGNPS model was applied in Upper Taibilla under different land use scenarios, in order to derive indications and criteria for future decisions of watershed management. On the whole, the study investigated on how management and land use change are effective on the hydrological response of watersheds and needs to be explored for watershed management purposes.

Playing off the curve - testing quantitative predictions of skill acquisition theories in development of chess performance.

PubMed

Gaschler, Robert; Progscha, Johanna; Smallbone, Kieran; Ram, Nilam; Bilalić, Merim

2014-01-01

Learning curves have been proposed as an adequate description of learning processes, no matter whether the processes manifest within minutes or across years. Different mechanisms underlying skill acquisition can lead to differences in the shape of learning curves. In the current study, we analyze the tournament performance data of 1383 chess players who begin competing at young age and play tournaments for at least 10 years. We analyze the performance development with the goal to test the adequacy of learning curves, and the skill acquisition theories they are based on, for describing and predicting expertise acquisition. On the one hand, we show that the skill acquisition theories implying a negative exponential learning curve do a better job in both describing early performance gains and predicting later trajectories of chess performance than those theories implying a power function learning curve. On the other hand, the learning curves of a large proportion of players show systematic qualitative deviations from the predictions of either type of skill acquisition theory. While skill acquisition theories predict larger performance gains in early years and smaller gains in later years, a substantial number of players begin to show substantial improvements with a delay of several years (and no improvement in the first years), deviations not fully accounted for by quantity of practice. The current work adds to the debate on how learning processes on a small time scale combine to large-scale changes.

Interference between Maintenance and Processing in Working Memory: The Effect of Item-Distractor Similarity in Complex Span

ERIC Educational Resources Information Center

Oberauer, Klaus; Farrell, Simon; Jarrold, Christopher; Pasiecznik, Kazimir; Greaves, Martin

2012-01-01

Four experiments examined the effect of phonological similarity between items and distractors on complex span performance. Item-distractor similarity benefited serial recall when distractors followed the items they were similar to, but not when distractors preceded the items they were similar to. These findings are predicted by C-SOB (contextual…

New submodel for watershed-scale simulations of fecal bacteria fate and transport at agricultural and pasture lands

USDA-ARS?s Scientific Manuscript database

Microbial contamination of waters is the critical public health issue. The watershed-scale process-based modeling of bacteria fate and transport (F&T) has been proven to serve as the useful tool for predicting microbial water quality and evaluating management practices. The objective of this work is...

Behind and beyond Self-Mastery: Risk, Vulnerability, and Becoming through Dewey and Heidegger

ERIC Educational Resources Information Center

d'Agnese, Vasco

2017-01-01

In the last two decades, a decisive anti-foundationalist turn has emerged in educational philosophy and theory. With such a shift, both the possibility and the desirability to conceive of educational processes and practices in terms of mastery and predictability has been challenged. In this paper, by locating my work on such an…

Supervision Anxiety as a Predictor for Organizational Cynicism in Teachers

ERIC Educational Resources Information Center

Gündüz, Hasan Basri; Ömür, Yunus Emre

2016-01-01

The purpose of this is study is to reveal how the anxiety that the teachers who work in the Beyoglu district of Istanbul experience, due to the supervision process, predict their organizational cynicism levels. With this respect, the study was conducted on 274 teachers with the relational screening model. The "Supervision Anxiety Scale"…

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

None

Many storms around the world have roots in the Indian Ocean, where they are churned up by the atmospheric process called the Madden-Julian Oscillation (MJO). PNNL is working to unlock the secrets of the MJO, particularly how it initiates in the Indian Ocean every 30-60 days. Better prediction of the MJO will help resource managers, weather forecasters and people worldwide better prepare for its effects.

The Reading Span Test and Its Predictive Power for Reading Comprehension Ability

ERIC Educational Resources Information Center

Friedman, Naomi P.; Miyake, Akira

2004-01-01

This study had two major goals: to test the effect of administration method on the criterion validity of a commonly used working memory span test, the reading span task, and to examine the relationship between processing and storage in this task. With respect to the first goal, although experimenter- and participant-administered reading span tasks…

Patients with Mild Alzheimer's Disease Fail When Using Their Working Memory: Evidence from the Eye Tracking Technique.

PubMed

Fernández, Gerardo; Manes, Facundo; Politi, Luis E; Orozco, David; Schumacher, Marcela; Castro, Liliana; Agamennoni, Osvaldo; Rotstein, Nora P

2016-01-01

Patients with Alzheimer's disease (AD) develop progressive language, visuoperceptual, attentional, and oculomotor changes that can have an impact on their reading comprehension. However, few studies have examined reading behavior in AD, and none have examined the contribution of predictive cueing in reading performance. For this purpose we analyzed the eye movement behavior of 35 healthy readers (Controls) and 35 patients with probable AD during reading of regular and high-predictable sentences. The cloze predictability of words N - 1, and N + 1 exerted an influence on the reader's gaze duration. The predictabilities of preceding words in high-predictable sentences served as task-appropriate cues that were used by Control readers. In contrast, these effects were not present in AD patients. In Controls, changes in predictability significantly affected fixation duration along the sentence; noteworthy, these changes did not affect fixation durations in AD patients. Hence, only in healthy readers did predictability of upcoming words influence fixation durations via memory retrieval. Our results suggest that Controls used stored information of familiar texts for enhancing their reading performance and imply that contextual-word predictability, whose processing is proposed to require memory retrieval, only affected reading behavior in healthy subjects. In AD patients, this loss reveals impairments in brain areas such as those corresponding to working memory and memory retrieval. These findings might be relevant for expanding the options for the early detection and monitoring in the early stages of AD. Furthermore, evaluation of eye movements during reading could provide a new tool for measuring drug impact on patients' behavior.

Coupling Processes Between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, M. K. W.; Weisenstein, Debra; Shia, Run-Li; Sze, N. D.

1997-01-01

This is the first semi-annual report for NAS5-97039 summarizing work performed for January 1997 through June 1997. Work in this project is related to NAS1-20666, also funded by NASA ACMAP. The work funded in this project also benefits from work at AER associated with the AER three-dimensional isentropic transport model funded by NASA AEAP and the AER two-dimensional climate-chemistry model (co-funded by Department of Energy). The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling tools for this work are the AER two-dimensional chemistry-transport model, the AER two-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry.

Working memory constraints on the processing of syntactic ambiguity.

PubMed

MacDonald, M C; Just, M A; Carpenter, P A

1992-01-01

We propose a model that explains how the working-memory capacity of a comprehender can constrain syntactic parsing and thereby affect the processing of syntactic ambiguities. The model's predictions are examined in four experiments that measure the reading times for two constructions that contain a temporary syntactic ambiguity. An example of the syntactic ambiguity is The soldiers warned about the dangers . . . ; the verb warned may either be the main verb, in which case soldiers is the agent; or the verb warned may introduce a relative clause, in which case soldiers is the patient of warned rather than the agent, as in The soldiers warned about the dangers conducted the midnight raid. The model proposes that both alternative interpretations of warned are initially activated. However, the duration for which both interpretations are maintained depends, in part, on the reader's working-memory capacity, which can be assessed by the Reading Span task (Daneman & Carpenter, 1980). The word-by-word reading times indicate that all subjects do additional processing after encountering an ambiguity, suggesting that they generate both representations. Furthermore, readers with larger working-memory capacities maintain both representations for some period of time (several words), whereas readers with smaller working-memory capacities revert to maintaining only the more likely representation.

Working memory still needs verbal rehearsal.

PubMed

Lucidi, Annalisa; Langerock, Naomi; Hoareau, Violette; Lemaire, Benoît; Camos, Valérie; Barrouillet, Pierre

2016-02-01

The causal role of verbal rehearsal in working memory has recently been called into question. For example, the SOB-CS (Serial Order in a Box-Complex Span) model assumes that there is no maintenance process for the strengthening of items in working memory, but instead a process of removal of distractors that are involuntarily encoded and create interference with memory items. In the present study, we tested the idea that verbal working memory performance can be accounted for without assuming a causal role of the verbal rehearsal process. We demonstrate in two experiments using a complex span task and a Brown-Peterson paradigm that increasing the number of repetitions of the same distractor (the syllable ba that was read aloud at each of its occurrences on screen) has a detrimental effect on the concurrent maintenance of consonants whereas the maintenance of spatial locations remains unaffected. A detailed analysis of the tasks demonstrates that accounting for this effect within the SOB-CS model requires a series of unwarranted assumptions leading to undesirable further predictions contradicted by available experimental evidence. We argue that the hypothesis of a maintenance mechanism based on verbal rehearsal that is impeded by concurrent articulation still provides the simplest and most compelling account of our results.

The role of predictive uncertainty in the operational management of reservoirs

NASA Astrophysics Data System (ADS)

Todini, E.

2014-09-01

The present work deals with the operational management of multi-purpose reservoirs, whose optimisation-based rules are derived, in the planning phase, via deterministic (linear and nonlinear programming, dynamic programming, etc.) or via stochastic (generally stochastic dynamic programming) approaches. In operation, the resulting deterministic or stochastic optimised operating rules are then triggered based on inflow predictions. In order to fully benefit from predictions, one must avoid using them as direct inputs to the reservoirs, but rather assess the "predictive knowledge" in terms of a predictive probability density to be operationally used in the decision making process for the estimation of expected benefits and/or expected losses. Using a theoretical and extremely simplified case, it will be shown why directly using model forecasts instead of the full predictive density leads to less robust reservoir management decisions. Moreover, the effectiveness and the tangible benefits for using the entire predictive probability density instead of the model predicted values will be demonstrated on the basis of the Lake Como management system, operational since 1997, as well as on the basis of a case study on the lake of Aswan.

The comprehensive health care orientation process indicators explain hospital organisation's attractiveness: a Bayesian analysis of newly hired nurse and physician survey data.

PubMed

Peltokoski, Jaana; Vehviläinen-Julkunen, Katri; Pitkäaho, Taina; Mikkonen, Santtu; Miettinen, Merja

2015-10-01

To examine the relationship of a comprehensive health care orientation process with a hospital's attractiveness. Little is known about indicators of the employee orientation process that most likely explain a hospital organisation's attractiveness. Empirical data collected from registered nurses (n = 145) and physicians (n = 37) working in two specialised hospital districts. A Naive Bayes Classification was applied to examine the comprehensive orientation process indicators that predict hospital's attractiveness. The model was composed of five orientation process indicators: the contribution of the orientation process to nurses' and physicians' intention to stay; the defined responsibilities of the orientation process; interaction between newcomer and colleagues; responsibilities that are adapted for tasks; and newcomers' baseline knowledge assessment that should be done before the orientation phase. The Naive Bayes Classification was used to explore employee orientation process and related indicators. The model constructed provides insight that can be used in designing and implementing the orientation process to promote the hospital organisation's attractiveness. Managers should focus on developing fluently organised orientation practices based on the indicators that predict the hospital's attractiveness. For the purpose of personalised orientation, employees' baseline knowledge and competence level should be assessed before the orientation phase. © 2014 John Wiley & Sons Ltd.

Daydreaming style moderates the relation between working memory and mind wandering: Integrating two hypotheses.

PubMed

Marcusson-Clavertz, David; Cardeña, Etzel; Terhune, Devin Blair

2016-03-01

Mind wandering-mentation unrelated to one's current activity and surroundings-is a ubiquitous phenomenon, but seemingly competing ideas have been proposed regarding its relation to executive cognitive processes. The control-failure hypothesis postulates that executive processes prevent mind wandering, whereas the global availability hypothesis proposes that mind wandering requires executive resources, and thus an excess of such resources enables mind wandering. Here, we examined whether these hypotheses could be reconciled by considering the moderating influence of daydreaming style. We expected that executive resources would be positively related to mind wandering in those who typically experience positive mind wandering mentation, but negatively related in those who typically experience negative mentation. One hundred eleven participants reported mind wandering over 4 days using experience sampling and completed the sustained attention to response task (SART), the symmetry span task, and the Stroop task. There was a significant interaction between working memory and negative, but not positive, daydreaming style on mind wandering: Working memory related positively to mind wandering in those with a low negative style, but negatively in those with a high negative style. In contrast, poor Stroop performance significantly predicted increased mind wandering, but only in those with a low positive style. SART responses did not predict mind wandering although the relation was suggestively enhanced as the difficulty of daily life activities increased, indicating that the SART is more generalizable to high-demanding than low-demanding activities. These results suggest that the content and context of mind wandering episodes play important roles in the relation between executive processes and mind wandering. (c) 2016 APA, all rights reserved).

Context-dependent switching between proactive and reactive working memory control mechanisms in the right inferior frontal gyrus.

PubMed

Marklund, Petter; Persson, Jonas

2012-11-15

A critical feature of higher cognitive functioning is the capacity to flexibly tailor information processing and behaviors to current situational demands. Recent neurocognitive models have been postulated to account for the dynamic nature of human executive processing by invoking two dissociable cognitive control modes, proactive and reactive control. These may involve partially overlapping, but temporally distinct neural implementation in the prefrontal cortex. Prior brain imaging studies exploring proactive control have mainly used tasks requiring only information about single-items to be retained over unfilled delays. Whether proactive control can also be utilized to facilitate performance in more complex working memory tasks, in which concurrent processing of intervening items and updating is mandatory during contextual cue maintenance remains an open question. To examine this issue and to elucidate the extent to which overlapping neural substrates underlie proactive and reactive control we used fMRI and a modified verbal 3-back paradigm with embedded cues predictive of high-interference trials. This task requires context information to be retained over multiple intervening trials. We found that performance improved with item-specific cues predicting forthcoming lures despite increased working memory load. Temporal dynamics of activation in the right inferior frontal gyrus suggest flexible switching between proactive and reactive control in a context-dependent fashion, with greater sustained responses elicited in the 3-back task involving context maintenance of cue information and greater transient responses elicited in the 3-back task absent of cues. Copyright © 2012 Elsevier Inc. All rights reserved.

Goal striving within agentic and communal roles: separate but functionally similar pathways to enhanced well-being.

PubMed

Sheldon, Kennon M; Cooper, M Lynne

2008-06-01

Do agency and communion strivings provide functionally similar but predictively independent pathways to enhanced well-being? We tested this idea via a year-long study of 493 diverse community adults. Our process model, based on self-determination and motive disposition theories, fit the data well. First, the need for achievement predicted initial autonomous motivation for agentic (work and school) role-goals and the need for intimacy predicted felt autonomy for communal (relationship and parenting) goals. For both agentic and communal goals, autonomous motivation predicted corresponding initial expectancies that predicted later goal attainment. Finally, each type of attainment predicted improved adjustment or role-satisfaction over the year. Besides being similar across agency and communion, the model was also similar across race and gender, except that the beneficial effects of communal goal attainment were stronger for high need for intimacy women and Blacks. Implications for agency/communion theories, motivation theories, and theories of well-being are discussed.

Action Prediction Allows Hypothesis Testing via Internal Forward Models at 6 Months of Age

PubMed Central

Gredebäck, Gustaf; Lindskog, Marcus; Juvrud, Joshua C.; Green, Dorota; Marciszko, Carin

2018-01-01

We propose that action prediction provides a cornerstone in a learning process known as internal forward models. According to this suggestion infants’ predictions (looking to the mouth of someone moving a spoon upward) will moments later be validated or proven false (spoon was in fact directed toward a bowl), information that is directly perceived as the distance between the predicted and actual goal. Using an individual difference approach we demonstrate that action prediction correlates with the tendency to react with surprise when social interactions are not acted out as expected (action evaluation). This association is demonstrated across tasks and in a large sample (n = 118) at 6 months of age. These results provide the first indication that infants might rely on internal forward models to structure their social world. Additional analysis, consistent with prior work and assumptions from embodied cognition, demonstrates that the latency of infants’ action predictions correlate with the infant’s own manual proficiency. PMID:29593600

Aggregation Trade Offs in Family Based Recommendations

NASA Astrophysics Data System (ADS)

Berkovsky, Shlomo; Freyne, Jill; Coombe, Mac

Personalized information access tools are frequently based on collaborative filtering recommendation algorithms. Collaborative filtering recommender systems typically suffer from a data sparsity problem, where systems do not have sufficient user data to generate accurate and reliable predictions. Prior research suggested using group-based user data in the collaborative filtering recommendation process to generate group-based predictions and partially resolve the sparsity problem. Although group recommendations are less accurate than personalized recommendations, they are more accurate than general non-personalized recommendations, which are the natural fall back when personalized recommendations cannot be generated. In this work we present initial results of a study that exploits the browsing logs of real families of users gathered in an eHealth portal. The browsing logs allowed us to experimentally compare the accuracy of two group-based recommendation strategies: aggregated group models and aggregated predictions. Our results showed that aggregating individual models into group models resulted in more accurate predictions than aggregating individual predictions into group predictions.

Evaluating a variety of text-mined features for automatic protein function prediction with GOstruct.

PubMed

Funk, Christopher S; Kahanda, Indika; Ben-Hur, Asa; Verspoor, Karin M

2015-01-01

Most computational methods that predict protein function do not take advantage of the large amount of information contained in the biomedical literature. In this work we evaluate both ontology term co-mention and bag-of-words features mined from the biomedical literature and analyze their impact in the context of a structured output support vector machine model, GOstruct. We find that even simple literature based features are useful for predicting human protein function (F-max: Molecular Function =0.408, Biological Process =0.461, Cellular Component =0.608). One advantage of using literature features is their ability to offer easy verification of automated predictions. We find through manual inspection of misclassifications that some false positive predictions could be biologically valid predictions based upon support extracted from the literature. Additionally, we present a "medium-throughput" pipeline that was used to annotate a large subset of co-mentions; we suggest that this strategy could help to speed up the rate at which proteins are curated.