Predicting reasoning from memory.

PubMed

Heit, Evan; Hayes, Brett K

2011-02-01

In an effort to assess the relations between reasoning and memory, in 8 experiments, the authors examined how well responses on an inductive reasoning task are predicted from responses on a recognition memory task for the same picture stimuli. Across several experimental manipulations, such as varying study time, presentation frequency, and the presence of stimuli from other categories, there was a high correlation between reasoning and memory responses (average r = .87), and these manipulations showed similar effects on the 2 tasks. The results point to common mechanisms underlying inductive reasoning and recognition memory abilities. A mathematical model, GEN-EX (generalization from examples), derived from exemplar models of categorization, is presented, which predicts both reasoning and memory responses from pairwise similarities among the stimuli, allowing for additional influences of subtyping and deterministic responding. (c) 2010 APA, all rights reserved.

The reasoned/reactive model: A new approach to examining eating decisions among female college dieters and nondieters.

PubMed

Ruhl, Holly; Holub, Shayla C; Dolan, Elaine A

2016-12-01

Female college students are prone to unhealthy eating patterns that can impact long-term health. This study examined female students' healthy and unhealthy eating behaviors with three decision-making models. Specifically, the theory of reasoned action, prototype/willingness model, and new reasoned/reactive model were compared to determine how reasoned (logical) and reactive (impulsive) factors relate to dietary decisions. Females (N=583, M age =20.89years) completed measures on reasoned cognitions about foods (attitudes, subjective norms, nutrition knowledge, intentions to eat foods), reactive cognitions about foods (prototypes, affect, willingness to eat foods), dieting, and food consumption. Structural equation modeling (SEM) revealed the new reasoned/reactive model to be the preeminent model for examining eating behaviors. This model showed that attitudes were related to intentions and willingness to eat healthy and unhealthy foods. Affect was related to willingness to eat healthy and unhealthy foods, whereas nutrition knowledge was related to intentions and willingness to eat healthy foods only. Intentions and willingness were related to healthy and unhealthy food consumption. Dieting status played a moderating role in the model and revealed mean-level differences between dieters and nondieters. This study highlights the importance of specific factors in relation to female students' eating decisions and unveils a comprehensive model for examining health behaviors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Machine Learning-based Intelligent Formal Reasoning and Proving System

NASA Astrophysics Data System (ADS)

Chen, Shengqing; Huang, Xiaojian; Fang, Jiaze; Liang, Jia

2018-03-01

The reasoning system can be used in many fields. How to improve reasoning efficiency is the core of the design of system. Through the formal description of formal proof and the regular matching algorithm, after introducing the machine learning algorithm, the system of intelligent formal reasoning and verification has high efficiency. The experimental results show that the system can verify the correctness of propositional logic reasoning and reuse the propositional logical reasoning results, so as to obtain the implicit knowledge in the knowledge base and provide the basic reasoning model for the construction of intelligent system.

Linear model analysis of the influencing factors of boar longevity in Southern China.

PubMed

Wang, Chao; Li, Jia-Lian; Wei, Hong-Kui; Zhou, Yuan-Fei; Jiang, Si-Wen; Peng, Jian

2017-04-15

This study aimed to investigate the factors influencing the boar herd life month (BHLM) in Southern China. A total of 1630 records of culling boars from nine artificial insemination centers were collected from January 2013 to May 2016. A logistic regression model and two linear models were used to analyze the effects of breed, housing type, age at herd entry, and seed stock herd on boar removal reason and BHLM, respectively. Boar breed and the age at herd entry had significant effects on the removal reasons (P < 0.001). Results of the two linear models (with or without removal reason including) showed boars raised individually in stalls exhibited shorter BHLM than those raised in pens (P < 0.001). Boars aged 5 and 6 months at herd entry (44.6%) showed shorter BHLM than those aged 8 and 9 months at herd entry (P < 0.05). Approximately 95% boars were culled for different reasons other than old age, and the BHLM of these boars was at least 12.3 months longer than that of boars culled for other reasons (P < 0.001). In conclusion, abnormal elimination in boars is serious and it had a negative effect on boar BHLM. Boar removal reason and BHLM can be affected by breed, housing type, and seed stock herd. Importantly, 8 months is suggested as the most suitable age for boar introduction. Copyright © 2017. Published by Elsevier Inc.

[Job satisfaction, volition and reasons for choice of temporary work].

PubMed

Muzzolon, Cristina; Spoto, Andrea; Vidotto, Giulio

2012-01-01

In this paper, we reviewed the literature on volition and the principal studies on the reasons for choosing temporary work, which explain in more details how voluntary/involuntary status is interpreted. The description of a research, based on a sample of 1979 workers, is presented with two aims: 1. confirm a structural model that examines the effects on satisfaction of some variables, such as motivation and trust; 2. evaluate the influence of volition and reasons for choosing a temporary employment on job satisfaction. The results confirm the plausibility of the proposed structural model and show interesting results regarding the reasons for choosing temporary work.

Reasoning strategies modulate gender differences in emotion processing.

PubMed

Markovits, Henry; Trémolière, Bastien; Blanchette, Isabelle

2018-01-01

The dual strategy model of reasoning has proposed that people's reasoning can be understood asa combination of two different ways of processing information related to problem premises: a counterexample strategy that examines information for explicit potential counterexamples and a statistical strategy that uses associative access to generate a likelihood estimate of putative conclusions. Previous studies have examined this model in the context of basic conditional reasoning tasks. However, the information processing distinction that underlies the dual strategy model can be seen asa basic description of differences in reasoning (similar to that described by many general dual process models of reasoning). In two studies, we examine how these differences in reasoning strategy may relate to processing very different information, specifically we focus on previously observed gender differences in processing negative emotions. Study 1 examined the intensity of emotional reactions to a film clip inducing primarily negative emotions. Study 2 examined the speed at which participants determine the emotional valence of sequences of negative images. In both studies, no gender differences were observed among participants using a counterexample strategy. Among participants using a statistical strategy, females produce significantly stronger emotional reactions than males (in Study 1) and were faster to recognize the valence of negative images than were males (in Study 2). Results show that the processing distinction underlying the dual strategy model of reasoning generalizes to the processing of emotions. Copyright © 2017 Elsevier B.V. All rights reserved.

Relations between inductive reasoning and deductive reasoning.

PubMed

Heit, Evan; Rotello, Caren M

2010-05-01

One of the most important open questions in reasoning research is how inductive reasoning and deductive reasoning are related. In an effort to address this question, we applied methods and concepts from memory research. We used 2 experiments to examine the effects of logical validity and premise-conclusion similarity on evaluation of arguments. Experiment 1 showed 2 dissociations: For a common set of arguments, deduction judgments were more affected by validity, and induction judgments were more affected by similarity. Moreover, Experiment 2 showed that fast deduction judgments were like induction judgments-in terms of being more influenced by similarity and less influenced by validity, compared with slow deduction judgments. These novel results pose challenges for a 1-process account of reasoning and are interpreted in terms of a 2-process account of reasoning, which was implemented as a multidimensional signal detection model and applied to receiver operating characteristic data. PsycINFO Database Record (c) 2010 APA, all rights reserved.

Structure induction in diagnostic causal reasoning.

PubMed

Meder, Björn; Mayrhofer, Ralf; Waldmann, Michael R

2014-07-01

Our research examines the normative and descriptive adequacy of alternative computational models of diagnostic reasoning from single effects to single causes. Many theories of diagnostic reasoning are based on the normative assumption that inferences from an effect to its cause should reflect solely the empirically observed conditional probability of cause given effect. We argue against this assumption, as it neglects alternative causal structures that may have generated the sample data. Our structure induction model of diagnostic reasoning takes into account the uncertainty regarding the underlying causal structure. A key prediction of the model is that diagnostic judgments should not only reflect the empirical probability of cause given effect but should also depend on the reasoner's beliefs about the existence and strength of the link between cause and effect. We confirmed this prediction in 2 studies and showed that our theory better accounts for human judgments than alternative theories of diagnostic reasoning. Overall, our findings support the view that in diagnostic reasoning people go "beyond the information given" and use the available data to make inferences on the (unobserved) causal rather than on the (observed) data level. (c) 2014 APA, all rights reserved.

Structured statistical models of inductive reasoning.

PubMed

Kemp, Charles; Tenenbaum, Joshua B

2009-01-01

Everyday inductive inferences are often guided by rich background knowledge. Formal models of induction should aim to incorporate this knowledge and should explain how different kinds of knowledge lead to the distinctive patterns of reasoning found in different inductive contexts. This article presents a Bayesian framework that attempts to meet both goals and describes [corrected] 4 applications of the framework: a taxonomic model, a spatial model, a threshold model, and a causal model. Each model makes probabilistic inferences about the extensions of novel properties, but the priors for the 4 models are defined over different kinds of structures that capture different relationships between the categories in a domain. The framework therefore shows how statistical inference can operate over structured background knowledge, and the authors argue that this interaction between structure and statistics is critical for explaining the power and flexibility of human reasoning.

An experimental investigation of emotional reasoning processes in depression.

PubMed

Berle, David; Moulds, Michelle L

2013-09-01

Cognitive models of depression emphasize how distorted thoughts and interpretations contribute to low mood. Emotional reasoning is considered to be one such interpretative style. We used an experimental procedure to determine whether elevated levels of emotional reasoning characterize depression. Participants who were currently experiencing a major depressive episode (n = 27) were compared with those who were non-depressed (n = 25 who had never been depressed and n = 26 previously but not currently depressed) on an emotional reasoning task. Although there were some trends for depressed participants to show greater levels of emotional reasoning relative to non-depressed participants, none of these differences attained significance. Interestingly, previously depressed participants engaged in more non-self-referent emotional reasoning than never-depressed participants. Emotional reasoning does not appear to characterize mild to moderate levels of depression. The lack of significant differences in emotional reasoning between currently depressed and non-depressed participants may have been a consequence of the fact that participants in our currently depressed group were, for the most part, only mildly depressed. Non-self-referent emotional reasoning may nevertheless be a risk factor for subsequent depressive episodes, or else serve as a 'cognitive scar' from previous episodes. In contrast with the predictions of cognitive models of depression, emotional reasoning tendencies may not be especially prominent in currently depressed individuals. Depressed individuals vary greatly in the degree to which they engage in emotional reasoning. Individuals with remitted depression may show elevated of levels non-self-referent emotional reasoning compared with those who have never had a depressive episode, that is, rely on their emotions when forming interpretations about situations. Our findings require replication using alternative indices of emotional reasoning. Our currently depressed individuals were only mildly clinically depressed precluding conclusions about individuals with more severe levels of depression. © 2013 The British Psychological Society.

Inductive reasoning about causally transmitted properties.

PubMed

Shafto, Patrick; Kemp, Charles; Bonawitz, Elizabeth Baraff; Coley, John D; Tenenbaum, Joshua B

2008-11-01

Different intuitive theories constrain and guide inferences in different contexts. Formalizing simple intuitive theories as probabilistic processes operating over structured representations, we present a new computational model of category-based induction about causally transmitted properties. A first experiment demonstrates undergraduates' context-sensitive use of taxonomic and food web knowledge to guide reasoning about causal transmission and shows good qualitative agreement between model predictions and human inferences. A second experiment demonstrates strong quantitative and qualitative fits to inferences about a more complex artificial food web. A third experiment investigates human reasoning about complex novel food webs where species have known taxonomic relations. Results demonstrate a double-dissociation between the predictions of our causal model and a related taxonomic model [Kemp, C., & Tenenbaum, J. B. (2003). Learning domain structures. In Proceedings of the 25th annual conference of the cognitive science society]: the causal model predicts human inferences about diseases but not genes, while the taxonomic model predicts human inferences about genes but not diseases. We contrast our framework with previous models of category-based induction and previous formal instantiations of intuitive theories, and outline challenges in developing a complete model of context-sensitive reasoning.

Incorporating time and spatial-temporal reasoning into situation management

NASA Astrophysics Data System (ADS)

Jakobson, Gabriel

2010-04-01

Spatio-temporal reasoning plays a significant role in situation management that is performed by intelligent agents (human or machine) by affecting how the situations are recognized, interpreted, acted upon or predicted. Many definitions and formalisms for the notion of spatio-temporal reasoning have emerged in various research fields including psychology, economics and computer science (computational linguistics, data management, control theory, artificial intelligence and others). In this paper we examine the role of spatio-temporal reasoning in situation management, particularly how to resolve situations that are described by using spatio-temporal relations among events and situations. We discuss a model for describing context sensitive temporal relations and show have the model can be extended for spatial relations.

Memory self-efficacy predicts responsiveness to inductive reasoning training in older adults.

PubMed

Payne, Brennan R; Jackson, Joshua J; Hill, Patrick L; Gao, Xuefei; Roberts, Brent W; Stine-Morrow, Elizabeth A L

2012-01-01

In the current study, we assessed the relationship between memory self-efficacy at pretest and responsiveness to inductive reasoning training in a sample of older adults. Participants completed a measure of self-efficacy assessing beliefs about memory capacity. Participants were then randomly assigned to a waitlist control group or an inductive reasoning training intervention. Latent change score models were used to examine the moderators of change in inductive reasoning. Inductive reasoning showed clear improvements in the training group compared with the control. Within the training group, initial memory capacity beliefs significantly predicted change in inductive reasoning such that those with higher levels of capacity beliefs showed greater responsiveness to the intervention. Further analyses revealed that self-efficacy had effects on how trainees allocated time to the training materials over the course of the intervention. Results indicate that self-referential beliefs about cognitive potential may be an important factor contributing to plasticity in adulthood.

Uncertain relational reasoning in the parietal cortex.

PubMed

Ragni, Marco; Franzmeier, Imke; Maier, Simon; Knauff, Markus

2016-04-01

The psychology of reasoning is currently transitioning from the study of deductive inferences under certainty to inferences that have degrees of uncertainty in both their premises and conclusions; however, only a few studies have explored the cortical basis of uncertain reasoning. Using transcranial magnetic stimulation (TMS), we show that areas in the right superior parietal lobe (rSPL) are necessary for solving spatial relational reasoning problems under conditions of uncertainty. Twenty-four participants had to decide whether a single presented order of objects agreed with a given set of indeterminate premises that could be interpreted in more than one way. During the presentation of the order, 10-Hz TMS was applied over the rSPL or a sham control site. Right SPL TMS during the inference phase disrupted performance in uncertain relational reasoning. Moreover, we found differences in the error rates between preferred mental models, alternative models, and inconsistent models. Our results suggest that different mechanisms are involved when people reason spatially and evaluate different kinds of uncertain conclusions. Copyright © 2016 Elsevier Inc. All rights reserved.

Investigating How German Biology Teachers Use Three-Dimensional Physical Models in Classroom Instruction: a Video Study

NASA Astrophysics Data System (ADS)

Werner, Sonja; Förtsch, Christian; Boone, William; von Kotzebue, Lena; Neuhaus, Birgit J.

2017-07-01

To obtain a general understanding of science, model use as part of National Education Standards is important for instruction. Model use can be characterized by three aspects: (1) the characteristics of the model, (2) the integration of the model into instruction, and (3) the use of models to foster scientific reasoning. However, there were no empirical results describing the implementation of National Education Standards in science instruction concerning the use of models. Therefore, the present study investigated the implementation of different aspects of model use in German biology instruction. Two biology lessons on the topic neurobiology in grade nine of 32 biology teachers were videotaped (N = 64 videos). These lessons were analysed using an event-based coding manual according to three aspects of model described above. Rasch analysis of the coded categories was conducted and showed reliable measurement. In the first analysis, we identified 68 lessons where a total of 112 different models were used. The in-depth analysis showed that special aspects of an elaborate model use according to several categories of scientific reasoning were rarely implemented in biology instruction. A critical reflection of the used model (N = 25 models; 22.3%) and models to demonstrate scientific reasoning (N = 26 models; 23.2%) were seldom observed. Our findings suggest that pre-service biology teacher education and professional development initiatives in Germany have to focus on both aspects.

The Effect of a Case-Based Reasoning Instructional Model on Korean High School Students' Awareness in Climate Change Unit

ERIC Educational Resources Information Center

Jeong, Jinwoo; Kim, Hyoungbum; Chae, Dong-hyun; Kim, Eunjeong

2014-01-01

The purpose of this study is to investigate the effects of the case-based reasoning instructional model on learning about climate change unit. Results suggest that students showed interest because it allowed them to find the solution to the problem and solve the problem for themselves by analogy from other cases such as crossword puzzles in an…

Reasoning with Vectors: A Continuous Model for Fast Robust Inference.

PubMed

Widdows, Dominic; Cohen, Trevor

2015-10-01

This paper describes the use of continuous vector space models for reasoning with a formal knowledge base. The practical significance of these models is that they support fast, approximate but robust inference and hypothesis generation, which is complementary to the slow, exact, but sometimes brittle behavior of more traditional deduction engines such as theorem provers. The paper explains the way logical connectives can be used in semantic vector models, and summarizes the development of Predication-based Semantic Indexing, which involves the use of Vector Symbolic Architectures to represent the concepts and relationships from a knowledge base of subject-predicate-object triples. Experiments show that the use of continuous models for formal reasoning is not only possible, but already demonstrably effective for some recognized informatics tasks, and showing promise in other traditional problem areas. Examples described in this paper include: predicting new uses for existing drugs in biomedical informatics; removing unwanted meanings from search results in information retrieval and concept navigation; type-inference from attributes; comparing words based on their orthography; and representing tabular data, including modelling numerical values. The algorithms and techniques described in this paper are all publicly released and freely available in the Semantic Vectors open-source software package.

Reasoning with Vectors: A Continuous Model for Fast Robust Inference

PubMed Central

Widdows, Dominic; Cohen, Trevor

2015-01-01

This paper describes the use of continuous vector space models for reasoning with a formal knowledge base. The practical significance of these models is that they support fast, approximate but robust inference and hypothesis generation, which is complementary to the slow, exact, but sometimes brittle behavior of more traditional deduction engines such as theorem provers. The paper explains the way logical connectives can be used in semantic vector models, and summarizes the development of Predication-based Semantic Indexing, which involves the use of Vector Symbolic Architectures to represent the concepts and relationships from a knowledge base of subject-predicate-object triples. Experiments show that the use of continuous models for formal reasoning is not only possible, but already demonstrably effective for some recognized informatics tasks, and showing promise in other traditional problem areas. Examples described in this paper include: predicting new uses for existing drugs in biomedical informatics; removing unwanted meanings from search results in information retrieval and concept navigation; type-inference from attributes; comparing words based on their orthography; and representing tabular data, including modelling numerical values. The algorithms and techniques described in this paper are all publicly released and freely available in the Semantic Vectors open-source software package.1 PMID:26582967

Student use of model-based reasoning when troubleshooting an electronic circuit

NASA Astrophysics Data System (ADS)

Lewandowski, Heather; Stetzer, Mackenzie; van de Bogart, Kevin; Dounas-Frazer, Dimitri

2016-03-01

Troubleshooting systems is an integral part of experimental physics in both research and educational settings. Accordingly, ability to troubleshoot is an important learning goal for undergraduate physics lab courses. We investigate students' model-based reasoning on a troubleshooting task using data collected in think-aloud interviews during which pairs of students from two institutions attempted to diagnose and repair a malfunctioning circuit. Our analysis scheme was informed by the Experimental Modeling Framework, which describes physicists' use of mathematical and conceptual models when reasoning about experimental systems. We show that system and subsystem models were crucial for the evaluation of repairs to the circuit and played an important role in some troubleshooting strategies. Finally, drawing on data from interviews with electronics instructors from a broad range of institution types, we outline recommendations for model-based approaches to teaching and learning troubleshooting skills.

Student use of model-based reasoning when troubleshooting an electric circuit

NASA Astrophysics Data System (ADS)

Dounas-Frazer, Dimitri

2016-05-01

Troubleshooting systems is an integral part of experimental physics in both research and educational settings. Accordingly, ability to troubleshoot is an important learning goal for undergraduate physics lab courses. We investigate students' model-based reasoning on a troubleshooting task using data collected in think-aloud interviews during which pairs of students from two institutions attempted to diagnose and repair a malfunctioning circuit. Our analysis scheme was informed by the Experimental Modeling Framework, which describes physicists' use of mathematical and conceptual models when reasoning about experimental systems. We show that system and subsystem models were crucial for the evaluation of repairs to the circuit and played an important role in some troubleshooting strategies. Finally, drawing on data from interviews with electronics instructors from a broad range of institution types, we outline recommendations for model-based approaches to teaching and learning troubleshooting skills.

Five-Year-Olds' Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study.

PubMed

Arslan, Burcu; Taatgen, Niels A; Verbrugge, Rineke

2017-01-01

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback "Wrong," they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children's failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy.

Five-Year-Olds’ Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study

PubMed Central

Arslan, Burcu; Taatgen, Niels A.; Verbrugge, Rineke

2017-01-01

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback “Wrong,” they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children’s failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy. PMID:28293206

The influence of cognitive ability and instructional set on causal conditional inference.

PubMed

Evans, Jonathan St B T; Handley, Simon J; Neilens, Helen; Over, David

2010-05-01

We report a large study in which participants are invited to draw inferences from causal conditional sentences with varying degrees of believability. General intelligence was measured, and participants were split into groups of high and low ability. Under strict deductive-reasoning instructions, it was observed that higher ability participants were significantly less influenced by prior belief than were those of lower ability. This effect disappeared, however, when pragmatic reasoning instructions were employed in a separate group. These findings are in accord with dual-process theories of reasoning. We also took detailed measures of beliefs in the conditional sentences used for the reasoning tasks. Statistical modelling showed that it is not belief in the conditional statement per se that is the causal factor, but rather correlates of it. Two different models of belief-based reasoning were found to fit the data according to the kind of instructions and the type of inference under consideration.

Intuitive Cognition and Models of Human-Automation Interaction.

PubMed

Patterson, Robert Earl

2017-02-01

The aim of this study was to provide an analysis of the implications of the dominance of intuitive cognition in human reasoning and decision making for conceptualizing models and taxonomies of human-automation interaction, focusing on the Parasuraman et al. model and taxonomy. Knowledge about how humans reason and make decisions, which has been shown to be largely intuitive, has implications for the design of future human-machine systems. One hundred twenty articles and books cited in other works as well as those obtained from an Internet search were reviewed. Works were deemed eligible if they were published within the past 50 years and common to a given literature. Analysis shows that intuitive cognition dominates human reasoning and decision making in all situations examined. The implications of the dominance of intuitive cognition for the Parasuraman et al. model and taxonomy are discussed. A taxonomy of human-automation interaction that incorporates intuitive cognition is suggested. Understanding the ways in which human reasoning and decision making is intuitive can provide insight for future models and taxonomies of human-automation interaction.

A Hybrid Approach Using Case-Based Reasoning and Rule-Based Reasoning to Support Cancer Diagnosis: A Pilot Study.

PubMed

Saraiva, Renata M; Bezerra, João; Perkusich, Mirko; Almeida, Hyggo; Siebra, Clauirton

2015-01-01

Recently there has been an increasing interest in applying information technology to support the diagnosis of diseases such as cancer. In this paper, we present a hybrid approach using case-based reasoning (CBR) and rule-based reasoning (RBR) to support cancer diagnosis. We used symptoms, signs, and personal information from patients as inputs to our model. To form specialized diagnoses, we used rules to define the input factors' importance according to the patient's characteristics. The model's output presents the probability of the patient having a type of cancer. To carry out this research, we had the approval of the ethics committee at Napoleão Laureano Hospital, in João Pessoa, Brazil. To define our model's cases, we collected real patient data at Napoleão Laureano Hospital. To define our model's rules and weights, we researched specialized literature and interviewed health professional. To validate our model, we used K-fold cross validation with the data collected at Napoleão Laureano Hospital. The results showed that our approach is an effective CBR system to diagnose cancer.

WAIS-IV subtest covariance structure: conceptual and statistical considerations.

PubMed

Ward, L Charles; Bergman, Maria A; Hebert, Katina R

2012-06-01

D. Wechsler (2008b) reported confirmatory factor analyses (CFAs) with standardization data (ages 16-69 years) for 10 core and 5 supplemental subtests from the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV). Analyses of the 15 subtests supported 4 hypothesized oblique factors (Verbal Comprehension, Working Memory, Perceptual Reasoning, and Processing Speed) but also revealed unexplained covariance between Block Design and Visual Puzzles (Perceptual Reasoning subtests). That covariance was not included in the final models. Instead, a path was added from Working Memory to Figure Weights (Perceptual Reasoning subtest) to improve fit and achieve a desired factor pattern. The present research with the same data (N = 1,800) showed that the path from Working Memory to Figure Weights increases the association between Working Memory and Matrix Reasoning. Specifying both paths improves model fit and largely eliminates unexplained covariance between Block Design and Visual Puzzles but with the undesirable consequence that Figure Weights and Matrix Reasoning are equally determined by Perceptual Reasoning and Working Memory. An alternative 4-factor model was proposed that explained theory-implied covariance between Block Design and Visual Puzzles and between Arithmetic and Figure Weights while maintaining compatibility with WAIS-IV Index structure. The proposed model compared favorably with a 5-factor model based on Cattell-Horn-Carroll theory. The present findings emphasize that covariance model comparisons should involve considerations of conceptual coherence and theoretical adherence in addition to statistical fit. (c) 2012 APA, all rights reserved

A relevance theory of induction.

PubMed

Medin, Douglas L; Coley, John D; Storms, Gert; Hayes, Brett K

2003-09-01

A framework theory, organized around the principle of relevance, is proposed for category-based reasoning. According to the relevance principle, people assume that premises are informative with respect to conclusions. This idea leads to the prediction that people will use causal scenarios and property reinforcement strategies in inductive reasoning. These predictions are contrasted with both existing models and normative logic. Judgments of argument strength were gathered in three different countries, and the results showed the importance of both causal scenarios and property reinforcement in category-based inferences. The relation between the relevance framework and existing models of category-based inductive reasoning is discussed in the light of these findings.

Memory Self-Efficacy Predicts Responsiveness to Inductive Reasoning Training in Older Adults

PubMed Central

Jackson, Joshua J.; Hill, Patrick L.; Gao, Xuefei; Roberts, Brent W.; Stine-Morrow, Elizabeth A. L.

2012-01-01

Objectives. In the current study, we assessed the relationship between memory self-efficacy at pretest and responsiveness to inductive reasoning training in a sample of older adults. Methods. Participants completed a measure of self-efficacy assessing beliefs about memory capacity. Participants were then randomly assigned to a waitlist control group or an inductive reasoning training intervention. Latent change score models were used to examine the moderators of change in inductive reasoning. Results. Inductive reasoning showed clear improvements in the training group compared with the control. Within the training group, initial memory capacity beliefs significantly predicted change in inductive reasoning such that those with higher levels of capacity beliefs showed greater responsiveness to the intervention. Further analyses revealed that self-efficacy had effects on how trainees allocated time to the training materials over the course of the intervention. Discussion. Results indicate that self-referential beliefs about cognitive potential may be an important factor contributing to plasticity in adulthood. PMID:21743037

Abstraction and Assume-Guarantee Reasoning for Automated Software Verification

NASA Technical Reports Server (NTRS)

Chaki, S.; Clarke, E.; Giannakopoulou, D.; Pasareanu, C. S.

2004-01-01

Compositional verification and abstraction are the key techniques to address the state explosion problem associated with model checking of concurrent software. A promising compositional approach is to prove properties of a system by checking properties of its components in an assume-guarantee style. This article proposes a framework for performing abstraction and assume-guarantee reasoning of concurrent C code in an incremental and fully automated fashion. The framework uses predicate abstraction to extract and refine finite state models of software and it uses an automata learning algorithm to incrementally construct assumptions for the compositional verification of the abstract models. The framework can be instantiated with different assume-guarantee rules. We have implemented our approach in the COMFORT reasoning framework and we show how COMFORT out-performs several previous software model checking approaches when checking safety properties of non-trivial concurrent programs.

Cortisol, insulin and leptin during space flight and bed rest

NASA Technical Reports Server (NTRS)

Stein, T. P.; Schluter, M. D.; Leskiw, M. J.

1999-01-01

Most ground based models for studying muscle atrophy and bone loss show reasonable fidelity to the space flight situation. However there are some differences. Investigation of the reasons for these differences can provide useful information about humans during space flight and aid in the refinement of ground based models. This report discusses three such differences, the relationships between: (i) cortisol and the protein loss, (ii) cortisol and ACTH and (iii) leptin, insulin and food intake.

Modeling visual problem solving as analogical reasoning.

PubMed

Lovett, Andrew; Forbus, Kenneth

2017-01-01

We present a computational model of visual problem solving, designed to solve problems from the Raven's Progressive Matrices intelligence test. The model builds on the claim that analogical reasoning lies at the heart of visual problem solving, and intelligence more broadly. Images are compared via structure mapping, aligning the common relational structure in 2 images to identify commonalities and differences. These commonalities or differences can themselves be reified and used as the input for future comparisons. When images fail to align, the model dynamically rerepresents them to facilitate the comparison. In our analysis, we find that the model matches adult human performance on the Standard Progressive Matrices test, and that problems which are difficult for the model are also difficult for people. Furthermore, we show that model operations involving abstraction and rerepresentation are particularly difficult for people, suggesting that these operations may be critical for performing visual problem solving, and reasoning more generally, at the highest level. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Zambian pre-service junior high school science teachers' chemical reasoning and ability

NASA Astrophysics Data System (ADS)

Banda, Asiana

The purpose of this study was two-fold: examine junior high school pre-service science teachers' chemical reasoning; and establish the extent to which the pre-service science teachers' chemical abilities explain their chemical reasoning. A sample comprised 165 junior high school pre-service science teachers at Mufulira College of Education in Zambia. There were 82 males and 83 females. Data were collected using a Chemical Concept Reasoning Test (CCRT). Pre-service science teachers' chemical reasoning was established through qualitative analysis of their responses to test items. The Rasch Model was used to determine the pre-service teachers' chemical abilities and item difficulty. Results show that most pre-service science teachers had incorrect chemical reasoning on chemical concepts assessed in this study. There was no significant difference in chemical understanding between the Full-Time and Distance Education pre-service science teachers, and between second and third year pre-service science teachers. However, there was a significant difference in chemical understanding between male and female pre-service science teachers. Male pre-service science teachers showed better chemical understanding than female pre-service science teachers. The Rasch model revealed that the pre-service science teachers had low chemical abilities, and the CCRT was very difficult for this group of pre-service science teachers. As such, their incorrect chemical reasoning was attributed to their low chemical abilities. These results have implications on science teacher education, chemistry teaching and learning, and chemical education research.

From neural oscillations to reasoning ability: Simulating the effect of the theta-to-gamma cycle length ratio on individual scores in a figural analogy test.

PubMed

Chuderski, Adam; Andrelczyk, Krzysztof

2015-02-01

Several existing computational models of working memory (WM) have predicted a positive relationship (later confirmed empirically) between WM capacity and the individual ratio of theta to gamma oscillatory band lengths. These models assume that each gamma cycle represents one WM object (e.g., a binding of its features), whereas the theta cycle integrates such objects into the maintained list. As WM capacity strongly predicts reasoning, it might be expected that this ratio also predicts performance in reasoning tasks. However, no computational model has yet explained how the differences in the theta-to-gamma ratio found among adult individuals might contribute to their scores on a reasoning test. Here, we propose a novel model of how WM capacity constraints figural analogical reasoning, aimed at explaining inter-individual differences in reasoning scores in terms of the characteristics of oscillatory patterns in the brain. In the model, the gamma cycle encodes the bindings between objects/features and the roles they play in the relations processed. Asynchrony between consecutive gamma cycles results from lateral inhibition between oscillating bindings. Computer simulations showed that achieving the highest WM capacity required reaching the optimal level of inhibition. When too strong, this inhibition eliminated some bindings from WM, whereas, when inhibition was too weak, the bindings became unstable and fell apart or became improperly grouped. The model aptly replicated several empirical effects and the distribution of individual scores, as well as the patterns of correlations found in the 100-people sample attempting the same reasoning task. Most importantly, the model's reasoning performance strongly depended on its theta-to-gamma ratio in same way as the performance of human participants depended on their WM capacity. The data suggest that proper regulation of oscillations in the theta and gamma bands may be crucial for both high WM capacity and effective complex cognition. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

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

Hohimer, Ryan E.; Greitzer, Frank L.; Noonan, Christine F.

2011-11-15

We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

A comparison of different statistical methods analyzing hypoglycemia data using bootstrap simulations.

PubMed

Jiang, Honghua; Ni, Xiao; Huster, William; Heilmann, Cory

2015-01-01

Hypoglycemia has long been recognized as a major barrier to achieving normoglycemia with intensive diabetic therapies. It is a common safety concern for the diabetes patients. Therefore, it is important to apply appropriate statistical methods when analyzing hypoglycemia data. Here, we carried out bootstrap simulations to investigate the performance of the four commonly used statistical models (Poisson, negative binomial, analysis of covariance [ANCOVA], and rank ANCOVA) based on the data from a diabetes clinical trial. Zero-inflated Poisson (ZIP) model and zero-inflated negative binomial (ZINB) model were also evaluated. Simulation results showed that Poisson model inflated type I error, while negative binomial model was overly conservative. However, after adjusting for dispersion, both Poisson and negative binomial models yielded slightly inflated type I errors, which were close to the nominal level and reasonable power. Reasonable control of type I error was associated with ANCOVA model. Rank ANCOVA model was associated with the greatest power and with reasonable control of type I error. Inflated type I error was observed with ZIP and ZINB models.

A Two-length Scale Turbulence Model for Single-phase Multi-fluid Mixing

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

Schwarzkopf, J. D.; Livescu, D.; Baltzer, J. R.

2015-09-08

A two-length scale, second moment turbulence model (Reynolds averaged Navier-Stokes, RANS) is proposed to capture a wide variety of single-phase flows, spanning from incompressible flows with single fluids and mixtures of different density fluids (variable density flows) to flows over shock waves. The two-length scale model was developed to address an inconsistency present in the single-length scale models, e.g. the inability to match both variable density homogeneous Rayleigh-Taylor turbulence and Rayleigh-Taylor induced turbulence, as well as the inability to match both homogeneous shear and free shear flows. The two-length scale model focuses on separating the decay and transport length scales,more » as the two physical processes are generally different in inhomogeneous turbulence. This allows reasonable comparisons with statistics and spreading rates over such a wide range of turbulent flows using a common set of model coefficients. The specific canonical flows considered for calibrating the model include homogeneous shear, single-phase incompressible shear driven turbulence, variable density homogeneous Rayleigh-Taylor turbulence, Rayleigh-Taylor induced turbulence, and shocked isotropic turbulence. The second moment model shows to compare reasonably well with direct numerical simulations (DNS), experiments, and theory in most cases. The model was then applied to variable density shear layer and shock tube data and shows to be in reasonable agreement with DNS and experiments. Additionally, the importance of using DNS to calibrate and assess RANS type turbulence models is highlighted.« less

CDMBE: A Case Description Model Based on Evidence

PubMed Central

Zhu, Jianlin; Yang, Xiaoping; Zhou, Jing

2015-01-01

By combining the advantages of argument map and Bayesian network, a case description model based on evidence (CDMBE), which is suitable to continental law system, is proposed to describe the criminal cases. The logic of the model adopts the credibility logical reason and gets evidence-based reasoning quantitatively based on evidences. In order to consist with practical inference rules, five types of relationship and a set of rules are defined to calculate the credibility of assumptions based on the credibility and supportability of the related evidences. Experiments show that the model can get users' ideas into a figure and the results calculated from CDMBE are in line with those from Bayesian model. PMID:26421006

Problem-based learning: effects on student’s scientific reasoning skills in science

NASA Astrophysics Data System (ADS)

Wulandari, F. E.; Shofiyah, N.

2018-04-01

This research aimed to develop instructional package of problem-based learning to enhance student’s scientific reasoning from concrete to formal reasoning skills level. The instructional package was developed using the Dick and Carey Model. Subject of this study was instructional package of problem-based learning which was consisting of lesson plan, handout, student’s worksheet, and scientific reasoning test. The instructional package was tried out on 4th semester science education students of Universitas Muhammadiyah Sidoarjo by using the one-group pre-test post-test design. The data of scientific reasoning skills was collected by making use of the test. The findings showed that the developed instructional package reflecting problem-based learning was feasible to be implemented in classroom. Furthermore, through applying the problem-based learning, students could dominate formal scientific reasoning skills in terms of functionality and proportional reasoning, control variables, and theoretical reasoning.

Models of clinical reasoning with a focus on general practice: A critical review.

PubMed

Yazdani, Shahram; Hosseinzadeh, Mohammad; Hosseini, Fakhrolsadat

2017-10-01

Diagnosis lies at the heart of general practice. Every day general practitioners (GPs) visit patients with a wide variety of complaints and concerns, with often minor but sometimes serious symptoms. General practice has many features which differentiate it from specialty care setting, but during the last four decades little attention was paid to clinical reasoning in general practice. Therefore, we aimed to critically review the clinical reasoning models with a focus on the clinical reasoning in general practice or clinical reasoning of general practitioners to find out to what extent the existing models explain the clinical reasoning specially in primary care and also identity the gaps of the model for use in primary care settings. A systematic search to find models of clinical reasoning were performed. To have more precision, we excluded the studies that focused on neurobiological aspects of reasoning, reasoning in disciplines other than medicine decision making or decision analysis on treatment or management plan. All the articles and documents were first scanned to see whether they include important relevant contents or any models. The selected studies which described a model of clinical reasoning in general practitioners or with a focus on general practice were then reviewed and appraisal or critics of other authors on these models were included. The reviewed documents on the model were synthesized. Six models of clinical reasoning were identified including hypothetic-deductive model, pattern recognition, a dual process diagnostic reasoning model, pathway for clinical reasoning, an integrative model of clinical reasoning, and model of diagnostic reasoning strategies in primary care. Only one model had specifically focused on general practitioners reasoning. A Model of clinical reasoning that included specific features of general practice to better help the general practitioners with the difficulties of clinical reasoning in this setting is needed.

Diversity-based reasoning in children.

PubMed

Heit, E; Hahn, U

2001-12-01

One of the hallmarks of inductive reasoning by adults is the diversity effect, namely that people draw stronger inferences from a diverse set of evidence than from a more homogenous set of evidence. However, past developmental work has not found consistent diversity effects with children age 9 and younger. We report robust sensitivity to diversity in children as young as 5, using everyday stimuli such as pictures of objects with people. Experiment 1 showed the basic diversity effect in 5- to 9-year-olds. Experiment 2 showed that, like adults, children restrict their use of diversity information when making inferences about remote categories. Experiment 3 used other stimulus sets to overcome an alternate explanation in terms of sample size rather than diversity effects. Finally, Experiment 4 showed that children more readily draw on diversity when reasoning about objects and their relations with people than when reasoning about objects' internal, hidden properties, thus partially explaining the negative findings of previous work. Relations to cross-cultural work and models of induction are discussed. Copyright 2001 Academic Press.

Model-based reasoning in the physics laboratory: Framework and initial results

NASA Astrophysics Data System (ADS)

Zwickl, Benjamin M.; Hu, Dehui; Finkelstein, Noah; Lewandowski, H. J.

2015-12-01

[This paper is part of the Focused Collection on Upper Division Physics Courses.] We review and extend existing frameworks on modeling to develop a new framework that describes model-based reasoning in introductory and upper-division physics laboratories. Constructing and using models are core scientific practices that have gained significant attention within K-12 and higher education. Although modeling is a broadly applicable process, within physics education, it has been preferentially applied to the iterative development of broadly applicable principles (e.g., Newton's laws of motion in introductory mechanics). A significant feature of the new framework is that measurement tools (in addition to the physical system being studied) are subjected to the process of modeling. Think-aloud interviews were used to refine the framework and demonstrate its utility by documenting examples of model-based reasoning in the laboratory. When applied to the think-aloud interviews, the framework captures and differentiates students' model-based reasoning and helps identify areas of future research. The interviews showed how students productively applied similar facets of modeling to the physical system and measurement tools: construction, prediction, interpretation of data, identification of model limitations, and revision. Finally, we document students' challenges in explicitly articulating assumptions when constructing models of experimental systems and further challenges in model construction due to students' insufficient prior conceptual understanding. A modeling perspective reframes many of the seemingly arbitrary technical details of measurement tools and apparatus as an opportunity for authentic and engaging scientific sense making.

Bayesian network modeling: A case study of an epidemiologic system analysis of cardiovascular risk.

PubMed

Fuster-Parra, P; Tauler, P; Bennasar-Veny, M; Ligęza, A; López-González, A A; Aguiló, A

2016-04-01

An extensive, in-depth study of cardiovascular risk factors (CVRF) seems to be of crucial importance in the research of cardiovascular disease (CVD) in order to prevent (or reduce) the chance of developing or dying from CVD. The main focus of data analysis is on the use of models able to discover and understand the relationships between different CVRF. In this paper a report on applying Bayesian network (BN) modeling to discover the relationships among thirteen relevant epidemiological features of heart age domain in order to analyze cardiovascular lost years (CVLY), cardiovascular risk score (CVRS), and metabolic syndrome (MetS) is presented. Furthermore, the induced BN was used to make inference taking into account three reasoning patterns: causal reasoning, evidential reasoning, and intercausal reasoning. Application of BN tools has led to discovery of several direct and indirect relationships between different CVRF. The BN analysis showed several interesting results, among them: CVLY was highly influenced by smoking being the group of men the one with highest risk in CVLY; MetS was highly influence by physical activity (PA) being again the group of men the one with highest risk in MetS, and smoking did not show any influence. BNs produce an intuitive, transparent, graphical representation of the relationships between different CVRF. The ability of BNs to predict new scenarios when hypothetical information is introduced makes BN modeling an Artificial Intelligence (AI) tool of special interest in epidemiological studies. As CVD is multifactorial the use of BNs seems to be an adequate modeling tool. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

An improved probabilistic account of counterfactual reasoning.

PubMed

Lucas, Christopher G; Kemp, Charles

2015-10-01

When people want to identify the causes of an event, assign credit or blame, or learn from their mistakes, they often reflect on how things could have gone differently. In this kind of reasoning, one considers a counterfactual world in which some events are different from their real-world counterparts and considers what else would have changed. Researchers have recently proposed several probabilistic models that aim to capture how people do (or should) reason about counterfactuals. We present a new model and show that it accounts better for human inferences than several alternative models. Our model builds on the work of Pearl (2000), and extends his approach in a way that accommodates backtracking inferences and that acknowledges the difference between counterfactual interventions and counterfactual observations. We present 6 new experiments and analyze data from 4 experiments carried out by Rips (2010), and the results suggest that the new model provides an accurate account of both mean human judgments and the judgments of individuals. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Activity in the fronto-parietal network indicates numerical inductive reasoning beyond calculation: An fMRI study combined with a cognitive model

PubMed Central

Liang, Peipeng; Jia, Xiuqin; Taatgen, Niels A.; Borst, Jelmer P.; Li, Kuncheng

2016-01-01

Numerical inductive reasoning refers to the process of identifying and extrapolating the rule involved in numeric materials. It is associated with calculation, and shares the common activation of the fronto-parietal regions with calculation, which suggests that numerical inductive reasoning may correspond to a general calculation process. However, compared with calculation, rule identification is critical and unique to reasoning. Previous studies have established the central role of the fronto-parietal network for relational integration during rule identification in numerical inductive reasoning. The current question of interest is whether numerical inductive reasoning exclusively corresponds to calculation or operates beyond calculation, and whether it is possible to distinguish between them based on the activity pattern in the fronto-parietal network. To directly address this issue, three types of problems were created: numerical inductive reasoning, calculation, and perceptual judgment. Our results showed that the fronto-parietal network was more active in numerical inductive reasoning which requires more exchanges between intermediate representations and long-term declarative knowledge during rule identification. These results survived even after controlling for the covariates of response time and error rate. A computational cognitive model was developed using the cognitive architecture ACT-R to account for the behavioral results and brain activity in the fronto-parietal network. PMID:27193284

Activity in the fronto-parietal network indicates numerical inductive reasoning beyond calculation: An fMRI study combined with a cognitive model.

PubMed

Liang, Peipeng; Jia, Xiuqin; Taatgen, Niels A; Borst, Jelmer P; Li, Kuncheng

2016-05-19

Numerical inductive reasoning refers to the process of identifying and extrapolating the rule involved in numeric materials. It is associated with calculation, and shares the common activation of the fronto-parietal regions with calculation, which suggests that numerical inductive reasoning may correspond to a general calculation process. However, compared with calculation, rule identification is critical and unique to reasoning. Previous studies have established the central role of the fronto-parietal network for relational integration during rule identification in numerical inductive reasoning. The current question of interest is whether numerical inductive reasoning exclusively corresponds to calculation or operates beyond calculation, and whether it is possible to distinguish between them based on the activity pattern in the fronto-parietal network. To directly address this issue, three types of problems were created: numerical inductive reasoning, calculation, and perceptual judgment. Our results showed that the fronto-parietal network was more active in numerical inductive reasoning which requires more exchanges between intermediate representations and long-term declarative knowledge during rule identification. These results survived even after controlling for the covariates of response time and error rate. A computational cognitive model was developed using the cognitive architecture ACT-R to account for the behavioral results and brain activity in the fronto-parietal network.

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

PubMed

Orr, Mark G; Thrush, Roxanne; Plaut, David C

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

The Theory of Reasoned Action as Parallel Constraint Satisfaction: Towards a Dynamic Computational Model of Health Behavior

PubMed Central

Orr, Mark G.; Thrush, Roxanne; Plaut, David C.

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual’s pre-existing belief structure and the beliefs of others in the individual’s social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics. PMID:23671603

Intelligent tutoring system for clinical reasoning skill acquisition in dental students.

PubMed

Suebnukarn, Siriwan

2009-10-01

Learning clinical reasoning is an important core activity of the modern dental curriculum. This article describes an intelligent tutoring system (ITS) for clinical reasoning skill acquisition. The system is designed to provide an experience that emulates that of live human-tutored problem-based learning (PBL) sessions as much as possible, while at the same time permitting the students to participate collaboratively from disparate locations. The system uses Bayesian networks to model individual student knowledge and activity, as well as that of the group. Tutoring algorithms use the models to generate tutoring hints. The system incorporates a multimodal interface that integrates text and graphics so as to provide a rich communication channel between the students and the system, as well as among students in the group. Comparison of learning outcomes shows that student clinical reasoning gains from the ITS are similar to those obtained from human-tutored sessions.

Models of clinical reasoning with a focus on general practice: A critical review

PubMed Central

YAZDANI, SHAHRAM; HOSSEINZADEH, MOHAMMAD; HOSSEINI, FAKHROLSADAT

2017-01-01

Introduction: Diagnosis lies at the heart of general practice. Every day general practitioners (GPs) visit patients with a wide variety of complaints and concerns, with often minor but sometimes serious symptoms. General practice has many features which differentiate it from specialty care setting, but during the last four decades little attention was paid to clinical reasoning in general practice. Therefore, we aimed to critically review the clinical reasoning models with a focus on the clinical reasoning in general practice or clinical reasoning of general practitioners to find out to what extent the existing models explain the clinical reasoning specially in primary care and also identity the gaps of the model for use in primary care settings. Methods: A systematic search to find models of clinical reasoning were performed. To have more precision, we excluded the studies that focused on neurobiological aspects of reasoning, reasoning in disciplines other than medicine decision making or decision analysis on treatment or management plan. All the articles and documents were first scanned to see whether they include important relevant contents or any models. The selected studies which described a model of clinical reasoning in general practitioners or with a focus on general practice were then reviewed and appraisal or critics of other authors on these models were included. The reviewed documents on the model were synthesized. Results: Six models of clinical reasoning were identified including hypothetic-deductive model, pattern recognition, a dual process diagnostic reasoning model, pathway for clinical reasoning, an integrative model of clinical reasoning, and model of diagnostic reasoning strategies in primary care. Only one model had specifically focused on general practitioners reasoning. Conclusion: A Model of clinical reasoning that included specific features of general practice to better help the general practitioners with the difficulties of clinical reasoning in this setting is needed. PMID:28979912

New normative standards of conditional reasoning and the dual-source model

PubMed Central

Singmann, Henrik; Klauer, Karl Christoph; Over, David

2014-01-01

There has been a major shift in research on human reasoning toward Bayesian and probabilistic approaches, which has been called a new paradigm. The new paradigm sees most everyday and scientific reasoning as taking place in a context of uncertainty, and inference is from uncertain beliefs and not from arbitrary assumptions. In this manuscript we present an empirical test of normative standards in the new paradigm using a novel probabilized conditional reasoning task. Our results indicated that for everyday conditional with at least a weak causal connection between antecedent and consequent only the conditional probability of the consequent given antecedent contributes unique variance to predicting the probability of conditional, but not the probability of the conjunction, nor the probability of the material conditional. Regarding normative accounts of reasoning, we found significant evidence that participants' responses were confidence preserving (i.e., p-valid in the sense of Adams, 1998) for MP inferences, but not for MT inferences. Additionally, only for MP inferences and to a lesser degree for DA inferences did the rate of responses inside the coherence intervals defined by mental probability logic (Pfeifer and Kleiter, 2005, 2010) exceed chance levels. In contrast to the normative accounts, the dual-source model (Klauer et al., 2010) is a descriptive model. It posits that participants integrate their background knowledge (i.e., the type of information primary to the normative approaches) and their subjective probability that a conclusion is seen as warranted based on its logical form. Model fits showed that the dual-source model, which employed participants' responses to a deductive task with abstract contents to estimate the form-based component, provided as good an account of the data as a model that solely used data from the probabilized conditional reasoning task. PMID:24860516

New normative standards of conditional reasoning and the dual-source model.

PubMed

Singmann, Henrik; Klauer, Karl Christoph; Over, David

2014-01-01

There has been a major shift in research on human reasoning toward Bayesian and probabilistic approaches, which has been called a new paradigm. The new paradigm sees most everyday and scientific reasoning as taking place in a context of uncertainty, and inference is from uncertain beliefs and not from arbitrary assumptions. In this manuscript we present an empirical test of normative standards in the new paradigm using a novel probabilized conditional reasoning task. Our results indicated that for everyday conditional with at least a weak causal connection between antecedent and consequent only the conditional probability of the consequent given antecedent contributes unique variance to predicting the probability of conditional, but not the probability of the conjunction, nor the probability of the material conditional. Regarding normative accounts of reasoning, we found significant evidence that participants' responses were confidence preserving (i.e., p-valid in the sense of Adams, 1998) for MP inferences, but not for MT inferences. Additionally, only for MP inferences and to a lesser degree for DA inferences did the rate of responses inside the coherence intervals defined by mental probability logic (Pfeifer and Kleiter, 2005, 2010) exceed chance levels. In contrast to the normative accounts, the dual-source model (Klauer et al., 2010) is a descriptive model. It posits that participants integrate their background knowledge (i.e., the type of information primary to the normative approaches) and their subjective probability that a conclusion is seen as warranted based on its logical form. Model fits showed that the dual-source model, which employed participants' responses to a deductive task with abstract contents to estimate the form-based component, provided as good an account of the data as a model that solely used data from the probabilized conditional reasoning task.

Model-based monitoring and diagnosis of a satellite-based instrument

NASA Technical Reports Server (NTRS)

Bos, Andre; Callies, Jorg; Lefebvre, Alain

1995-01-01

For about a decade model-based reasoning has been propounded by a number of researchers. Maybe one of the most convincing arguments in favor of this kind of reasoning has been given by Davis in his paper on diagnosis from first principles (Davis 1984). Following their guidelines we have developed a system to verify the behavior of a satellite-based instrument GOME (which will be measuring Ozone concentrations in the near future (1995)). We start by giving a description of model-based monitoring. Besides recognizing that something is wrong, we also like to find the cause for misbehaving automatically. Therefore, we show how the monitoring technique can be extended to model-based diagnosis.

Model-based monitoring and diagnosis of a satellite-based instrument

NASA Astrophysics Data System (ADS)

Bos, Andre; Callies, Jorg; Lefebvre, Alain

1995-05-01

For about a decade model-based reasoning has been propounded by a number of researchers. Maybe one of the most convincing arguments in favor of this kind of reasoning has been given by Davis in his paper on diagnosis from first principles (Davis 1984). Following their guidelines we have developed a system to verify the behavior of a satellite-based instrument GOME (which will be measuring Ozone concentrations in the near future (1995)). We start by giving a description of model-based monitoring. Besides recognizing that something is wrong, we also like to find the cause for misbehaving automatically. Therefore, we show how the monitoring technique can be extended to model-based diagnosis.

The Effect of Functional Hearing and Hearing Aid Usage on Verbal Reasoning in a Large Community-Dwelling Population.

PubMed

Keidser, Gitte; Rudner, Mary; Seeto, Mark; Hygge, Staffan; Rönnberg, Jerker

2016-01-01

Verbal reasoning performance is an indicator of the ability to think constructively in everyday life and relies on both crystallized and fluid intelligence. This study aimed to determine the effect of functional hearing on verbal reasoning when controlling for age, gender, and education. In addition, the study investigated whether hearing aid usage mitigated the effect and examined different routes from hearing to verbal reasoning. Cross-sectional data on 40- to 70-year-old community-dwelling participants from the UK Biobank resource were accessed. Data consisted of behavioral and subjective measures of functional hearing, assessments of numerical and linguistic verbal reasoning, measures of executive function, and demographic and lifestyle information. Data on 119,093 participants who had completed hearing and verbal reasoning tests were submitted to multiple regression analyses, and data on 61,688 of these participants, who had completed additional cognitive tests and provided relevant lifestyle information, were submitted to structural equation modeling. Poorer performance on the behavioral measure of functional hearing was significantly associated with poorer verbal reasoning in both the numerical and linguistic domains (p < 0.001). There was no association between the subjective measure of functional hearing and verbal reasoning. Functional hearing significantly interacted with education (p < 0.002), showing a trend for functional hearing to have a greater impact on verbal reasoning among those with a higher level of formal education. Among those with poor hearing, hearing aid usage had a significant positive, but not necessarily causal, effect on both numerical and linguistic verbal reasoning (p < 0.005). The estimated effect of hearing aid usage was less than the effect of poor functional hearing. Structural equation modeling analyses confirmed that controlling for education reduced the effect of functional hearing on verbal reasoning and showed that controlling for executive function eliminated the effect. However, when computer usage was controlled for, the eliminating effect of executive function was weakened. Poor functional hearing was associated with poor verbal reasoning in a 40- to 70-year-old community-dwelling population after controlling for age, gender, and education. The effect of functional hearing on verbal reasoning was significantly reduced among hearing aid users and completely overcome by good executive function skills, which may be enhanced by playing computer games.

Content-related interactions and methods of reasoning within self-initiated organic chemistry study groups

NASA Astrophysics Data System (ADS)

Christian, Karen Jeanne

2011-12-01

Students often use study groups to prepare for class or exams; yet to date, we know very little about how these groups actually function. This study looked at the ways in which undergraduate organic chemistry students prepared for exams through self-initiated study groups. We sought to characterize the methods of social regulation, levels of content processing, and types of reasoning processes used by students within their groups. Our analysis showed that groups engaged in predominantly three types of interactions when discussing chemistry content: co-construction, teaching, and tutoring. Although each group engaged in each of these types of interactions at some point, their prevalence varied between groups and group members. Our analysis suggests that the types of interactions that were most common depended on the relative content knowledge of the group members as well as on the difficulty of the tasks in which they were engaged. Additionally, we were interested in characterizing the reasoning methods used by students within their study groups. We found that students used a combination of three content-relevant methods of reasoning: model-based reasoning, case-based reasoning, or rule-based reasoning, in conjunction with one chemically-irrelevant method of reasoning: symbol-based reasoning. The most common way for groups to reason was to use rules, whereas the least common way was for students to work from a model. In general, student reasoning correlated strongly to the subject matter to which students were paying attention, and was only weakly related to student interactions. Overall, results from this study may help instructors to construct appropriate tasks to guide what and how students study outside of the classroom. We found that students had a decidedly strategic approach in their study groups, relying heavily on material provided by their instructors, and using the reasoning strategies that resulted in the lowest levels of content processing. We suggest that instructors create more opportunities for students to explore model-based reasoning, and to create opportunities for students to be able to co-construct in a collaborative manner within the context of their organic chemistry course.

The effect of emotion on interpretation and logic in a conditional reasoning task.

PubMed

Blanchette, Isabelle

2006-07-01

The effect of emotional content on logical reasoning is explored in three experiments. Theparticipants completed a conditional reasoning task (If p, then q) with emotional and neutral contents. In Experiment 1, existing emotional and neutral words were used. The emotional value of initially neutral words was experimentally manipulated in Experiments 1B and 2, using classical conditioning. In all experiments, participants were less likely to provide normatively correct answers when reasoning about emotional stimuli, compared with neutral stimuli. This was true for both negative (Experiments 1B and 2) and positive contents (Experiment 2). The participants' interpretations of the conditional statements were also measured (perceived sufficiency, necessity, causality, and plausibility). The results showed the expected relationship between interpretation and reasoning. However, emotion did not affect interpretation. Emotional and neutral conditional statements were interpreted similarly. The results are discussed in light of current models of emotion and reasoning.

Sketching the Invisible to Predict the Visible: From Drawing to Modeling in Chemistry.

PubMed

Cooper, Melanie M; Stieff, Mike; DeSutter, Dane

2017-10-01

Sketching as a scientific practice goes beyond the simple act of inscribing diagrams onto paper. Scientists produce a wide range of representations through sketching, as it is tightly coupled to model-based reasoning. Chemists in particular make extensive use of sketches to reason about chemical phenomena and to communicate their ideas. However, the chemical sciences have a unique problem in that chemists deal with the unseen world of the atomic-molecular level. Using sketches, chemists strive to develop causal mechanisms that emerge from the structure and behavior of molecular-level entities, to explain observations of the macroscopic visible world. Interpreting these representations and constructing sketches of molecular-level processes is a crucial component of student learning in the modern chemistry classroom. Sketches also serve as an important component of assessment in the chemistry classroom as student sketches give insight into developing mental models, which allows instructors to observe how students are thinking about a process. In this paper we discuss how sketching can be used to promote such model-based reasoning in chemistry and discuss two case studies of curricular projects, CLUE and The Connected Chemistry Curriculum, that have demonstrated a benefit of this approach. We show how sketching activities can be centrally integrated into classroom norms to promote model-based reasoning both with and without component visualizations. Importantly, each of these projects deploys sketching in support of other types of inquiry activities, such as making predictions or depicting models to support a claim; sketching is not an isolated activity but is used as a tool to support model-based reasoning in the discipline. Copyright © 2017 Cognitive Science Society, Inc.

[Experimental analysis of some determinants of inductive reasoning].

PubMed

Ono, K

1989-02-01

Three experiments were conducted from a behavioral perspective to investigate the determinants of inductive reasoning and to compare some methodological differences. The dependent variable used in these experiments was the threshold of confident response (TCR), which was defined as "the minimal sample size required to establish generalization from instances." Experiment 1 examined the effects of population size on inductive reasoning, and the results from 35 college students showed that the TCR varied in proportion to the logarithm of population size. In Experiment 2, 30 subjects showed distinct sensitivity to both prior probability and base-rate. The results from 70 subjects who participated in Experiment 3 showed that the TCR was affected by its consequences (risk condition), and especially, that humans were sensitive to a loss situation. These results demonstrate the sensitivity of humans to statistical variables in inductive reasoning. Furthermore, methodological comparison indicated that the experimentally observed values of TCR were close to, but not as precise as the optimal values predicted by Bayes' model. On the other hand, the subjective TCR estimated by subjects was highly discrepant from the observed TCR. These findings suggest that various aspects of inductive reasoning can be fruitfully investigated not only from subjective estimations such as probability likelihood but also from an objective behavioral perspective.

Applying Model Analysis to a Resource-Based Analysis of the Force and Motion Conceptual Evaluation

ERIC Educational Resources Information Center

Smith, Trevor I.; Wittmann, Michael C.; Carter, Tom

2014-01-01

Previously, we analyzed the Force and Motion Conceptual Evaluation in terms of a resources-based model that allows for clustering of questions so as to provide useful information on how students correctly or incorrectly reason about physics. In this paper, we apply model analysis to show that the associated model plots provide more information…

Reinforcement learning and counterfactual reasoning explain adaptive behavior in a changing environment.

PubMed

Zhang, Yunfeng; Paik, Jaehyon; Pirolli, Peter

2015-04-01

Animals routinely adapt to changes in the environment in order to survive. Though reinforcement learning may play a role in such adaptation, it is not clear that it is the only mechanism involved, as it is not well suited to producing rapid, relatively immediate changes in strategies in response to environmental changes. This research proposes that counterfactual reasoning might be an additional mechanism that facilitates change detection. An experiment is conducted in which a task state changes over time and the participants had to detect the changes in order to perform well and gain monetary rewards. A cognitive model is constructed that incorporates reinforcement learning with counterfactual reasoning to help quickly adjust the utility of task strategies in response to changes. The results show that the model can accurately explain human data and that counterfactual reasoning is key to reproducing the various effects observed in this change detection paradigm. Copyright © 2015 Cognitive Science Society, Inc.

Assessing clinical reasoning (ASCLIRE): Instrument development and validation.

PubMed

Kunina-Habenicht, Olga; Hautz, Wolf E; Knigge, Michel; Spies, Claudia; Ahlers, Olaf

2015-12-01

Clinical reasoning is an essential competency in medical education. This study aimed at developing and validating a test to assess diagnostic accuracy, collected information, and diagnostic decision time in clinical reasoning. A norm-referenced computer-based test for the assessment of clinical reasoning (ASCLIRE) was developed, integrating the entire clinical decision process. In a cross-sectional study participants were asked to choose as many diagnostic measures as they deemed necessary to diagnose the underlying disease of six different cases with acute or sub-acute dyspnea and provide a diagnosis. 283 students and 20 content experts participated. In addition to diagnostic accuracy, respective decision time and number of used relevant diagnostic measures were documented as distinct performance indicators. The empirical structure of the test was investigated using a structural equation modeling approach. Experts showed higher accuracy rates and lower decision times than students. In a cross-sectional comparison, the diagnostic accuracy of students improved with the year of study. Wrong diagnoses provided by our sample were comparable to wrong diagnoses in practice. We found an excellent fit for a model with three latent factors-diagnostic accuracy, decision time, and choice of relevant diagnostic information-with diagnostic accuracy showing no significant correlation with decision time. ASCLIRE considers decision time as an important performance indicator beneath diagnostic accuracy and provides evidence that clinical reasoning is a complex ability comprising diagnostic accuracy, decision time, and choice of relevant diagnostic information as three partly correlated but still distinct aspects.

An adaptable architecture for patient cohort identification from diverse data sources.

PubMed

Bache, Richard; Miles, Simon; Taweel, Adel

2013-12-01

We define and validate an architecture for systems that identify patient cohorts for clinical trials from multiple heterogeneous data sources. This architecture has an explicit query model capable of supporting temporal reasoning and expressing eligibility criteria independently of the representation of the data used to evaluate them. The architecture has the key feature that queries defined according to the query model are both pre and post-processed and this is used to address both structural and semantic heterogeneity. The process of extracting the relevant clinical facts is separated from the process of reasoning about them. A specific instance of the query model is then defined and implemented. We show that the specific instance of the query model has wide applicability. We then describe how it is used to access three diverse data warehouses to determine patient counts. Although the proposed architecture requires greater effort to implement the query model than would be the case for using just SQL and accessing a data-based management system directly, this effort is justified because it supports both temporal reasoning and heterogeneous data sources. The query model only needs to be implemented once no matter how many data sources are accessed. Each additional source requires only the implementation of a lightweight adaptor. The architecture has been used to implement a specific query model that can express complex eligibility criteria and access three diverse data warehouses thus demonstrating the feasibility of this approach in dealing with temporal reasoning and data heterogeneity.

Affective cognition: Exploring lay theories of emotion.

PubMed

Ong, Desmond C; Zaki, Jamil; Goodman, Noah D

2015-10-01

Humans skillfully reason about others' emotions, a phenomenon we term affective cognition. Despite its importance, few formal, quantitative theories have described the mechanisms supporting this phenomenon. We propose that affective cognition involves applying domain-general reasoning processes to domain-specific content knowledge. Observers' knowledge about emotions is represented in rich and coherent lay theories, which comprise consistent relationships between situations, emotions, and behaviors. Observers utilize this knowledge in deciphering social agents' behavior and signals (e.g., facial expressions), in a manner similar to rational inference in other domains. We construct a computational model of a lay theory of emotion, drawing on tools from Bayesian statistics, and test this model across four experiments in which observers drew inferences about others' emotions in a simple gambling paradigm. This work makes two main contributions. First, the model accurately captures observers' flexible but consistent reasoning about the ways that events and others' emotional responses to those events relate to each other. Second, our work models the problem of emotional cue integration-reasoning about others' emotion from multiple emotional cues-as rational inference via Bayes' rule, and we show that this model tightly tracks human observers' empirical judgments. Our results reveal a deep structural relationship between affective cognition and other forms of inference, and suggest wide-ranging applications to basic psychological theory and psychiatry. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Building Regression Models: The Importance of Graphics.

ERIC Educational Resources Information Center

Dunn, Richard

1989-01-01

Points out reasons for using graphical methods to teach simple and multiple regression analysis. Argues that a graphically oriented approach has considerable pedagogic advantages in the exposition of simple and multiple regression. Shows that graphical methods may play a central role in the process of building regression models. (Author/LS)

Moral dilemmas in females: children are more utilitarian than adults

PubMed Central

Bucciarelli, Monica

2015-01-01

Influential theories on moral judgments propose that they rely either on emotions or on innate moral principles. In contrast, the mental model theory postulates that moral judgments rely on reasoning, either intuition or deliberation. The theory allows for the possibility that intuitions lead to utilitarian judgments. This paper reports two experiments involving fifth-grade children, adolescents, and adults; the results revealed that children reason intuitively to resolve moral dilemmas in which action and inaction lead to different outcomes. In particular, the results showed female children to be more utilitarian than female adults in resolving classical moral dilemmas: they preferred an action that achieved a good outcome for a greater number of people. Within the mental model theory's framework there is no reason to expect that females and males differ in their ability to reason, but at the moment the results for females cannot be generalized to males who were not properly represented in the adults groups of the two experiments. The result revealing that (female) children are more utilitarian than (female) adults, which is hard to explain via many current theories, was predicted by the mental model theory. PMID:26441722

Moral dilemmas and abortion decision-making: Lessons learnt from abortion research in England and Wales.

PubMed

Hoggart, Lesley

2018-05-21

This paper scrutinises the concepts of moral reasoning and personal reasoning, problematising the binary model by looking at young women's pregnancy decision-making. Data from two UK empirical studies are subjected to theoretically driven qualitative secondary analysis, and illustrative cases show how complex decision-making is characterised by an intertwining of the personal and the moral, and is thus best understood by drawing on moral relativism.

REASONS FOR ELECTRONIC CIGARETTE USE BEYOND CIGARETTE SMOKING CESSATION: A CONCEPT MAPPING APPROACH

PubMed Central

Soule, Eric K.; Rosas, Scott R.; Nasim, Aashir

2016-01-01

Introduction Electronic cigarettes (ECIGs) continue to grow in popularity, however, limited research has examined reasons for ECIG use. Methods This study used an integrated, mixed-method participatory research approach called concept mapping (CM) to characterize and describe adults’ reasons for using ECIGs. A total of 108 adults completed a multi-module online CM study that consisted of brainstorming statements about their reasons for ECIG use, sorting each statement into conceptually similar categories, and then rating each statement based on whether it represented a reason why they have used an ECIG in the past month. Results Participants brainstormed a total of 125 unique statements related to their reasons for ECIG use. Multivariate analyses generated a map revealing 11, interrelated components or domains that characterized their reasons for use. Importantly, reasons related to Cessation Methods, Perceived Health Benefits, Private Regard, Convenience and Conscientiousness were rated significantly higher than other categories/types of reasons related to ECIG use (p<.05). There also were significant model differences in participants’ endorsement of reasons based on their demography and ECIG behaviors. Conclusions This study shows that ECIG users are motivated to use ECIGs for many reasons. ECIG regulations should address these reasons for ECIG use in addition to smoking cessation. PMID:26803400

Reasons for electronic cigarette use beyond cigarette smoking cessation: A concept mapping approach.

PubMed

Soule, Eric K; Rosas, Scott R; Nasim, Aashir

2016-05-01

Electronic cigarettes (ECIGs) continue to grow in popularity, however, limited research has examined reasons for ECIG use. This study used an integrated, mixed-method participatory research approach called concept mapping (CM) to characterize and describe adults' reasons for using ECIGs. A total of 108 adults completed a multi-module online CM study that consisted of brainstorming statements about their reasons for ECIG use, sorting each statement into conceptually similar categories, and then rating each statement based on whether it represented a reason why they have used an ECIG in the past month. Participants brainstormed a total of 125 unique statements related to their reasons for ECIG use. Multivariate analyses generated a map revealing 11, interrelated components or domains that characterized their reasons for use. Importantly, reasons related to Cessation Methods, Perceived Health Benefits, Private Regard, Convenience and Conscientiousness were rated significantly higher than other categories/types of reasons related to ECIG use (p<.05). There also were significant model differences in participants' endorsement of reasons based on their demography and ECIG behaviors. This study shows that ECIG users are motivated to use ECIGs for many reasons. ECIG regulations should address these reasons for ECIG use in addition to smoking cessation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Application of nonlinear models to estimate the gain of one-dimensional free-electron lasers

NASA Astrophysics Data System (ADS)

Peter, E.; Rizzato, F. B.; Endler, A.

2017-06-01

In the present work, we make use of simplified nonlinear models based on the compressibility factor (Peter et al., Phys. Plasmas, vol. 20 (12), 2013, 123104) to predict the gain of one-dimensional (1-D) free-electron lasers (FELs), considering space-charge and thermal effects. These models proved to be reasonable to estimate some aspects of 1-D FEL theory, such as the position of the onset of mixing, in the case of a initially cold electron beam, and the position of the breakdown of the laminar regime, in the case of an initially warm beam (Peter et al., Phys. Plasmas, vol. 21 (11), 2014, 113104). The results given by the models are compared to wave-particle simulations showing a reasonable agreement.

Preliminary results from a four-working space, double-acting piston, Stirling engine controls model

NASA Technical Reports Server (NTRS)

Daniele, C. J.; Lorenzo, C. F.

1980-01-01

A four working space, double acting piston, Stirling engine simulation is being developed for controls studies. The development method is to construct two simulations, one for detailed fluid behavior, and a second model with simple fluid behaviour but containing the four working space aspects and engine inertias, validate these models separately, then upgrade the four working space model by incorporating the detailed fluid behaviour model for all four working spaces. The single working space (SWS) model contains the detailed fluid dynamics. It has seven control volumes in which continuity, energy, and pressure loss effects are simulated. Comparison of the SWS model with experimental data shows reasonable agreement in net power versus speed characteristics for various mean pressure levels in the working space. The four working space (FWS) model was built to observe the behaviour of the whole engine. The drive dynamics and vehicle inertia effects are simulated. To reduce calculation time, only three volumes are used in each working space and the gas temperature are fixed (no energy equation). Comparison of the FWS model predicted power with experimental data shows reasonable agreement. Since all four working spaces are simulated, the unique capabilities of the model are exercised to look at working fluid supply transients, short circuit transients, and piston ring leakage effects.

Minority games and stylized facts

NASA Astrophysics Data System (ADS)

Challet, Damien; Marsili, Matteo; Zhang, Yi-Cheng

2001-10-01

The minority game is a generic model of competing adaptive agents, which is often believed to be a model of financial markets. We discuss to which extent this is a reasonable statement, and present minimal modifications that make this model reproduce stylized facts. The resulting model shows that without speculators, prices follow random walks, and that stylized facts disappear if enough speculators take into account their market impact.

Gambling and the Reasoned Action Model: Predicting Past Behavior, Intentions, and Future Behavior.

PubMed

Dahl, Ethan; Tagler, Michael J; Hohman, Zachary P

2018-03-01

Gambling is a serious concern for society because it is highly addictive and is associated with a myriad of negative outcomes. The current study applied the Reasoned Action Model (RAM) to understand and predict gambling intentions and behavior. Although prior studies have taken a reasoned action approach to understand gambling, no prior study has fully applied the RAM or used the RAM to predict future gambling. Across two studies the RAM was used to predict intentions to gamble, past gambling behavior, and future gambling behavior. In study 1 the model significantly predicted intentions and past behavior in both a college student and Amazon Mechanical Turk sample. In study 2 the model predicted future gambling behavior, measured 2 weeks after initial measurement of the RAM constructs. This study stands as the first to show the utility of the RAM in predicting future gambling behavior. Across both studies, attitudes and perceived normative pressure were the strongest predictors of intentions to gamble. These findings provide increased understanding of gambling and inform the development of gambling interventions based on the RAM.

Toward an Aristotelian Model of Teacher Reasoning.

ERIC Educational Resources Information Center

Orton, Robert E.

1997-01-01

Utilizes Aristotle's three-way distinctions between theory, practice, and production to describe a balanced model of teacher reasoning. Reviews differing models of teacher reasoning that emphasize the role of contemplation and subject-matter representations. Uses the Aristotelian model to point toward a normative vision of teacher reasoning. (MJP)

Individual differences and reasoning: a study on personality traits.

PubMed

Bensi, Luca; Giusberti, Fiorella; Nori, Raffaella; Gambetti, Elisa

2010-08-01

Personality can play a crucial role in how people reason and decide. Identifying individual differences related to how we actively gather information and use evidence could lead to a better comprehension and predictability of human reasoning. Recent findings have shown that some personality traits are related to similar decision-making patterns showed by people with mental disorders. We performed research with the aim to investigate delusion-proneness, obsessive-like personality, anxiety (trait and state), and reasoning styles in individuals from the general population. We introduced personality trait and state anxiety scores in a regression model to explore specific associations with: (1) amount of data-gathered prior to making a decision; and (2) the use of confirmatory and disconfirmatory evidence. Results showed that all our independent variables were positively or negatively associated with the amount of data collected in order to make simple probabilistic decisions. Anxiety and obsessiveness were the only predictors of the weight attributed to evidence in favour or against a hypothesis. Findings were discussed in relation to theoretical assumptions, predictions, and clinical implications. Personality traits can predict peculiar ways to reason and decide that, in turn, could be involved to some extent in the formation and/or maintenance of psychological disorders.

OWL reasoning framework over big biological knowledge network.

PubMed

Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity.

OWL Reasoning Framework over Big Biological Knowledge Network

PubMed Central

Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity. PMID:24877076

Option Generation Techniques for Command and Control.

DTIC Science & Technology

1983-01-01

and discuss some reasons why decision making is often less than perfect. 3.2. The Process of Decision Making Figure 3.1 shows a model of the various...responses to changes in the problem context. Most of these potential reasons for poor decision making stem from the human decision maker’s cognitive...several advantages: (1) It provides a mechanism for quickly estimating the scope of the effort that should be involved in making the decison and a road map

An adaptable architecture for patient cohort identification from diverse data sources

PubMed Central

Bache, Richard; Miles, Simon; Taweel, Adel

2013-01-01

Objective We define and validate an architecture for systems that identify patient cohorts for clinical trials from multiple heterogeneous data sources. This architecture has an explicit query model capable of supporting temporal reasoning and expressing eligibility criteria independently of the representation of the data used to evaluate them. Method The architecture has the key feature that queries defined according to the query model are both pre and post-processed and this is used to address both structural and semantic heterogeneity. The process of extracting the relevant clinical facts is separated from the process of reasoning about them. A specific instance of the query model is then defined and implemented. Results We show that the specific instance of the query model has wide applicability. We then describe how it is used to access three diverse data warehouses to determine patient counts. Discussion Although the proposed architecture requires greater effort to implement the query model than would be the case for using just SQL and accessing a data-based management system directly, this effort is justified because it supports both temporal reasoning and heterogeneous data sources. The query model only needs to be implemented once no matter how many data sources are accessed. Each additional source requires only the implementation of a lightweight adaptor. Conclusions The architecture has been used to implement a specific query model that can express complex eligibility criteria and access three diverse data warehouses thus demonstrating the feasibility of this approach in dealing with temporal reasoning and data heterogeneity. PMID:24064442

Casuistry as bioethical method: an empirical perspective.

PubMed

Braunack-Mayer, A

2001-07-01

This paper examines the role that casuistry, a model of bioethical reasoning revived by Jonsen and Toulmin, plays in ordinary moral reasoning. I address the question: 'What is the evidence for contemporary casuistry's claim that everyday moral reasoning is casuistic in nature?' The paper begins with a description of the casuistic method, and then reviews the empirical arguments Jonsen and Toulmin offer to show that every-day moral decision-making is casuistic. Finally, I present the results of qualitative research conducted with 15 general practitioners (GPs) in South Australia, focusing on the ways in which these GP participants used stories and anecdotes in their own moral reasoning. This research found that the GPs interviewed did use a form of casuistry when talking about ethical dilemmas. However, the GPs' homespun casuistry often lacked one central element of casuistic reasoning--clear paradigm cases on which to base comparisons. I conclude that casuistic reasoning does appear to play a role in every-day moral decision-making, but that it is a more subdued role than perhaps casuists would like.

In defense of compilation: A response to Davis' form and content in model-based reasoning

NASA Technical Reports Server (NTRS)

Keller, Richard

1990-01-01

In a recent paper entitled 'Form and Content in Model Based Reasoning', Randy Davis argues that model based reasoning research aimed at compiling task specific rules from underlying device models is mislabeled, misguided, and diversionary. Some of Davis' claims are examined and his basic conclusions are challenged about the value of compilation research to the model based reasoning community. In particular, Davis' claim is refuted that model based reasoning is exempt from the efficiency benefits provided by knowledge compilation techniques. In addition, several misconceptions are clarified about the role of representational form in compilation. It is concluded that techniques have the potential to make a substantial contribution to solving tractability problems in model based reasoning.

Reasons for dropout in swimmers, differences between gender and age and intentions to return to competition.

PubMed

Monteiro, Diogo M; Marinho, Daniel A; Moutão, João M; Vitorino, Anabela P; Antunes, Raúl N; Cid, Luís

2018-01-01

This study's main purpose was to analyze reasons for dropout in competitive swimmers and differences between gender and age groups. The influence of dropout on swimmers intentions to return to competition, invariance across gender and validation of Questionnaire of Reasons for Attrition were also analyzed. Study 1 - 366 athletes participated (N.=366; mean age 15.96, SD 5.99) and the data gathered was used for the exploratory analysis, and data gathered on 1008 athletes were used for the confirmatory analysis and the structural equations (N.=1008; mean age 16.26, SD 6.12); Study 2: 1008 athletes participated (N.=1008; mean age 16.26, SD 6.12) on the descriptive and inferential analysis of the reasons behind the practice dropout. The Questionnaire of Reasons Attrition was used in both studies to assess the reasons associated with the practice dropout. In study 1, the results showed an acceptable fit of the measurement model and invariance across gender and also predictive validity regarding swimmers intentions to return to competition (e.g., "demands/pressure" negatively predict intentions). In study 2, the main results showed that the most significant reason for dropout in both genders and all age groups was "dissatisfaction/other priorities"; the study also showed there to be differences between gender and age groups (e.g., female and younger athletes valued "demands/ pressure "more). This study offers useful guidelines for the training process and to support decisions on sports politics to be implemented to overcome the dropout rate. However, it is important to broaden the evidence to other sports and implement programs on identified priority areas based on longitudinal perspectives.

Engine isolation for structural-borne interior noise reduction in a general aviation aircraft

NASA Technical Reports Server (NTRS)

Unruh, J. F.; Scheidt, D. C.

1981-01-01

Engine vibration isolation for structural-borne interior noise reduction is investigated. A laboratory based test procedure to simulate engine induced structure-borne noise transmission, the testing of a range of candidate isolators for relative performance data, and the development of an analytical model of the transmission phenomena for isolator design evaluation are addressed. The isolator relative performance test data show that the elastomeric isolators do not appear to operate as single degree of freedom systems with respect to noise isolation. Noise isolation beyond 150 Hz levels off and begins to decrease somewhat above 600 Hz. Coupled analytical and empirical models were used to study the structure-borne noise transmission phenomena. Correlation of predicted results with measured data show that (1) the modeling procedures are reasonably accurate for isolator design evaluation, (2) the frequency dependent properties of the isolators must be included in the model if reasonably accurate noise prediction beyond 150 Hz is desired. The experimental and analytical studies were carried out in the frequency range from 10 Hz to 1000 Hz.

A Film Depositional Model of Permeability for Mineral Reactions in Unsaturated Media.

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

Freedman, Vicky L.; Saripalli, Prasad; Bacon, Diana H.

2004-11-15

A new modeling approach based on the biofilm models of Taylor et al. (1990, Water Resources Research, 26, 2153-2159) has been developed for modeling changes in porosity and permeability in saturated porous media and implemented in an inorganic reactive transport code. Application of the film depositional models to mineral precipitation and dissolution reactions requires that calculations of mineral films be dynamically changing as a function of time dependent reaction processes. Since calculations of film thicknesses do not consider mineral density, results show that the film porosity model does not adequately describe volumetric changes in the porous medium. These effects canmore » be included in permeability calculations by coupling the film permeability models (Mualem and Childs and Collis-George) to a volumetric model that incorporates both mineral density and reactive surface area. Model simulations demonstrate that an important difference between the biofilm and mineral film models is in the translation of changes in mineral radii to changes in pore space. Including the effect of tortuosity on pore radii changes improves the performance of the Mualem permeability model for both precipitation and dissolution. Results from simulation of simultaneous dissolution and secondary mineral precipitation provides reasonable estimates of porosity and permeability. Moreover, a comparison of experimental and simulated data show that the model yields qualitatively reasonable results for permeability changes due to solid-aqueous phase reactions.« less

Detaching reasons from aims: fair play and well-being in soccer as a function of pursuing performance-approach goals for autonomous or controlling reasons.

PubMed

Vansteenkiste, Maarten; Mouratidis, Athanasios; Lens, Willy

2010-04-01

In two cross-sectional studies we investigated whether soccer players' well-being (Study 1) and moral functioning (Studies 1 and 2) is related to performance-approach goals and to the autonomous and controlling reasons underlying their pursuit. In support of our hypotheses, we found in Study 1 that autonomous reasons were positively associated with vitality and positive affect, whereas controlling reasons were positively related to negative affect and mostly unrelated to indicators of morality. To investigate the lack of systematic association with moral outcomes, we explored in Study 2 whether performance-approach goals or their underlying reasons would yield an indirect relation to moral outcomes through their association with players' objectifying attitude-their tendency to depersonalize their opponents. Structural equation modeling showed that controlling reasons for performance-approach goals were positively associated with an objectifying attitude, which in turn was positively associated to unfair functioning. Results are discussed within the achievement goal perspective (Elliot, 2005) and self-determination theory (Deci & Ryan, 2000).

The neural basis of conditional reasoning with arbitrary content.

PubMed

Noveck, Ira A; Goel, Vinod; Smith, Kathleen W

2004-01-01

Behavioral predictions about reasoning have usually contrasted two accounts, Mental Logic and Mental Models. Neuroimaging techniques have been providing new measures that transcend this debate. We tested a hypothesis from Goel and Dolan (2003) that predicts neural activity predominantly in a left parietal-frontal system when participants reason with arbitrary (non-meaningful) materials. In an event-related fMRI investigation, we employed propositional syllogisms, the majority of which involved conditional reasoning. While investigating conditional reasoning generally, we ultimately focused on the neural activity linked to the two valid conditional forms--Modus Ponens (If p then q; p//q) and Modus Tollens (If p then q; not-q//not-p). Consistent with Goel and Dolan (2003), we found a left lateralized parietal frontal network for both inference forms with increasing activation when reasoning becomes more challenging by way of Modus Tollens. These findings show that the previous findings with more complex Aristotlean syllogisms are robust and cast doubt upon accounts of reasoning that accord primary inferential processes uniquely to either the right hemisphere or to language areas.

Robust Fusion of Color and Depth Data for RGB-D Target Tracking Using Adaptive Range-Invariant Depth Models and Spatio-Temporal Consistency Constraints.

PubMed

Xiao, Jingjing; Stolkin, Rustam; Gao, Yuqing; Leonardis, Ales

2017-09-06

This paper presents a novel robust method for single target tracking in RGB-D images, and also contributes a substantial new benchmark dataset for evaluating RGB-D trackers. While a target object's color distribution is reasonably motion-invariant, this is not true for the target's depth distribution, which continually varies as the target moves relative to the camera. It is therefore nontrivial to design target models which can fully exploit (potentially very rich) depth information for target tracking. For this reason, much of the previous RGB-D literature relies on color information for tracking, while exploiting depth information only for occlusion reasoning. In contrast, we propose an adaptive range-invariant target depth model, and show how both depth and color information can be fully and adaptively fused during the search for the target in each new RGB-D image. We introduce a new, hierarchical, two-layered target model (comprising local and global models) which uses spatio-temporal consistency constraints to achieve stable and robust on-the-fly target relearning. In the global layer, multiple features, derived from both color and depth data, are adaptively fused to find a candidate target region. In ambiguous frames, where one or more features disagree, this global candidate region is further decomposed into smaller local candidate regions for matching to local-layer models of small target parts. We also note that conventional use of depth data, for occlusion reasoning, can easily trigger false occlusion detections when the target moves rapidly toward the camera. To overcome this problem, we show how combining target information with contextual information enables the target's depth constraint to be relaxed. Our adaptively relaxed depth constraints can robustly accommodate large and rapid target motion in the depth direction, while still enabling the use of depth data for highly accurate reasoning about occlusions. For evaluation, we introduce a new RGB-D benchmark dataset with per-frame annotated attributes and extensive bias analysis. Our tracker is evaluated using two different state-of-the-art methodologies, VOT and object tracking benchmark, and in both cases it significantly outperforms four other state-of-the-art RGB-D trackers from the literature.

Using Computer Simulations for Promoting Model-based Reasoning. Epistemological and Educational Dimensions

NASA Astrophysics Data System (ADS)

Develaki, Maria

2017-11-01

Scientific reasoning is particularly pertinent to science education since it is closely related to the content and methodologies of science and contributes to scientific literacy. Much of the research in science education investigates the appropriate framework and teaching methods and tools needed to promote students' ability to reason and evaluate in a scientific way. This paper aims (a) to contribute to an extended understanding of the nature and pedagogical importance of model-based reasoning and (b) to exemplify how using computer simulations can support students' model-based reasoning. We provide first a background for both scientific reasoning and computer simulations, based on the relevant philosophical views and the related educational discussion. This background suggests that the model-based framework provides an epistemologically valid and pedagogically appropriate basis for teaching scientific reasoning and for helping students develop sounder reasoning and decision-taking abilities and explains how using computer simulations can foster these abilities. We then provide some examples illustrating the use of computer simulations to support model-based reasoning and evaluation activities in the classroom. The examples reflect the procedure and criteria for evaluating models in science and demonstrate the educational advantages of their application in classroom reasoning activities.

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

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

Zhou, Z; Folkert, M; Wang, J

2016-06-15

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidentialmore » reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.« less

Inverse magnetic catalysis from improved holographic QCD in the Veneziano limit

NASA Astrophysics Data System (ADS)

Gürsoy, Umut; Iatrakis, Ioannis; Järvinen, Matti; Nijs, Govert

2017-03-01

We study the dependence of the chiral condensate on external magnetic field in the context of holographic QCD at large number of flavors. We consider a holographic QCD model where the flavor degrees of freedom fully backreact on the color dynamics. Perturbative QCD calculations have shown that B acts constructively on the chiral condensate, a phenomenon called "magnetic catalysis". In contrast, recent lattice calculations show that, depending on the number of flavors and temperature, the magnetic field may also act destructively, which is called "inverse magnetic catalysis". Here we show that the holographic theory is capable of both behaviors depending on the choice of parameters. For reasonable choice of the potentials entering the model we find qualitative agreement with the lattice expectations. Our results provide insight for the physical reasons behind the inverse magnetic catalysis. In particular, we argue that the backreaction of the flavors to the background geometry decatalyzes the condensate.

The Coastal Zone: Man and Nature. An Application of the Socio-Scientific Reasoning Model.

ERIC Educational Resources Information Center

Maul, June Paradise; And Others

The curriculum model described here has been designed by incorporating the socio-scientific reasoning model with a simulation design in an attempt to have students investigate the onshore impacts of Outer Continental Shelf (OCS) gas and oil development. The socio-scientific reasoning model incorporates a logical/physical reasoning component as…

A mediation model to explain decision making under conditions of risk among adolescents: the role of fluid intelligence and probabilistic reasoning.

PubMed

Donati, Maria Anna; Panno, Angelo; Chiesi, Francesca; Primi, Caterina

2014-01-01

This study tested the mediating role of probabilistic reasoning ability in the relationship between fluid intelligence and advantageous decision making among adolescents in explicit situations of risk--that is, in contexts in which information on the choice options (gains, losses, and probabilities) were explicitly presented at the beginning of the task. Participants were 282 adolescents attending high school (77% males, mean age = 17.3 years). We first measured fluid intelligence and probabilistic reasoning ability. Then, to measure decision making under explicit conditions of risk, participants performed the Game of Dice Task, in which they have to decide among different alternatives that are explicitly linked to a specific amount of gain or loss and have obvious winning probabilities that are stable over time. Analyses showed a significant positive indirect effect of fluid intelligence on advantageous decision making through probabilistic reasoning ability that acted as a mediator. Specifically, fluid intelligence may enhance ability to reason in probabilistic terms, which in turn increases the likelihood of advantageous choices when adolescents are confronted with an explicit decisional context. Findings show that in experimental paradigm settings, adolescents are able to make advantageous decisions using cognitive abilities when faced with decisions under explicit risky conditions. This study suggests that interventions designed to promote probabilistic reasoning, for example by incrementing the mathematical prerequisites necessary to reason in probabilistic terms, may have a positive effect on adolescents' decision-making abilities.

The relationship between memory and inductive reasoning: does it develop?

PubMed

Hayes, Brett K; Fritz, Kristina; Heit, Evan

2013-05-01

In 2 studies, the authors examined the development of the relationship between inductive reasoning and visual recognition memory. In both studies, 5- to 6-year-old children and adults were shown instances of a basic-level category (dogs) followed by a test set containing old and new category members that varied in their similarity to study items. Participants were given either recognition instructions (memorize study items and discriminate between old and new test items) or induction instructions (learn about a novel property shared by the study items and decide whether it generalizes to test items). Across both tasks, children made a greater number of positive responses than did adults. Across both age groups, a greater number of positive responses were made in induction than in recognition. The application of a mathematical model, called GEN-EX for generalization from examples, showed that both memory and reasoning data could be explained by a single exemplar-based process that assumes task and age differences in generalization gradients. These results show considerable developmental continuity in the cognitive processes that underlie memory and inductive reasoning.

A New Energy-Critical Plane Damage Parameter for Multiaxial Fatigue Life Prediction of Turbine Blades.

PubMed

Yu, Zheng-Yong; Zhu, Shun-Peng; Liu, Qiang; Liu, Yunhan

2017-05-08

As one of fracture critical components of an aircraft engine, accurate life prediction of a turbine blade to disk attachment is significant for ensuring the engine structural integrity and reliability. Fatigue failure of a turbine blade is often caused under multiaxial cyclic loadings at high temperatures. In this paper, considering different failure types, a new energy-critical plane damage parameter is proposed for multiaxial fatigue life prediction, and no extra fitted material constants will be needed for practical applications. Moreover, three multiaxial models with maximum damage parameters on the critical plane are evaluated under tension-compression and tension-torsion loadings. Experimental data of GH4169 under proportional and non-proportional fatigue loadings and a case study of a turbine disk-blade contact system are introduced for model validation. Results show that model predictions by Wang-Brown (WB) and Fatemi-Socie (FS) models with maximum damage parameters are conservative and acceptable. For the turbine disk-blade contact system, both of the proposed damage parameters and Smith-Watson-Topper (SWT) model show reasonably acceptable correlations with its field number of flight cycles. However, life estimations of the turbine blade reveal that the definition of the maximum damage parameter is not reasonable for the WB model but effective for both the FS and SWT models.

A New Energy-Critical Plane Damage Parameter for Multiaxial Fatigue Life Prediction of Turbine Blades

PubMed Central

Yu, Zheng-Yong; Zhu, Shun-Peng; Liu, Qiang; Liu, Yunhan

2017-01-01

As one of fracture critical components of an aircraft engine, accurate life prediction of a turbine blade to disk attachment is significant for ensuring the engine structural integrity and reliability. Fatigue failure of a turbine blade is often caused under multiaxial cyclic loadings at high temperatures. In this paper, considering different failure types, a new energy-critical plane damage parameter is proposed for multiaxial fatigue life prediction, and no extra fitted material constants will be needed for practical applications. Moreover, three multiaxial models with maximum damage parameters on the critical plane are evaluated under tension-compression and tension-torsion loadings. Experimental data of GH4169 under proportional and non-proportional fatigue loadings and a case study of a turbine disk-blade contact system are introduced for model validation. Results show that model predictions by Wang-Brown (WB) and Fatemi-Socie (FS) models with maximum damage parameters are conservative and acceptable. For the turbine disk-blade contact system, both of the proposed damage parameters and Smith-Watson-Topper (SWT) model show reasonably acceptable correlations with its field number of flight cycles. However, life estimations of the turbine blade reveal that the definition of the maximum damage parameter is not reasonable for the WB model but effective for both the FS and SWT models. PMID:28772873

A rational account of pedagogical reasoning: teaching by, and learning from, examples.

PubMed

Shafto, Patrick; Goodman, Noah D; Griffiths, Thomas L

2014-06-01

Much of learning and reasoning occurs in pedagogical situations--situations in which a person who knows a concept chooses examples for the purpose of helping a learner acquire the concept. We introduce a model of teaching and learning in pedagogical settings that predicts which examples teachers should choose and what learners should infer given a teacher's examples. We present three experiments testing the model predictions for rule-based, prototype, and causally structured concepts. The model shows good quantitative and qualitative fits to the data across all three experiments, predicting novel qualitative phenomena in each case. We conclude by discussing implications for understanding concept learning and implications for theoretical claims about the role of pedagogy in human learning. Copyright © 2014 Elsevier Inc. All rights reserved.

Aminoglycoside Therapy Manager: An Advanced Computer Program for Decision Support for Drug Dosing and Therapeutic Monitoring

PubMed Central

Lenert, Leslie; Lurie, Jon; Coleman, Robert; Klosterman, Heidrun; Blaschke, Terrence

1990-01-01

In this paper, we will describe an advanced drug dosing program, Aminoglycoside Therapy Manager that reasons using Bayesian pharmacokinetic modeling and symbolic modeling of patient status and drug response. Our design is similar to the design of the Digitalis Therapy Advisor program, but extends previous work by incorporating a Bayesian pharmacokinetic model, a “meta-level” analysis of drug concentrations to identify sampling errors and changes in pharmacokinetics, and including the results of the “meta-level” analysis in reasoning for dosing and therapeutic monitoring recommendations. The program is user friendly and runs on low cost general-purpose hardware. Validation studies show that the program is as accurate in predicting future drug concentrations as an expert using commercial Bayesian forecasting software.

Experimental Modeling of a Formula Student Carbon Composite Nose Cone

PubMed Central

Fellows, Neil A.

2017-01-01

A numerical impact study is presented on a Formula Student (FS) racing car carbon composite nose cone. The effect of material model and model parameter selection on the numerical deceleration curves is discussed in light of the experimental deceleration data. The models show reasonable correlation in terms of the shape of the deceleration-displacement curves but do not match the peak deceleration values with errors greater that 30%. PMID:28772982

Estimating potential habitat for 134 eastern US tree species under six climate scenarios

Treesearch

Louis R. Iverson; Anantha M. Prasad; Stephen N. Matthews; Matthew Peters

2008-01-01

We modeled and mapped, using the predictive data mining tool Random Forests, 134 tree species from the eastern United States for potential response to several scenarios of climate change. Each species was modeled individually to show current and potential future habitats according to two emission scenarios (high emissions on current trajectory and reasonable...

Can cognitive psychological research on reasoning enhance the discussion around moral judgments?

PubMed

Bialek, Michal; Terbeck, Sylvia

2016-08-01

In this article we will demonstrate how cognitive psychological research on reasoning and decision making could enhance discussions and theories of moral judgments. In the first part, we will present recent dual-process models of moral judgments and describe selected studies which support these approaches. However, we will also present data that contradict the model predictions, suggesting that approaches to moral judgment might be more complex. In the second part, we will show how cognitive psychological research on reasoning might be helpful in understanding moral judgments. Specifically, we will highlight approaches addressing the interaction between intuition and reflection. Our data suggest that a sequential model of engaging in deliberation might have to be revised. Therefore, we will present an approach based on Signal Detection Theory and on intuitive conflict detection. We predict that individuals arrive at the moral decisions by comparing potential action outcomes (e.g., harm caused and utilitarian gain) simultaneously. The response criterion can be influenced by intuitive processes, such as heuristic moral value processing, or considerations of harm caused.

Can Earth System Model Provide Reasonable Natural Runoff Estimates to Support Water Management Studies?

NASA Astrophysics Data System (ADS)

Kao, S. C.; Shi, X.; Kumar, J.; Ricciuto, D. M.; Mao, J.; Thornton, P. E.

2017-12-01

With the concern of changing hydrologic regime, there is a crucial need to better understand how water availability may change and influence water management decisions in the projected future climate conditions. Despite that surface hydrology has long been simulated by land model within the Earth System modeling (ESM) framework, given the coarser horizontal resolution and lack of engineering-level calibration, raw runoff from ESM is generally discarded by water resource managers when conducting hydro-climate impact assessments. To identify a likely path to improve the credibility of ESM-simulated natural runoff, we conducted regional model simulation using the land component (ALM) of the Accelerated Climate Modeling for Energy (ACME) version 1 focusing on the conterminous United States (CONUS). Two very different forcing data sets, including (1) the conventional 0.5° CRUNCEP (v5, 1901-2013) and (2) the 1-km Daymet (v3, 1980-2013) aggregated to 0.5°, were used to conduct 20th century transient simulation with satellite phenology. Additional meteorologic and hydrologic observations, including PRISM precipitation and U.S. Geological Survey WaterWatch runoff, were used for model evaluation. For various CONUS hydrologic regions (such as Pacific Northwest), we found that Daymet can significantly improve the reasonableness of simulated ALM runoff even without intensive calibration. The large dry bias of CRUNCEP precipitation (evaluated by PRISM) in multiple CONUS hydrologic regions is believed to be the main reason causing runoff underestimation. The results suggest that when driving with skillful precipitation estimates, ESM has the ability to produce reasonable natural runoff estimates to support further water management studies. Nevertheless, model calibration will be required for regions (such as Upper Colorado) where ill performance is showed for multiple different forcings.

Radiosity diffusion model in 3D

NASA Astrophysics Data System (ADS)

Riley, Jason D.; Arridge, Simon R.; Chrysanthou, Yiorgos; Dehghani, Hamid; Hillman, Elizabeth M. C.; Schweiger, Martin

2001-11-01

We present the Radiosity-Diffusion model in three dimensions(3D), as an extension to previous work in 2D. It is a method for handling non-scattering spaces in optically participating media. We present the extension of the model to 3D including an extension to the model to cope with increased complexity of the 3D domain. We show that in 3D more careful consideration must be given to the issues of meshing and visibility to model the transport of light within reasonable computational bounds. We demonstrate the model to be comparable to Monte-Carlo simulations for selected geometries, and show preliminary results of comparisons to measured time-resolved data acquired on resin phantoms.

The Co-Emergence of Aggregate and Modelling Reasoning

ERIC Educational Resources Information Center

Aridor, Keren; Ben-Zvi, Dani

2017-01-01

This article examines how two processes--reasoning with statistical modelling of a real phenomenon and aggregate reasoning--can co-emerge. We focus in this case study on the emergent reasoning of two fifth graders (aged 10) involved in statistical data analysis, informal inference, and modelling activities using TinkerPlots™. We describe nine…

Proportional Reasoning of Preservice Elementary Education Majors: An Epistemic Model of the Proportional Reasoning Construct.

ERIC Educational Resources Information Center

Fleener, M. Jayne

Current research and learning theory suggest that a hierarchy of proportional reasoning exists that can be tested. Using G. Vergnaud's four complexity variables (structure, content, numerical characteristics, and presentation) and T. E. Kieren's model of rational number knowledge building, an epistemic model of proportional reasoning was…

Modeling of air pollution from the power plant ash dumps

NASA Astrophysics Data System (ADS)

Aleksic, Nenad M.; Balać, Nedeljko

A simple model of air pollution from power plant ash dumps is presented, with emission rates calculated from the Bagnold formula and transport simulated by the ATDL type model. Moisture effects are accounted for by assumption that there is no pollution on rain days. Annual mean daily sedimentation rates, calculated for the area around the 'Nikola Tesla' power plants near Belgrade for 1987, show reasonably good agreement with observations.

The single-zone numerical model of homogeneous charge compression ignition engine performance

NASA Astrophysics Data System (ADS)

Fedyanov, E. A.; Itkis, E. M.; Kuzmin, V. N.; Shumskiy, S. N.

2017-02-01

The single-zone model of methane-air mixture combustion in the Homogeneous Charge Compression Ignition engine was developed. First modeling efforts resulted in the selection of the detailed kinetic reaction mechanism, most appropriate for the conditions of the HCCI process. Then, the model was completed so as to simulate the performance of the four-stroke engine and was coupled by physically reasonable adjusting functions. Validation of calculations against experimental data showed acceptable agreement.

"Role Models Are Real People": Speakers and Field Trips for Chicago's American Indian Elementary School Children.

ERIC Educational Resources Information Center

Hill, Lola L.

This two-part document describes the background and development of "Role Models Are Real People," a speakers' program for at-risk American Indian students, grades 6-8, in Chicago. The first part of the document includes the program proposal, outlining dropout statistics and other data showing reason for concern about American Indian…

Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?

ERIC Educational Resources Information Center

Ghassib, Hisham B.

2010-01-01

The basic premise of this paper is the fact that science has become a major industry: the knowledge industry. The paper throws some light on the reasons for the transformation of science from a limited, constrained and marginal craft into a major industry. It, then, presents a productivist industrial model of knowledge production, which shows its…

Finding Groups Using Model-based Cluster Analysis: Heterogeneous Emotional Self-regulatory Processes and Heavy Alcohol Use Risk

PubMed Central

Mun, Eun-Young; von Eye, Alexander; Bates, Marsha E.; Vaschillo, Evgeny G.

2010-01-01

Model-based cluster analysis is a new clustering procedure to investigate population heterogeneity utilizing finite mixture multivariate normal densities. It is an inferentially based, statistically principled procedure that allows comparison of non-nested models using the Bayesian Information Criterion (BIC) to compare multiple models and identify the optimum number of clusters. The current study clustered 36 young men and women based on their baseline heart rate (HR) and HR variability (HRV), chronic alcohol use, and reasons for drinking. Two cluster groups were identified and labeled High Alcohol Risk and Normative groups. Compared to the Normative group, individuals in the High Alcohol Risk group had higher levels of alcohol use and more strongly endorsed disinhibition and suppression reasons for use. The High Alcohol Risk group showed significant HRV changes in response to positive and negative emotional and appetitive picture cues, compared to neutral cues. In contrast, the Normative group showed a significant HRV change only to negative cues. Findings suggest that the individuals with autonomic self-regulatory difficulties may be more susceptible to heavy alcohol use and use alcohol for emotional regulation. PMID:18331138

Predicting and understanding undergraduate students' intentions to gamble in a casino using an extended model of the theory of reasoned action and the theory of planned behavior.

PubMed

Lee, Hyung-Seok

2013-06-01

Given that current television programming contains numerous gambling portrayals, it is imperative to understand whether and to what extent these gambling behaviors in media influence individuals' beliefs, attitudes, and intentions. This study explores an extended model of the theory of reasoned action (TRA) by including gambling media exposure as a distal, mediating and mediated factor in predicting undergraduate students' intentions to gamble in a casino. Findings show that the extended model of TRA clearly indicates that the constructs of gambling media exposure, prior gambling experience, and level of gambling addiction contribute to the prediction of undergraduate students' casino gambling intentions. Theoretical implications of gambling media effects and practical implications for public policy are discussed, and future research directions are outlined.

Mental models: an alternative evaluation of a sensemaking approach to ethics instruction.

PubMed

Brock, Meagan E; Vert, Andrew; Kligyte, Vykinta; Waples, Ethan P; Sevier, Sydney T; Mumford, Michael D

2008-09-01

In spite of the wide variety of approaches to ethics training it is still debatable which approach has the highest potential to enhance professionals' integrity. The current effort assesses a novel curriculum that focuses on metacognitive reasoning strategies researchers use when making sense of day-to-day professional practices that have ethical implications. The evaluated trainings effectiveness was assessed by examining five key sensemaking processes, such as framing, emotion regulation, forecasting, self-reflection, and information integration that experts and novices apply in ethical decision-making. Mental models of trained and untrained graduate students, as well as faculty, working in the field of physical sciences were compared using a think-aloud protocol 6 months following the ethics training. Evaluation and comparison of the mental models of participants provided further validation evidence for sensemaking training. Specifically, it was found that trained students applied metacognitive reasoning strategies learned during training in their ethical decision-making that resulted in complex mental models focused on the objective assessment of the situation. Mental models of faculty and untrained students were externally-driven with a heavy focus on autobiographical processes. The study shows that sensemaking training has a potential to induce shifts in researchers' mental models by making them more cognitively complex via the use of metacognitive reasoning strategies. Furthermore, field experts may benefit from sensemaking training to improve their ethical decision-making framework in highly complex, novel, and ambiguous situations.

Training versus engagement as paths to cognitive enrichment with aging.

PubMed

Stine-Morrow, Elizabeth A L; Payne, Brennan R; Roberts, Brent W; Kramer, Arthur F; Morrow, Daniel G; Payne, Laura; Hill, Patrick L; Jackson, Joshua J; Gao, Xuefei; Noh, Soo Rim; Janke, Megan C; Parisi, Jeanine M

2014-12-01

While a training model of cognitive intervention targets the improvement of particular skills through instruction and practice, an engagement model is based on the idea that being embedded in an intellectually and socially complex environment can impact cognition, perhaps even broadly, without explicit instruction. We contrasted these 2 models of cognitive enrichment by randomly assigning healthy older adults to a home-based inductive reasoning training program, a team-based competitive program in creative problem solving, or a wait-list control. As predicted, those in the training condition showed selective improvement in inductive reasoning. Those in the engagement condition, on the other hand, showed selective improvement in divergent thinking, a key ability exercised in creative problem solving. On average, then, both groups appeared to show ability-specific effects. However, moderators of change differed somewhat for those in the engagement and training interventions. Generally, those who started either intervention with a more positive cognitive profile showed more cognitive growth, suggesting that cognitive resources enabled individuals to take advantage of environmental enrichment. Only in the engagement condition did initial levels of openness and social network size moderate intervention effects on cognition, suggesting that comfort with novelty and an ability to manage social resources may be additional factors contributing to the capacity to take advantage of the environmental complexity associated with engagement. Collectively, these findings suggest that training and engagement models may offer alternative routes to cognitive resilience in late life. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Training versus Engagement as Paths to Cognitive Enrichment with Aging

PubMed Central

Stine-Morrow, Elizabeth A. L.; Payne, Brennan R.; Roberts, Brent W.; Kramer, Arthur F.; Morrow, Daniel G.; Payne, Laura; Hill, Patrick L.; Jackson, Joshua J.; Gao, Xuefei; Noh, Soo Rim; Janke, Megan C.; Parisi, Jeanine M.

2015-01-01

While a training model of cognitive intervention targets the improvement of particular skills through instruction and practice, an engagement model is based on the idea that being embedded in an intellectually and socially complex environment can impact cognition, perhaps even broadly, without explicit instruction. We contrasted these two models of cognitive enrichment by randomly assigning healthy older adults to a home-based inductive reasoning training program, a team-based competitive program in creative problem solving, or to a wait-list control. As predicted, those in the training condition showed selective improvement in inductive reasoning. Those in the engagement condition, on the other hand, showed selective improvement in divergent thinking, a key ability exercised in creative problem solving. On average, then, both groups appeared to show ability-specific effects. However, moderators of change differed somewhat for those in the engagement and training interventions. Generally, those who started either intervention with a more positive cognitive profile showed more cognitive growth, suggesting that cognitive resources enabled individuals to take advantage of environmental enrichment. Only in the engagement condition did initial levels of openness and social network size moderate intervention effects on cognition, suggesting that comfort with novelty and an ability to manage social resources may be additional factors contributing to the capacity to take advantage of the environmental complexity associated with engagement. Collectively, these findings suggest that training and engagement models may offer alternative routes to cognitive resilience in late life. PMID:25402337

Exploring students’ adaptive reasoning skills and van Hiele levels of geometric thinking: a case study in geometry

NASA Astrophysics Data System (ADS)

Rizki, H. T. N.; Frentika, D.; Wijaya, A.

2018-03-01

This study aims to explore junior high school students’ adaptive reasoning and the Van Hiele level of geometric thinking. The present study was a quasi-experiment with the non-equivalent control group design. The participants of the study were 34 seventh graders and 35 eighth graders in the experiment classes and 34 seventh graders and 34 eighth graders in the control classes. The students in the experiment classes learned geometry under the circumstances of a Knisley mathematical learning. The data were analyzed quantitatively by using inferential statistics. The results of data analysis show an improvement of adaptive reasoning skills both in the grade seven and grade eight. An improvement was also found for the Van Hiele level of geometric thinking. These results indicate the positive impact of Knisley learning model on students’ adaptive reasoning skills and Van Hiele level of geometric thinking.

Heuristic and analytic processes in reasoning: an event-related potential study of belief bias.

PubMed

Banks, Adrian P; Hope, Christopher

2014-03-01

Human reasoning involves both heuristic and analytic processes. This study of belief bias in relational reasoning investigated whether the two processes occur serially or in parallel. Participants evaluated the validity of problems in which the conclusions were either logically valid or invalid and either believable or unbelievable. Problems in which the conclusions presented a conflict between the logically valid response and the believable response elicited a more positive P3 than problems in which there was no conflict. This shows that P3 is influenced by the interaction of belief and logic rather than either of these factors on its own. These findings indicate that belief and logic influence reasoning at the same time, supporting models in which belief-based and logical evaluations occur in parallel but not theories in which belief-based heuristic evaluations precede logical analysis.

A semantic-web oriented representation of the clinical element model for secondary use of electronic health records data.

PubMed

Tao, Cui; Jiang, Guoqian; Oniki, Thomas A; Freimuth, Robert R; Zhu, Qian; Sharma, Deepak; Pathak, Jyotishman; Huff, Stanley M; Chute, Christopher G

2013-05-01

The clinical element model (CEM) is an information model designed for representing clinical information in electronic health records (EHR) systems across organizations. The current representation of CEMs does not support formal semantic definitions and therefore it is not possible to perform reasoning and consistency checking on derived models. This paper introduces our efforts to represent the CEM specification using the Web Ontology Language (OWL). The CEM-OWL representation connects the CEM content with the Semantic Web environment, which provides authoring, reasoning, and querying tools. This work may also facilitate the harmonization of the CEMs with domain knowledge represented in terminology models as well as other clinical information models such as the openEHR archetype model. We have created the CEM-OWL meta ontology based on the CEM specification. A convertor has been implemented in Java to automatically translate detailed CEMs from XML to OWL. A panel evaluation has been conducted, and the results show that the OWL modeling can faithfully represent the CEM specification and represent patient data.

A semantic-web oriented representation of the clinical element model for secondary use of electronic health records data

PubMed Central

Tao, Cui; Jiang, Guoqian; Oniki, Thomas A; Freimuth, Robert R; Zhu, Qian; Sharma, Deepak; Pathak, Jyotishman; Huff, Stanley M; Chute, Christopher G

2013-01-01

The clinical element model (CEM) is an information model designed for representing clinical information in electronic health records (EHR) systems across organizations. The current representation of CEMs does not support formal semantic definitions and therefore it is not possible to perform reasoning and consistency checking on derived models. This paper introduces our efforts to represent the CEM specification using the Web Ontology Language (OWL). The CEM-OWL representation connects the CEM content with the Semantic Web environment, which provides authoring, reasoning, and querying tools. This work may also facilitate the harmonization of the CEMs with domain knowledge represented in terminology models as well as other clinical information models such as the openEHR archetype model. We have created the CEM-OWL meta ontology based on the CEM specification. A convertor has been implemented in Java to automatically translate detailed CEMs from XML to OWL. A panel evaluation has been conducted, and the results show that the OWL modeling can faithfully represent the CEM specification and represent patient data. PMID:23268487

A decision network account of reasoning about other people's choices

PubMed Central

Jern, Alan; Kemp, Charles

2015-01-01

The ability to predict and reason about other people's choices is fundamental to social interaction. We propose that people reason about other people's choices using mental models that are similar to decision networks. Decision networks are extensions of Bayesian networks that incorporate the idea that choices are made in order to achieve goals. In our first experiment, we explore how people predict the choices of others. Our remaining three experiments explore how people infer the goals and knowledge of others by observing the choices that they make. We show that decision networks account for our data better than alternative computational accounts that do not incorporate the notion of goal-directed choice or that do not rely on probabilistic inference. PMID:26010559

The emotional dog and its rational tail: a social intuitionist approach to moral judgment.

PubMed

Haidt, J

2001-10-01

Research on moral judgment has been dominated by rationalist models, in which moral judgment is thought to be caused by moral reasoning. The author gives 4 reasons for considering the hypothesis that moral reasoning does not cause moral judgment; rather, moral reasoning is usually a post hoc construction, generated after a judgment has been reached. The social intuitionist model is presented as an alternative to rationalist models. The model is a social model in that it deemphasizes the private reasoning done by individuals and emphasizes instead the importance of social and cultural influences. The model is an intuitionist model in that it states that moral judgment is generally the result of quick, automatic evaluations (intuitions). The model is more consistent that rationalist models with recent findings in social, cultural, evolutionary, and biological psychology, as well as in anthropology and primatology.

Dual Processes in Decision Making and Developmental Neuroscience: A Fuzzy-Trace Model.

PubMed

Reyna, Valerie F; Brainerd, Charles J

2011-09-01

From Piaget to the present, traditional and dual-process theories have predicted improvement in reasoning from childhood to adulthood, and improvement has been observed. However, developmental reversals-that reasoning biases emerge with development -have also been observed in a growing list of paradigms. We explain how fuzzy-trace theory predicts both improvement and developmental reversals in reasoning and decision making. Drawing on research on logical and quantitative reasoning, as well as on risky decision making in the laboratory and in life, we illustrate how the same small set of theoretical principles apply to typical neurodevelopment, encompassing childhood, adolescence, and adulthood, and to neurological conditions such as autism and Alzheimer's disease. For example, framing effects-that risk preferences shift when the same decisions are phrases in terms of gains versus losses-emerge in early adolescence as gist-based intuition develops. In autistic individuals, who rely less on gist-based intuition and more on verbatim-based analysis, framing biases are attenuated (i.e., they outperform typically developing control subjects). In adults, simple manipulations based on fuzzy-trace theory can make framing effects appear and disappear depending on whether gist-based intuition or verbatim-based analysis is induced. These theoretical principles are summarized and integrated in a new mathematical model that specifies how dual modes of reasoning combine to produce predictable variability in performance. In particular, we show how the most popular and extensively studied model of decision making-prospect theory-can be derived from fuzzy-trace theory by combining analytical (verbatim-based) and intuitive (gist-based) processes.

Dual Processes in Decision Making and Developmental Neuroscience: A Fuzzy-Trace Model

PubMed Central

Reyna, Valerie F.; Brainerd, Charles J.

2011-01-01

From Piaget to the present, traditional and dual-process theories have predicted improvement in reasoning from childhood to adulthood, and improvement has been observed. However, developmental reversals—that reasoning biases emerge with development —have also been observed in a growing list of paradigms. We explain how fuzzy-trace theory predicts both improvement and developmental reversals in reasoning and decision making. Drawing on research on logical and quantitative reasoning, as well as on risky decision making in the laboratory and in life, we illustrate how the same small set of theoretical principles apply to typical neurodevelopment, encompassing childhood, adolescence, and adulthood, and to neurological conditions such as autism and Alzheimer's disease. For example, framing effects—that risk preferences shift when the same decisions are phrases in terms of gains versus losses—emerge in early adolescence as gist-based intuition develops. In autistic individuals, who rely less on gist-based intuition and more on verbatim-based analysis, framing biases are attenuated (i.e., they outperform typically developing control subjects). In adults, simple manipulations based on fuzzy-trace theory can make framing effects appear and disappear depending on whether gist-based intuition or verbatim-based analysis is induced. These theoretical principles are summarized and integrated in a new mathematical model that specifies how dual modes of reasoning combine to produce predictable variability in performance. In particular, we show how the most popular and extensively studied model of decision making—prospect theory—can be derived from fuzzy-trace theory by combining analytical (verbatim-based) and intuitive (gist-based) processes. PMID:22096268

Using the SEE-SEP Model to Analyze Upper Secondary Students' Use of Supporting Reasons in Arguing Socioscientific Issues

NASA Astrophysics Data System (ADS)

Christenson, Nina; Chang Rundgren, Shu-Nu; Höglund, Hans-Olof

2012-06-01

To achieve the goal of scientific literacy, the skills of argumentation have been emphasized in science education during the past decades. But the extent to which students can apply scientific knowledge to their argumentation is still unclear. The purpose of this study was to analyse 80 Swedish upper secondary students' informal argumentation on four socioscientific issues (SSIs) to explore students' use of supporting reasons and to what extent students used scientific knowledge in their arguments. Eighty upper secondary students were asked to express their opinions on one SSI topic they chose through written reports. The four SSIs in this study include global warming, genetically modified organisms (GMO), nuclear power, and consumption. To analyse students' supporting reasons from a holistic view, we used the SEE-SEP model, which links the six subject areas of sociology/culture (So), environment (En), economy (Ec), science (Sc), ethics/morality (Et) and policy (Po) connecting with three aspects, knowledge, value and personal experience (KVP). The results showed that students used value to a greater extent (67%) than they did scientific knowledge (27%) for all four SSI topics. According to the SEE-SEP model, the distribution of supporting reasons generated by students differed among the SSI topics. Also, some alternative concepts were disclosed in students' arguments. The implications for research and education are discussed.

Extending pure luminosity evolution models into the mid-infrared, far-infrared and submillimetre

NASA Astrophysics Data System (ADS)

Hill, Michael D.; Shanks, Tom

2011-07-01

Simple pure luminosity evolution (PLE) models, in which galaxies brighten at high redshift due to increased star formation rates (SFRs), are known to provide a good fit to the colours and number counts of galaxies throughout the optical and near-infrared. We show that optically defined PLE models, where dust reradiates absorbed optical light into infrared spectra composed of local galaxy templates, fit galaxy counts and colours out to 8 μm and to at least z≈ 2.5. At 24-70 μm, the model is able to reproduce the observed source counts with reasonable success if 16 per cent of spiral galaxies show an excess in mid-IR flux due to a warmer dust component and a higher SFR, in line with observations of local starburst galaxies. There remains an underprediction of the number of faint-flux, high-z sources at 24 μm, so we explore how the evolution may be altered to correct this. At 160 μm and longer wavelengths, the model fails, with our model of normal galaxies accounting for only a few percent of sources in these bands. However, we show that a PLE model of obscured AGN, which we have previously shown to give a good fit to observations at 850 μm, also provides a reasonable fit to the Herschel/BLAST number counts and redshift distributions at 250-500 μm. In the context of a ΛCDM cosmology, an AGN contribution at 250-870 μm would remove the need to invoke a top-heavy IMF for high-redshift starburst galaxies.

Promoting the Multidimensional Character of Scientific Reasoning.

PubMed

Bradshaw, William S; Nelson, Jennifer; Adams, Byron J; Bell, John D

2017-04-01

This study reports part of a long-term program to help students improve scientific reasoning using higher-order cognitive tasks set in the discipline of cell biology. This skill was assessed using problems requiring the construction of valid conclusions drawn from authentic research data. We report here efforts to confirm the hypothesis that data interpretation is a complex, multifaceted exercise. Confirmation was obtained using a statistical treatment showing that various such problems rank students differently-each contains a unique set of cognitive challenges. Additional analyses of performance results have allowed us to demonstrate that individuals differ in their capacity to navigate five independent generic elements that constitute successful data interpretation: biological context, connection to course concepts, experimental protocols, data inference, and integration of isolated experimental observations into a coherent model. We offer these aspects of scientific thinking as a "data analysis skills inventory," along with usable sample problems that illustrate each element. Additionally, we show that this kind of reasoning is rigorous in that it is difficult for most novice students, who are unable to intuitively implement strategies for improving these skills. Instructors armed with knowledge of the specific challenges presented by different types of problems can provide specific helpful feedback during formative practice. The use of this instructional model is most likely to require changes in traditional classroom instruction.

Overcoming limitations of model-based diagnostic reasoning systems

NASA Technical Reports Server (NTRS)

Holtzblatt, Lester J.; Marcotte, Richard A.; Piazza, Richard L.

1989-01-01

The development of a model-based diagnostic system to overcome the limitations of model-based reasoning systems is discussed. It is noted that model-based reasoning techniques can be used to analyze the failure behavior and diagnosability of system and circuit designs as part of the system process itself. One goal of current research is the development of a diagnostic algorithm which can reason efficiently about large numbers of diagnostic suspects and can handle both combinational and sequential circuits. A second goal is to address the model-creation problem by developing an approach for using design models to construct the GMODS model in an automated fashion.

Helping Students Develop Statistical Reasoning: Implementing a Statistical Reasoning Learning Environment

ERIC Educational Resources Information Center

Garfield, Joan; Ben-Zvi, Dani

2009-01-01

This article describes a model for an interactive, introductory secondary- or tertiary-level statistics course that is designed to develop students' statistical reasoning. This model is called a "Statistical Reasoning Learning Environment" and is built on the constructivist theory of learning.

Promoting the self-regulation of clinical reasoning skills in nursing students.

PubMed

Kuiper, R; Pesut, D; Kautz, D

2009-10-02

The purpose of this paper is to describe the research surrounding the theories and models the authors united to describe the essential components of clinical reasoning in nursing practice education. The research was conducted with nursing students in health care settings through the application of teaching and learning strategies with the Self-Regulated Learning Model (SRL) and the Outcome-Present-State-Test (OPT) Model of Reflective Clinical Reasoning. Standardized nursing languages provided the content and clinical vocabulary for the clinical reasoning task. This descriptive study described the application of the OPT model of clinical reasoning, use of nursing language content, and reflective journals based on the SRL model with 66 undergraduate nursing students over an 8 month period of time. The study tested the idea that self-regulation of clinical reasoning skills can be developed using self-regulation theory and the OPT model. This research supports a framework for effective teaching and learning methods to promote and document learner progress in mastering clinical reasoning skills. Self-regulated Learning strategies coupled with the OPT model suggest benefits of self-observation and self-monitoring during clinical reasoning activities, and pinpoints where guidance is needed for the development of cognitive and metacognitive awareness. Thinking and reasoning about the complexities of patient care needs requires attention to the content, processes and outcomes that make a nursing care difference. These principles and concepts are valuable to clinical decision making for nurses globally as they deal with local, regional, national and international health care issues.

Logical Reasoning versus Information Processing in the Dual-Strategy Model of Reasoning

ERIC Educational Resources Information Center

Markovits, Henry; Brisson, Janie; de Chantal, Pier-Luc

2017-01-01

One of the major debates concerning the nature of inferential reasoning is between counterexample-based strategies such as mental model theory and statistical strategies underlying probabilistic models. The dual-strategy model, proposed by Verschueren, Schaeken, & d'Ydewalle (2005a, 2005b), which suggests that people might have access to both…

Preventable Medical Errors Driven Modeling of Medical Best Practice Guidance Systems.

PubMed

Ou, Andrew Y-Z; Jiang, Yu; Wu, Po-Liang; Sha, Lui; Berlin, Richard B

2017-01-01

In a medical environment such as Intensive Care Unit, there are many possible reasons to cause errors, and one important reason is the effect of human intellectual tasks. When designing an interactive healthcare system such as medical Cyber-Physical-Human Systems (CPHSystems), it is important to consider whether the system design can mitigate the errors caused by these tasks or not. In this paper, we first introduce five categories of generic intellectual tasks of humans, where tasks among each category may lead to potential medical errors. Then, we present an integrated modeling framework to model a medical CPHSystem and use UPPAAL as the foundation to integrate and verify the whole medical CPHSystem design models. With a verified and comprehensive model capturing the human intellectual tasks effects, we can design a more accurate and acceptable system. We use a cardiac arrest resuscitation guidance and navigation system (CAR-GNSystem) for such medical CPHSystem modeling. Experimental results show that the CPHSystem models help determine system design flaws and can mitigate the potential medical errors caused by the human intellectual tasks.

Don't Think, Just Feel the Music: Individuals with Strong Pavlovian-to-Instrumental Transfer Effects Rely Less on Model-based Reinforcement Learning.

PubMed

Sebold, Miriam; Schad, Daniel J; Nebe, Stephan; Garbusow, Maria; Jünger, Elisabeth; Kroemer, Nils B; Kathmann, Norbert; Zimmermann, Ulrich S; Smolka, Michael N; Rapp, Michael A; Heinz, Andreas; Huys, Quentin J M

2016-07-01

Behavioral choice can be characterized along two axes. One axis distinguishes reflexive, model-free systems that slowly accumulate values through experience and a model-based system that uses knowledge to reason prospectively. The second axis distinguishes Pavlovian valuation of stimuli from instrumental valuation of actions or stimulus-action pairs. This results in four values and many possible interactions between them, with important consequences for accounts of individual variation. We here explored whether individual variation along one axis was related to individual variation along the other. Specifically, we asked whether individuals' balance between model-based and model-free learning was related to their tendency to show Pavlovian interferences with instrumental decisions. In two independent samples with a total of 243 participants, Pavlovian-instrumental transfer effects were negatively correlated with the strength of model-based reasoning in a two-step task. This suggests a potential common underlying substrate predisposing individuals to both have strong Pavlovian interference and be less model-based and provides a framework within which to interpret the observation of both effects in addiction.

Autonomy, Trust, and Respect

PubMed Central

Nys, Thomas

2016-01-01

This article seeks to explore and analyze the relationship between autonomy and trust, and to show how these findings could be relevant to medical ethics. First, I will argue that the way in which so-called “relational autonomy theories” tie the notions of autonomy and trust together is not entirely satisfying Then, I will introduce the so-called Encapsulated Interest Account as developed by Russell Hardin. This will bring out the importance of the reasons for trust. What good reasons do we have for trusting someone? I will criticize Hardin’s business model as insufficiently robust, especially in the context of health care, and then turn to another source of trust, namely, love. It may seem that trust-through-love is much better suited for the vulnerability that is often involved in health care, but I will also show that it has its own deficiencies. Good health care should therefore pay attention to both models of trust, and I will offer some tentative remarks on how to do this. PMID:26668168

Common sense reasoning about petroleum flow

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

Rosenberg, S.

1981-02-01

This paper describes an expert system for understanding and Reasoning in a petroleum resources domain. A basic model is implemented in FRL (Frame Representation Language). Expertise is encoded as rule frames. The model consists of a set of episodic contexts which are sequentially generated over time. Reasoning occurs in separate reasoning contexts consisting of a buffer frame and packets of rules. These function similar to small production systems. reasoning is linked to the model through an interface of Sentinels (instance driven demons) which notice anomalous conditions. Heuristics and metaknowledge are used through the creation of further reasoning contexts which overlaymore » the simpler ones.« less

Investigating College and Graduate Students' Multivariable Reasoning in Computational Modeling

ERIC Educational Resources Information Center

Wu, Hsin-Kai; Wu, Pai-Hsing; Zhang, Wen-Xin; Hsu, Ying-Shao

2013-01-01

Drawing upon the literature in computational modeling, multivariable reasoning, and causal attribution, this study aims at characterizing multivariable reasoning practices in computational modeling and revealing the nature of understanding about multivariable causality. We recruited two freshmen, two sophomores, two juniors, two seniors, four…

Forecasting of Water Consumptions Expenditure Using Holt-Winter’s and ARIMA

NASA Astrophysics Data System (ADS)

Razali, S. N. A. M.; Rusiman, M. S.; Zawawi, N. I.; Arbin, N.

2018-04-01

This study is carried out to forecast water consumption expenditure of Malaysian university specifically at University Tun Hussein Onn Malaysia (UTHM). The proposed Holt-Winter’s and Auto-Regressive Integrated Moving Average (ARIMA) models were applied to forecast the water consumption expenditure in Ringgit Malaysia from year 2006 until year 2014. The two models were compared and performance measurement of the Mean Absolute Percentage Error (MAPE) and Mean Absolute Deviation (MAD) were used. It is found that ARIMA model showed better results regarding the accuracy of forecast with lower values of MAPE and MAD. Analysis showed that ARIMA (2,1,4) model provided a reasonable forecasting tool for university campus water usage.

Risk Factors Analysis and Death Prediction in Some Life-Threatening Ailments Using Chi-Square Case-Based Reasoning (χ2 CBR) Model.

PubMed

Adeniyi, D A; Wei, Z; Yang, Y

2018-01-30

A wealth of data are available within the health care system, however, effective analysis tools for exploring the hidden patterns in these datasets are lacking. To alleviate this limitation, this paper proposes a simple but promising hybrid predictive model by suitably combining the Chi-square distance measurement with case-based reasoning technique. The study presents the realization of an automated risk calculator and death prediction in some life-threatening ailments using Chi-square case-based reasoning (χ 2 CBR) model. The proposed predictive engine is capable of reducing runtime and speeds up execution process through the use of critical χ 2 distribution value. This work also showcases the development of a novel feature selection method referred to as frequent item based rule (FIBR) method. This FIBR method is used for selecting the best feature for the proposed χ 2 CBR model at the preprocessing stage of the predictive procedures. The implementation of the proposed risk calculator is achieved through the use of an in-house developed PHP program experimented with XAMP/Apache HTTP server as hosting server. The process of data acquisition and case-based development is implemented using the MySQL application. Performance comparison between our system, the NBY, the ED-KNN, the ANN, the SVM, the Random Forest and the traditional CBR techniques shows that the quality of predictions produced by our system outperformed the baseline methods studied. The result of our experiment shows that the precision rate and predictive quality of our system in most cases are equal to or greater than 70%. Our result also shows that the proposed system executes faster than the baseline methods studied. Therefore, the proposed risk calculator is capable of providing useful, consistent, faster, accurate and efficient risk level prediction to both the patients and the physicians at any time, online and on a real-time basis.

Student Development of Model-Based Reasoning about Carbon Cycling and Climate Change in a Socio-Scientific Issues Unit

ERIC Educational Resources Information Center

Zangori, Laura; Peel, Amanda; Kinslow, Andrew; Friedrichsen, Patricia; Sadler, Troy D.

2017-01-01

Carbon cycling is a key natural system that requires robust science literacy to understand how and why climate change is occurring. Studies show that students tend to compartmentalize carbon movement within plants and animals and are challenged to make sense of how carbon cycles on a global scale. Studies also show that students hold faulty models…

Building an environment model using depth information

NASA Technical Reports Server (NTRS)

Roth-Tabak, Y.; Jain, Ramesh

1989-01-01

Modeling the environment is one of the most crucial issues for the development and research of autonomous robot and tele-perception. Though the physical robot operates (navigates and performs various tasks) in the real world, any type of reasoning, such as situation assessment, planning or reasoning about action, is performed based on information in its internal world. Hence, the robot's intentional actions are inherently constrained by the models it has. These models may serve as interfaces between sensing modules and reasoning modules, or in the case of telerobots serve as interface between the human operator and the distant robot. A robot operating in a known restricted environment may have a priori knowledge of its whole possible work domain, which will be assimilated in its World Model. As the information in the World Model is relatively fixed, an Environment Model must be introduced to cope with the changes in the environment and to allow exploring entirely new domains. Introduced here is an algorithm that uses dense range data collected at various positions in the environment to refine and update or generate a 3-D volumetric model of an environment. The model, which is intended for autonomous robot navigation and tele-perception, consists of cubic voxels with the possible attributes: Void, Full, and Unknown. Experimental results from simulations of range data in synthetic environments are given. The quality of the results show great promise for dealing with noisy input data. The performance measures for the algorithm are defined, and quantitative results for noisy data and positional uncertainty are presented.

Two-Dimensional Simulation of Left-Handed Metamaterial Flat Lens Using Remcon XFDTD

NASA Technical Reports Server (NTRS)

Wilson, Jeffrey D.; Reinert, Jason M.

2006-01-01

Remcom's XFDTD software was used to model the properties of a two-dimensional left-handed metamaterial (LHM) flat lens. The focusing capability and attenuation of the material were examined. The results showed strong agreement with experimental results and theoretical predictions of focusing effects and focal length. The inherent attenuation in the model corresponds well with the experimental results and implies that the code does a reasonably accurate job of modeling the actual metamaterial.

Wave attenuation in the marginal ice zone during LIMEX

NASA Technical Reports Server (NTRS)

Liu, Antony K.; Peng, Chih Y.; Vachon, Paris W.

1991-01-01

During LIMEX'87 and '89, the CCRS CV-580 aircraft collected SAR (synthetic aperture radar) data over the marginal ice zone off the coast of Newfoundland. Based upon the wavenumber spectra from SAR data, the wave attenuation rate is estimated and compared with a model. The model-data comparisons are reasonably good for the ice conditions during LIMEX (Labrador Ice Margin Experiment). Both model and SAR-derived wave attenuation rates show a roll-over at high wavenumbers.

The Emergence of Metaethical Reasoning.

ERIC Educational Resources Information Center

Langford, Peter E.

A multidimensional model of the growth of moral reasoning is described that is significantly different from those proposed by Kohlberg and Piaget. A study that tests several aspects of the model on university students is reported. The suggestion that well-developed chains of reasons are a prerequisite for the emergence of metaethical reasoning was…

Cognitive Trait Modelling: The Case of Inductive Reasoning Ability

ERIC Educational Resources Information Center

Kinshuk, Taiyu Lin; McNab, Paul

2006-01-01

Researchers have regarded inductive reasoning as one of the seven primary mental abilities that account for human intelligent behaviours. Researchers have also shown that inductive reasoning ability is one of the best predictors for academic performance. Modelling of inductive reasoning is therefore an important issue for providing adaptivity in…

An electricity consumption model for electric vehicular flow

NASA Astrophysics Data System (ADS)

Xiao, Hong; Huang, Hai-Jun; Tang, Tie-Qiao

2016-09-01

In this paper, we apply the relationships between the macro and micro variables of traffic flow to develop an electricity consumption model for electric vehicular flow. We use the proposed model to study the quantitative relationships between the electricity consumption/total power and speed/density under uniform flow, and the electricity consumptions during the evolution processes of shock, rarefaction wave and small perturbation. The numerical results indicate that the proposed model can perfectly describe the electricity consumption for electric vehicular flow, which shows that the proposed model is reasonable.

The contrasting response of Hadley circulation to different meridional structure of sea surface temperature in CMIP5

NASA Astrophysics Data System (ADS)

Feng, Juan; Li, Jianping; Zhu, Jianlei; Li, Yang; Li, Fei

2018-02-01

The response of the Hadley circulation (HC) to the sea surface temperature (SST) is determined by the meridional structure of SST and varies according to the changing nature of this meridional structure. The capability of the models from the phase 5 of the Coupled Model Intercomparison Project (CMIP5) is utilized to represent the contrast response of the HC to different meridional SST structures. To evaluate the responses, the variations of HC and SST were linearly decomposed into two components: the equatorially asymmetric (HEA for HC, and SEA for SST) and equatorially symmetric (HES for HC, and SES for SST) components. The result shows that the climatological features of HC and tropical SST (including the spatial structures and amplitude) are reasonably simulated in all the models. However, the response contrast of HC to different SST meridional structures shows uncertainties among models. This may be due to the fact that the long-term temporal variabilities of HEA, HES, and SEA are limited reproduced in the models, although the spatial structures of their long-term variabilities are relatively reasonably simulated. These results indicate that the performance of the CMIP5 models to simulate long-term temporal variability of different meridional SST structures and related HC variations plays a fundamental role in the successful reproduction of the response of HC to different meridional SST structures.

Comparing Simultaneous Stratospheric Aerosol and Ozone Lidar Measurements with SAGE 2 Data after the Mount Pinatubo Eruption

NASA Technical Reports Server (NTRS)

Yue, G. K.; Poole, L. R.; McCormick, M. P.; Veiga, R. E.; Wang, P.-H.; Rizi, V.; Masci, F.; DAltorio, A.; Visconti, G.

1995-01-01

Stratospheric aerosol and ozone profiles obtained simultaneously from the lidar station at the University of L'Aquila (42.35 deg N, 13.33 deg E, 683 m above sea level) during the first 6 months following the eruption of Mount Pinatubo are compared with corresponding nearby Stratospheric Aerosol and Gas Experiment (SAGE) 2 profiles. The agreement between the two data sets is found to be reasonably good. The temporal change of aerosol profiles obtained by both techniques showed the intrusion and growth of Pinatubo aerosols. In addition, ozone concentration profiles derived from an empirical time-series model based on SAGE 2 ozone data obtained before the Pinatubo eruption are compared with measured profiles. Good agreement is shown in the 1991 profiles, but ozone concentrations measured in January 1992 were reduced relative to time-series model estimates. Possible reasons for the differences between measured and model-based ozone profiles are discussed.

Case Study: Applying OpenEHR Archetypes to a Clinical Data Repository in a Chinese Hospital.

PubMed

Min, Lingtong; Wang, Li; Lu, Xudong; Duan, Huilong

2015-01-01

openEHR is a flexible and scalable modeling methodology for clinical information and has been widely adopted in Europe and Australia. Due to the reasons of differences in clinical process and management, there are few research projects involving openEHR in China. To investigate the feasibility of openEHR methodology for clinical information modelling in China, this paper carries out a case study to apply openEHR archetypes to Clinical Data Repository (CDR) in a Chinese hospital. The results show that a set of 26 archetypes are found to cover all the concepts used in the CDR. Of all these, 9 (34.6%) are reused without change, 10 are modified and/or extended, and 7 are newly defined. The reasons for modification, extension and newly definition have been discussed, including granularity of archetype, metadata-level versus data-level modelling, and the representation of relationships between archetypes.

The strategic use of noise in pragmatic reasoning.

PubMed

Bergen, Leon; Goodman, Noah D

2015-04-01

We combine two recent probabilistic approaches to natural language understanding, exploring the formal pragmatics of communication on a noisy channel. We first extend a model of rational communication between a speaker and listener, to allow for the possibility that messages are corrupted by noise. In this model, common knowledge of a noisy channel leads to the use and correct understanding of sentence fragments. A further extension of the model, which allows the speaker to intentionally reduce the noise rate on a word, is used to model prosodic emphasis. We show that the model derives several well-known changes in meaning associated with prosodic emphasis. Our results show that nominal amounts of actual noise can be leveraged for communicative purposes. Copyright © 2015 Cognitive Science Society, Inc.

Drug retention and discontinuation reasons between seven biologics in patients with rheumatoid arthritis -The ANSWER cohort study.

PubMed

Ebina, Kosuke; Hashimoto, Motomu; Yamamoto, Wataru; Ohnishi, Akira; Kabata, Daijiro; Hirano, Toru; Hara, Ryota; Katayama, Masaki; Yoshida, Shuzo; Nagai, Koji; Son, Yonsu; Amuro, Hideki; Akashi, Kengo; Fujimura, Takanori; Hirao, Makoto; Yamamoto, Keiichi; Shintani, Ayumi; Kumanogoh, Atsushi; Yoshikawa, Hideki

2018-01-01

The purpose of this study was to evaluate the retention and discontinuation reasons of seven biological disease-modifying antirheumatic drugs (bDMARDs) in a real-world setting of patients with rheumatoid arthritis (RA). 1,037 treatment courses with bDMARDs from 2009 to 2016 [female, 81.8%; baseline age, 59.6 y; disease duration 7.8 y; rheumatoid factor positivity 81.5%; Disease Activity Score in 28 joints using erythrocyte sedimentation rate (DAS28-ESR), 4.4; concomitant prednisolone 43.5% and methotrexate 68.6%; Bio-naïve, 57.1%; abatacept (ABT), 21.3%; tocilizumab (TCZ), 20.7%; golimumab (GLM), 16.9%; etanercept (ETN), 13.6%; adalimumab (ADA), 11.1%; infliximab (IFX), 8.5%; certolizumab pegol (CZP), 7.9%] were included in this multi-center, retrospective study. Drug retention and discontinuation reasons at 36 months were estimated using the Kaplan-Meier method and adjusted by potent confounders using Cox proportional hazards modeling. As a result, 455 treatment courses (43.9%) were stopped, with 217 (20.9%) stopping due to inefficacy, 113 (10.9%) due to non-toxic reasons, 86 (8.3%) due to toxic adverse events, and 39 (3.8%) due to remission. Drug retention rates in the adjusted model were as follows: total retention (ABT, 60.7%; ADA, 32.7%; CZP, 43.3%; ETN, 51.9%; GLM, 45.4%; IFX, 31.1%; and TCZ, 59.2%; P < 0.001); inefficacy (ABT, 81.4%; ADA, 65.7%; CZP, 60.7%; ETN, 71.3%; GLM, 68.5%; IFX, 65.0%; and TCZ, 81.4%; P = 0.015), toxic adverse events (ABT, 89.8%; ADA, 80.5%; CZP, 83.9%; ETN, 89.2%; GLM, 85.5%; IFX, 75.6%; and TCZ, 77.2%; P = 0.50), and remission (ABT, 95.5%; ADA, 88.1%; CZP, 91.1%; ETN, 97.5%; GLM, 94.7%; IFX, 86.4%; and TCZ, 98.4%; P < 0.001). In the treatment of RA, ABT and TCZ showed higher overall retention, and TCZ showed lower inefficacy compared to IFX, while IFX showed higher discontinuation due to remission compared to ABT, ETN, GLM, and TCZ in adjusted modeling.

Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI)

PubMed Central

Deane, Thomas; Nomme, Kathy; Jeffery, Erica; Pollock, Carol; Birol, Gülnur

2016-01-01

We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non–expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI’s robustness and sensitivity in capturing useful data relating to the students’ conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. PMID:26903497

Promoting the Self-Regulation of Clinical Reasoning Skills in Nursing Students

PubMed Central

Kuiper, R; Pesut, D; Kautz, D

2009-01-01

Aim: The purpose of this paper is to describe the research surrounding the theories and models the authors united to describe the essential components of clinical reasoning in nursing practice education. The research was conducted with nursing students in health care settings through the application of teaching and learning strategies with the Self-Regulated Learning Model (SRL) and the Outcome-Present-State-Test (OPT) Model of Reflective Clinical Reasoning. Standardized nursing languages provided the content and clinical vocabulary for the clinical reasoning task. Materials and Methods: This descriptive study described the application of the OPT model of clinical reasoning, use of nursing language content, and reflective journals based on the SRL model with 66 undergraduate nursing students over an 8 month period of time. The study tested the idea that self-regulation of clinical reasoning skills can be developed using self-regulation theory and the OPT model. Results: This research supports a framework for effective teaching and learning methods to promote and document learner progress in mastering clinical reasoning skills. Self-regulated Learning strategies coupled with the OPT model suggest benefits of self-observation and self-monitoring during clinical reasoning activities, and pinpoints where guidance is needed for the development of cognitive and metacognitive awareness. Recommendations and Conclusions: Thinking and reasoning about the complexities of patient care needs requires attention to the content, processes and outcomes that make a nursing care difference. These principles and concepts are valuable to clinical decision making for nurses globally as they deal with local, regional, national and international health care issues. PMID:19888432

Attitudes and exercise adherence: test of the Theories of Reasoned Action and Planned Behaviour.

PubMed

Smith, R A; Biddle, S J

1999-04-01

Three studies of exercise adherence and attitudes are reported that tested the Theory of Reasoned Action and the Theory of Planned Behaviour. In a prospective study of adherence to a private fitness club, structural equation modelling path analysis showed that attitudinal and social normative components of the Theory of Reasoned Action accounted for 13.1% of the variance in adherence 4 months later, although only social norm significantly predicted intention. In a second study, the Theory of Planned Behaviour was used to predict both physical activity and sedentary behaviour. Path analyses showed that attitude and perceived control, but not social norm, predicted total physical activity. Physical activity was predicted from intentions and control over sedentary behaviour. Finally, an intervention study with previously sedentary adults showed that intentions to be active measured at the start and end of a 10-week intervention were associated with the planned behaviour variables. A multivariate analysis of variance revealed no significant multivariate effects for time on the planned behaviour variables measured before and after intervention. Qualitative data provided evidence that participants had a positive experience on the intervention programme and supported the role of social normative factors in the adherence process.

Model-Based Reasoning

ERIC Educational Resources Information Center

Ifenthaler, Dirk; Seel, Norbert M.

2013-01-01

In this paper, there will be a particular focus on mental models and their application to inductive reasoning within the realm of instruction. A basic assumption of this study is the observation that the construction of mental models and related reasoning is a slowly developing capability of cognitive systems that emerges effectively with proper…

A decision network account of reasoning about other people's choices.

PubMed

Jern, Alan; Kemp, Charles

2015-09-01

The ability to predict and reason about other people's choices is fundamental to social interaction. We propose that people reason about other people's choices using mental models that are similar to decision networks. Decision networks are extensions of Bayesian networks that incorporate the idea that choices are made in order to achieve goals. In our first experiment, we explore how people predict the choices of others. Our remaining three experiments explore how people infer the goals and knowledge of others by observing the choices that they make. We show that decision networks account for our data better than alternative computational accounts that do not incorporate the notion of goal-directed choice or that do not rely on probabilistic inference. Copyright © 2015 Elsevier B.V. All rights reserved.

CNTRO: A Semantic Web Ontology for Temporal Relation Inferencing in Clinical Narratives.

PubMed

Tao, Cui; Wei, Wei-Qi; Solbrig, Harold R; Savova, Guergana; Chute, Christopher G

2010-11-13

Using Semantic-Web specifications to represent temporal information in clinical narratives is an important step for temporal reasoning and answering time-oriented queries. Existing temporal models are either not compatible with the powerful reasoning tools developed for the Semantic Web, or designed only for structured clinical data and therefore are not ready to be applied on natural-language-based clinical narrative reports directly. We have developed a Semantic-Web ontology which is called Clinical Narrative Temporal Relation ontology. Using this ontology, temporal information in clinical narratives can be represented as RDF (Resource Description Framework) triples. More temporal information and relations can then be inferred by Semantic-Web based reasoning tools. Experimental results show that this ontology can represent temporal information in real clinical narratives successfully.

Computational Fluid Dynamic Modeling of Rocket Based Combined Cycle Engine Flowfields

NASA Technical Reports Server (NTRS)

Daines, Russell L.; Merkle, Charles L.

1994-01-01

Computational Fluid Dynamic techniques are used to study the flowfield of a fixed geometry Rocket Based Combined Cycle engine operating in rocket ejector mode. Heat addition resulting from the combustion of injected fuel causes the subsonic engine flow to choke and go supersonic in the slightly divergent combustor-mixer section. Reacting flow computations are undertaken to predict the characteristics of solutions where the heat addition is determined by the flowfield. Here, adaptive gridding is used to improve resolution in the shear layers. Results show that the sonic speed is reached in the unheated portions of the flow first, while the heated portions become supersonic later. Comparison with results from another code show reasonable agreement. The coupled solutions show that the character of the combustion-based thermal choking phenomenon can be controlled reasonably well such that there is opportunity to optimize the length and expansion ratio of the combustor-mixer.

Evaluation of a novel scoring and grading model for VP-based exams in postgraduate nurse education.

PubMed

Forsberg, Elenita; Ziegert, Kristina; Hult, Håkan; Fors, Uno

2015-12-01

For Virtual Patient-based exams, several scoring and grading methods have been proposed, but none have yet been validated. The aim of this study was to evaluate a new scoring and grading model for VP-based exams in postgraduate paediatric nurse education. The same student group of 19 students performed a VP-based exam in three consecutive courses. When using the scoring and grading assessment model, which contains a deduction system for unnecessary or unwanted actions, a progression was found in the three courses: 53% of the students passed the first exam, 63% the second and 84% passed the final exam. The most common reason for deduction of points was due to students asking too many interview questions or ordering too many laboratory tests. The results showed that the new scoring model made it possible to judge the students' clinical reasoning process as well as their progress. Copyright © 2015 Elsevier Ltd. All rights reserved.

Model fitting data from syllogistic reasoning experiments.

PubMed

Hattori, Masasi

2016-12-01

The data presented in this article are related to the research article entitled "Probabilistic representation in syllogistic reasoning: A theory to integrate mental models and heuristics" (M. Hattori, 2016) [1]. This article presents predicted data by three signature probabilistic models of syllogistic reasoning and model fitting results for each of a total of 12 experiments ( N =404) in the literature. Models are implemented in R, and their source code is also provided.

A flow resistance model for assessing the impact of vegetation on flood routing mechanics

NASA Astrophysics Data System (ADS)

Katul, Gabriel G.; Poggi, Davide; Ridolfi, Luca

2011-08-01

The specification of a flow resistance factor to account for vegetative effects in the Saint-Venant equation (SVE) remains uncertain and is a subject of active research in flood routing mechanics. Here, an analytical model for the flow resistance factor is proposed for submerged vegetation, where the water depth is commensurate with the canopy height and the roughness Reynolds number is sufficiently large so as to ignore viscous effects. The analytical model predicts that the resistance factor varies with three canonical length scales: the adjustment length scale that depends on the foliage drag and leaf area density, the canopy height, and the water level. These length scales can reasonably be inferred from a range of remote sensing products making the proposed flow resistance model eminently suitable for operational flood routing. Despite the numerous simplifications, agreement between measured and modeled resistance factors and bulk velocities is reasonable across a range of experimental and field studies. The proposed model asymptotically recovers the flow resistance formulation when the water depth greatly exceeds the canopy height. This analytical treatment provides a unifying framework that links the resistance factor to a number of concepts and length scales already in use to describe canopy turbulence. The implications of the coupling between the resistance factor and the water depth on solutions to the SVE are explored via a case study, which shows a reasonable match between empirical design standard and theoretical predictions.

An improved car-following model from the perspective of driver’s forecast behavior

NASA Astrophysics Data System (ADS)

Liu, Da-Wei; Shi, Zhong-Ke; Ai, Wen-Huan

In this paper, a new car-following model considering effect of the driver’s forecast behavior is proposed based on the full velocity difference model (FVDM). Using the new model, we investigate the starting process of the vehicle motion under a traffic signal and find that the delay time of vehicle motion is reduced. Then the stability condition of the new model is derived and the modified Korteweg-de Vries (mKdV) equation is constructed to describe the traffic behavior near the critical point. Numerical simulation is compatible with the analysis of theory such as density wave, hysteresis loop, which shows that the new model is reasonable. The results show that considering the effect of driver’s forecast behavior can help to enhance the stability of traffic flow.

3D model retrieval method based on mesh segmentation

NASA Astrophysics Data System (ADS)

Gan, Yuanchao; Tang, Yan; Zhang, Qingchen

2012-04-01

In the process of feature description and extraction, current 3D model retrieval algorithms focus on the global features of 3D models but ignore the combination of global and local features of the model. For this reason, they show less effective performance to the models with similar global shape and different local shape. This paper proposes a novel algorithm for 3D model retrieval based on mesh segmentation. The key idea is to exact the structure feature and the local shape feature of 3D models, and then to compares the similarities of the two characteristics and the total similarity between the models. A system that realizes this approach was built and tested on a database of 200 objects and achieves expected results. The results show that the proposed algorithm improves the precision and the recall rate effectively.

A Comparison of Reasoning Processes in a Collaborative Modelling Environment: Learning about genetics problems using virtual chat

NASA Astrophysics Data System (ADS)

Pata, Kai; Sarapuu, Tago

2006-09-01

This study investigated the possible activation of different types of model-based reasoning processes in two learning settings, and the influence of various terms of reasoning on the learners’ problem representation development. Changes in 53 students’ problem representations about genetic issue were analysed while they worked with different modelling tools in a synchronous network-based environment. The discussion log-files were used for the “microgenetic” analysis of reasoning types. For studying the stages of students’ problem representation development, individual pre-essays and post-essays and their utterances during two reasoning phases were used. An approach for mapping problem representations was developed. Characterizing the elements of mental models and their reasoning level enabled the description of five hierarchical categories of problem representations. Learning in exploratory and experimental settings was registered as the shift towards more complex stages of problem representations in genetics. The effect of different types of reasoning could be observed as the divergent development of problem representations within hierarchical categories.

Proof Rules for Automated Compositional Verification through Learning

NASA Technical Reports Server (NTRS)

Barringer, Howard; Giannakopoulou, Dimitra; Pasareanu, Corina S.

2003-01-01

Compositional proof systems not only enable the stepwise development of concurrent processes but also provide a basis to alleviate the state explosion problem associated with model checking. An assume-guarantee style of specification and reasoning has long been advocated to achieve compositionality. However, this style of reasoning is often non-trivial, typically requiring human input to determine appropriate assumptions. In this paper, we present novel assume- guarantee rules in the setting of finite labelled transition systems with blocking communication. We show how these rules can be applied in an iterative and fully automated fashion within a framework based on learning.

A CLASSICAL ANALOG FOR RELATIVISTIC CONTRACTION

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

Epstein, L.

1963-12-01

It is possible to construct a mechanical model that demonstrates the Fitzgerald contraction. An equation is derived to describe the shape of a dimple moving across an elastic membrane, clearly showing the analogy to the field of a point charge in free space, including the relativistic contraction in the direction of motion. This model should suggest some reason to the inquiring mind that persists in wondering---- what really makes it shrink.'' (auth)

Confirmatory factor analysis of the Child Oral Health Impact Profile (Korean version).

PubMed

Cho, Young Il; Lee, Soonmook; Patton, Lauren L; Kim, Hae-Young

2016-04-01

Empirical support for the factor structure of the Child Oral Health Impact Profile (COHIP) has not been fully established. The purposes of this study were to evaluate the factor structure of the Korean version of the COHIP (COHIP-K) empirically using confirmatory factor analysis (CFA) based on the theoretical framework and then to assess whether any of the factors in the structure could be grouped into a simpler single second-order factor. Data were collected through self-reported COHIP-K responses from a representative community sample of 2,236 Korean children, 8-15 yr of age. Because a large inter-factor correlation of 0.92 was estimated in the original five-factor structure, the two strongly correlated factors were combined into one factor, resulting in a four-factor structure. The revised four-factor model showed a reasonable fit with appropriate inter-factor correlations. Additionally, the second-order model with four sub-factors was reasonable with sufficient fit and showed equal fit to the revised four-factor model. A cross-validation procedure confirmed the appropriateness of the findings. Our analysis empirically supported a four-factor structure of COHIP-K, a summarized second-order model, and the use of an integrated summary COHIP score. © 2016 Eur J Oral Sci.

Variation of student numerical and figural reasoning approaches by pattern generalization type, strategy use and grade level

NASA Astrophysics Data System (ADS)

El Mouhayar, Rabih; Jurdak, Murad

2016-02-01

This paper explored variation of student numerical and figural reasoning approaches across different pattern generalization types and across grade level. An instrument was designed for this purpose. The instrument was given to a sample of 1232 students from grades 4 to 11 from five schools in Lebanon. Analysis of data showed that the numerical reasoning approach seems to be more dominant than the figural reasoning approach for the near and far pattern generalization types but not for the immediate generalization type. The findings showed that for the recursive strategy, the numerical reasoning approach seems to be more dominant than the figural reasoning approach for each of the three pattern generalization types. However, the figural reasoning approach seems to be more dominant than the numerical reasoning approach for the functional strategy, for each generalization type. The findings also showed that the numerical reasoning was more dominant than the figural reasoning in lower grade levels (grades 4 and 5) for each generalization type. In contrast, the figural reasoning became more dominant than the numerical reasoning in the upper grade levels (grades 10 and 11).

An integrated model of clinical reasoning: dual-process theory of cognition and metacognition.

PubMed

Marcum, James A

2012-10-01

Clinical reasoning is an important component for providing quality medical care. The aim of the present paper is to develop a model of clinical reasoning that integrates both the non-analytic and analytic processes of cognition, along with metacognition. The dual-process theory of cognition (system 1 non-analytic and system 2 analytic processes) and the metacognition theory are used to develop an integrated model of clinical reasoning. In the proposed model, clinical reasoning begins with system 1 processes in which the clinician assesses a patient's presenting symptoms, as well as other clinical evidence, to arrive at a differential diagnosis. Additional clinical evidence, if necessary, is acquired and analysed utilizing system 2 processes to assess the differential diagnosis, until a clinical decision is made diagnosing the patient's illness and then how best to proceed therapeutically. Importantly, the outcome of these processes feeds back, in terms of metacognition's monitoring function, either to reinforce or to alter cognitive processes, which, in turn, enhances synergistically the clinician's ability to reason quickly and accurately in future consultations. The proposed integrated model has distinct advantages over other models proposed in the literature for explicating clinical reasoning. Moreover, it has important implications for addressing the paradoxical relationship between experience and expertise, as well as for designing a curriculum to teach clinical reasoning skills. © 2012 Blackwell Publishing Ltd.

Processes Underlying Children's Adjustment in Families Characterized by Physical Aggression.

ERIC Educational Resources Information Center

Onyskiw, Judee; Hayduk, Leslie A.

2001-01-01

The hypothesis that physical aggression in the family affects children's adjustment through both observational learning/modeling and through its impact on parenting was tested, via LISREL, using data from a sample of Canadian children (N=11,221). Results showed observational learning and disrupted parenting provide reasonable explanations of…

What Influences Chinese Undergraduates' Time Management in Online Groupwork? An Empirical Investigation

ERIC Educational Resources Information Center

Xu, Jianzhong; Du, Jianxia; Fan, Xitao

2017-01-01

The present investigation examines models of factors influencing time management in online groupwork for Chinese undergraduates. Multilevel findings showed that time management was positively related to five individual-level variables, including online courses taken previously, learning-oriented reasons, arranging the environment, help-seeking and…

Virtual Patients in Primary Care: Developing a Reusable Model That Fosters Reflective Practice and Clinical Reasoning

PubMed Central

Zary, Nabil; Björklund, Karin; Toth-Pal, Eva; Leanderson, Charlotte

2014-01-01

Background Primary care is an integral part of the medical curriculum at Karolinska Institutet, Sweden. It is present at every stage of the students’ education. Virtual patients (VPs) may support learning processes and be a valuable complement in teaching communication skills, patient-centeredness, clinical reasoning, and reflective thinking. Current literature on virtual patients lacks reports on how to design and use virtual patients with a primary care perspective. Objective The objective of this study was to create a model for a virtual patient in primary care that facilitates medical students’ reflective practice and clinical reasoning. The main research question was how to design a virtual patient model with embedded process skills suitable for primary care education. Methods The VP model was developed using the Open Tufts University Sciences Knowledgebase (OpenTUSK) virtual patient system as a prototyping tool. Both the VP model and the case created using the developed model were validated by a group of 10 experienced primary care physicians and then further improved by a work group of faculty involved in the medical program. The students’ opinions on the VP were investigated through focus group interviews with 14 students and the results analyzed using content analysis. Results The VP primary care model was based on a patient-centered model of consultation modified according to the Calgary-Cambridge Guides, and the learning outcomes of the study program in medicine were taken into account. The VP primary care model is based on Kolb’s learning theories and consists of several learning cycles. Each learning cycle includes a didactic inventory and then provides the student with a concrete experience (video, pictures, and other material) and preformulated feedback. The students’ learning process was visualized by requiring the students to expose their clinical reasoning and reflections in-action in every learning cycle. Content analysis of the focus group interviews showed good acceptance of the model by students. The VP was regarded as an intermediate learning activity and a complement to both the theoretical and the clinical part of the education, filling out gaps in clinical knowledge. The content of the VP case was regarded as authentic and the students appreciated the immediate feedback. The students found the structure of the model interactive and easy to follow. The students also reported that the VP case supported their self-directed learning and reflective ability. Conclusions We have built a new VP model for primary care with embedded communication training and iterated learning cycles that in pilot testing showed good acceptance by students, supporting their self-directed learning and reflective thinking. PMID:24394603

Development and Assessment of CFD Models Including a Supplemental Program Code for Analyzing Buoyancy-Driven Flows Through BWR Fuel Assemblies in SFP Complete LOCA Scenarios

NASA Astrophysics Data System (ADS)

Artnak, Edward Joseph, III

This work seeks to illustrate the potential benefits afforded by implementing aspects of fluid dynamics, especially the latest computational fluid dynamics (CFD) modeling approach, through numerical experimentation and the traditional discipline of physical experimentation to improve the calibration of the severe reactor accident analysis code, MELCOR, in one of several spent fuel pool (SFP) complete loss-ofcoolant accident (LOCA) scenarios. While the scope of experimental work performed by Sandia National Laboratories (SNL) extends well beyond that which is reasonably addressed by our allotted resources and computational time in accordance with initial project allocations to complete the report, these simulated case trials produced a significant array of supplementary high-fidelity solutions and hydraulic flow-field data in support of SNL research objectives. Results contained herein show FLUENT CFD model representations of a 9x9 BWR fuel assembly in conditions corresponding to a complete loss-of-coolant accident scenario. In addition to the CFD model developments, a MATLAB based controlvolume model was constructed to independently assess the 9x9 BWR fuel assembly under similar accident scenarios. The data produced from this work show that FLUENT CFD models are capable of resolving complex flow fields within a BWR fuel assembly in the realm of buoyancy-induced mass flow rates and that characteristic hydraulic parameters from such CFD simulations (or physical experiments) are reasonably employed in corresponding constitutive correlations for developing simplified numerical models of comparable solution accuracy.

Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961-2000

NASA Astrophysics Data System (ADS)

Sanchez-Gomez, Emilia; Somot, S.; Déqué, M.

2009-10-01

One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961-2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation.

SSME seal test program: Test results for smooth, hole-pattern and helically-grooved stators

NASA Technical Reports Server (NTRS)

Childs, Dara W.

1987-01-01

All of the listed seals were tested in a liquid Halon test facility at high Reynolds numbers. In addition, a helically-grooved-stator seal was tested in an air seal facility. An analysis of the test results with comparisons to theoretical predictions supports the following conclusions: (1) For small seals, the Hirs' friction-factor model is more restricted than had been thought; (2) For smooth seals, predictions of stiffness and damping improve markedly as the radical clearance is reduced; (3) Friction-factor data for hole-pattern-seal stators frequently deviates from the Hirs model; (4) Predictions of stiffness and damping coefficients for hole-pattern-stator seals is generally reasonable; (5) Tests for the hole-pattern stators at reduced clearances show no clear optimum for hole-pattern seals with respect to either hole-area ratio or hole depth to minimum clearance ratios; (6) Tests of these hole-pattern stators show no significant advantage in net damping over smooth seals; (7) Tests of helically-grooved seal stators in Halon show reasonable agreement between theory and prediction for leakage and direct stiffness but poor agreement for the net damping coefficient.

Midwives׳ clinical reasoning during second stage labour: Report on an interpretive study.

PubMed

Jefford, Elaine; Fahy, Kathleen

2015-05-01

clinical reasoning was once thought to be the exclusive domain of medicine - setting it apart from 'non-scientific' occupations like midwifery. Poor assessment, clinical reasoning and decision-making skills are well known contributors to adverse outcomes in maternity care. Midwifery decision-making models share a common deficit: they are insufficiently detailed to guide reasoning processes for midwives in practice. For these reasons we wanted to explore if midwives actively engaged in clinical reasoning processes within their clinical practice and if so to what extent. The study was conducted using post structural, feminist methodology. to what extent do midwives engage in clinical reasoning processes when making decisions in the second stage labour? twenty-six practising midwives were interviewed. Feminist interpretive analysis was conducted by two researchers guided by the steps of a model of clinical reasoning process. Six narratives were excluded from analysis because they did not sufficiently address the research question. The midwives narratives were prepared via data reduction. A theoretically informed analysis and interpretation was conducted. using a feminist, interpretive approach we created a model of midwifery clinical reasoning grounded in the literature and consistent with the data. Thirteen of the 20 participant narratives demonstrate analytical clinical reasoning abilities but only nine completed the process and implemented the decision. Seven midwives used non-analytical decision-making without adequately checking against assessment data. over half of the participants demonstrated the ability to use clinical reasoning skills. Less than half of the midwives demonstrated clinical reasoning as their way of making decisions. The new model of Midwifery Clinical Reasoning includes 'intuition' as a valued way of knowing. Using intuition, however, should not replace clinical reasoning which promotes through decision-making can be made transparent and be consensually validated. Copyright © 2015 Elsevier Ltd. All rights reserved.

The use of multiple models in case-based diagnosis

NASA Technical Reports Server (NTRS)

Karamouzis, Stamos T.; Feyock, Stefan

1993-01-01

The work described in this paper has as its goal the integration of a number of reasoning techniques into a unified intelligent information system that will aid flight crews with malfunction diagnosis and prognostication. One of these approaches involves using the extensive archive of information contained in aircraft accident reports along with various models of the aircraft as the basis for case-based reasoning about malfunctions. Case-based reasoning draws conclusions on the basis of similarities between the present situation and prior experience. We maintain that the ability of a CBR program to reason about physical systems is significantly enhanced by the addition to the CBR program of various models. This paper describes the diagnostic concepts implemented in a prototypical case based reasoner that operates in the domain of in-flight fault diagnosis, the various models used in conjunction with the reasoner's CBR component, and results from a preliminary evaluation.

Multistate Landau-Zener models with all levels crossing at one point

DOE PAGES

Li, Fuxiang; Sun, Chen; Chernyak, Vladimir Y.; ...

2017-08-04

Within this paper, we discuss common properties and reasons for integrability in the class of multistate Landau-Zener models with all diabatic levels crossing at one point. Exploring the Stokes phenomenon, we show that each previously solved model has a dual one, whose scattering matrix can be also obtained analytically. For applications, we demonstrate how our results can be used to study conversion of molecular into atomic Bose condensates during passage through the Feshbach resonance, and provide purely algebraic solutions of the bowtie and special cases of the driven Tavis-Cummings model.

Promoting the Multidimensional Character of Scientific Reasoning †

PubMed Central

Bradshaw, William S.; Nelson, Jennifer; Adams, Byron J.; Bell, John D.

2017-01-01

This study reports part of a long-term program to help students improve scientific reasoning using higher-order cognitive tasks set in the discipline of cell biology. This skill was assessed using problems requiring the construction of valid conclusions drawn from authentic research data. We report here efforts to confirm the hypothesis that data interpretation is a complex, multifaceted exercise. Confirmation was obtained using a statistical treatment showing that various such problems rank students differently—each contains a unique set of cognitive challenges. Additional analyses of performance results have allowed us to demonstrate that individuals differ in their capacity to navigate five independent generic elements that constitute successful data interpretation: biological context, connection to course concepts, experimental protocols, data inference, and integration of isolated experimental observations into a coherent model. We offer these aspects of scientific thinking as a “data analysis skills inventory,” along with usable sample problems that illustrate each element. Additionally, we show that this kind of reasoning is rigorous in that it is difficult for most novice students, who are unable to intuitively implement strategies for improving these skills. Instructors armed with knowledge of the specific challenges presented by different types of problems can provide specific helpful feedback during formative practice. The use of this instructional model is most likely to require changes in traditional classroom instruction. PMID:28512524

Applying the reasoned action approach to understanding health protection and health risk behaviors.

PubMed

Conner, Mark; McEachan, Rosemary; Lawton, Rebecca; Gardner, Peter

2017-12-01

The Reasoned Action Approach (RAA) developed out of the Theory of Reasoned Action and Theory of Planned Behavior but has not yet been widely applied to understanding health behaviors. The present research employed the RAA in a prospective design to test predictions of intention and action for groups of protection and risk behaviors separately in the same sample. To test the RAA for health protection and risk behaviors. Measures of RAA components plus past behavior were taken in relation to eight protection and six risk behaviors in 385 adults. Self-reported behavior was assessed one month later. Multi-level modelling showed instrumental attitude, experiential attitude, descriptive norms, capacity and past behavior were significant positive predictors of intentions to engage in protection or risk behaviors. Injunctive norms were only significant predictors of intention in protection behaviors. Autonomy was a significant positive predictor of intentions in protection behaviors and a negative predictor in risk behaviors (the latter relationship became non-significant when controlling for past behavior). Multi-level modelling showed that intention, capacity, and past behavior were significant positive predictors of action for both protection and risk behaviors. Experiential attitude and descriptive norm were additional significant positive predictors of risk behaviors. The RAA has utility in predicting both protection and risk health behaviors although the power of predictors may vary across these types of health behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

California's population geography: lessons for a fourth grade class.

PubMed

Rushdoony, H A

1978-11-01

Purpose of this paper is to present a model for teaching fourth grade children some aspects of the population geography of California from a nontextual approach. The objective is to interest and instruct children in the mobility of the people, and on the reasons why so many families have moved to California from other states. Students should be alerted not only to internal migration problems, but to the excess of births over deaths. Materials necessary for the lessons are transparencies, overhead projector, marking pencils, chalk and chalkboard. After showing the students that California population has approximately doubled every 20 years, the students should be encouraged to find reasons explaining why people have moved to the state, should be able to categorize those reasons under the terms industrial/manufacturing, agricultural, urban or recreational, should learn how to plot population distribution on a California regional outline map, and should attempt to explain why certain parts of California are more popular than others. The teaching model described in this paper may be replicated with modfications for any grade level and area of study.

Features that contribute to the usefulness of low-fidelity models for surgical skills training.

PubMed

Langebæk, R; Berendt, M; Pedersen, L T; Jensen, A L; Eika, B

2012-04-07

For practical, ethical and economic reasons, veterinary surgical education is becoming increasingly dependent on models for training. The limited availability and high cost of commercially produced surgical models has increased the need for useful, low-cost alternatives. For this reason, a number of models were developed to be used in a basic surgical skills course for veterinary students. The models were low fidelity, having limited resemblance to real animals. The aim of the present study was to describe the students' learning experience with the models and to report their perception of the usefulness of the models in applying the trained skills to live animal surgery. One hundred and forty-six veterinary fourth-year students evaluated the models on a four-point Likert scale. Of these, 26 additionally participated in individual semistructured interviews. The survey results showed that 75 per cent of the students rated the models 'useful'/'very useful'. Interviews revealed that tactile, dimensional, visual, situational and emotional features are important to students' perception of a successful translation of skills from models to live animal. In conclusion, low-fidelity models are useful educational tools in preparation for live animal surgery. However, there are specific features to take into account when developing models in order for students to perceive them as useful.

Getting expert systems off the ground: Lessons learned from integrating model-based diagnostics with prototype flight hardware

NASA Technical Reports Server (NTRS)

Stephan, Amy; Erikson, Carol A.

1991-01-01

As an initial attempt to introduce expert system technology into an onboard environment, a model based diagnostic system using the TRW MARPLE software tool was integrated with prototype flight hardware and its corresponding control software. Because this experiment was designed primarily to test the effectiveness of the model based reasoning technique used, the expert system ran on a separate hardware platform, and interactions between the control software and the model based diagnostics were limited. While this project met its objective of showing that model based reasoning can effectively isolate failures in flight hardware, it also identified the need for an integrated development path for expert system and control software for onboard applications. In developing expert systems that are ready for flight, artificial intelligence techniques must be evaluated to determine whether they offer a real advantage onboard, identify which diagnostic functions should be performed by the expert systems and which are better left to the procedural software, and work closely with both the hardware and the software developers from the beginning of a project to produce a well designed and thoroughly integrated application.

How similar are recognition memory and inductive reasoning?

PubMed

Hayes, Brett K; Heit, Evan

2013-07-01

Conventionally, memory and reasoning are seen as different types of cognitive activities driven by different processes. In two experiments, we challenged this view by examining the relationship between recognition memory and inductive reasoning involving multiple forms of similarity. A common study set (members of a conjunctive category) was followed by a test set containing old and new category members, as well as items that matched the study set on only one dimension. The study and test sets were presented under recognition or induction instructions. In Experiments 1 and 2, the inductive property being generalized was varied in order to direct attention to different dimensions of similarity. When there was no time pressure on decisions, patterns of positive responding were strongly affected by property type, indicating that different types of similarity were driving recognition and induction. By comparison, speeded judgments showed weaker property effects and could be explained by generalization based on overall similarity. An exemplar model, GEN-EX (GENeralization from EXamples), could account for both the induction and recognition data. These findings show that induction and recognition share core component processes, even when the tasks involve flexible forms of similarity.

Five-equation and robust three-equation methods for solution verification of large eddy simulation

NASA Astrophysics Data System (ADS)

Dutta, Rabijit; Xing, Tao

2018-02-01

This study evaluates the recently developed general framework for solution verification methods for large eddy simulation (LES) using implicitly filtered LES of periodic channel flows at friction Reynolds number of 395 on eight systematically refined grids. The seven-equation method shows that the coupling error based on Hypothesis I is much smaller as compared with the numerical and modeling errors and therefore can be neglected. The authors recommend five-equation method based on Hypothesis II, which shows a monotonic convergence behavior of the predicted numerical benchmark ( S C ), and provides realistic error estimates without the need of fixing the orders of accuracy for either numerical or modeling errors. Based on the results from seven-equation and five-equation methods, less expensive three and four-equation methods for practical LES applications were derived. It was found that the new three-equation method is robust as it can be applied to any convergence types and reasonably predict the error trends. It was also observed that the numerical and modeling errors usually have opposite signs, which suggests error cancellation play an essential role in LES. When Reynolds averaged Navier-Stokes (RANS) based error estimation method is applied, it shows significant error in the prediction of S C on coarse meshes. However, it predicts reasonable S C when the grids resolve at least 80% of the total turbulent kinetic energy.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing.

PubMed

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing

PubMed Central

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models. PMID:29062288

Model-Based Knowing: How Do Students Ground Their Understanding About Climate Systems in Agent-Based Computer Models?

NASA Astrophysics Data System (ADS)

Markauskaite, Lina; Kelly, Nick; Jacobson, Michael J.

2017-12-01

This paper gives a grounded cognition account of model-based learning of complex scientific knowledge related to socio-scientific issues, such as climate change. It draws on the results from a study of high school students learning about the carbon cycle through computational agent-based models and investigates two questions: First, how do students ground their understanding about the phenomenon when they learn and solve problems with computer models? Second, what are common sources of mistakes in students' reasoning with computer models? Results show that students ground their understanding in computer models in five ways: direct observation, straight abstraction, generalisation, conceptualisation, and extension. Students also incorporate into their reasoning their knowledge and experiences that extend beyond phenomena represented in the models, such as attitudes about unsustainable carbon emission rates, human agency, external events, and the nature of computational models. The most common difficulties of the students relate to seeing the modelled scientific phenomenon and connecting results from the observations with other experiences and understandings about the phenomenon in the outside world. An important contribution of this study is the constructed coding scheme for establishing different ways of grounding, which helps to understand some challenges that students encounter when they learn about complex phenomena with agent-based computer models.

[Study on the nutrition of alpine meadow based on hyperspectral data].

PubMed

Wang, Xun; Liu, Shu-Jie; Jia, Hai-Feng; Chai, Sha-Tuo; Dang, An-Rong; Liu, Xue-Hua; Hao, Li-Zhuang; Cui, Zhan-Hong

2012-10-01

Remote sensing monitoring of alpine grassland nutritional status is a key factor of grassland reasonable utilization, also a difficulty for dynamic vegetation monitoring. The present paper studies the correlations between vegetation nutrition and hyperspectral data. The results showed that two band ratio models have a significant correlation with biomass, air-DM, P, CF, and CP. MAXR models have a significant correlation with most of nutrition index when selected wavebands equaled five. On the whole, the MAXR model precedes two band ratio models. Using MAXR models to estimate air-DM, P and CF can obtain higher accuracy.

Optimal allocation model of construction land based on two-level system optimization theory

NASA Astrophysics Data System (ADS)

Liu, Min; Liu, Yanfang; Xia, Yuping; Lei, Qihong

2007-06-01

The allocation of construction land is an important task in land-use planning. Whether implementation of planning decisions is a success or not, usually depends on a reasonable and scientific distribution method. Considering the constitution of land-use planning system and planning process in China, multiple levels and multiple objective decision problems is its essence. Also, planning quantity decomposition is a two-level system optimization problem and an optimal resource allocation decision problem between a decision-maker in the topper and a number of parallel decision-makers in the lower. According the characteristics of the decision-making process of two-level decision-making system, this paper develops an optimal allocation model of construction land based on two-level linear planning. In order to verify the rationality and the validity of our model, Baoan district of Shenzhen City has been taken as a test case. Under the assistance of the allocation model, construction land is allocated to ten townships of Baoan district. The result obtained from our model is compared to that of traditional method, and results show that our model is reasonable and usable. In the end, the paper points out the shortcomings of the model and further research directions.

A Next-Generation Model of the Corona and Solar Wind

DTIC Science & Technology

2011-03-31

2007. The Sun was very quiet during this time. An extended coronal hole is visible in the observations and the simulation. (d) July 19, 2008...those synthesized from our model for August 27, 1996, when the “Elephant’s trunk” equatorial coronal hole was visible. To make a quantitative...especially the coronal hole regions, agree reasonably well. Figure 3 shows comparisons of simulated and actual emission for four other time periods. Frame (a

The stress-response dampening hypothesis: how self-esteem and stress act as mechanisms between negative parental bonds and alcohol-related problems in emerging adulthood.

PubMed

Backer-Fulghum, Lindsey M; Patock-Peckham, Julie A; King, Kevin M; Roufa, Lindsay; Hagen, Leslie

2012-04-01

The stress dampening model (Marlatt, 1987; Sayette, 1993; Sher, 1987) suggests certain individuals may use alcohol to escape from their negative life experiences. Pathological reasons for drinking (e.g., using alcohol as a means to cope) reflect the degree to which individuals are motivated to use alcohol in order to dampen or alleviate the stress they are experiencing (Johnson, Schwitters, Wilson, Nagoshi, & McClearn, 1985). Direct and mediational links among parental bonds (rejection, care, overprotection, autonomy, and neglect), self-esteem, stress, pathological reasons for drinking, and alcohol-related problems were explored. A Structural Equation Model with (405 students; 164 women, 241 men) college students was examined. Three path mediational analyses revealed several mediated pathways. Greater feelings of perceived father/mother neglectfulness (i.e., offspring feeling parents do not show up for them) were indirectly linked to more alcohol-related problems (e.g., indicative of alcohol use or dependence in emerging adulthood) through increased stress and pathological reasons for drinking. Furthermore, higher levels of father rejection (i.e., perception of feeling unwanted) were indirectly linked to more pathological reasons for drinking through low self-esteem and increased stress. However, greater feelings of mother care (affectionate and attentive) were indirectly linked to fewer pathological reasons for drinking through higher self-esteem and lower levels of stress. Moreover, high self-esteem was found to be indirectly linked to fewer alcohol-related problems through decreased stress and pathological reasons for drinking. These findings suggest several specific pathways for using alcohol to self-medicate (i.e., consume alcohol for a specific purpose) or dampen feelings of stress. Copyright © 2011 Elsevier Ltd. All rights reserved.

Experimental Validation of the Transverse Shear Behavior of a Nomex Core for Sandwich Panels

NASA Astrophysics Data System (ADS)

Farooqi, M. I.; Nasir, M. A.; Ali, H. M.; Ali, Y.

2017-05-01

This work deals with determination of the transverse shear moduli of a Nomex® honeycomb core of sandwich panels. Their out-of-plane shear characteristics depend on the transverse shear moduli of the honeycomb core. These moduli were determined experimentally, numerically, and analytically. Numerical simulations were performed by using a unit cell model and three analytical approaches. Analytical calculations showed that two of the approaches provided reasonable predictions for the transverse shear modulus as compared with experimental results. However, the approach based upon the classical lamination theory showed large deviations from experimental data. Numerical simulations also showed a trend similar to that resulting from the analytical models.

Simulation of climatology and Interannual Variability of Spring Persistent Rains by Meteorological Research Institute Model: Impacts of different horizontal resolutions

NASA Astrophysics Data System (ADS)

Li, Puxi; Zhou, Tianjun; Zou, Liwei

2016-04-01

The authors evaluated the performance of Meteorological Research Institute (MRI) AGCM3.2 models in the simulations of climatology and interannual variability of the Spring Persistent Rains (SPR) over southeastern China. The possible impacts of different horizontal resolutions were also investigated based on the experiments with three different horizontal resolutions (i.e., 120, 60, and 20km). The model could reasonably reproduce the main rainfall center over southeastern China in boreal spring under the three different resolutions. In comparison with 120 simulation, it revealed that 60km and 20km simulations show the superiority in simulating rainfall centers anchored by the Nanling-Wuyi Mountains, but overestimate rainfall intensity. Water vapor budget diagnosis showed that, the 60km and 20km simulations tended to overestimate the water vapor convergence over southeastern China, which leads to wet biases. In the aspect of interannual variability of SPR, the model could reasonably reproduce the anomalous lower-tropospheric anticyclone in the western North Pacific (WNPAC) and positive precipitation anomalies over southeastern China in El Niño decaying spring. Compared with the 120km resolution, the large positive biases are substantially reduced in the mid and high resolution models which evidently improve the simulation of horizontal moisture advection in El Niño decaying spring. We highlight the importance of developing high resolution climate model as it could potentially improve the climatology and interannual variability of SPR.

Relating Derived Relations as a Model of Analogical Reasoning: Reaction Times and Event-Related Potentials

PubMed Central

Barnes-Holmes, Dermot; Regan, Donal; Barnes-Holmes, Yvonne; Commins, Sean; Walsh, Derek; Stewart, Ian; Smeets, Paul M; Whelan, Robert; Dymond, Simon

2005-01-01

The current study aimed to test a Relational Frame Theory (RFT) model of analogical reasoning based on the relating of derived same and derived difference relations. Experiment 1 recorded reaction time measures of similar–similar (e.g., “apple is to orange as dog is to cat”) versus different–different (e.g., “he is to his brother as chalk is to cheese”) derived relational responding, in both speed-contingent and speed-noncontingent conditions. Experiment 2 examined the event-related potentials (ERPs) associated with these two response patterns. Both experiments showed similar–similar responding to be significantly faster than different–different responding. Experiment 2 revealed significant differences between the waveforms of the two response patterns in the left-hemispheric prefrontal regions; different–different waveforms were significantly more negative than similar–similar waveforms. The behavioral and neurophysiological data support the RFT prediction that, all things being equal, similar–similar responding is relationally “simpler” than, and functionally distinct from, different–different analogical responding. The ERP data were fully consistent with findings in the neurocognitive literature on analogy. These findings strengthen the validity of the RFT model of analogical reasoning and supplement the behavior-analytic approach to analogy based on the relating of derived relations. PMID:16596974

Tableau Calculus for the Logic of Comparative Similarity over Arbitrary Distance Spaces

NASA Astrophysics Data System (ADS)

Alenda, Régis; Olivetti, Nicola

The logic CSL (first introduced by Sheremet, Tishkovsky, Wolter and Zakharyaschev in 2005) allows one to reason about distance comparison and similarity comparison within a modal language. The logic can express assertions of the kind "A is closer/more similar to B than to C" and has a natural application to spatial reasoning, as well as to reasoning about concept similarity in ontologies. The semantics of CSL is defined in terms of models based on different classes of distance spaces and it generalizes the logic S4 u of topological spaces. In this paper we consider CSL defined over arbitrary distance spaces. The logic comprises a binary modality to represent comparative similarity and a unary modality to express the existence of the minimum of a set of distances. We first show that the semantics of CSL can be equivalently defined in terms of preferential models. As a consequence we obtain the finite model property of the logic with respect to its preferential semantic, a property that does not hold with respect to the original distance-space semantics. Next we present an analytic tableau calculus based on its preferential semantics. The calculus provides a decision procedure for the logic, its termination is obtained by imposing suitable blocking restrictions.

Reasoning and memory: People make varied use of the information available in working memory.

PubMed

Hardman, Kyle O; Cowan, Nelson

2016-05-01

Working memory (WM) is used for storing information in a highly accessible state so that other mental processes, such as reasoning, can use that information. Some WM tasks require that participants not only store information, but also reason about that information to perform optimally on the task. In this study, we used visual WM tasks that had both storage and reasoning components to determine both how ideally people are able to reason about information in WM and if there is a relationship between information storage and reasoning. We developed novel psychological process models of the tasks that allowed us to estimate for each participant both how much information they had in WM and how efficiently they reasoned about that information. Our estimates of information use showed that participants are not all ideal information users or minimal information users, but rather that there are individual differences in the thoroughness of information use in our WM tasks. However, we found that our participants tended to be more ideal than minimal. One implication of this work is that to accurately estimate the amount of information in WM, it is important to also estimate how efficiently that information is used. This new analysis contributes to the theoretical premise that human rationality may be bounded by the complexity of task demands. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Reasoning and memory: People make varied use of the information available in working memory

PubMed Central

Hardman, Kyle O.; Cowan, Nelson

2015-01-01

Working memory (WM) is used for storing information in a highly-accessible state so that other mental processes, such as reasoning, can use that information. Some WM tasks require that participants not only store information, but also reason about that information in order to perform optimally on the task. In this study, we used visual WM tasks that had both storage and reasoning components in order to determine both how ideally people are able to reason about information in WM and if there is a relationship between information storage and reasoning. We developed novel psychological process models of the tasks that allowed us to estimate for each participant both how much information they had in WM and how efficiently they reasoned about that information. Our estimates of information use showed that participants are not all ideal information users or minimal information users, but rather that there are individual differences in the thoroughness of information use in our WM tasks. However, we found that our participants tended to be more ideal than minimal. One implication of this work is that in order to accurately estimate the amount of information in WM, it is important to also estimate how efficiently that information is used. This new analysis contributes to the theoretical premise that human rationality may be bounded by the complexity of task demands. PMID:26569436

Mechanical Characteristics Analysis of Surrounding Rock on Anchor Bar Reinforcement

NASA Astrophysics Data System (ADS)

Gu, Shuan-cheng; Zhou, Pan; Huang, Rong-bin

2018-03-01

Through the homogenization method, the composite of rock and anchor bar is considered as the equivalent material of continuous, homogeneous, isotropic and strength parameter enhancement, which is defined as reinforcement body. On the basis of elasticity, the composite and the reinforcement are analyzed, Based on strengthening theory of surrounding rock and displacement equivalent conditions, the expression of reinforcement body strength parameters and mechanical parameters is deduced. The example calculation shows that the theoretical results are close to the results of the Jia-mei Gao[9], however, closer to the results of FLAC3D numerical simulation, it is proved that the model and surrounding rock reinforcement body theory are reasonable. the model is easy to analyze and calculate, provides a new way for determining reasonable bolt support parameters, can also provides reference for the stability analysis of underground cavern bolting support.

Follow the heart or the head? The interactive influence model of emotion and cognition.

PubMed

Luo, Jiayi; Yu, Rongjun

2015-01-01

The experience of emotion has a powerful influence on daily-life decision making. Following Plato's description of emotion and reason as two horses pulling us in opposite directions, modern dual-system models of decision making endorse the antagonism between reason and emotion. Decision making is perceived as the competition between an emotion system that is automatic but prone to error and a reason system that is slow but rational. The reason system (in "the head") reins in our impulses (from "the heart") and overrides our snap judgments. However, from Darwin's evolutionary perspective, emotion is adaptive, guiding us to make sound decisions in uncertainty. Here, drawing findings from behavioral economics and neuroeconomics, we provide a new model, labeled "The interactive influence model of emotion and cognition," to elaborate the relationship of emotion and reason in decision making. Specifically, in our model, we identify factors that determine when emotions override reason and delineate the type of contexts in which emotions help or hurt decision making. We then illustrate how cognition modulates emotion and how they cooperate to affect decision making.

The Cure for Ailing Self-Service Business Intelligence

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

Burke, Marsha; Simpson, Wayne; Staples, Shad

There are many reasons that self-service models fail. Furthermore, these reasons are directly applicable in the management of self-service business inteligence modeling. Our article expands upon the reasons for failure and suggests how self-service models can be made successful through implementation of a centralized approach to development, testing, implementation and support for the delivery of decision making information.

The Cure for Ailing Self-Service Business Intelligence

DOE PAGES

Burke, Marsha; Simpson, Wayne; Staples, Shad

2016-09-14

There are many reasons that self-service models fail. Furthermore, these reasons are directly applicable in the management of self-service business inteligence modeling. Our article expands upon the reasons for failure and suggests how self-service models can be made successful through implementation of a centralized approach to development, testing, implementation and support for the delivery of decision making information.

#13ReasonsWhy Health Professionals and Educators are Tweeting: A Systematic Analysis of Uses and Perceptions of Show Content and Learning Outcomes.

PubMed

Walker, Kimberly K; Burns, Kelli

2018-04-27

This study is a content analysis of health professionals' and educators' tweets about a popular Netflix show that depicts teen suicide: 13 Reasons Why. A content analysis of 740 tweets was conducted to determine the main themes associated with professionals' and educators' tweets about the show, as well as the valence of the tweets. Additionally, a thematic analysis of linked content in tweets (n = 178) was conducted to explore additional content shared about the show and modeling outcomes. Results indicated the largest percentage of tweets was related to social learning, particularly about outcomes that could occur from viewing the show. The valence of the tweets about outcomes was more positive than negative. However, linked materials commonly circulated in tweets signified greater concern with unintended learning outcomes. Some of the linked content included media guidelines for reporting on suicide with recommendations that entertainment producers follow the guidelines. This study emphasizes the importance of including social learning objectives in future typologies of Twitter uses and demonstrates the importance of examining linked content in Twitter studies.

Remarks on the general solution for the flat Friedmann universe with exponential scalar-field potential and dust

NASA Astrophysics Data System (ADS)

Andrianov, A. A.; Cannata, F.; Kamenshchik, A. Yu.

2012-11-01

We show that the simple extension of the method of obtaining the general exact solution for the cosmological model with the exponential scalar-field potential to the case when the dust is present fails, and we discuss the reasons of this puzzling phenomenon.

Spatial Processes in Linear Ordering

ERIC Educational Resources Information Center

von Hecker, Ulrich; Klauer, Karl Christoph; Wolf, Lukas; Fazilat-Pour, Masoud

2016-01-01

Memory performance in linear order reasoning tasks (A > B, B > C, C > D, etc.) shows quicker, and more accurate responses to queries on wider (AD) than narrower (AB) pairs on a hypothetical linear mental model (A -- B -- C -- D). While indicative of an analogue representation, research so far did not provide positive evidence for spatial…

The Architecture, Dynamics, and Development of Mental Processing: Greek, Chinese, or Universal?

ERIC Educational Resources Information Center

Demetriou, A.; Kui, Z.X.; Spanoudis, G.; Christou, C.; Kyriakides, L.; Platsidou, M.

2005-01-01

This study compared Greeks with Chinese, from 8 to 14 years of age, on measures of processing efficiency, working memory, and reasoning. All processes were addressed through three domains of relations: verbal/propositional, quantitative, and visuo/spatial. Structural equations modelling and rating scale analysis showed that the architecture and…

Heat transfer and fire spread

Treesearch

Hal E. Anderson

1969-01-01

Experimental testing of a mathematical model showed that radiant heat transfer accounted for no more than 40% of total heat flux required to maintain rate of spread. A reasonable prediction of spread was possible by assuming a horizontal convective heat transfer coefficient when certain fuel and flame characteristics were known. Fuel particle size had a linear relation...

Causal Premise Semantics

ERIC Educational Resources Information Center

Kaufmann, Stefan

2013-01-01

The rise of causality and the attendant graph-theoretic modeling tools in the study of counterfactual reasoning has had resounding effects in many areas of cognitive science, but it has thus far not permeated the mainstream in linguistic theory to a comparable degree. In this study I show that a version of the predominant framework for the formal…

Solving probability reasoning based on DNA strand displacement and probability modules.

PubMed

Zhang, Qiang; Wang, Xiaobiao; Wang, Xiaojun; Zhou, Changjun

2017-12-01

In computation biology, DNA strand displacement technology is used to simulate the computation process and has shown strong computing ability. Most researchers use it to solve logic problems, but it is only rarely used in probabilistic reasoning. To process probabilistic reasoning, a conditional probability derivation model and total probability model based on DNA strand displacement were established in this paper. The models were assessed through the game "read your mind." It has been shown to enable the application of probabilistic reasoning in genetic diagnosis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Words of Reason.

ERIC Educational Resources Information Center

Beer, Francis A.

1994-01-01

Examines the word "reason" as it is used in political discourse. Argues that "reason"'s plasticity and flexibility help it to stimulate and evoke variable mental images and responses in different settings and situations. Notes that the example of reason of state shows "reason"'s rhetorical power and privilege, its…

Autocorrelated residuals in inverse modelling of soil hydrological processes: a reason for concern or something that can safely be ignored?

NASA Astrophysics Data System (ADS)

Scharnagl, Benedikt; Durner, Wolfgang

2013-04-01

Models are inherently imperfect because they simplify processes that are themselves imperfectly known and understood. Moreover, the input variables and parameters needed to run a model are typically subject to various sources of error. As a consequence of these imperfections, model predictions will always deviate from corresponding observations. In most applications in soil hydrology, these deviations are clearly not random but rather show a systematic structure. From a statistical point of view, this systematic mismatch may be a reason for concern because it violates one of the basic assumptions made in inverse parameter estimation: the assumption of independence of the residuals. But what are the consequences of simply ignoring the autocorrelation in the residuals, as it is current practice in soil hydrology? Are the parameter estimates still valid even though the statistical foundation they are based on is partially collapsed? Theory and practical experience from other fields of science have shown that violation of the independence assumption will result in overconfident uncertainty bounds and that in some cases it may lead to significantly different optimal parameter values. In our contribution, we present three soil hydrological case studies, in which the effect of autocorrelated residuals on the estimated parameters was investigated in detail. We explicitly accounted for autocorrelated residuals using a formal likelihood function that incorporates an autoregressive model. The inverse problem was posed in a Bayesian framework, and the posterior probability density function of the parameters was estimated using Markov chain Monte Carlo simulation. In contrast to many other studies in related fields of science, and quite surprisingly, we found that the first-order autoregressive model, often abbreviated as AR(1), did not work well in the soil hydrological setting. We showed that a second-order autoregressive, or AR(2), model performs much better in these applications, leading to parameter and uncertainty estimates that satisfy all the underlying statistical assumptions. For theoretical reasons, these estimates are deemed more reliable than those estimates based on the neglect of autocorrelation in the residuals. In compliance with theory and results reported in the literature, our results showed that parameter uncertainty bounds were substantially wider if autocorrelation in the residuals was explicitly accounted for, and also the optimal parameter vales were slightly different in this case. We argue that the autoregressive model presented here should be used as a matter of routine in inverse modeling of soil hydrological processes.

The probability heuristics model of syllogistic reasoning.

PubMed

Chater, N; Oaksford, M

1999-03-01

A probability heuristic model (PHM) for syllogistic reasoning is proposed. An informational ordering over quantified statements suggests simple probability based heuristics for syllogistic reasoning. The most important is the "min-heuristic": choose the type of the least informative premise as the type of the conclusion. The rationality of this heuristic is confirmed by an analysis of the probabilistic validity of syllogistic reasoning which treats logical inference as a limiting case of probabilistic inference. A meta-analysis of past experiments reveals close fits with PHM. PHM also compares favorably with alternative accounts, including mental logics, mental models, and deduction as verbal reasoning. Crucially, PHM extends naturally to generalized quantifiers, such as Most and Few, which have not been characterized logically and are, consequently, beyond the scope of current mental logic and mental model theories. Two experiments confirm the novel predictions of PHM when generalized quantifiers are used in syllogistic arguments. PHM suggests that syllogistic reasoning performance may be determined by simple but rational informational strategies justified by probability theory rather than by logic. Copyright 1999 Academic Press.

The heuristic-analytic theory of reasoning: extension and evaluation.

PubMed

Evans, Jonathan St B T

2006-06-01

An extensively revised heuristic-analytic theory of reasoning is presented incorporating three principles of hypothetical thinking. The theory assumes that reasoning and judgment are facilitated by the formation of epistemic mental models that are generated one at a time (singularity principle) by preconscious heuristic processes that contextualize problems in such a way as to maximize relevance to current goals (relevance principle). Analytic processes evaluate these models but tend to accept them unless there is good reason to reject them (satisficing principle). At a minimum, analytic processing of models is required so as to generate inferences or judgments relevant to the task instructions, but more active intervention may result in modification or replacement of default models generated by the heuristic system. Evidence for this theory is provided by a review of a wide range of literature on thinking and reasoning.

Automatic determination of fault effects on aircraft functionality

NASA Technical Reports Server (NTRS)

Feyock, Stefan

1989-01-01

The problem of determining the behavior of physical systems subsequent to the occurrence of malfunctions is discussed. It is established that while it was reasonable to assume that the most important fault behavior modes of primitive components and simple subsystems could be known and predicted, interactions within composite systems reached levels of complexity that precluded the use of traditional rule-based expert system techniques. Reasoning from first principles, i.e., on the basis of causal models of the physical system, was required. The first question that arises is, of course, how the causal information required for such reasoning should be represented. The bond graphs presented here occupy a position intermediate between qualitative and quantitative models, allowing the automatic derivation of Kuipers-like qualitative constraint models as well as state equations. Their most salient feature, however, is that entities corresponding to components and interactions in the physical system are explicitly represented in the bond graph model, thus permitting systematic model updates to reflect malfunctions. Researchers show how this is done, as well as presenting a number of techniques for obtaining qualitative information from the state equations derivable from bond graph models. One insight is the fact that one of the most important advantages of the bond graph ontology is the highly systematic approach to model construction it imposes on the modeler, who is forced to classify the relevant physical entities into a small number of categories, and to look for two highly specific types of interactions among them. The systematic nature of bond graph model construction facilitates the process to the point where the guidelines are sufficiently specific to be followed by modelers who are not domain experts. As a result, models of a given system constructed by different modelers will have extensive similarities. Researchers conclude by pointing out that the ease of updating bond graph models to reflect malfunctions is a manifestation of the systematic nature of bond graph construction, and the regularity of the relationship between bond graph models and physical reality.

Know the risk, take the win: how executive functions and probability processing influence advantageous decision making under risk conditions.

PubMed

Brand, Matthias; Schiebener, Johannes; Pertl, Marie-Theres; Delazer, Margarete

2014-01-01

Recent models on decision making under risk conditions have suggested that numerical abilities are important ingredients of advantageous decision-making performance, but empirical evidence is still limited. The results of our first study show that logical reasoning and basic mental calculation capacities predict ratio processing and that ratio processing predicts decision making under risk. In the second study, logical reasoning together with executive functions predicted probability processing (numeracy and probability knowledge), and probability processing predicted decision making under risk. These findings suggest that increasing an individual's understanding of ratios and probabilities should lead to more advantageous decisions under risk conditions.

Low-order nonlinear dynamic model of IC engine-variable pitch propeller system for general aviation aircraft

NASA Technical Reports Server (NTRS)

Richard, Jacques C.

1995-01-01

This paper presents a dynamic model of an internal combustion engine coupled to a variable pitch propeller. The low-order, nonlinear time-dependent model is useful for simulating the propulsion system of general aviation single-engine light aircraft. This model is suitable for investigating engine diagnostics and monitoring and for control design and development. Furthermore, the model may be extended to provide a tool for the study of engine emissions, fuel economy, component effects, alternative fuels, alternative engine cycles, flight simulators, sensors, and actuators. Results show that the model provides a reasonable representation of the propulsion system dynamics from zero to 10 Hertz.

Model-based analysis of the effect of different operating conditions on fouling mechanisms in a membrane bioreactor.

PubMed

Sabia, Gianpaolo; Ferraris, Marco; Spagni, Alessandro

2016-01-01

This study proposes a model-based evaluation of the effect of different operating conditions with and without pre-denitrification treatment and applying three different solids retention times on the fouling mechanisms involved in membrane bioreactors (MBRs). A total of 11 fouling models obtained from literature were used to fit the transmembrane pressure variations measured in a pilot-scale MBR treating real wastewater for more than 1 year. The results showed that all the models represent reasonable descriptions of the fouling processes in the MBR tested. The model-based analysis confirmed that membrane fouling started by pore blocking (complete blocking model) and by a reduction of the pore diameter (standard blocking) while cake filtration became the dominant fouling mechanism over long-term operation. However, the different fouling mechanisms occurred almost simultaneously making it rather difficult to identify each one. The membrane "history" (i.e. age, lifespan, etc.) seems the most important factor affecting the fouling mechanism more than the applied operating conditions. Nonlinear regression of the most complex models (combined models) evaluated in this study sometimes demonstrated unreliable parameter estimates suggesting that the four basic fouling models (complete, standard, intermediate blocking and cake filtration) contain enough details to represent a reasonable description of the main fouling processes occurring in MBRs.

Development and initial evaluation of an instrument to assess physiotherapists' clinical reasoning focused on clients' behavior change.

PubMed

Elvén, Maria; Hochwälder, Jacek; Dean, Elizabeth; Söderlund, Anne

2018-05-01

A systematically developed and evaluated instrument is needed to support investigations of physiotherapists' clinical reasoning integrated with the process of clients' behavior change. This study's aim was to develop an instrument to assess physiotherapy students' and physiotherapists' clinical reasoning focused on clients' activity-related behavior and behavior change, and initiate its evaluation, including feasibility and content validity. The study was conducted in three phases: 1) determination of instrument structure and item generation, based on a model, guidelines for assessing clinical reasoning, and existing measures; 2) cognitive interviews with five physiotherapy students to evaluate item understanding and feasibility; and 3) a Delphi process with 18 experts to evaluate content relevance. Phase 1 resulted in an instrument with four domains: Physiotherapist; Input from client; Functional behavioral analysis; and Strategies for behavior change. The instrument consists of case scenarios followed by items in which key features are identified, prioritized, or interpreted. Phase 2 resulted in revisions of problems and approval of feasibility. Phase 3 demonstrated high level of consensus regarding the instrument's content relevance. This feasible and content-validated instrument shows potential for use in investigations of physiotherapy students' and physiotherapists' clinical reasoning, however continued development and testing are needed.

Faults Discovery By Using Mined Data

NASA Technical Reports Server (NTRS)

Lee, Charles

2005-01-01

Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.

A simulation study on Bayesian Ridge regression models for several collinearity levels

NASA Astrophysics Data System (ADS)

Efendi, Achmad; Effrihan

2017-12-01

When analyzing data with multiple regression model if there are collinearities, then one or several predictor variables are usually omitted from the model. However, there sometimes some reasons, for instance medical or economic reasons, the predictors are all important and should be included in the model. Ridge regression model is not uncommon in some researches to use to cope with collinearity. Through this modeling, weights for predictor variables are used for estimating parameters. The next estimation process could follow the concept of likelihood. Furthermore, for the estimation nowadays the Bayesian version could be an alternative. This estimation method does not match likelihood one in terms of popularity due to some difficulties; computation and so forth. Nevertheless, with the growing improvement of computational methodology recently, this caveat should not at the moment become a problem. This paper discusses about simulation process for evaluating the characteristic of Bayesian Ridge regression parameter estimates. There are several simulation settings based on variety of collinearity levels and sample sizes. The results show that Bayesian method gives better performance for relatively small sample sizes, and for other settings the method does perform relatively similar to the likelihood method.

Integration of Optimal Scheduling with Case-Based Planning.

DTIC Science & Technology

1995-08-01

integrates Case-Based Reasoning (CBR) and Rule-Based Reasoning (RBR) systems. ’ Tachyon : A Constraint-Based Temporal Reasoning Model and Its...Implementation’ provides an overview of the Tachyon temporal’s reasoning system and discusses its possible applications. ’Dual-Use Applications of Tachyon : From...Force Structure Modeling to Manufacturing Scheduling’ discusses the application of Tachyon to real world problems, specifically military force deployment and manufacturing scheduling.

The Probability Heuristics Model of Syllogistic Reasoning.

ERIC Educational Resources Information Center

Chater, Nick; Oaksford, Mike

1999-01-01

Proposes a probability heuristic model for syllogistic reasoning and confirms the rationality of this heuristic by an analysis of the probabilistic validity of syllogistic reasoning that treats logical inference as a limiting case of probabilistic inference. Meta-analysis and two experiments involving 40 adult participants and using generalized…

Is It a Dangerous World Out There? The Motivational Bases of American Gun Ownership.

PubMed

Stroebe, Wolfgang; Leander, N Pontus; Kruglanski, Arie W

2017-08-01

Americans are the world's best armed citizens and public polling suggests protection/self-defense is their main reason for gun ownership. However, there is virtually no psychological research on gun ownership. The present article develops the first psychological process model of defensive gun ownership-specifically, a two-component model that considers both the antecedents and consequences of owning a gun for protection/self-defense. We demonstrate that different levels of threat construal-the specific perceived threat of assault and a diffuse threat of a dangerous world-independently predict handgun ownership; we also show how utility judgments can explain the motivated reasoning that drives beliefs about gun rights. We tested our model in two independent samples of gun owners (total N = 899), from just before and after the Orlando mass shooting. This study illustrates how social-cognitive theories can help explain what motivates Americans to own handguns and advocate for broad rights to carry and use them.

Clinical reasoning in nursing, a think-aloud study using virtual patients - a base for an innovative assessment.

PubMed

Forsberg, Elenita; Ziegert, Kristina; Hult, Håkan; Fors, Uno

2014-04-01

In health-care education, it is important to assess the competencies that are essential for the professional role. To develop clinical reasoning skills is crucial for nursing practice and therefore an important learning outcome in nursing education programmes. Virtual patients (VPs) are interactive computer simulations of real-life clinical scenarios and have been suggested for use not only for learning, but also for assessment of clinical reasoning. The aim of this study was to investigate how experienced paediatric nurses reason regarding complex VP cases and how they make clinical decisions. The study was also aimed to give information about possible issues that should be assessed in clinical reasoning exams for post-graduate students in diploma specialist paediatric nursing education. The information from this study is believed to be of high value when developing scoring and grading models for a VP-based examination for the specialist diploma in paediatric nursing education. Using the think-aloud method, data were collected from 30 RNs working in Swedish paediatric departments, and child or school health-care centres. Content analysis was used to analyse the data. The results indicate that experienced nurses try to consolidate their hypotheses by seeing a pattern and judging the value of signs, symptoms, physical examinations, laboratory tests and radiology. They show high specific competence but earlier experience of similar cases was also of importance for the decision making. The nurses thought it was an innovative assessment focusing on clinical reasoning and clinical decision making. They thought it was an enjoyable way to be assessed and that all three main issues could be assessed using VPs. In conclusion, VPs seem to be a possible model for assessing the clinical reasoning process and clinical decision making, but how to score and grade such exams needs further research. © 2013.

d∗(2380) Resonance in a Chiral SU(3) Constituent Quark Model

NASA Astrophysics Data System (ADS)

Dong, Yubing; Shen, Pengnian; Huang, Fei; Zhang, Zongye

Recent studies on the newly observed resonance d∗(2380)(I(JP) = 0(3+)) with a compact structure in a chiral SU(3) constituent quark model are briefly reported. the overall properties, including the mass, the partial decay widths in various decay modes, and the total width, comparing with the experimental data, show that a compact hexaquark dominated structure might be a reasonable interpretation for this state. Moreover, the charge distribution of d∗ is also discussed.

Why learning and development can lead to poorer recognition memory.

PubMed

Hayes, Brett K; Heit, Evan

2004-08-01

Current models of inductive reasoning in children and adults assume a central role for categorical knowledge. A recent paper by Sloutsky and Fisher challenges this assumption, showing that children are more likely than adults to rely on perceptual similarity as a basis for induction, and introduces a more direct method for examining the representations activated during induction. This method has the potential to constrain models of induction in novel ways, although there are still important challenges.

Mechanism underlying the diverse collective behavior in the swarm oscillator model

NASA Astrophysics Data System (ADS)

Iwasa, Masatomo; Tanaka, Dan

2017-09-01

The swarm oscillator model describes the long-time behavior of interacting chemotactic particles, and it shows numerous types of macroscopic patterns. However, the reason why so many kinds of patterns emerge is not clear. In this study, we elucidate the mechanism underlying the diversity of the pattens by analyzing the model for two particles. Focusing on the behavior when the two particles are spatially close, we find that the dynamics is classified into eight types, which explain most of the observed 13 types of patterns.

The Dimensionality of Reasoning: Inductive and Deductive Inference can be Explained by a Single Process.

PubMed

Hayes, Brett K; Stephens, Rachel G; Ngo, Jeremy; Dunn, John C

2018-02-01

Three-experiments examined the number of qualitatively different processing dimensions needed to account for inductive and deductive reasoning. In each study, participants were presented with arguments that varied in logical validity and consistency with background knowledge (believability), and evaluated them according to deductive criteria (whether the conclusion was necessarily true given the premises) or inductive criteria (whether the conclusion was plausible given the premises). We examined factors including working memory load (Experiments 1 and 2), individual working memory capacity (Experiments 1 and 2), and decision time (Experiment 3), which according to dual-processing theories, modulate the contribution of heuristic and analytic processes to reasoning. A number of empirical dissociations were found. Argument validity affected deduction more than induction. Argument believability affected induction more than deduction. Lower working memory capacity reduced sensitivity to argument validity and increased sensitivity to argument believability, especially under induction instructions. Reduced decision time led to decreased sensitivity to argument validity. State-trace analyses of each experiment, however, found that only a single underlying dimension was required to explain patterns of inductive and deductive judgments. These results show that the dissociations, which have traditionally been seen as supporting dual-processing models of reasoning, are consistent with a single-process model that assumes a common evidentiary scale for induction and deduction. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The possible modifications of the Hisse model for pure LANDSAT agricultural data

NASA Technical Reports Server (NTRS)

Peters, C.

1982-01-01

An idea, due to A. Feiveson, is presented for relaxing the assumption of class conditional independence of LANDSAT spectral measurements within the same patch (field). Theoretical arguments are given which show that any significant refinement of the model beyond Feiveson's proposal will not allow the reduction, essential to HISSE, of the pure data to patch summary statistics. A slight alteration of the new model is shown to be a reasonable approximation to the model which describes pure data elements from the same patch as jointly Guassian with a covariance function which exhibits exponential decay with respect to spatial separation.

The possible modifications of the HISSE model for pure LANDSAT agricultural data

NASA Technical Reports Server (NTRS)

Peters, C.

1981-01-01

A method for relaxing the assumption of class conditional independence of LANDSAT spectral measurements within the same patch (field) is discussed. Theoretical arguments are given which show that any significant refinement of the model beyond this proposal will not allow the reduction, essential to HISSE, of the pure data to patch summary statistics. A slight alteration of the new model is shown to be a reasonable approximation to the model which describes pure data elements from the same patch as jointly Gaussian with a covariance function which exhibits exponential decay with respect to spatial separation.

Applying the Technology Acceptance Model and flow theory to Cyworld user behavior: implication of the Web2.0 user acceptance.

PubMed

Shin, Dong-Hee; Kim, Won-Yong; Kim, Won-Young

2008-06-01

This study explores attitudinal and behavioral patterns when using Cyworld by adopting an expanded Technology Acceptance Model (TAM). A model for Cyworld acceptance is used to examine how various factors modified from the TAM influence acceptance and its antecedents. This model is examined through an empirical study involving Cyworld users using structural equation modeling techniques. The model shows reasonably good measurement properties and the constructs are validated. The results not only confirm the model but also reveal general factors applicable to Web2.0. A set of constructs in the model can be the Web2.0-specific factors, playing as enhancing factor to attitudes and intention.

Health, Supportive Environments, and the Reasonable Person Model

Treesearch

Stephen Kaplan; Rachel Kaplan

2003-01-01

The Reasonable Person Model is a conceptual framework that links environmental factors with human behavior. People are more reasonable, cooperative, helpful, and satisfied when the environment supports their basic informational needs. The same environmental supports are important factors in enhancing human health. We use this framework to identify the informational...

The Child as Econometrician: A Rational Model of Preference Understanding in Children

PubMed Central

Lucas, Christopher G.; Griffiths, Thomas L.; Xu, Fei; Fawcett, Christine; Gopnik, Alison; Kushnir, Tamar; Markson, Lori; Hu, Jane

2014-01-01

Recent work has shown that young children can learn about preferences by observing the choices and emotional reactions of other people, but there is no unified account of how this learning occurs. We show that a rational model, built on ideas from economics and computer science, explains the behavior of children in several experiments, and offers new predictions as well. First, we demonstrate that when children use statistical information to learn about preferences, their inferences match the predictions of a simple econometric model. Next, we show that this same model can explain children's ability to learn that other people have preferences similar to or different from their own and use that knowledge to reason about the desirability of hidden objects. Finally, we use the model to explain a developmental shift in preference understanding. PMID:24667309

The child as econometrician: a rational model of preference understanding in children.

PubMed

Lucas, Christopher G; Griffiths, Thomas L; Xu, Fei; Fawcett, Christine; Gopnik, Alison; Kushnir, Tamar; Markson, Lori; Hu, Jane

2014-01-01

Recent work has shown that young children can learn about preferences by observing the choices and emotional reactions of other people, but there is no unified account of how this learning occurs. We show that a rational model, built on ideas from economics and computer science, explains the behavior of children in several experiments, and offers new predictions as well. First, we demonstrate that when children use statistical information to learn about preferences, their inferences match the predictions of a simple econometric model. Next, we show that this same model can explain children's ability to learn that other people have preferences similar to or different from their own and use that knowledge to reason about the desirability of hidden objects. Finally, we use the model to explain a developmental shift in preference understanding.

Information Management for Unmanned Systems: Combining DL-Reasoning with Publish/Subscribe

NASA Astrophysics Data System (ADS)

Moser, Herwig; Reichelt, Toni; Oswald, Norbert; Förster, Stefan

Sharing capabilities and information between collaborating entities by using modem information- and communication-technology is a core principle in complex distributed civil or military mission scenarios. Previous work proved the suitability of Service-oriented Architectures for modelling and sharing the participating entities' capabilities. Albeit providing a satisfactory model for capabilities sharing, pure service-orientation curtails expressiveness for information exchange as opposed to dedicated data-centric communication principles. In this paper we introduce an Information Management System which combines OWL-Ontologies and automated reasoning with Publish/Subscribe-Systems, providing for a shared but decoupled data model. While confirming existing related research results, we emphasise the novel application and lack of practical experience of using Semantic Web technologies in areas other than originally intended. That is, aiding decision support and software design in the context of a mission scenario for an unmanned system. Experiments within a complex simulation environment show the immediate benefits of a semantic information-management and -dissemination platform: Clear separation of concerns in code and data model, increased service re-usability and extensibility as well as regulation of data flow and respective system behaviour through declarative rules.

Predicting airborne particle deposition by a modified Markov chain model for fast estimation of potential contaminant spread

NASA Astrophysics Data System (ADS)

Mei, Xiong; Gong, Guangcai

2018-07-01

As potential carriers of hazardous pollutants, airborne particles may deposit onto surfaces due to gravitational settling. A modified Markov chain model to predict gravity induced particle dispersion and deposition is proposed in the paper. The gravity force is considered as a dominant weighting factor to adjust the State Transfer Matrix, which represents the probabilities of the change of particle spatial distributions between consecutive time steps within an enclosure. The model performance has been further validated by particle deposition in a ventilation chamber and a horizontal turbulent duct flow in pre-existing literatures. Both the proportion of deposited particles and the dimensionless deposition velocity are adopted to characterize the validation results. Comparisons between our simulated results and the experimental data from literatures show reasonable accuracy. Moreover, it is also found that the dimensionless deposition velocity can be remarkably influenced by particle size and stream-wise velocity in a typical horizontal flow. This study indicates that the proposed model can predict the gravity-dominated airborne particle deposition with reasonable accuracy and acceptable computing time.

Differences in Moral Judgment on Animal and Human Ethics Issues between University Students in Animal-Related, Human Medical and Arts Programs.

PubMed

Verrinder, Joy M; Ostini, Remo; Phillips, Clive J C

2016-01-01

Moral judgment in relation to animal ethics issues has rarely been investigated. Among the research that has been conducted, studies of veterinary students have shown greater use of reasoning based on universal principles for animal than human ethics issues. This study aimed to identify if this was unique to students of veterinary and other animal-related professions. The moral reasoning of first year students of veterinary medicine, veterinary technology, and production animal science was compared with that of students in non-animal related disciplines of human medicine and arts. All students (n = 531) completed a moral reasoning test, the VetDIT, with animal and human scenarios. When compared with reasoning on human ethics issues, the combined group of students evaluating animal ethics issues showed higher levels of Universal Principles reasoning, lower levels of Personal Interest reasoning and similar levels of Maintaining Norms reasoning. Arts students showed more personal interest reasoning than students in most animal-related programs on both animal and human ethics issues, and less norms-based reasoning on animal ethics issues. Medical students showed more norms-based reasoning on animal ethics issues than all of the animal-related groups. There were no differences in principled reasoning on animal ethics issues between program groups. This has implications for animal-related professions and education programs showing that students' preference for principled reasoning on animal ethics issues is not unique to animal-related disciplines, and highlighting the need to develop student (and professional) capacity to apply principled reasoning to address ethics issues in animal industries to reduce the risk of moral distress.

Differences in Moral Judgment on Animal and Human Ethics Issues between University Students in Animal-Related, Human Medical and Arts Programs

PubMed Central

Verrinder, Joy M.; Ostini, Remo; Phillips, Clive J. C.

2016-01-01

Moral judgment in relation to animal ethics issues has rarely been investigated. Among the research that has been conducted, studies of veterinary students have shown greater use of reasoning based on universal principles for animal than human ethics issues. This study aimed to identify if this was unique to students of veterinary and other animal-related professions. The moral reasoning of first year students of veterinary medicine, veterinary technology, and production animal science was compared with that of students in non-animal related disciplines of human medicine and arts. All students (n = 531) completed a moral reasoning test, the VetDIT, with animal and human scenarios. When compared with reasoning on human ethics issues, the combined group of students evaluating animal ethics issues showed higher levels of Universal Principles reasoning, lower levels of Personal Interest reasoning and similar levels of Maintaining Norms reasoning. Arts students showed more personal interest reasoning than students in most animal-related programs on both animal and human ethics issues, and less norms-based reasoning on animal ethics issues. Medical students showed more norms-based reasoning on animal ethics issues than all of the animal-related groups. There were no differences in principled reasoning on animal ethics issues between program groups. This has implications for animal-related professions and education programs showing that students’ preference for principled reasoning on animal ethics issues is not unique to animal-related disciplines, and highlighting the need to develop student (and professional) capacity to apply principled reasoning to address ethics issues in animal industries to reduce the risk of moral distress. PMID:26934582

Highly specific reasons for nonadherence to antiretroviral therapy: results from the German adherence study.

PubMed

Boretzki, Johanna; Wolf, Eva; Wiese, Carmen; Noe, Sebastian; Balogh, Annamaria; Meurer, Anja; Krznaric, Ivanka; Zink, Alexander; Lersch, Christian; Spinner, Christoph D

2017-01-01

Reasons for and frequency of nonadherence to antiretroviral therapy (ART) may have changed due to pharmacological improvements. In addition, the importance of known non-pharmacologic reasons for nonadherence is unclear. We performed a cross-sectional, noninterventional, multicenter study to identify current reasons for nonadherence. Patients were categorized by physicians into the following adherence groups: good, unstable, or poor adherence. Co-variables of interest included age, sex, time since HIV diagnosis, ART duration, current ART regimen, HIV transmission route, comorbidity, HIV-1 RNA viral load (VL), and CD4 cell count. Patients self-reported the number of missed doses and provided their specific reasons for nonadherent behavior. Statistical analyses were performed using Fisher's extended exact test, Kruskal-Wallis test, and logistic regression models. Our study assessed 215 participants with good (n=162), unstable (n=36), and poor adherence (n=17). Compared to patients with good adherence, patients with unstable and poor adherence reported more often to have missed at least one dose during the last week (good 11% vs unstable 47% vs poor 63%, p <0.001). Physicians' adherence assessment was concordant with patients' self-reports of missed doses during the last week (no vs one or more) in 81% cases. Similarly, we found a strong association of physicians' assessment with viral suppression. Logistic regression analysis showed that "reduced adherence" - defined as unstable or poor - was significantly associated with patients <30 years old, intravenous drug use, history of acquired immune deficiency syndrome (AIDS), and psychiatric disorders ( p <0.05). Univariate analyses showed that specific reasons, such as questioning the efficacy/dosing of ART, HIV stigma, interactive toxicity beliefs regarding alcohol and/or party drugs, and dissatisfaction with regimen complexity, correlated with unstable or poor adherence ( p <0.05). Identification of factors associated with poor adherence helps in identifying patients with a higher risk for nonadherence. Reasons for nonadherence should be directly addressed in every patient, because they are common and constitute possible adherence intervention points.

The use of the bi-factor model to test the uni-dimensionality of a battery of reasoning tests.

PubMed

Primi, Ricardo; Rocha da Silva, Marjorie Cristina; Rodrigues, Priscila; Muniz, Monalisa; Almeida, Leandro S

2013-02-01

The Battery of Reasoning Tests 5 (BPR-5) aims to assess the reasoning ability of individuals, using sub-tests with different formats and contents that require basic processes of inductive and deductive reasoning for their resolution. The BPR has three sequential forms: BPR-5i (for children from first to fifth grade), BPR-5 - Form A (for children from sixth to eighth grade) and BPR-5 - form B (for high school and undergraduate students). The present study analysed 412 questionnaires concerning BPR-5i, 603 questionnaires concerning BPR-5 - Form A and 1748 questionnaires concerning BPR-5 - Form B. The main goal was to test the uni-dimensionality of the battery and its tests in relation to items using the bi-factor model. Results suggest that the g factor loadings (extracted by the uni-dimensional model) do not change when the data is adjusted for a more flexible multi-factor model (bi-factor model). A general reasoning factor underlying different contents items is supported.

Physical Vapor Transport of Mercurous Chloride Crystals: Design of a Microgravity Experiment

NASA Technical Reports Server (NTRS)

Duval, W, M. B.; Singh, N. B.; Glicksman, M. E.

1997-01-01

Flow field characteristics predicted from a computational model show that the dynamical state of the flow, for practical crystal growth conditions of mercurous chloride, can range from steady to unsteady. Evidence that the flow field can be strongly dominated by convection for ground-based conditions is provided by the prediction of asymmetric velocity profiles bv the model which show reasonable agreement with laser Doppler velocimetry experiments in both magnitude and planform. Unsteady flow is shown to be correlated with a degradation of crystal quality as quantified by light scattering pattern measurements, A microgravity experiment is designed to show that an experiment performed with parameters which yield an unsteady flow becomes steady (diffusive-advective) in a microgravity environment of 10(exp -3) g(sub 0) as predicted by the model, and hence yields crystals with optimal quality.

Conceptual modelling to predict unobserved system states - the case of groundwater flooding in the UK Chalk

NASA Astrophysics Data System (ADS)

Hartmann, A. J.; Ireson, A. M.

2017-12-01

Chalk aquifers represent an important source of drinking water in the UK. Due to its fractured-porous structure, Chalk aquifers are characterized by highly dynamic groundwater fluctuations that enhance the risk of groundwater flooding. The risk of groundwater flooding can be assessed by physically-based groundwater models. But for reliable results, a-priori information about the distribution of hydraulic conductivities and porosities is necessary, which is often not available. For that reason, conceptual simulation models are often used to predict groundwater behaviour. They commonly require calibration by historic groundwater observations. Consequently, their prediction performance may reduce significantly, when it comes to system states that did not occur within the calibration time series. In this study, we calibrate a conceptual model to the observed groundwater level observations at several locations within a Chalk system in Southern England. During the calibration period, no groundwater flooding occurred. We then apply our model to predict the groundwater dynamics of the system at a time that includes a groundwater flooding event. We show that the calibrated model provides reasonable predictions before and after the flooding event but it over-estimates groundwater levels during the event. After modifying the model structure to include topographic information, the model is capable of prediction the groundwater flooding event even though groundwater flooding never occurred in the calibration period. Although straight forward, our approach shows how conceptual process-based models can be applied to predict system states and dynamics that did not occur in the calibration period. We believe such an approach can be transferred to similar cases, especially to regions where rainfall intensities are expected to trigger processes and system states that may have not yet been observed.

Statistical Modelling for Dropped Out School Children (DOSC) in East Nusa Tenggara Province Indonesia

NASA Astrophysics Data System (ADS)

Guntur, R. D.; Lobo, M.

2017-02-01

A research has been carried out to investigate the characteristics of reasons for DOSC and to determine the statistical model explaining factors which influence on the DOSC in the age group 7 - 18 years in East Nusa Tenggara (ENT) Province. Primary data of out of school children had been collected throughout interviews using prepared questionnaires in three selected districts. Data was then analysed using descriptive and logistic regression method. The analysis shows that from the 341 samples, there were 194DOSC. The majority of them were males, lived in the countryside, had farmer parents, had family size of 5, and had mothers with only primary education level. The main reasons of children to drop out from the primary and junior education levels were the inabilities of paying the school fees and the willingness to work in the farms to help their parents. For senior education level, it was because of the unaffordable school tuitions and no desire of children in having good education. Both partial and simultaneous parameter tests in the logistic regression model show that children who lived in countryside, from poor families, males were the three factors that significantly affected the number of DOSC in the group age with odds ratio values 2.48; 2.37; 1.97 respectively.

Routes to failure: analysis of 41 civil aviation accidents from the Republic of China using the human factors analysis and classification system.

PubMed

Li, Wen-Chin; Harris, Don; Yu, Chung-San

2008-03-01

The human factors analysis and classification system (HFACS) is based upon Reason's organizational model of human error. HFACS was developed as an analytical framework for the investigation of the role of human error in aviation accidents, however, there is little empirical work formally describing the relationship between the components in the model. This research analyses 41 civil aviation accidents occurring to aircraft registered in the Republic of China (ROC) between 1999 and 2006 using the HFACS framework. The results show statistically significant relationships between errors at the operational level and organizational inadequacies at both the immediately adjacent level (preconditions for unsafe acts) and higher levels in the organization (unsafe supervision and organizational influences). The pattern of the 'routes to failure' observed in the data from this analysis of civil aircraft accidents show great similarities to that observed in the analysis of military accidents. This research lends further support to Reason's model that suggests that active failures are promoted by latent conditions in the organization. Statistical relationships linking fallible decisions in upper management levels were found to directly affect supervisory practices, thereby creating the psychological preconditions for unsafe acts and hence indirectly impairing the performance of pilots, ultimately leading to accidents.

Discrete virus infection model of hepatitis B virus.

PubMed

Zhang, Pengfei; Min, Lequan; Pian, Jianwei

2015-01-01

In 1996 Nowak and his colleagues proposed a differential equation virus infection model, which has been widely applied in the study for the dynamics of hepatitis B virus (HBV) infection. Biological dynamics may be described more practically by discrete events rather than continuous ones. Using discrete systems to describe biological dynamics should be reasonable. Based on one revised Nowak et al's virus infection model, this study introduces a discrete virus infection model (DVIM). Two equilibriums of this model, E1 and E2, represents infection free and infection persistent, respectively. Similar to the case of the basic virus infection model, this study deduces a basic virus reproductive number R0 independing on the number of total cells of an infected target organ. A proposed theorem proves that if the basic virus reproductive number R0<1 then the virus free equilibrium E1 is locally stable. The DVIM is more reasonable than an abstract discrete susceptible-infected-recovered model (SIRS) whose basic virus reproductive number R0 is relevant to the number of total cells of the infected target organ. As an application, this study models the clinic HBV DNA data of a patient who was accepted via anti-HBV infection therapy with drug lamivudine. The results show that the numerical simulation is good in agreement with the clinic data.

Constraint reasoning in deep biomedical models.

PubMed

Cruz, Jorge; Barahona, Pedro

2005-05-01

Deep biomedical models are often expressed by means of differential equations. Despite their expressive power, they are difficult to reason about and make decisions, given their non-linearity and the important effects that the uncertainty on data may cause. The objective of this work is to propose a constraint reasoning framework to support safe decisions based on deep biomedical models. The methods used in our approach include the generic constraint propagation techniques for reducing the bounds of uncertainty of the numerical variables complemented with new constraint reasoning techniques that we developed to handle differential equations. The results of our approach are illustrated in biomedical models for the diagnosis of diabetes, tuning of drug design and epidemiology where it was a valuable decision-supporting tool notwithstanding the uncertainty on data. The main conclusion that follows from the results is that, in biomedical decision support, constraint reasoning may be a worthwhile alternative to traditional simulation methods, especially when safe decisions are required.

Analysis of undergraduate students' conceptual models of a complex biological system across a diverse body of learners

NASA Astrophysics Data System (ADS)

Dirnbeck, Matthew R.

Biological systems pose a challenge both for learners and teachers because they are complex systems mediated by feedback loops; networks of cause-effect relationships; and non-linear, hierarchical, and emergent properties. Teachers and scientists routinely use models to communicate ideas about complex systems. Model-based pedagogies engage students in model construction as a means of practicing higher-order reasoning skills. One such modeling paradigm describes systems in terms of their structures, behaviors, and functions (SBF). The SBF framework is a simple modeling language that has been used to teach about complex biological systems. Here, we used student-generated SBF models to assess students' causal reasoning in the context of a novel biological problem on an exam. We compared students' performance on the modeling problem, their performance on a set of knowledge/comprehension questions, and their performance on a set of scientific reasoning questions. We found that students who performed well on knowledge and understanding questions also constructed more networked, higher quality models. Previous studies have shown that learners' mental maps increase in complexity with increased expertise. We wanted to investigate if biology students with varying levels of training in biology showed a similar pattern when constructing system models. In a pilot study, we administered the same modeling problem to two additional groups of students: 1) an animal physiology course for students pursuing a major in biology (n=37) and 2) an exercise physiology course for non-majors (n=27). We found that there was no significant difference in model organization across the three student populations, but there was a significant difference in the ability to represent function between the three populations. Between the three groups the non-majors had the lowest function scores, the introductory majors had the middle function scores, and the upper division majors had the highest function scores.

Conditional solvation thermodynamics of isoleucine in model peptides and the limitations of the group-transfer model.

PubMed

Tomar, Dheeraj S; Weber, Valéry; Pettitt, B Montgomery; Asthagiri, D

2014-04-17

The hydration thermodynamics of the amino acid X relative to the reference G (glycine) or the hydration thermodynamics of a small-molecule analog of the side chain of X is often used to model the contribution of X to protein stability and solution thermodynamics. We consider the reasons for successes and limitations of this approach by calculating and comparing the conditional excess free energy, enthalpy, and entropy of hydration of the isoleucine side chain in zwitterionic isoleucine, in extended penta-peptides, and in helical deca-peptides. Butane in gauche conformation serves as a small-molecule analog for the isoleucine side chain. Parsing the hydrophobic and hydrophilic contributions to hydration for the side chain shows that both of these aspects of hydration are context-sensitive. Furthermore, analyzing the solute-solvent interaction contribution to the conditional excess enthalpy of the side chain shows that what is nominally considered a property of the side chain includes entirely nonobvious contributions of the background. The context-sensitivity of hydrophobic and hydrophilic hydration and the conflation of background contributions with energetics attributed to the side chain limit the ability of a single scaling factor, such as the fractional solvent exposure of the group in the protein, to map the component energetic contributions of the model-compound data to their value in the protein. But ignoring the origin of cancellations in the underlying components the group-transfer model may appear to provide a reasonable estimate of the free energy for a given error tolerance.

Logic as Marr's Computational Level: Four Case Studies.

PubMed

Baggio, Giosuè; van Lambalgen, Michiel; Hagoort, Peter

2015-04-01

We sketch four applications of Marr's levels-of-analysis methodology to the relations between logic and experimental data in the cognitive neuroscience of language and reasoning. The first part of the paper illustrates the explanatory power of computational level theories based on logic. We show that a Bayesian treatment of the suppression task in reasoning with conditionals is ruled out by EEG data, supporting instead an analysis based on defeasible logic. Further, we describe how results from an EEG study on temporal prepositions can be reanalyzed using formal semantics, addressing a potential confound. The second part of the article demonstrates the predictive power of logical theories drawing on EEG data on processing progressive constructions and on behavioral data on conditional reasoning in people with autism. Logical theories can constrain processing hypotheses all the way down to neurophysiology, and conversely neuroscience data can guide the selection of alternative computational level models of cognition. Copyright © 2014 Cognitive Science Society, Inc.

Follow the heart or the head? The interactive influence model of emotion and cognition

PubMed Central

Luo, Jiayi; Yu, Rongjun

2015-01-01

The experience of emotion has a powerful influence on daily-life decision making. Following Plato’s description of emotion and reason as two horses pulling us in opposite directions, modern dual-system models of decision making endorse the antagonism between reason and emotion. Decision making is perceived as the competition between an emotion system that is automatic but prone to error and a reason system that is slow but rational. The reason system (in “the head”) reins in our impulses (from “the heart”) and overrides our snap judgments. However, from Darwin’s evolutionary perspective, emotion is adaptive, guiding us to make sound decisions in uncertainty. Here, drawing findings from behavioral economics and neuroeconomics, we provide a new model, labeled “The interactive influence model of emotion and cognition,” to elaborate the relationship of emotion and reason in decision making. Specifically, in our model, we identify factors that determine when emotions override reason and delineate the type of contexts in which emotions help or hurt decision making. We then illustrate how cognition modulates emotion and how they cooperate to affect decision making. PMID:25999889

MODELING THE HARD TeV SPECTRA OF BLAZARS 1ES 0229+200 AND 3C 66A WITH AN INTERNAL ABSORPTION SCENARIO

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

Zacharopoulou, O.; Aharonian, F. A.; Khangulyan, D.

2011-09-10

We study the applicability of the idea of internal absorption of {gamma}-rays produced through synchrotron radiation of ultrarelativistic protons in highly magnetized blobs to 1ES 0229+200 and 3C 66A, the two TeV blazars which show unusually hard intrinsic {gamma}-ray spectra after being corrected for the intergalactic absorption. We show that for certain combinations of reasonable model parameters, even with quite modest energy requirements, the scenario allows a self-consistent explanation of the non-thermal emission of these objects in the keV, GeV, and TeV energy bands.

Complex groundwater flow systems as traveling agent models

PubMed Central

Padilla, Pablo; Escolero, Oscar; González, Tomas; Morales-Casique, Eric; Osorio-Olvera, Luis

2014-01-01

Analyzing field data from pumping tests, we show that as with many other natural phenomena, groundwater flow exhibits complex dynamics described by 1/f power spectrum. This result is theoretically studied within an agent perspective. Using a traveling agent model, we prove that this statistical behavior emerges when the medium is complex. Some heuristic reasoning is provided to justify both spatial and dynamic complexity, as the result of the superposition of an infinite number of stochastic processes. Even more, we show that this implies that non-Kolmogorovian probability is needed for its study, and provide a set of new partial differential equations for groundwater flow. PMID:25337455

Monte Carlo simulation of Ray-Scan 64 PET system and performance evaluation using GATE toolkit

NASA Astrophysics Data System (ADS)

Li, Suying; Zhang, Qiushi; Vuletic, Ivan; Xie, Zhaoheng; Yang, Kun; Ren, Qiushi

2017-02-01

In this study, we aimed to develop a GATE model for the simulation of Ray-Scan 64 PET scanner and model its performance characteristics. A detailed implementation of system geometry and physical process were included in the simulation model. Then we modeled the performance characteristics of Ray-Scan 64 PET system for the first time, based on National Electrical Manufacturers Association (NEMA) NU-2 2007 protocols and validated the model against experimental measurement, including spatial resolution, sensitivity, counting rates and noise equivalent count rate (NECR). Moreover, an accurate dead time module was investigated to simulate the counting rate performance. Overall results showed reasonable agreement between simulation and experimental data. The validation results showed the reliability and feasibility of the GATE model to evaluate major performance of Ray-Scan 64 PET system. It provided a useful tool for a wide range of research applications.

Modeling and analysis of Galfenol cantilever vibration energy harvester with nonlinear magnetic force

NASA Astrophysics Data System (ADS)

Cao, Shuying; Sun, Shuaishuai; Zheng, Jiaju; Wang, Bowen; Wan, Lili; Pan, Ruzheng; Zhao, Ran; Zhang, Changgeng

2018-05-01

Galfenol traditional cantilever energy harvesters (TCEHs) have bigger electrical output only at resonance and exhibit nonlinear mechanical-magnetic-electric coupled (NMMEC) behaviors. To increase low-frequency broadband performances of a TCEH, an improved CEH (ICEH) with magnetic repulsive force is studied. Based on the magnetic dipole model, the nonlinear model of material, the Faraday law and the dynamic principle, a lumped parameter NMMEC model of the devices is established. Comparisons between the calculated and measured results show that the proposed model can provide reasonable data trends of TCEH under acceleration, bias field and different loads. Simulated results show that ICEH exhibits low-frequency resonant, hard spring and bistable behaviors, thus can harvest more low-frequency broadband vibration energy than TCEH, and can elicit snap-through and generate higher voltage even under weak noise. The proposed structure and model are useful for improving performances of the devices.

Sexual Response Models: Toward a More Flexible Pattern of Women's Sexuality.

PubMed

Ferenidou, Fotini; Kirana, Paraskevi-Sofia; Fokas, Konstantinos; Hatzichristou, Dimitrios; Athanasiadis, Loukas

2016-09-01

Recent research suggests that none of the current theoretical models can sufficiently describe women's sexual response, because several factors and situations can influence this. To explore individual variations of a sexual model that describes women's sexual responses and to assess the association of endorsement of that model with sexual dysfunctions and reasons to engage in sexual activity. A sample of 157 randomly selected hospital employees completed self-administered questionnaires. Two models were developed: one merged the Master and Johnson model with the Kaplan model (linear) and the other was the Basson model (circular). Sexual function was evaluated by the Female Sexual Function Index and the Brief Sexual Symptom Checklist for Women. The Reasons for Having Sex Questionnaire was administered to investigate the reasons for which women have sex. Women reported that their current sexual experiences were at times consistent with the linear and circular models (66.9%), only the linear model (27%), only the circular model (5.4%), and neither model (0.7%). When the groups were reconfigured to the group that endorsed more than 5 of 10 sexual experiences, 64.3% of women endorsed the linear model, 20.4% chose the linear and circular models, 14.6% chose the circular model, and 0.7% selected neither. The Female Sexual Function Index, demographic factors, having sex for insecurity reasons, and sexual satisfaction correlated with the endorsement of a sexual response model. When these factors were entered in a stepwise logistic regression analysis, only the Female Sexual Function Index and having sex for insecurity reasons maintained a significant association with the sexual response model. The present study emphasizes the heterogeneity of female sexuality, with most of the sample reporting alternating between the linear and circular models. Sexual dysfunctions and having sex for insecurity reasons were associated with the Basson model. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Stimulating Scientific Reasoning with Drawing-Based Modeling

ERIC Educational Resources Information Center

Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

2018-01-01

We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each…

Characteristics of Hijacked Journals and Predatory Publishers: Our Observations in the Academic World.

PubMed

Dadkhah, Mehdi; Maliszewski, Tomasz; Jazi, Mohammad Davarpanah

2016-06-01

The academic world today includes hijacked journals and predatory publishers that operate based on a 'pay and publish' model and function for financial reasons only. Here we present lesser known aspects and practices of these journals to researchers, showing the core of the problem. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nurses' intention to leave: critically analyse the theory of reasoned action and organizational commitment model.

PubMed

Liou, Shwu-Ru

2009-01-01

To systematically analyse the Organizational Commitment model and Theory of Reasoned Action and determine concepts that can better explain nurses' intention to leave their job. The Organizational Commitment model and Theory of Reasoned Action have been proposed and applied to understand intention to leave and turnover behaviour, which are major contributors to nursing shortage. However, the appropriateness of applying these two models in nursing was not analysed. Three main criteria of a useful model were used for the analysis: consistency in the use of concepts, testability and predictability. Both theories use concepts consistently. Concepts in the Theory of Reasoned Action are defined broadly whereas they are operationally defined in the Organizational Commitment model. Predictability of the Theory of Reasoned Action is questionable whereas the Organizational Commitment model can be applied to predict intention to leave. A model was proposed based on this analysis. Organizational commitment, intention to leave, work experiences, job characteristics and personal characteristics can be concepts for predicting nurses' intention to leave. Nursing managers may consider nurses' personal characteristics and experiences to increase their organizational commitment and enhance their intention to stay. Empirical studies are needed to test and cross-validate the re-synthesized model for nurses' intention to leave their job.

Intuitive Logic Revisited: New Data and a Bayesian Mixed Model Meta-Analysis

PubMed Central

Singmann, Henrik; Klauer, Karl Christoph; Kellen, David

2014-01-01

Recent research on syllogistic reasoning suggests that the logical status (valid vs. invalid) of even difficult syllogisms can be intuitively detected via differences in conceptual fluency between logically valid and invalid syllogisms when participants are asked to rate how much they like a conclusion following from a syllogism (Morsanyi & Handley, 2012). These claims of an intuitive logic are at odds with most theories on syllogistic reasoning which posit that detecting the logical status of difficult syllogisms requires effortful and deliberate cognitive processes. We present new data replicating the effects reported by Morsanyi and Handley, but show that this effect is eliminated when controlling for a possible confound in terms of conclusion content. Additionally, we reanalyze three studies () without this confound with a Bayesian mixed model meta-analysis (i.e., controlling for participant and item effects) which provides evidence for the null-hypothesis and against Morsanyi and Handley's claim. PMID:24755777

A quantitative examination of explanations for reasons for internet nonuse.

PubMed

Helsper, Ellen J; Reisdorf, Bianca C

2013-02-01

This article investigates patterns of reasons for digital disengagement of British adults. It adds a psychological dimension to research that is mostly sociological in nature in trying to separate out explanations for disengaging from the Internet by choice or by forced exclusion. The analysis of a nationally representative survey shows differences between the number of reasons and the most important reasons among different sociodemographic groups, but also among individuals with different psychological profiles. The findings suggest that ex- and nonusers do not have one simple reason for nonuse, but a multifaceted range of reasons, which often represent disadvantages at several levels. The range of often mentioned reasons, moreover, shows that motivations for disengagement cannot be measured by means of the most important reason, but that all reasons have to be taken into account and looked at concertedly.

Testing process predictions of models of risky choice: a quantitative model comparison approach

PubMed Central

Pachur, Thorsten; Hertwig, Ralph; Gigerenzer, Gerd; Brandstätter, Eduard

2013-01-01

This article presents a quantitative model comparison contrasting the process predictions of two prominent views on risky choice. One view assumes a trade-off between probabilities and outcomes (or non-linear functions thereof) and the separate evaluation of risky options (expectation models). Another view assumes that risky choice is based on comparative evaluation, limited search, aspiration levels, and the forgoing of trade-offs (heuristic models). We derived quantitative process predictions for a generic expectation model and for a specific heuristic model, namely the priority heuristic (Brandstätter et al., 2006), and tested them in two experiments. The focus was on two key features of the cognitive process: acquisition frequencies (i.e., how frequently individual reasons are looked up) and direction of search (i.e., gamble-wise vs. reason-wise). In Experiment 1, the priority heuristic predicted direction of search better than the expectation model (although neither model predicted the acquisition process perfectly); acquisition frequencies, however, were inconsistent with both models. Additional analyses revealed that these frequencies were primarily a function of what Rubinstein (1988) called “similarity.” In Experiment 2, the quantitative model comparison approach showed that people seemed to rely more on the priority heuristic in difficult problems, but to make more trade-offs in easy problems. This finding suggests that risky choice may be based on a mental toolbox of strategies. PMID:24151472

An assessment of precipitation and surface air temperature over China by regional climate models

NASA Astrophysics Data System (ADS)

Wang, Xueyuan; Tang, Jianping; Niu, Xiaorui; Wang, Shuyu

2016-12-01

An analysis of a 20-year summer time simulation of present-day climate (1989-2008) over China using four regional climate models coupled with different land surface models is carried out. The climatic means, interannual variability, linear trends, and extremes are examined, with focus on precipitation and near surface air temperature. The models are able to reproduce the basic features of the observed summer mean precipitation and temperature over China and the regional detail due to topographic forcing. Overall, the model performance is better for temperature than that of precipitation. The models reasonably grasp the major anomalies and standard deviations over China and the five subregions studied. The models generally reproduce the spatial pattern of high interannual variability over wet regions, and low variability over the dry regions. The models also capture well the variable temperature gradient increase to the north by latitude. Both the observed and simulated linear trend of precipitation shows a drying tendency over the Yangtze River Basin and wetting over South China. The models capture well the relatively small temperature trends in large areas of China. The models reasonably simulate the characteristics of extreme precipitation indices of heavy rain days and heavy precipitation fraction. Most of the models also performed well in capturing both the sign and magnitude of the daily maximum and minimum temperatures over China.

A meta-model analysis of a finite element simulation for defining poroelastic properties of intervertebral discs.

PubMed

Nikkhoo, Mohammad; Hsu, Yu-Chun; Haghpanahi, Mohammad; Parnianpour, Mohamad; Wang, Jaw-Lin

2013-06-01

Finite element analysis is an effective tool to evaluate the material properties of living tissue. For an interactive optimization procedure, the finite element analysis usually needs many simulations to reach a reasonable solution. The meta-model analysis of finite element simulation can be used to reduce the computation of a structure with complex geometry or a material with composite constitutive equations. The intervertebral disc is a complex, heterogeneous, and hydrated porous structure. A poroelastic finite element model can be used to observe the fluid transferring, pressure deviation, and other properties within the disc. Defining reasonable poroelastic material properties of the anulus fibrosus and nucleus pulposus is critical for the quality of the simulation. We developed a material property updating protocol, which is basically a fitting algorithm consisted of finite element simulations and a quadratic response surface regression. This protocol was used to find the material properties, such as the hydraulic permeability, elastic modulus, and Poisson's ratio, of intact and degenerated porcine discs. The results showed that the in vitro disc experimental deformations were well fitted with limited finite element simulations and a quadratic response surface regression. The comparison of material properties of intact and degenerated discs showed that the hydraulic permeability significantly decreased but Poisson's ratio significantly increased for the degenerated discs. This study shows that the developed protocol is efficient and effective in defining material properties of a complex structure such as the intervertebral disc.

Age-Related Changes in Associations Between Reasons for Alcohol Use and High-Intensity Drinking Across Young Adulthood.

PubMed

Patrick, Megan E; Evans-Polce, Rebecca; Kloska, Deborah D; Maggs, Jennifer L; Lanza, Stephanie T

2017-07-01

Analyses focus on whether self-reported reasons for drinking alcohol change in their associations with high-intensity drinking across the transition to adulthood. Self-report data on high-intensity drinking (10+ drinks) collected from the national Monitoring the Future study in 2005 to 2014 from those ages 18-26 were used (N = 2,664 [60% women] for all drinkers and 1,377 for heavy episodic [5+] drinkers; up to 6,541 person-waves). Time-varying effect modeling examined changes in the direction and magnitude of associations between eight reasons for drinking and high-intensity alcohol use across continuous age. Four reasons to drink showed quite stable associations with high-intensity drinking across age: drinking to get away from problems, to get high, to relax, and to sleep. Associations between two reasons and high-intensity drinking decreased with age: anger/frustration and to have a good time. The association between drinking because of boredom and high-intensity drinking increased with age. Drinking because it tastes good had a weak association with high-intensity drinking. Among heavy episodic drinkers, reasons for use also differentiated high-intensity drinking, with two exceptions: drinking to have a good time and to relax did not distinguish drinking 10+ drinks from drinking 5-9 drinks. Reasons for drinking are differentially associated with high-intensity drinking, compared with any other drinking and compared with lower intensity heavy drinking, across age during the transition to adulthood. Intervention programs seeking to mitigate alcohol-related harms should focus on reasons for use when they are the most developmentally salient.

Circulation and rainfall climatology of a 10-year (1979 - 1988) integration with the Goddard Laboratory for atmospheres general circulation model

NASA Technical Reports Server (NTRS)

Kim, J.-H.; Sud, Y. C.

1993-01-01

A 10-year (1979-1988) integration of Goddard Laboratory for Atmospheres (GLA) general circulation model (GCM) under Atmospheric Model Intercomparison Project (AMIP) is analyzed and compared with observation. The first momentum fields of circulation variables and also hydrological variables including precipitation, evaporation, and soil moisture are presented. Our goals are (1) to produce a benchmark documentation of the GLA GCM for future model improvements; (2) to examine systematic errors between the simulated and the observed circulation, precipitation, and hydrologic cycle; (3) to examine the interannual variability of the simulated atmosphere and compare it with observation; and (4) to examine the ability of the model to capture the major climate anomalies in response to events such as El Nino and La Nina. The 10-year mean seasonal and annual simulated circulation is quite reasonable compared to the analyzed circulation, except the polar regions and area of high orography. Precipitation over tropics are quite well simulated, and the signal of El Nino/La Nina episodes can be easily identified. The time series of evaporation and soil moisture in the 12 biomes of the biosphere also show reasonable patterns compared to the estimated evaporation and soil moisture.

Development of Constructivist Theory of Mind from Middle Childhood to Early Adulthood and Its Relation to Social Cognition and Behavior

PubMed Central

Weimer, Amy A.; Parault Dowds, Susan J.; Fabricius, William V.; Schwanenflugel, Paula J.; Suh, Go Woon

2016-01-01

Two studies examined the development of constructivist theory of mind (ToM) during late childhood and early adolescence. In Study 1 a new measure was developed to assess participants’ understanding of the interpretive and constructive processes embedded in memory, comprehension, attention, comparison, planning, and inference. Using this measure, Study 2 tested a mediational model in which prosocial reasoning about conflict mediated the relation between constructivist ToM and behavior problems in high school. Results showed that the onset of constructivist ToM occurs between late childhood and early adolescence, and that adolescents who have more advanced constructivist ToM have more prosocial reasoning about conflict, which in turn mediated the relation with fewer serious behavior problems in high school, after controlling for academic performance and sex. In both studies, females showed more advanced constructivist ToM than males in high school. PMID:27821294

Venous gas embolism after an open-water air dive and identical repetitive dive.

PubMed

Schellart, N A M; Sterk, W

2012-01-01

Decompression tables indicate that a repetitive dive to the same depth as a first dive should be shortened to obtain the same probability of occurrence of decompression sickness (pDCS). Repetition protocols are based on small numbers, a reason for re-examination. Since venous gas embolism (VGE) and pDCS are related, one would expect a higher bubble grade (BG) of VGE after the repetitive dive without reducing bottom time. BGs were determined in 28 divers after a first and an identical repetitive air dive of 40 minutes to 20 meters of sea water. Doppler BG scores were transformed to log number of bubbles/cm2 (logB) to allow numerical analysis. With a previously published model (Model2), pDCS was calculated for the first dive and for both dives together. From pDCS, theoretical logBs were estimated with a pDCS-to-logB model constructed from literature data. However, pDCS the second dive was provided using conditional probability. This was achieved in Model2 and indirectly via tissue saturations. The combination of both models shows a significant increase of logB after the second dive, whereas the measurements showed an unexpected lower logB. These differences between measurements and model expectations are significant (p-values < 0.01). A reason for this discrepancy is uncertain. The most likely speculation would be that the divers, who were relatively old, did not perform physical activity for some days before the first dive. Our data suggest that, wisely, the first dive after a period of no exercise should be performed conservatively, particularly for older divers.

More than just "plug-and-chug": Exploring how physics students make sense with equations

NASA Astrophysics Data System (ADS)

Kuo, Eric

Although a large part the Physics Education Research (PER) literature investigates students' conceptual understanding in physics, these investigations focus on qualitative, conceptual reasoning. Even in modeling expert problem solving, attention to conceptual understanding means a focus on initial qualitative analysis of the problem; the equations are typically conceived of as tools for "plug-and-chug" calculations. In this dissertation, I explore the ways that undergraduate physics students make conceptual sense of physics equations and the factors that support this type of reasoning through three separate studies. In the first study, I investigate how students' can understand physics equations intuitively through use of a particular class of cognitive elements, symbolic forms (Sherin, 2001). Additionally, I show how students leverage this intuitive, conceptual meaning of equations in problem solving. By doing so, these students avoid algorithmic manipulations, instead using a heuristic approach that leverages the equation in a conceptual argument. The second study asks the question why some students use symbolic forms and others don't. Although it is possible that students simply lack the knowledge required, I argue that this is not the only explanation. Rather, symbolic forms use is connected to particular epistemological stances, in-the-moment views on what kinds of knowledge and reasoning are appropriate in physics. Specifically, stances that value coherence between formal, mathematical knowledge and intuitive, conceptual knowledge are likely to support symbolic forms use. Through the case study of one student, I argue that both reasoning with equations and epistemological stances are dynamic, and that shifts in epistemological stance can produce shifts in whether symbolic forms are used to reason with equations. The third study expands the focus to what influences how students reason with equations across disciplinary problem contexts. In seeking to understand differences in how the same student reasons on two similar problems in calculus and physics, I show two factors, beyond the content or structure of the problems, that can help explain why reasoning on these two problems would be so different. This contributes to an understanding of what can support or impede transfer of content knowledge across disciplinary boundaries.

Chromospheric activity in open clusters

NASA Technical Reports Server (NTRS)

Pilger, E. J.

1987-01-01

Spectra of Ca II H and K are being taken for stars of similar mass in the Hyades, the Pleiades, and NGC 752. These spectra will be used to create indices of chromospheric activity on these stars. The dispersion in these indices will then be compared to model dispersions which take into account stellar inclination, position of active regions, and filling factor. Only a few observations have been made to date. These show that a high signal to noise is achievable over reasonable exposure times. Modeling has only just begun.

A Tri-part Model for Genetics Literacy: Exploring Undergraduate Student Reasoning About Authentic Genetics Dilemmas

NASA Astrophysics Data System (ADS)

Shea, Nicole A.; Duncan, Ravit Golan; Stephenson, Celeste

2015-08-01

Genetics literacy is becoming increasingly important as advancements in our application of genetic technologies such as stem cell research, cloning, and genetic screening become more prevalent. Very few studies examine how genetics literacy is applied when reasoning about authentic genetic dilemmas. However, there is evidence that situational features of a reasoning task may influence how students apply content knowledge as they generate and support arguments. Understanding how students apply content knowledge to reason about authentic and complex issues is important for considering instructional practices that best support student thinking and reasoning. In this conceptual report, we present a tri-part model for genetics literacy that embodies the relationships between content knowledge use, argumentation quality, and the role of situational features in reasoning to support genetics literacy. Using illustrative examples from an interview study with early career undergraduate students majoring in the biological sciences and late career undergraduate students majoring in genetics, we provide insights into undergraduate student reasoning about complex genetics issues and discuss implications for teaching and learning. We further discuss the need for research about how the tri-part model of genetics literacy can be used to explore students' thinking and reasoning abilities in genetics.

Model-Based Reasoning in the Physics Laboratory: Framework and Initial Results

ERIC Educational Resources Information Center

Zwickl, Benjamin M.; Hu, Dehui; Finkelstein, Noah; Lewandowski, H. J.

2015-01-01

We review and extend existing frameworks on modeling to develop a new framework that describes model-based reasoning in introductory and upper-division physics laboratories. Constructing and using models are core scientific practices that have gained significant attention within K-12 and higher education. Although modeling is a broadly applicable…

Conditional dissipation of scalars in homogeneous turbulence: Closure for MMC modelling

NASA Astrophysics Data System (ADS)

Wandel, Andrew P.

2013-08-01

While the mean and unconditional variance are to be predicted well by any reasonable turbulent combustion model, these are generally not sufficient for the accurate modelling of complex phenomena such as extinction/reignition. An additional criterion has been recently introduced: accurate modelling of the dissipation timescales associated with fluctuations of scalars about their conditional mean (conditional dissipation timescales). Analysis of Direct Numerical Simulation (DNS) results for a passive scalar shows that the conditional dissipation timescale is of the order of the integral timescale and smaller than the unconditional dissipation timescale. A model is proposed: the conditional dissipation timescale is proportional to the integral timescale. This model is used in Multiple Mapping Conditioning (MMC) modelling for a passive scalar case and a reactive scalar case, comparing to DNS results for both. The results show that this model improves the accuracy of MMC predictions so as to match the DNS results more closely using a relatively-coarse spatial resolution compared to other turbulent combustion models.

An exploratory study of proficient undergraduate Chemistry II students' application of Lewis's model

NASA Astrophysics Data System (ADS)

Lewis, Sumudu R.

This exploratory study was based on the assumption that proficiency in chemistry must not be determined exclusively on students' declarative and procedural knowledge, but it should be also described as the ability to use variety of reasoning strategies that enrich and diversify procedural methods. The study furthermore assumed that the ability to describe the structure of a molecule using Lewis's model and use it to predict its geometry as well as some of its properties is indicative of proficiency in the essential concepts of covalent bonding and molecule structure. The study therefore inquired into the reasoning methods and procedural techniques of proficient undergraduate Chemistry II students when solving problems, which require them to use Lewis's model. The research design included an original survey, designed by the researcher for this study, and two types of interviews, with students and course instructors. The purpose of the survey was two-fold. First and foremost, the survey provided a base for the student interview selection, and second it served as the foundation for the inquiry into the strategies the student use when solving survey problems. Twenty two students were interviewed over the course of the study. The interview with six instructors allowed to identify expected prior knowledge and skills, which the students should have acquired upon completion of the Chemistry I course. The data, including videos, audios, and photographs of the artifacts produced by students during the interviews, were organized and analyzed manually and using QSR NVivo 10. The research found and described the differences between proficient and non-proficient students' reasoning and procedural strategies when using Lewis's model to describe the structure of a molecule. One of the findings clearly showed that the proficient students used a variety of cues to reason, whereas other students used one memorized cue, or an algorithm, which often led to incorrect representations in cases where the algorithm cannot be applied. Additionally, the proficient students' understanding (i.e., representation, explanation and application) of the Valence Shell Electron-Pair Repulsion theory was accurate and precise, and they used the key terms in the correct context when explaining their reasoning. The results of this study can be of great importance to general chemistry and organic chemistry courses' instructors. This study identified students' baseline academic skills and abilities that lead to conceptual understanding of the essential concepts of covalent bonding and molecule structure, which instructors could use as a guide for developing instruction. Furthermore knowing the effective methods of reasoning the students use while applying Lewis's model, the instructors may be better informed and be able to better facilitate students' learning of Lewis' model and its application. Finally, the ideas and methods used in this study can be of value to chemistry education researchers to learn more about developing proficiency through reasoning methods in other chemistry concepts.

Verification of Orthogrid Finite Element Modeling Techniques

NASA Technical Reports Server (NTRS)

Steeve, B. E.

1996-01-01

The stress analysis of orthogrid structures, specifically with I-beam sections, is regularly performed using finite elements. Various modeling techniques are often used to simplify the modeling process but still adequately capture the actual hardware behavior. The accuracy of such 'Oshort cutso' is sometimes in question. This report compares three modeling techniques to actual test results from a loaded orthogrid panel. The finite element models include a beam, shell, and mixed beam and shell element model. Results show that the shell element model performs the best, but that the simpler beam and beam and shell element models provide reasonable to conservative results for a stress analysis. When deflection and stiffness is critical, it is important to capture the effect of the orthogrid nodes in the model.

Ecological models supporting environmental decision making: a strategy for the future

USGS Publications Warehouse

Schmolke, Amelie; Thorbek, Pernille; DeAngelis, Donald L.; Grimm, Volker

2010-01-01

Ecological models are important for environmental decision support because they allow the consequences of alternative policies and management scenarios to be explored. However, current modeling practice is unsatisfactory. A literature review shows that the elements of good modeling practice have long been identified but are widely ignored. The reasons for this might include lack of involvement of decision makers, lack of incentives for modelers to follow good practice, and the use of inconsistent terminologies. As a strategy for the future, we propose a standard format for documenting models and their analyses: transparent and comprehensive ecological modeling (TRACE) documentation. This standard format will disclose all parts of the modeling process to scrutiny and make modeling itself more efficient and coherent.

Hydration entropy change from the hard sphere model.

PubMed

Graziano, Giuseppe; Lee, Byungkook

2002-12-10

The gas to liquid transfer entropy change for a pure non-polar liquid can be calculated quite accurately using a hard sphere model that obeys the Carnahan-Starling equation of state. The same procedure fails to produce a reasonable value for hydrogen bonding liquids such as water, methanol and ethanol. However, the size of the molecules increases when the hydrogen bonds are turned off to produce the hard sphere system and the volume packing density rises. We show here that the hard sphere system that has this increased packing density reproduces the experimental transfer entropy values rather well. The gas to water transfer entropy values for small non-polar hydrocarbons is also not reproduced by a hard sphere model, whether one uses the normal (2.8 A diameter) or the increased (3.2 A) size for water. At least part of the reason that the hard sphere model with 2.8 A size water produces too small entropy change is that the size of water is too small for a system without hydrogen bonds. The reason that the 3.2 A model also produces too small entropy values is that this is an overly crowded system and that the free volume introduced in the system by the addition of a solute molecule produces too much of a relief to this crowding. A hard sphere model, in which the free volume increase is limited by requiring that the average surface-to-surface distance between the solute and water molecules is the same as that between the increased-size water molecules, does approximately reproduce the experimental hydration entropy values. Copyright 2002 Elsevier Science B.V.

Properties of inductive reasoning.

PubMed

Heit, E

2000-12-01

This paper reviews the main psychological phenomena of inductive reasoning, covering 25 years of experimental and model-based research, in particular addressing four questions. First, what makes a case or event generalizable to other cases? Second, what makes a set of cases generalizable? Third, what makes a property or predicate projectable? Fourth, how do psychological models of induction address these results? The key results in inductive reasoning are outlined, and several recent models, including a new Bayesian account, are evaluated with respect to these results. In addition, future directions for experimental and model-based work are proposed.

Students' Initial Knowledge of Electric and Magnetic Fields--More Profound Explanations and Reasoning Models for Undesired Conceptions

ERIC Educational Resources Information Center

Saarelainen, M.; Laaksonen, A.; Hirvonen, P. E.

2007-01-01

This study explores undergraduate students' understanding and reasoning models of electric and magnetic fields. The results indicate that the tested students had various alternative concepts in applying their reasoning to certain CSEM test questions. The total number of physics students tested at the beginning of the first course on…

Spatial Reasoning Training Through Light Curves Of Model Asteroids

NASA Astrophysics Data System (ADS)

Ziffer, Julie; Nakroshis, Paul A.; Rudnick, Benjamin T.; Brautigam, Maxwell J.; Nelson, Tyler W.

2015-11-01

Recent research has demonstrated that spatial reasoning skills, long known to be crucial to math and science success, are teachable. Even short stints of training can improve spatial reasoning skills among students who lack them (Sorby et al., 2006). Teaching spatial reasoning is particularly valuable to women and minorities who, through societal pressure, often doubt their spatial reasoning skill (Hill et al., 2010). We have designed a hands on asteroid rotation lab that provides practice in spatial reasoning tasks while building the student’s understanding of photometry. For our tool, we mount a model asteroid, with any shape of our choosing, on a slowly rotating motor shaft, whose speed is controlled by the experimenter. To mimic an asteroid light curve, we place the model asteroid in a dark box, shine a movable light source upon our asteroid, and record the light reflected onto a moveable camera. Students may then observe changes in the light curve that result from varying a) the speed of rotation, b) the model asteroid’s orientation with respect to the motor axis, c) the model asteroid’s shape or albedo, and d) the phase angle. After practicing with our tool, students are asked to pair new objects to their corresponding light curves. To correctly pair objects to their light curves, students must imagine how light scattering off of a three dimensional rotating object is imaged on a ccd sensor plane, and then reduced to a series of points on a light curve plot. Through the use of our model asteroid, the student develops confidence in spatial reasoning skills.

Remarks on Height-Diameter Modeling

Treesearch

Lei Yuancai; Bernard R. Parresol

2001-01-01

Height-diameter model forms in earlier published papers are examined. The selection criteria used in height-diameter model forms are not reasonable when considering tree biological growth pattern. During model selection, forms for height-diameter relationships should include consideration of both data-related and reasonable biological criteria, not just data-related...

Developing Computer Model-Based Assessment of Chemical Reasoning: A Feasibility Study

ERIC Educational Resources Information Center

Liu, Xiufeng; Waight, Noemi; Gregorius, Roberto; Smith, Erica; Park, Mihwa

2012-01-01

This paper reports a feasibility study on developing computer model-based assessments of chemical reasoning at the high school level. Computer models are flash and NetLogo environments to make simultaneously available three domains in chemistry: macroscopic, submicroscopic, and symbolic. Students interact with computer models to answer assessment…

Massive integration of diverse protein quality assessment methods to improve template based modeling in CASP11

PubMed Central

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2015-01-01

Model evaluation and selection is an important step and a big challenge in template-based protein structure prediction. Individual model quality assessment methods designed for recognizing some specific properties of protein structures often fail to consistently select good models from a model pool because of their limitations. Therefore, combining multiple complimentary quality assessment methods is useful for improving model ranking and consequently tertiary structure prediction. Here, we report the performance and analysis of our human tertiary structure predictor (MULTICOM) based on the massive integration of 14 diverse complementary quality assessment methods that was successfully benchmarked in the 11th Critical Assessment of Techniques of Protein Structure prediction (CASP11). The predictions of MULTICOM for 39 template-based domains were rigorously assessed by six scoring metrics covering global topology of Cα trace, local all-atom fitness, side chain quality, and physical reasonableness of the model. The results show that the massive integration of complementary, diverse single-model and multi-model quality assessment methods can effectively leverage the strength of single-model methods in distinguishing quality variation among similar good models and the advantage of multi-model quality assessment methods of identifying reasonable average-quality models. The overall excellent performance of the MULTICOM predictor demonstrates that integrating a large number of model quality assessment methods in conjunction with model clustering is a useful approach to improve the accuracy, diversity, and consequently robustness of template-based protein structure prediction. PMID:26369671

Computational fluid dynamic on the temperature simulation of air preheat effect combustion in propane turbulent flame

NASA Astrophysics Data System (ADS)

Elwina; Yunardi; Bindar, Yazid

2018-04-01

this paper presents results obtained from the application of a computational fluid dynamics (CFD) code Fluent 6.3 to modelling of temperature in propane flames with and without air preheat. The study focuses to investigate the effect of air preheat temperature on the temperature of the flame. A standard k-ε model and Eddy Dissipation model are utilized to represent the flow field and combustion of the flame being investigated, respectively. The results of calculations are compared with experimental data of propane flame taken from literature. The results of the study show that a combination of the standard k-ε turbulence model and eddy dissipation model is capable of producing reasonable predictions of temperature, particularly in axial profile of all three flames. Both experimental works and numerical simulation showed that increasing the temperature of the combustion air significantly increases the flame temperature.

Ozone Temporal Variability in the Subarctic Region: Comparison of Satellite Measurements with Numerical Simulations

NASA Astrophysics Data System (ADS)

Shved, G. M.; Virolainen, Ya. A.; Timofeyev, Yu. M.; Ermolenko, S. I.; Smyshlyaev, S. P.; Motsakov, M. A.; Kirner, O.

2018-01-01

Fourier and wavelet spectra of time series for the ozone column abundance in the atmospheric 0-25 and 25-60 km layers are analyzed from SBUV satellite observations and from numerical simulations based on the RSHU and EMAC models. The analysis uses datasets for three subarctic locations (St. Petersburg, Harestua, and Kiruna) for 2000-2014. The Fourier and wavelet spectra show periodicities in the range from 10 days to 10 years and from 1 day to 2 years, respectively. The comparison of the spectra shows overall agreement between the observational and modeled datasets. However, the analysis has revealed differences both between the measurements and the models and between the models themselves. The differences primarily concern the Rossby wave period region and the 11-year and semiannual periodicities. Possible reasons are given for the differences between the models and the measurements.

Acid–base chemical reaction model for nucleation rates in the polluted atmospheric boundary layer

PubMed Central

Chen, Modi; Titcombe, Mari; Jiang, Jingkun; Jen, Coty; Kuang, Chongai; Fischer, Marc L.; Eisele, Fred L.; Siepmann, J. Ilja; Hanson, David R.; Zhao, Jun; McMurry, Peter H.

2012-01-01

Climate models show that particles formed by nucleation can affect cloud cover and, therefore, the earth's radiation budget. Measurements worldwide show that nucleation rates in the atmospheric boundary layer are positively correlated with concentrations of sulfuric acid vapor. However, current nucleation theories do not correctly predict either the observed nucleation rates or their functional dependence on sulfuric acid concentrations. This paper develops an alternative approach for modeling nucleation rates, based on a sequence of acid–base reactions. The model uses empirical estimates of sulfuric acid evaporation rates obtained from new measurements of neutral molecular clusters. The model predicts that nucleation rates equal the sulfuric acid vapor collision rate times a prefactor that is less than unity and that depends on the concentrations of basic gaseous compounds and preexisting particles. Predicted nucleation rates and their dependence on sulfuric acid vapor concentrations are in reasonable agreement with measurements from Mexico City and Atlanta. PMID:23091030

Acid-base chemical reaction model for nucleation rates in the polluted atmospheric boundary layer.

PubMed

Chen, Modi; Titcombe, Mari; Jiang, Jingkun; Jen, Coty; Kuang, Chongai; Fischer, Marc L; Eisele, Fred L; Siepmann, J Ilja; Hanson, David R; Zhao, Jun; McMurry, Peter H

2012-11-13

Climate models show that particles formed by nucleation can affect cloud cover and, therefore, the earth's radiation budget. Measurements worldwide show that nucleation rates in the atmospheric boundary layer are positively correlated with concentrations of sulfuric acid vapor. However, current nucleation theories do not correctly predict either the observed nucleation rates or their functional dependence on sulfuric acid concentrations. This paper develops an alternative approach for modeling nucleation rates, based on a sequence of acid-base reactions. The model uses empirical estimates of sulfuric acid evaporation rates obtained from new measurements of neutral molecular clusters. The model predicts that nucleation rates equal the sulfuric acid vapor collision rate times a prefactor that is less than unity and that depends on the concentrations of basic gaseous compounds and preexisting particles. Predicted nucleation rates and their dependence on sulfuric acid vapor concentrations are in reasonable agreement with measurements from Mexico City and Atlanta.

Drawing-to-Learn: A Framework for Using Drawings to Promote Model-Based Reasoning in Biology

PubMed Central

Quillin, Kim; Thomas, Stephen

2015-01-01

The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report’s Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. PMID:25713094

"Clinical Reasoning Theater": A New Approach to Clinical Reasoning Education.

ERIC Educational Resources Information Center

Borleffs, Jan C. C.; Custers, Eugene J. F. M.; van Gijn, Jan; ten Gate, Olle Th. J.

2003-01-01

Describes a new approach to clinical reasoning education called clinical reasoning theater (CRT). With students as the audience, the doctor's clinical reasoning skills are modeled in CRT when he or she thinks aloud during conversations with the patient. Preliminary results of students' evaluations of the relevance of CRT reveal that they…

Secondary Students' Dynamic Modeling Processes: Analyzing, Reasoning About, Synthesizing, and Testing Models of Stream Ecosystems.

ERIC Educational Resources Information Center

Stratford, Steven J.; Krajeik, Joseph; Soloway, Elliot

This paper presents the results of a study of the cognitive strategies in which ninth-grade science students engaged as they used a learner-centered dynamic modeling tool (called Model-It) to make original models based upon stream ecosystem scenarios. The research questions were: (1) In what Cognitive Strategies for Modeling (analyzing, reasoning,…

A three-dimensional semianalytical model of hydraulic fracture growth through weak barriers

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

Luiskutty, C.T.; Tomutes, L.; Palmer, I.D.

1989-08-01

The goal of this research was to develop a fracture model for length/height ratio {le}4 that includes 2D flow (and a line source corresponding to the perforated interval) but makes approximations that allow a semianalytical solution, with large computer-time savings over the fully numerical mode. The height, maximum width, and pressure at the wellbore in this semianalytical model are calculated and compared with the results of the fully three-dimensional (3D) model. There is reasonable agreement in all parameters, the maximum discrepancy being 24%. Comparisons of fracture volume and leakoff volume also show reasonable agreement in volume and fluid efficiencies. Themore » values of length/height ratio, in the four cases in which agreement is found, vary from 1.5 to 3.7. The model offers a useful first-order (or screening) calculation of fracture-height growth through weak barriers (e.g., low stress contrasts). When coupled with the model developed for highly elongated fractures of length/height ratio {ge}4, which are also found to be in basic agreement with the fully numerical model, this new model provides the capability for approximating fracture-height growth through barriers for vertical fracture shapes that vary from penny to highly elongated. The computer time required is estimated to be less than the time required for the fully numerical model by a factor of 10 or more.« less

Age-related increase in brain activity during task-related and -negative networks and numerical inductive reasoning.

PubMed

Sun, Li; Liang, Peipeng; Jia, Xiuqin; Qi, Zhigang; Li, Kuncheng

2014-01-01

Recent neuroimaging studies have shown that elderly adults exhibit increased and decreased activation on various cognitive tasks, yet little is known about age-related changes in inductive reasoning. To investigate the neural basis for the aging effect on inductive reasoning, 15 young and 15 elderly subjects performed numerical inductive reasoning while in a magnetic resonance (MR) scanner. Functional magnetic resonance imaging (fMRI) analysis revealed that numerical inductive reasoning, relative to rest, yielded multiple frontal, temporal, parietal, and some subcortical area activations for both age groups. In addition, the younger participants showed significant regions of task-induced deactivation, while no deactivation occurred in the elderly adults. Direct group comparisons showed that elderly adults exhibited greater activity in regions of task-related activation and areas showing task-induced deactivation (TID) in the younger group. Our findings suggest an age-related deficiency in neural function and resource allocation during inductive reasoning.

Real-time scheduling using minimum search

NASA Technical Reports Server (NTRS)

Tadepalli, Prasad; Joshi, Varad

1992-01-01

In this paper we consider a simple model of real-time scheduling. We present a real-time scheduling system called RTS which is based on Korf's Minimin algorithm. Experimental results show that the schedule quality initially improves with the amount of look-ahead search and tapers off quickly. So it sppears that reasonably good schedules can be produced with a relatively shallow search.

Inhibitory Control as a Core Process of Creative Problem Solving and Idea Generation from Childhood to Adulthood

ERIC Educational Resources Information Center

Cassotti, Mathieu; Agogué, Marine; Camarda, Anaëlle; Houdé, Olivier; Borst, Grégoire

2016-01-01

Developmental cognitive neuroscience studies tend to show that the prefrontal brain regions (known to be involved in inhibitory control) are activated during the generation of creative ideas. In the present article, we discuss how a dual-process model of creativity--much like the ones proposed to account for decision making and reasoning--could…

Autonomy, Trust, and Respect.

PubMed

Nys, Thomas

2016-02-01

This article seeks to explore and analyze the relationship between autonomy and trust, and to show how these findings could be relevant to medical ethics. First, I will argue that the way in which so-called "relational autonomy theories" tie the notions of autonomy and trust together is not entirely satisfying Then, I will introduce the so-called Encapsulated Interest Account as developed by Russell Hardin. This will bring out the importance of the reasons for trust. What good reasons do we have for trusting someone? I will criticize Hardin's business model as insufficiently robust, especially in the context of health care, and then turn to another source of trust, namely, love. It may seem that trust-through-love is much better suited for the vulnerability that is often involved in health care, but I will also show that it has its own deficiencies. Good health care should therefore pay attention to both models of trust, and I will offer some tentative remarks on how to do this. © The Author 2015. Published by Oxford University Press, on behalf of the Journal of Medicine and Philosophy Inc. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Effects of crowders on the equilibrium and kinetic properties of protein aggregation

NASA Astrophysics Data System (ADS)

Bridstrup, John; Yuan, Jian-Min

2016-08-01

The equilibrium and kinetic properties of protein aggregation systems in the presence of crowders are investigated using simple, illuminating models based on mass-action laws. Our model yields analytic results for equilibrium properties of protein aggregates, which fit experimental data of actin and ApoC-II with crowders reasonably well. When the effects of crowders on rate constants are considered, our kinetic model is in good agreement with experimental results for actin with dextran as the crowder. Furthermore, the model shows that as crowder volume fraction increases, the length distribution of fibrils becomes narrower and shifts to shorter values due to volume exclusion.

Skolem and pessimism about proof in mathematics.

PubMed

Cohen, Paul J

2005-10-15

Attitudes towards formalization and proof have gone through large swings during the last 150 years. We sketch the development from Frege's first formalization, to the debates over intuitionism and other schools, through Hilbert's program and the decisive blow of the Gödel Incompleteness Theorem. A critical role is played by the Skolem-Lowenheim Theorem, which showed that no first-order axiom system can characterize a unique infinite model. Skolem himself regarded this as a body blow to the belief that mathematics can be reliably founded only on formal axiomatic systems. In a remarkably prescient paper, he even sketches the possibility of interesting new models for set theory itself, something later realized by the method of forcing. This is in contrast to Hilbert's belief that mathematics could resolve all its questions. We discuss the role of new axioms for set theory, questions in set theory itself, and their relevance for number theory. We then look in detail at what the methods of the predicate calculus, i.e. mathematical reasoning, really entail. The conclusion is that there is no reasonable basis for Hilbert's assumption. The vast majority of questions even in elementary number theory, of reasonable complexity, are beyond the reach of any such reasoning. Of course this cannot be proved and we present only plausibility arguments. The great success of mathematics comes from considering 'natural problems', those which are related to previous work and offer a good chance of being solved. The great glories of human reasoning, beginning with the Greek discovery of geometry, are in no way diminished by this pessimistic view. We end by wishing good health to present-day mathematics and the mathematics of many centuries to come.

A public health decision support system model using reasoning methods.

PubMed

Mera, Maritza; González, Carolina; Blobel, Bernd

2015-01-01

Public health programs must be based on the real health needs of the population. However, the design of efficient and effective public health programs is subject to availability of information that can allow users to identify, at the right time, the health issues that require special attention. The objective of this paper is to propose a case-based reasoning model for the support of decision-making in public health. The model integrates a decision-making process and case-based reasoning, reusing past experiences for promptly identifying new population health priorities. A prototype implementation of the model was performed, deploying the case-based reasoning framework jColibri. The proposed model contributes to solve problems found today when designing public health programs in Colombia. Current programs are developed under uncertain environments, as the underlying analyses are carried out on the basis of outdated and unreliable data.

Understanding clinical reasoning in osteopathy: a qualitative research approach.

PubMed

Grace, Sandra; Orrock, Paul; Vaughan, Brett; Blaich, Raymond; Coutts, Rosanne

2016-01-01

Clinical reasoning has been described as a process that draws heavily on the knowledge, skills and attributes that are particular to each health profession. However, the clinical reasoning processes of practitioners of different disciplines demonstrate many similarities, including hypothesis generation and reflective practice. The aim of this study was to understand clinical reasoning in osteopathy from the perspective of osteopathic clinical educators and the extent to which it was similar or different from clinical reasoning in other health professions. This study was informed by constructivist grounded theory. Participants were clinical educators in osteopathic teaching institutions in Australia, New Zealand and the UK. Focus groups and written critical reflections provided a rich data set. Data were analysed using constant comparison to develop inductive categories. According to participants, clinical reasoning in osteopathy is different from clinical reasoning in other health professions. Osteopaths use a two-phase approach: an initial biomedical screen for serious pathology, followed by use of osteopathic reasoning models that are based on the relationship between structure and function in the human body. Clinical reasoning in osteopathy was also described as occurring in a number of contexts (e.g. patient, practitioner and community) and drawing on a range of metaskills (e.g. hypothesis generation and reflexivity) that have been described in other health professions. The use of diagnostic reasoning models that are based on the relationship between structure and function in the human body differentiated clinical reasoning in osteopathy. These models were not used to name a medical condition but rather to guide the selection of treatment approaches. If confirmed by further research that clinical reasoning in osteopathy is distinct from clinical reasoning in other health professions, then osteopaths may have a unique perspective to bring to multidisciplinary decision-making and potentially enhance the quality of patient care. Where commonalities exist in the clinical reasoning processes of osteopathy and other health professions, shared learning opportunities may be available, including the exchange of scaffolded clinical reasoning exercises and assessment practices among health disciplines.

The effect of the hot oxygen corona on the interaction of the solar wind with Venus

NASA Technical Reports Server (NTRS)

Belotserkovskii, O. M.; Mitnitskii, V. IA.; Breus, T. K.; Krymskii, A. M.; Nagy, A. F.

1987-01-01

A numerical gasdynamic model, which includes the effects of mass loading of the shocked solar wind, was used to calculate the density and magnetic field variations in the magnetosheath of Venus. These calculations were carried out for conditions corresponding to a specific orbit of the Pioneer Venus Orbiter (PVO orbit 582). A comparison of the model predictions and the measured shock position, density and magnetic field values showed a reasonable agreement, indicating that a gasdynamic model that includes the effects of mass loading can be used to predict these parameters.

Situation awareness-based agent transparency for human-autonomy teaming effectiveness

NASA Astrophysics Data System (ADS)

Chen, Jessie Y. C.; Barnes, Michael J.; Wright, Julia L.; Stowers, Kimberly; Lakhmani, Shan G.

2017-05-01

We developed the Situation awareness-based Agent Transparency (SAT) model to support human operators' situation awareness of the mission environment through teaming with intelligent agents. The model includes the agent's current actions and plans (Level 1), its reasoning process (Level 2), and its projection of future outcomes (Level 3). Human-inthe-loop simulation experiments have been conducted (Autonomous Squad Member and IMPACT) to illustrate the utility of the model for human-autonomy team interface designs. Across studies, the results consistently showed that human operators' task performance improved as the agents became more transparent. They also perceived transparent agents as more trustworthy.

DEVS representation of dynamical systems - Event-based intelligent control. [Discrete Event System Specification

NASA Technical Reports Server (NTRS)

Zeigler, Bernard P.

1989-01-01

It is shown how systems can be advantageously represented as discrete-event models by using DEVS (discrete-event system specification), a set-theoretic formalism. Such DEVS models provide a basis for the design of event-based logic control. In this control paradigm, the controller expects to receive confirming sensor responses to its control commands within definite time windows determined by its DEVS model of the system under control. The event-based contral paradigm is applied in advanced robotic and intelligent automation, showing how classical process control can be readily interfaced with rule-based symbolic reasoning systems.

The effect of the hot oxygen corona on the interaction of the solar wind with Venus

NASA Astrophysics Data System (ADS)

Belotserkovskii, O. M.; Breus, T. K.; Krymskii, A. M.; Mitnitskii, V. Ya.; Nagey, A. F.; Gombosi, T. I.

1987-05-01

A numerical gas dynamic model, which includes the effects of mass loading of the shocked solar wind, was used to calculate the density and magnetic field variations in the magnetosheath of Venus. These calculations were carried out for conditions corresponding to a specific orbit of the Pioneer Venus Orbiter (PVO orbit 582). A comparison of the model predictions and the measured shock position, density and magnetic field values showed a reasonable agreement, indicating that a gas dynamic model that includes the effects of mass loading can be used to predict these parameters.

A clinical reasoning model focused on clients' behaviour change with reference to physiotherapists: its multiphase development and validation.

PubMed

Elvén, Maria; Hochwälder, Jacek; Dean, Elizabeth; Söderlund, Anne

2015-05-01

A biopsychosocial approach and behaviour change strategies have long been proposed to serve as a basis for addressing current multifaceted health problems. This emphasis has implications for clinical reasoning of health professionals. This study's aim was to develop and validate a conceptual model to guide physiotherapists' clinical reasoning focused on clients' behaviour change. Phase 1 consisted of the exploration of existing research and the research team's experiences and knowledge. Phases 2a and 2b consisted of validation and refinement of the model based on input from physiotherapy students in two focus groups (n = 5 per group) and from experts in behavioural medicine (n = 9). Phase 1 generated theoretical and evidence bases for the first version of a model. Phases 2a and 2b established the validity and value of the model. The final model described clinical reasoning focused on clients' behaviour change as a cognitive, reflective, collaborative and iterative process with multiple interrelated levels that included input from the client and physiotherapist, a functional behavioural analysis of the activity-related target behaviour and the selection of strategies for behaviour change. This unique model, theory- and evidence-informed, has been developed to help physiotherapists to apply clinical reasoning systematically in the process of behaviour change with their clients.

Exploring the entanglement of personal epistemologies and emotions in students' thinking

NASA Astrophysics Data System (ADS)

Gupta, Ayush; Elby, Andrew; Danielak, Brian A.

2018-06-01

Evidence from psychology, cognitive science, and neuroscience suggests that cognition and emotions are coupled. Education researchers have also documented correlations between emotions (such as joy, anxiety, fear, curiosity, boredom) and academic performance. Nonetheless, most research on students' reasoning and conceptual change within the learning sciences and physics and science education research has not attended to the role of learners' emotions in describing or modeling the fine timescale dynamics of their conceptual reasoning. The few studies that integrate emotions into models of learners' cognition have mostly done so at a coarse grain size. In this study, toward the long-term goal of incorporating emotions into models of in-the-moment cognitive dynamics, we present a case study of Judy, an undergraduate electrical engineering and physics major. We show that shifts in the intensity of a fine-grained aspect of Judy's emotions, her annoyance at conceptual homework problems, co-occur with shifts in her epistemological stance toward differentiating knowledge about and the practical utility of real circuits and idealized circuit models. We then argue for the plausibility of a cognitive model in which Judy's emotions and epistemological stances mutually affect each other. We end with discussions on how models of learners' cognition that incorporate their emotions are generative for instructional purposes and research on learning.

Modeling the Effects of Argument Length and Validity on Inductive and Deductive Reasoning

ERIC Educational Resources Information Center

Rotello, Caren M.; Heit, Evan

2009-01-01

In an effort to assess models of inductive reasoning and deductive reasoning, the authors, in 3 experiments, examined the effects of argument length and logical validity on evaluation of arguments. In Experiments 1a and 1b, participants were given either induction or deduction instructions for a common set of stimuli. Two distinct effects were…

Differences in cognitive and emotional processes between persecutory and grandiose delusions.

PubMed

Garety, Philippa A; Gittins, Matthew; Jolley, Suzanne; Bebbington, Paul; Dunn, Graham; Kuipers, Elizabeth; Fowler, David; Freeman, Daniel

2013-05-01

Cognitive models propose that cognitive and emotional processes, in the context of anomalies of experience, lead to and maintain delusions. No large-scale studies have investigated whether persecutory and grandiose delusions reflect differing contributions of reasoning and affective processes. This is complicated by their frequent cooccurrence in schizophrenia. We hypothesized that persecutory and grandiose subtypes would differ significantly in their associations with psychological processes. Participants were the 301 patients from the Psychological Prevention of Relapse in Psychosis Trial (ISRCTN83557988). Persecutory delusions were present in 192 participants, and grandiose delusions were present in 97, while 58 were rated as having delusions both of persecution and grandiosity. Measures of emotional and reasoning processes, at baseline only, were employed. A bivariate response model was used. Negative self-evaluations and depression and anxiety predicted a significantly increased chance of persecutory delusions whereas grandiose delusions were predicted by less negative self-evaluations and lower anxiety and depression, along with higher positive self and positive other evaluations. Reasoning biases were common in the whole group and in categorically defined subgroups with only persecutory delusions and only grandiose delusions; however, jumping to conclusions, and belief flexibility were significantly different in the 2 groups, the grandiose group having a higher likelihood of showing a reasoning bias than the persecutory group. The significant differences in the processes associated with these 2 delusion subtypes have implications for etiology and for the development of targeted treatment strategies.

Age at treatment predicts reason for discontinuation of TNF antagonists: data from the BIOBADASER 2.0 registry.

PubMed

Busquets, Noemí; Tomero, Eva; Descalzo, Miguel Ángel; Ponce, Andrés; Ortiz-Santamaría, Vera; Surís, Xavier; Carmona, Loreto; Gómez-Reino, Juan J

2011-11-01

To assess the retention rate of TNF antagonists in elderly patients suffering from chronic arthropathies and to identify predictive variables of discontinuation by inefficacy or by adverse events (AEs). All patients treated with TNF antagonists in BIOBADASER 2.0, with a diagnosis of either RA or spondyloarthritis (SpA: AS and PsA) were included and classified as <65 (younger) or ≥65 years of age (older) at start of the treatment. Cumulative incidence function for discontinuation (inefficacy or AE) was estimated as being the alternative reason for a competing risk. Competing-risks regression models were used to measure the association between study groups, covariates and reason for discontinuation. A total of 4851 patients were studied; 2957 RA (2291 in the younger group and 666 in the older group) and 1894 SpA (1795 in the younger group and 99 in the older group). Retention curves were statistically differently stratified by age groups, with the SpA younger group having the largest retention rate. Competing-risks regression models showed that in the older group, AEs were the most common reason for discontinuation regardless of the diagnosis of the patient and TNF antagonist molecule, whereas in the younger group, the most common cause of discontinuation was inefficacy. In conclusion, factors predicting discontinuation of TNF antagonists due to AEs are older age and diagnosis of RA. On the other hand, younger age predicts discontinuation due to lack of efficacy.

Turbulence Model Comparisons for Supersonic Transports at Transonic and Supersonic Conditions

NASA Technical Reports Server (NTRS)

Rivers, S. M. B.; Wahls, R. A.

2003-01-01

Results of turbulence model comparisons from two studies on supersonic transport configurations performed during the NASA High-speed Research program are given. Results are presented for both transonic conditions at Mach 0.90 and supersonic conditions at Mach 2.48. A feature of these two studies was the availability of higher Reynolds number wind tunnel data with which to compare the computational results. The transonic wind tunnel data was obtained in the National Transonic Facility at NASA Langley, and the supersonic data was obtained in the Boeing Polysonic Wind Tunnel. The computational data was acquired using a state of the art Navier-Stokes flow solver with a wide range of turbulence models implemented. The results show that the computed forces compare reasonably well with the experimental data, with the Baldwin- Lomax with Degani-Schiff modifications and the Baldwin-Barth models showing the best agreement for the transonic conditions and the Spalart-Allmaras model showing the best agreement for the supersonic conditions. The transonic results were more sensitive to the choice of turbulence model than were the supersonic results.

On the road toward formal reasoning: reasoning with factual causal and contrary-to-fact causal premises during early adolescence.

PubMed

Markovits, Henry

2014-12-01

Understanding the development of conditional (if-then) reasoning is critical for theoretical and educational reasons. Here we examined the hypothesis that there is a developmental transition between reasoning with true and contrary-to-fact (CF) causal conditionals. A total of 535 students between 11 and 14 years of age received priming conditions designed to encourage use of either a true or CF alternatives generation strategy and reasoning problems with true causal and CF causal premises (with counterbalanced order). Results show that priming had no effect on reasoning with true causal premises. By contrast, priming with CF alternatives significantly improved logical reasoning with CF premises. Analysis of the effect of order showed that reasoning with CF premises reduced logical responding among younger students but had no effect among older students. Results support the idea that there is a transition in the reasoning processes in this age range associated with the nature of the alternatives generation process required for logical reasoning with true and CF causal conditionals. Copyright © 2014 Elsevier Inc. All rights reserved.

Methods for Probabilistic Radiological Dose Assessment at a High-Level Radioactive Waste Repository.

NASA Astrophysics Data System (ADS)

Maheras, Steven James

Methods were developed to assess and evaluate the uncertainty in offsite and onsite radiological dose at a high-level radioactive waste repository to show reasonable assurance that compliance with applicable regulatory requirements will be achieved. Uncertainty in offsite dose was assessed by employing a stochastic precode in conjunction with Monte Carlo simulation using an offsite radiological dose assessment code. Uncertainty in onsite dose was assessed by employing a discrete-event simulation model of repository operations in conjunction with an occupational radiological dose assessment model. Complementary cumulative distribution functions of offsite and onsite dose were used to illustrate reasonable assurance. Offsite dose analyses were performed for iodine -129, cesium-137, strontium-90, and plutonium-239. Complementary cumulative distribution functions of offsite dose were constructed; offsite dose was lognormally distributed with a two order of magnitude range. However, plutonium-239 results were not lognormally distributed and exhibited less than one order of magnitude range. Onsite dose analyses were performed for the preliminary inspection, receiving and handling, and the underground areas of the repository. Complementary cumulative distribution functions of onsite dose were constructed and exhibited less than one order of magnitude range. A preliminary sensitivity analysis of the receiving and handling areas was conducted using a regression metamodel. Sensitivity coefficients and partial correlation coefficients were used as measures of sensitivity. Model output was most sensitive to parameters related to cask handling operations. Model output showed little sensitivity to parameters related to cask inspections.

MESA: An Interactive Modeling and Simulation Environment for Intelligent Systems Automation

NASA Technical Reports Server (NTRS)

Charest, Leonard

1994-01-01

This report describes MESA, a software environment for creating applications that automate NASA mission opterations. MESA enables intelligent automation by utilizing model-based reasoning techniques developed in the field of Artificial Intelligence. Model-based reasoning techniques are realized in Mesa through native support of causal modeling and discrete event simulation.

Mental Models: Understanding the Impact of Fantasy Violence on Children's Moral Reasoning.

ERIC Educational Resources Information Center

Krcmar, Marina; Curtis, Stephen

2003-01-01

Tests the efficacy of mental models in understanding the effect of exposure to fantasy violence on children's responses to and reasoning about moral dilemmas involving aggression. Offers a possible extension to mental models that is consistent with current theory in cognitive science. Suggests that the activation of mental models regarding…

Dietary restrictions in healing among speakers of Iquito, an endangered language of the Peruvian Amazon

PubMed Central

2011-01-01

Background Ethnobotanical research was carried out with speakers of Iquito, a critically endangered Amazonian language of the Zaparoan family. The study focused on the concept of "dieting" (siyan++ni in Iquito), a practice involving prohibitions considered necessary to the healing process. These restrictions include: 1) foods and activities that can exacerbate illness, 2) environmental influences that conflict with some methods of healing (e.g. steam baths or enemas) and 3) foods and activities forbidden by the spirits of certain powerful medicinal plants. The study tested the following hypotheses: H1 - Each restriction will correlate with specific elements in illness explanatory models and H2 - Illnesses whose explanatory models have personalistic elements will show a greater number and variety of restrictions than those based on naturalistic reasoning. Methods The work was carried out in 2009 and 2010 in the Alto Nanay region of Peru. In structured interviews, informants gave explanatory models for illness categories, including etiologies, pathophysiologies, treatments and dietary restrictions necessary for 49 illnesses. Seventeen botanical vouchers for species said to have powerful spirits that require diets were also collected. Results All restrictions found correspond to some aspect of illness explanatory models. Thirty-five percent match up with specific illness etiologies, 53% correspond to particular pathophysiologies, 18% correspond with overall seriousness of the illness and 18% are only found with particular forms of treatment. Diets based on personalistic reasoning have a significantly higher average number of restrictions than those based on naturalistic reasoning. Conclusions Dieting plays a central role in healing among Iquito speakers. Specific prohibitions can be explained in terms of specific aspects of illness etiologies, pathophysiologies and treatments. Although the Amazonian literature contains few studies focusing on dietary proscriptions over a wide range of illnesses, some specific restrictions reported here do correspond with trends seen in other Amazonian societies, particularly those related to sympathetic reasoning and for magical and spiritual uses of plants. PMID:21745400

Dietary restrictions in healing among speakers of Iquito, an endangered language of the Peruvian Amazon.

PubMed

Jernigan, Kevin A

2011-07-11

Ethno botanical research was carried out with speakers of Iquitos, a critically endangered Amazonian language of the Zaparoan family. The study focused on the concept of "dieting" (siyan++ni in Iquitos), a practice involving prohibitions considered necessary to the healing process. These restrictions include: 1) foods and activities that can exacerbate illness, 2) environmental influences that conflict with some methods of healing (e.g. steam baths or enemas) and 3) foods and activities forbidden by the spirits of certain powerful medicinal plants. The study tested the following hypotheses: H1--Each restriction will correlate with specific elements in illness explanatory models and H2--Illnesses whose explanatory models have personality elements will show a greater number and variety of restrictions than those based on naturalistic reasoning. The work was carried out in 2009 and 2010 in the Alto Nanay region of Peru. In structured interviews, informants gave explanatory models for illness categories, including etiologies, pathophysiologies, treatments and dietary restrictions necessary for 49 illnesses. Seventeen botanical vouchers for species said to have powerful spirits that require diets were also collected. All restrictions found correspond to some aspect of illness explanatory models. Thirty-five percent match up with specific illness etiologies, 53% correspond to particular pathophysiologies, 18% correspond with overall seriousness of the illness and 18% are only found with particular forms of treatment. Diets based on personalistic reasoning have a significantly higher average number of restrictions than those based on naturalistic reasoning. Dieting plays a central role in healing among Iquitos speakers. Specific prohibitions can be explained in terms of specific aspects of illness etiologies, pathophysiologies and treatments. Although the Amazonian literature contains few studies focusing on dietary proscriptions over a wide range of illnesses, some specific restrictions reported here do correspond with trends seen in other Amazonian societies, particularly those related to sympathetic reasoning and for magical and spiritual uses of plants.

Artificial neural networks and approximate reasoning for intelligent control in space

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

A method is introduced for learning to refine the control rules of approximate reasoning-based controllers. A reinforcement-learning technique is used in conjunction with a multi-layer neural network model of an approximate reasoning-based controller. The model learns by updating its prediction of the physical system's behavior. The model can use the control knowledge of an experienced operator and fine-tune it through the process of learning. Some of the space domains suitable for applications of the model such as rendezvous and docking, camera tracking, and tethered systems control are discussed.

Learning about causes from people and about people as causes: probabilistic models and social causal reasoning.

PubMed

Buchsbaum, Daphna; Seiver, Elizabeth; Bridgers, Sophie; Gopnik, Alison

2012-01-01

A major challenge children face is uncovering the causal structure of the world around them. Previous research on children's causal inference has demonstrated their ability to learn about causal relationships in the physical environment using probabilistic evidence. However, children must also learn about causal relationships in the social environment, including discovering the causes of other people's behavior, and understanding the causal relationships between others' goal-directed actions and the outcomes of those actions. In this chapter, we argue that social reasoning and causal reasoning are deeply linked, both in the real world and in children's minds. Children use both types of information together and in fact reason about both physical and social causation in fundamentally similar ways. We suggest that children jointly construct and update causal theories about their social and physical environment and that this process is best captured by probabilistic models of cognition. We first present studies showing that adults are able to jointly infer causal structure and human action structure from videos of unsegmented human motion. Next, we describe how children use social information to make inferences about physical causes. We show that the pedagogical nature of a demonstrator influences children's choices of which actions to imitate from within a causal sequence and that this social information interacts with statistical causal evidence. We then discuss how children combine evidence from an informant's testimony and expressed confidence with evidence from their own causal observations to infer the efficacy of different potential causes. We also discuss how children use these same causal observations to make inferences about the knowledge state of the social informant. Finally, we suggest that psychological causation and attribution are part of the same causal system as physical causation. We present evidence that just as children use covariation between physical causes and their effects to learn physical causal relationships, they also use covaration between people's actions and the environment to make inferences about the causes of human behavior.

Exploring Third-Grade Student Model-Based Explanations about Plant Relationships within an Ecosystem

NASA Astrophysics Data System (ADS)

Zangori, Laura; Forbes, Cory T.

2015-12-01

Elementary students should have opportunities to develop scientific models to reason and build understanding about how and why plants depend on relationships within an ecosystem for growth and survival. However, scientific modeling practices are rarely included within elementary science learning environments and disciplinary content is often treated as discrete pieces separate from scientific practice. Elementary students have few, if any, opportunities to reason about how individual organisms, such as plants, hold critical relationships with their surrounding environment. The purpose of this design-based research study is to build a learning performance to identify and explore the third-grade students' baseline understanding of and their reasoning about plant-ecosystem relationships when engaged in the practices of modeling. The developed learning performance integrated scientific content and core scientific activity to identify and measure how students build knowledge about the role of plants in ecosystems through the practices of modeling. Our findings indicate that the third-grade students' ideas about plant growth include abiotic and biotic relationships. Further, they used their models to reason about how and why these relationships were necessary to maintain plant stasis. However, while the majority of the third-grade students were able to identify and reason about plant-abiotic relationships, a much smaller group reasoned about plant-abiotic-animal relationships. Implications from the study suggest that modeling serves as a tool to support elementary students in reasoning about system relationships, but they require greater curricular and instructional support in conceptualizing how and why ecosystem relationships are necessary for plant growth and development. This paper is based on data from a doctoral dissertation. An earlier version of this paper was presented at the 2015 international conference for the National Association for Research in Science Teaching (NARST) Zangori, L., & Forbes, C. T. (2015). Exploring 3rd-grade student model-based explanations about plant process interactions within the hydrosphere Portions of this paper are based on that work.

The new car following model considering vehicle dynamics influence and numerical simulation

NASA Astrophysics Data System (ADS)

Sun, Dihua; Liu, Hui; Zhang, Geng; Zhao, Min

2015-12-01

In this paper, the car following model is investigated by considering the vehicle dynamics in a cyber physical view. In fact, that driving is a typical cyber physical process which couples the cyber aspect of the vehicles' information and driving decision tightly with the dynamics and physics of the vehicles and traffic environment. However, the influence from the physical (vehicle) view was been ignored in the previous car following models. In order to describe the car following behavior more reasonably in real traffic, a new car following model by considering vehicle dynamics (for short, D-CFM) is proposed. In this paper, we take the full velocity difference (FVD) car following model as a case. The stability condition is given on the base of the control theory. The analytical method and numerical simulation results show that the new models can describe the evolution of traffic congestion. The simulations also show vehicles with a more actual acceleration of starting process than early models.

Conditional Solvation Thermodynamics of Isoleucine in Model Peptides and the Limitations of the Group-Transfer Model

PubMed Central

2015-01-01

The hydration thermodynamics of the amino acid X relative to the reference G (glycine) or the hydration thermodynamics of a small-molecule analog of the side chain of X is often used to model the contribution of X to protein stability and solution thermodynamics. We consider the reasons for successes and limitations of this approach by calculating and comparing the conditional excess free energy, enthalpy, and entropy of hydration of the isoleucine side chain in zwitterionic isoleucine, in extended penta-peptides, and in helical deca-peptides. Butane in gauche conformation serves as a small-molecule analog for the isoleucine side chain. Parsing the hydrophobic and hydrophilic contributions to hydration for the side chain shows that both of these aspects of hydration are context-sensitive. Furthermore, analyzing the solute–solvent interaction contribution to the conditional excess enthalpy of the side chain shows that what is nominally considered a property of the side chain includes entirely nonobvious contributions of the background. The context-sensitivity of hydrophobic and hydrophilic hydration and the conflation of background contributions with energetics attributed to the side chain limit the ability of a single scaling factor, such as the fractional solvent exposure of the group in the protein, to map the component energetic contributions of the model-compound data to their value in the protein. But ignoring the origin of cancellations in the underlying components the group-transfer model may appear to provide a reasonable estimate of the free energy for a given error tolerance. PMID:24650057

Delving into α-stable distribution in noise suppression for seizure detection from scalp EEG

NASA Astrophysics Data System (ADS)

Wang, Yueming; Qi, Yu; Wang, Yiwen; Lei, Zhen; Zheng, Xiaoxiang; Pan, Gang

2016-10-01

Objective. There is serious noise in EEG caused by eye blink and muscle activities. The noise exhibits similar morphologies to epileptic seizure signals, leading to relatively high false alarms in most existing seizure detection methods. The objective in this paper is to develop an effective noise suppression method in seizure detection and explore the reason why it works. Approach. Based on a state-space model containing a non-linear observation function and multiple features as the observations, this paper delves deeply into the effect of the α-stable distribution in the noise suppression for seizure detection from scalp EEG. Compared with the Gaussian distribution, the α-stable distribution is asymmetric and has relatively heavy tails. These properties make it more powerful in modeling impulsive noise in EEG, which usually can not be handled by the Gaussian distribution. Specially, we give a detailed analysis in the state estimation process to show the reason why the α-stable distribution can suppress the impulsive noise. Main results. To justify each component in our model, we compare our method with 4 different models with different settings on a collected 331-hour epileptic EEG data. To show the superiority of our method, we compare it with the existing approaches on both our 331-hour data and 892-hour public data. The results demonstrate that our method is most effective in both the detection rate and the false alarm. Significance. This is the first attempt to incorporate the α-stable distribution to a state-space model for noise suppression in seizure detection and achieves the state-of-the-art performance.

Mental models and human reasoning

PubMed Central

Johnson-Laird, Philip N.

2010-01-01

To be rational is to be able to reason. Thirty years ago psychologists believed that human reasoning depended on formal rules of inference akin to those of a logical calculus. This hypothesis ran into difficulties, which led to an alternative view: reasoning depends on envisaging the possibilities consistent with the starting point—a perception of the world, a set of assertions, a memory, or some mixture of them. We construct mental models of each distinct possibility and derive a conclusion from them. The theory predicts systematic errors in our reasoning, and the evidence corroborates this prediction. Yet, our ability to use counterexamples to refute invalid inferences provides a foundation for rationality. On this account, reasoning is a simulation of the world fleshed out with our knowledge, not a formal rearrangement of the logical skeletons of sentences. PMID:20956326

Modality, probability, and mental models.

PubMed

Hinterecker, Thomas; Knauff, Markus; Johnson-Laird, P N

2016-10-01

We report 3 experiments investigating novel sorts of inference, such as: A or B or both. Therefore, possibly (A and B). Where the contents were sensible assertions, for example, Space tourism will achieve widespread popularity in the next 50 years or advances in material science will lead to the development of antigravity materials in the next 50 years, or both . Most participants accepted the inferences as valid, though they are invalid in modal logic and in probabilistic logic too. But, the theory of mental models predicts that individuals should accept them. In contrast, inferences of this sort—A or B but not both. Therefore, A or B or both—are both logically valid and probabilistically valid. Yet, as the model theory also predicts, most reasoners rejected them. The participants’ estimates of probabilities showed that their inferences tended not to be based on probabilistic validity, but that they did rate acceptable conclusions as more probable than unacceptable conclusions. We discuss the implications of the results for current theories of reasoning. PsycINFO Database Record (c) 2016 APA, all rights reserved

Power flows and Mechanical Intensities in structural finite element analysis

NASA Technical Reports Server (NTRS)

Hambric, Stephen A.

1989-01-01

The identification of power flow paths in dynamically loaded structures is an important, but currently unavailable, capability for the finite element analyst. For this reason, methods for calculating power flows and mechanical intensities in finite element models are developed here. Formulations for calculating input and output powers, power flows, mechanical intensities, and power dissipations for beam, plate, and solid element types are derived. NASTRAN is used to calculate the required velocity, force, and stress results of an analysis, which a post-processor then uses to calculate power flow quantities. The SDRC I-deas Supertab module is used to view the final results. Test models include a simple truss and a beam-stiffened cantilever plate. Both test cases showed reasonable power flow fields over low to medium frequencies, with accurate power balances. Future work will include testing with more complex models, developing an interactive graphics program to view easily and efficiently the analysis results, applying shape optimization methods to the problem with power flow variables as design constraints, and adding the power flow capability to NASTRAN.

The enhancement of mathematical analogical reasoning ability of university students through concept attainment model

NASA Astrophysics Data System (ADS)

Angraini, L. M.; Kusumah, Y. S.; Dahlan, J. A.

2018-05-01

This study aims to see the enhancement of mathematical analogical reasoning ability of the university students through concept attainment model learning based on overall and Prior Mathematical Knowledge (PMK) and interaction of both. Quasi experiments with the design of this experimental-controlled equivalent group involved 54 of second semester students at the one of State Islamic University. The instrument used is pretest-postest. Kolmogorov-Smirnov test, Levene test, t test, two-way ANOVA test were used to analyse the data. The result of this study includes: (1) The enhancement of the mathematical analogical reasoning ability of the students who gets the learning of concept attainment model is better than the enhancement of the mathematical analogical reasoning ability of the students who gets the conventional learning as a whole and based on PMK; (2) There is no interaction between the learning that is used and PMK on enhancing mathematical analogical reasoning ability.

Model of critical diagnostic reasoning: achieving expert clinician performance.

PubMed

Harjai, Prashant Kumar; Tiwari, Ruby

2009-01-01

Diagnostic reasoning refers to the analytical processes used to determine patient health problems. While the education curriculum and health care system focus on training nurse clinicians to accurately recognize and rescue clinical situations, assessments of non-expert nurses have yielded less than satisfactory data on diagnostic competency. The contrast between the expert and non-expert nurse clinician raises the important question of how differences in thinking may contribute to a large divergence in accurate diagnostic reasoning. This article recognizes superior organization of one's knowledge base, using prototypes, and quick retrieval of pertinent information, using similarity recognition as two reasons for the expert's superior diagnostic performance. A model of critical diagnostic reasoning, using prototypes and similarity recognition, is proposed and elucidated using case studies. This model serves as a starting point toward bridging the gap between clinical data and accurate problem identification, verification, and management while providing a structure for a knowledge exchange between expert and non-expert clinicians.

A review on the kinetics of microbially induced calcium carbonate precipitation by urea hydrolysis

NASA Astrophysics Data System (ADS)

van Paassen, L. A.

2017-12-01

In this study the kinetics of calcium carbonate precipitation induced by the ureolytic bacteria are reviewed based on experiments and mathematical modelling. The study shows how urea hydrolysis rate depends on the amount of bacteria and the conditions during growth, storage, hydrolysis and precipitation. The dynamics of Microbially Induced Carbonate Precipitation has been monitored in non-seeded liquid batch experiments. Results show that particulary for a fast hydrolysis of urea (>1 M-urea day-1) in a highly concentrated equimolar solution with calcium chloride (>0.25 M) the solubility product of CaCO3 is exceeded within a short period (less than 30 minutes), the supersaturation remains high for an exended period, resulting in prolonged periods of nucleation and crystal growth and extended growth of metastable precursor mineral phases. The pH, being a result of the speciation, quickly rises until critical supersaturation is reached and precipitation is initiated. Then pH drops (sometimes showing oscillating behaviour) to about neutral where it stays until all substrates are depleted. Higher hydrolysis rates lead to higher supersaturation and pH and relatively many small crystals, whereas higher concentrations of urea and calcium chloride mainly lead to lower pH values. The conversion can be reasonably monitored by electrical conductivity and reasonably predicted, using a simplified model based on a single reaction as long as the urea hydrolysis rate is known. Complex geochemical models, which include chemical speciciation through acid-base equilibria and kinetic equations to describe mineral precipitation, do not show significant difference from the simplified model regarding the bulk chemistry and the total amount of precipitates. However, experiments show that ureolytic MICP can result in a highly variable crystal morphologies with large variation in the affected hydraulic properties when applied in a porous medium. In order to calculate the number, size and type of crystals, use of these more complex models is essential. Quantitative prediction to a level at which the pH and conductivity are simulated accurately is not yet possible as experimental data regarding the interaction between existing mineral surfaces are the surface interaction between ions and micro-organisms is still lacking.

Mapping the level of scientific reasoning skills to instructional methodologies among Malaysian science-mathematics-engineering undergraduates

NASA Astrophysics Data System (ADS)

Tajudin, Nor'ain Mohd.; Saad, Noor Shah; Rahman, Nurulhuda Abd; Yahaya, Asmayati; Alimon, Hasimah; Dollah, Mohd. Uzi; Abd Karim, Mohd. Mustaman

2012-05-01

The objectives of this quantitative survey research were (1) to establish the level of scientific reasoning (SR) skills among science, mathematics and engineering (SME) undergraduates in Malaysian Institute of Higher Learning (IHL); (b) to identify the types of instructional methods in teaching SME at universities; and (c) to map instructional methods employed to the level of SR skills among the undergraduates. There were six universities according to zone involved in this study using the stratification random sampling technique. For each university, the faculties that involved were faculties which have degree students in science, mathematics and engineering programme. A total of 975 students were participated in this study. There were two instruments used in this study namely, the Lawson Scientific Reasoning Skills Test and the Lecturers' Teaching Style Survey. The descriptive statistics and the inferential statistics such as mean, t-test and Pearson correlation were used to analyze the data. Findings of the study showed that most students had concrete level of scientific reasoning skills where the overall mean was 3.23. The expert and delegator were dominant lecturers' teaching styles according to students' perception. In addition, there was no correlation between lecturers' teaching style and the level of scientific reasoning skills. Thus, this study cannot map the dominant lecturers' teaching style to the level of scientific reasoning skills of Science, Mathematics and Engineering undergraduates in Malaysian Public Institute of Higher Learning. Nevertheless, this study gave some indications that the expert and delegator teaching styles were not contributed to the development of students' scientific reasoning skills. This study can be used as a baseline for Science, Mathematics and Engineering undergraduates' level of scientific reasoning skills in Malaysian Public Institute of Higher Learning. Overall, this study also opens an endless source of other researchers to investigate more areas on scientific reasoning skills so that the potential instructional model can be developed to enhance students' level of scientific reasoning skills in Malaysian Public Institute of Higher Learning.

Forecasting United States heartworm Dirofilaria immitis prevalence in dogs.

PubMed

Bowman, Dwight D; Liu, Yan; McMahan, Christopher S; Nordone, Shila K; Yabsley, Michael J; Lund, Robert B

2016-10-10

This paper forecasts next year's canine heartworm prevalence in the United States from 16 climate, geographic and societal factors. The forecast's construction and an assessment of its performance are described. The forecast is based on a spatial-temporal conditional autoregressive model fitted to over 31 million antigen heartworm tests conducted in the 48 contiguous United States during 2011-2015. The forecast uses county-level data on 16 predictive factors, including temperature, precipitation, median household income, local forest and surface water coverage, and presence/absence of eight mosquito species. Non-static factors are extrapolated into the forthcoming year with various statistical methods. The fitted model and factor extrapolations are used to estimate next year's regional prevalence. The correlation between the observed and model-estimated county-by-county heartworm prevalence for the 5-year period 2011-2015 is 0.727, demonstrating reasonable model accuracy. The correlation between 2015 observed and forecasted county-by-county heartworm prevalence is 0.940, demonstrating significant skill and showing that heartworm prevalence can be forecasted reasonably accurately. The forecast presented herein can a priori alert veterinarians to areas expected to see higher than normal heartworm activity. The proposed methods may prove useful for forecasting other diseases.

Nonrational Processes in Ethical Decision Making

ERIC Educational Resources Information Center

Rogerson, Mark D.; Gottlieb, Michael C.; Handelsman, Mitchell M.; Knapp, Samuel; Younggren, Jeffrey

2011-01-01

Most current ethical decision-making models provide a logical and reasoned process for making ethical judgments, but these models are empirically unproven and rely upon assumptions of rational, conscious, and quasi-legal reasoning. Such models predominate despite the fact that many nonrational factors influence ethical thought and behavior,…

Answering Questions about Complex Events

DTIC Science & Technology

2008-12-19

in their environment. To reason about events requires a means of describing, simulating, and analyzing their underlying dynamic processes . For our...that are relevant to our goal of connecting inference and reasoning about processes to answering questions about events. 11 We start with a...different event and process descriptions, ontologies, and models. 2.1.1 Logical AI In AI, formal approaches to model the ability to reason about

Ontology method for 3DGIS modeling

NASA Astrophysics Data System (ADS)

Sun, Min; Chen, Jun

2006-10-01

Data modeling is a baffling problem in 3DGIS, no satisfied solution has been provided until today, reason come from various sides. In this paper, a new solution named "Ontology method" is proposed. GIS traditional modeling method mainly focus on geometrical modeling, i.e., try to abstract geometry primitives for objects representation, this kind modeling method show it's awkward in 3DGIS modeling process. Ontology method begins modeling from establishing a set of ontology with different levels. The essential difference of this method is to swap the position of 'spatial data' and 'attribute data' in 2DGIS modeling process for 3DGIS modeling. Ontology method has great advantages in many sides, a system based on ontology is easy to realize interoperation for communication and data mining for knowledge deduction, in addition has many other advantages.

Applying Structural Equation Modeling in the Context of the Theory of Reasoned Action: Some Problems and Solutions.

ERIC Educational Resources Information Center

van den Putte, Bas; Hoogstraten, Johan

1997-01-01

Problems found in the application of structural equation modeling to the theory of reasoned action are explored, and an alternative model specification is proposed that improves the fit of the data while leaving intact the structural part of the model being tested. Problems and the proposed alternative are illustrated. (SLD)

The Difficult Process of Scientific Modelling: An Analysis Of Novices' Reasoning During Computer-Based Modelling

ERIC Educational Resources Information Center

Sins, Patrick H. M.; Savelsbergh, Elwin R.; van Joolingen, Wouter R.

2005-01-01

Although computer modelling is widely advocated as a way to offer students a deeper understanding of complex phenomena, the process of modelling is rather complex itself and needs scaffolding. In order to offer adequate support, a thorough understanding of the reasoning processes students employ and of difficulties they encounter during a…

Using lab notebooks to examine students' engagement in modeling in an upper-division electronics lab course

NASA Astrophysics Data System (ADS)

Stanley, Jacob T.; Su, Weifeng; Lewandowski, H. J.

2017-12-01

We demonstrate how students' use of modeling can be examined and assessed using student notebooks collected from an upper-division electronics lab course. The use of models is a ubiquitous practice in undergraduate physics education, but the process of constructing, testing, and refining these models is much less common. We focus our attention on a lab course that has been transformed to engage students in this modeling process during lab activities. The design of the lab activities was guided by a framework that captures the different components of model-based reasoning, called the Modeling Framework for Experimental Physics. We demonstrate how this framework can be used to assess students' written work and to identify how students' model-based reasoning differed from activity to activity. Broadly speaking, we were able to identify the different steps of students' model-based reasoning and assess the completeness of their reasoning. Varying degrees of scaffolding present across the activities had an impact on how thoroughly students would engage in the full modeling process, with more scaffolded activities resulting in more thorough engagement with the process. Finally, we identified that the step in the process with which students had the most difficulty was the comparison between their interpreted data and their model prediction. Students did not use sufficiently sophisticated criteria in evaluating such comparisons, which had the effect of halting the modeling process. This may indicate that in order to engage students further in using model-based reasoning during lab activities, the instructor needs to provide further scaffolding for how students make these types of experimental comparisons. This is an important design consideration for other such courses attempting to incorporate modeling as a learning goal.

The use of the BDA Case Mix Model to assess the need for referral of patients to specialist dental services.

PubMed

AlKindi, N A; Nunn, J

2016-04-22

Access to health services is a right for every individual. However, there is evidence that people with disabilities face barriers in accessing dental health. One of the reasons associated with this is the unclear referral pathway existing in the Irish dental health service. The appropriate assignment of patients to relevant services is an important issue to ensure better access to healthcare. This is all the more pertinent because there are only a few trained dental practitioners to provide dental treatment for people with disabilities, as well as even fewer qualified specialists in special care dentistry. The aim of this part of the study was to assess the use of the BDA Case Mix Model to determine the need for referral of patients to specialist dental services, and to determine any association between patient complexity and the need for adjunct measures, such as sedation and general anaesthesia for the management of people with disabilities and complex needs. A retrospective analysis of dental records using the BDA Case Mix Model.Results The results showed that patients with different levels of complexities were being referred to the special care dentistry clinic at the Dublin Dental University Hospital. The results also showed that the need for supportive adjunct measures such as sedation and general anaesthesia was not necessarily the main reason for referring patients to specialist services. The assessment with the BDA Case Mix Model was comprehensive as it looked at many factors contributing to the cases' complexity. Not all categories in the Case Mix Model had significant association with the need for an adjunct.Conclusion The BDA Case Mix Model can be used to measure the need for supportive adjunct measures, such as sedation and general anaesthesia.

Effects of cognitive training on change in accuracy in inductive reasoning ability.

PubMed

Boron, Julie Blaskewicz; Turiano, Nicholas A; Willis, Sherry L; Schaie, K Warner

2007-05-01

We investigated cognitive training effects on accuracy and number of items attempted in inductive reasoning performance in a sample of 335 older participants (M = 72.78 years) from the Seattle Longitudinal Study. We assessed the impact of individual characteristics, including chronic disease. The reasoning training group showed significantly greater gain in accuracy and number of attempted items than did the comparison group; gain was primarily due to enhanced accuracy. Reasoning training effects involved a complex interaction of gender, prior cognitive status, and chronic disease. Women with prior decline on reasoning but no heart disease showed the greatest accuracy increase. In addition, stable reasoning-trained women with heart disease demonstrated significant accuracy gain. Comorbidity was associated with less change in accuracy. The results support the effectiveness of cognitive training on improving the accuracy of reasoning performance.

To Reason or Not to Reason: Is Autobiographical Reasoning Always Beneficial?

ERIC Educational Resources Information Center

McLean, Kate C.; Mansfield, Cade D.

2011-01-01

Autobiographical reasoning has been found to be a critical process in identity development; however, the authors suggest that existing research shows that such reasoning may not always be critical to another important outcome: well-being. The authors describe characteristics of people such as personality and age, contexts such as conversations,…

Aspects of Theory of Mind that attenuate the relationship between persecutory delusions and social functioning in schizophrenia spectrum disorders.

PubMed

Phalen, Peter L; Dimaggio, Giancarlo; Popolo, Raffaele; Lysaker, Paul H

2017-09-01

Despite the apparent relevance of persecutory delusions to social relationships, evidence linking these beliefs to social functioning has been inconsistent. In this study, we examined the hypothesis that theory of mind moderates the relationship between persecutory delusions and social functioning. 88 adults with schizophrenia or schizoaffective disorder were assessed concurrently for social functioning, severity of persecutory delusions, and two components of theory of mind: mental state decoding and mental state reasoning. Mental state decoding was assessed using the Eyes Test, mental state reasoning using the Hinting Task, and social functioning assessed with the Social Functioning Scale. Moderation effects were evaluated using linear models and the Johnson-Neyman procedure. Mental state reasoning was found to moderate the relationship between persecutory delusions and social functioning, controlling for overall psychopathology. For participants with reasoning scores in the bottom 78th percentile, persecutory delusions showed a significant negative relationship with social functioning. However, for those participants with mental state reasoning scores in the top 22nd percentile, more severe persecutory delusions were not significantly associated with worse social functioning. Mental state decoding was not a statistically significant moderator. Generalizability is limited as participants were generally men in later phases of illness. Mental state reasoning abilities may buffer the impact of persecutory delusions on social functioning, possibly by helping individuals avoid applying global beliefs of persecution to specific individuals or by allowing for the correction of paranoid inferences. Published by Elsevier Ltd.

6 Principles for Quantitative Reasoning and Modeling

ERIC Educational Resources Information Center

Weber, Eric; Ellis, Amy; Kulow, Torrey; Ozgur, Zekiye

2014-01-01

Encouraging students to reason with quantitative relationships can help them develop, understand, and explore mathematical models of real-world phenomena. Through two examples--modeling the motion of a speeding car and the growth of a Jactus plant--this article describes how teachers can use six practical tips to help students develop quantitative…

Reasoning About Relations

ERIC Educational Resources Information Center

Goodwin, Geoffrey P.; Johnson-Laird, P. N.

2005-01-01

Inferences about spatial, temporal, and other relations are ubiquitous. This article presents a novel model-based theory of such reasoning. The theory depends on 5 principles. (a) The structure of mental models is iconic as far as possible. (b) The logical consequences of relations emerge from models constructed from the meanings of the relations…

Reasoning with Causal Cycles

ERIC Educational Resources Information Center

Rehder, Bob

2017-01-01

This article assesses how people reason with categories whose features are related in causal cycles. Whereas models based on causal graphical models (CGMs) have enjoyed success modeling category-based judgments as well as a number of other cognitive phenomena, CGMs are only able to represent causal structures that are acyclic. A number of new…

Deep Learning Improves Antimicrobial Peptide Recognition.

PubMed

Veltri, Daniel; Kamath, Uday; Shehu, Amarda

2018-03-24

Bacterial resistance to antibiotics is a growing concern. Antimicrobial peptides (AMPs), natural components of innate immunity, are popular targets for developing new drugs. Machine learning methods are now commonly adopted by wet-laboratory researchers to screen for promising candidates. In this work we utilize deep learning to recognize antimicrobial activity. We propose a neural network model with convolutional and recurrent layers that leverage primary sequence composition. Results show that the proposed model outperforms state-of-the-art classification models on a comprehensive data set. By utilizing the embedding weights, we also present a reduced-alphabet representation and show that reasonable AMP recognition can be maintained using nine amino-acid types. Models and data sets are made freely available through the Antimicrobial Peptide Scanner vr.2 web server at: www.ampscanner.com. amarda@gmu.edu for general inquiries and dan.veltri@gmail.com for web server information. Supplementary data are available at Bioinformatics online.

Kaiser Permanente-Sandia National Health Care Model: Phase 1 prototype final report. Part 2 -- Domain analysis

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

Edwards, D.; Yoshimura, A.; Butler, D.

This report describes the results of a Cooperative Research and Development Agreement between Sandia National Laboratories and Kaiser Permanente Southern California to develop a prototype computer model of Kaiser Permanente`s health care delivery system. As a discrete event simulation, SimHCO models for each of 100,000 patients the progression of disease, individual resource usage, and patient choices in a competitive environment. SimHCO is implemented in the object-oriented programming language C{sup 2}, stressing reusable knowledge and reusable software components. The versioned implementation of SimHCO showed that the object-oriented framework allows the program to grow in complexity in an incremental way. Furthermore, timingmore » calculations showed that SimHCO runs in a reasonable time on typical workstations, and that a second phase model will scale proportionally and run within the system constraints of contemporary computer technology.« less

Answer Sets in a Fuzzy Equilibrium Logic

NASA Astrophysics Data System (ADS)

Schockaert, Steven; Janssen, Jeroen; Vermeir, Dirk; de Cock, Martine

Since its introduction, answer set programming has been generalized in many directions, to cater to the needs of real-world applications. As one of the most general “classical” approaches, answer sets of arbitrary propositional theories can be defined as models in the equilibrium logic of Pearce. Fuzzy answer set programming, on the other hand, extends answer set programming with the capability of modeling continuous systems. In this paper, we combine the expressiveness of both approaches, and define answer sets of arbitrary fuzzy propositional theories as models in a fuzzification of equilibrium logic. We show that the resulting notion of answer set is compatible with existing definitions, when the syntactic restrictions of the corresponding approaches are met. We furthermore locate the complexity of the main reasoning tasks at the second level of the polynomial hierarchy. Finally, as an illustration of its modeling power, we show how fuzzy equilibrium logic can be used to find strong Nash equilibria.

Mechanical-magnetic-electric coupled behaviors for stress-driven Terfenol-D energy harvester

NASA Astrophysics Data System (ADS)

Cao, Shuying; Zheng, Jiaju; Wang, Bowen; Pan, Ruzheng; Zhao, Ran; Weng, Ling; Sun, Ying; Liu, Chengcheng

2017-05-01

The stress-driven Terfernol-D energy harvester exhibits the nonlinear mechanical-magnetic-electric coupled (MMEC) behaviors and the eddy current effects. To analyze and design the device, it is necessary to establish an accurate model of the device. Based on the effective magnetic field expression, the constitutive equations with eddy currents and variable coefficients, and the dynamic equations, a nonlinear dynamic MMEC model for the device is founded. Comparisons between the measured and calculated results show that the model can describe the nonlinear coupled curves of magnetization versus stress and strain versus stress under different bias fields, and can provide the reasonable data trends of piezomagnetic coefficients, Young's modulus and relative permeability for Terfenol-D. Moreover, the calculated power results show that the model can determine the optimal bias conditions, optimal resistance, suitable proof mass, suitable slices for the maximum energy extraction of the device under broad stress amplitude and broad frequency.

Selective advantage of tolerant cultural traits in the Axelrod-Schelling model

NASA Astrophysics Data System (ADS)

Gracia-Lázaro, C.; Floría, L. M.; Moreno, Y.

2011-05-01

The Axelrod-Schelling model incorporates into the original Axelrod’s model of cultural dissemination the possibility that cultural agents placed in culturally dissimilar environments move to other places, the strength of this mobility being controlled by an intolerance parameter. By allowing heterogeneity in the intolerance of cultural agents, and considering it as a cultural feature, i.e., susceptible of cultural transmission (thus breaking the original symmetry of Axelrod-Schelling dynamics), we address here the question of whether tolerant or intolerant traits are more likely to become dominant in the long-term cultural dynamics. Our results show that tolerant traits possess a clear selective advantage in the framework of the Axelrod-Schelling model. We show that the reason for this selective advantage is the development, as time evolves, of a positive correlation between the number of neighbors that an agent has in its environment and its tolerant character.

Selective advantage of tolerant cultural traits in the Axelrod-Schelling model.

PubMed

Gracia-Lázaro, C; Floría, L M; Moreno, Y

2011-05-01

The Axelrod-Schelling model incorporates into the original Axelrod's model of cultural dissemination the possibility that cultural agents placed in culturally dissimilar environments move to other places, the strength of this mobility being controlled by an intolerance parameter. By allowing heterogeneity in the intolerance of cultural agents, and considering it as a cultural feature, i.e., susceptible of cultural transmission (thus breaking the original symmetry of Axelrod-Schelling dynamics), we address here the question of whether tolerant or intolerant traits are more likely to become dominant in the long-term cultural dynamics. Our results show that tolerant traits possess a clear selective advantage in the framework of the Axelrod-Schelling model. We show that the reason for this selective advantage is the development, as time evolves, of a positive correlation between the number of neighbors that an agent has in its environment and its tolerant character. © 2011 American Physical Society

Constructing Models in Teaching of Chemical Bonds: Ionic Bond, Covalent Bond, Double and Triple Bonds, Hydrogen Bond and Molecular Geometry

ERIC Educational Resources Information Center

Uce, Musa

2015-01-01

Studies in chemistry education show that chemistry topics are considered as abstract, complicated and hard to understand by students. For this reason, it is important to develop new materials and use them in classes for better understanding of abstract concepts. Moving from this point, a student-centered research guided by a teacher was conducted…

Do Different Value-Added Models Tell Us the Same Things? What We Know Series: Value-Added Methods and Applications. Knowledge Brief 4

ERIC Educational Resources Information Center

Goldhaber, Dan; Theobald, Roddy

2012-01-01

There are good reasons for re-thinking teacher evaluation. Evaluation systems in most school districts appear to be far from rigorous. A recent study showed that more than 99 percent of teachers in a number of districts were rated "satisfactory," which does not comport with empirical evidence that teachers differ substantially from each…

The Array Representation and Primary Children's Understanding and Reasoning in Multiplication

ERIC Educational Resources Information Center

Barmby, Patrick; Harries, Tony; Higgins, Steve; Suggate, Jennifer

2009-01-01

We examine whether the array representation can support children's understanding and reasoning in multiplication. To begin, we define what we mean by understanding and reasoning. We adopt a "representational-reasoning" model of understanding, where understanding is seen as connections being made between mental representations of concepts, with…

Approximate spatial reasoning

NASA Technical Reports Server (NTRS)

Dutta, Soumitra

1988-01-01

A model for approximate spatial reasoning using fuzzy logic to represent the uncertainty in the environment is presented. Algorithms are developed which can be used to reason about spatial information expressed in the form of approximate linguistic descriptions similar to the kind of spatial information processed by humans. Particular attention is given to static spatial reasoning.

Gas-phase geometry optimization of biological molecules as a reasonable alternative to a continuum environment description: fact, myth, or fiction?

PubMed

Sousa, Sérgio Filipe; Fernandes, Pedro Alexandrino; Ramos, Maria João

2009-12-31

Gas-phase optimization of single biological molecules and of small active-site biological models has become a standard approach in first principles computational enzymology. The important role played by the surrounding environment (solvent, enzyme, both) is normally only accounted for through higher-level single point energy calculations performed using a polarizable continuum model (PCM) and an appropriate dielectric constant with the gas-phase-optimized geometries. In this study we analyze this widely used approximation, by comparing gas-phase-optimized geometries with geometries optimized with different PCM approaches (and considering different dielectric constants) for a representative data set of 20 very important biological molecules--the 20 natural amino acids. A total of 323 chemical bonds and 469 angles present in standard amino acid residues were evaluated. The results show that the use of gas-phase-optimized geometries can in fact be quite a reasonable alternative to the use of the more computationally intensive continuum optimizations, providing a good description of bond lengths and angles for typical biological molecules, even for charged amino acids, such as Asp, Glu, Lys, and Arg. This approximation is particularly successful if the protonation state of the biological molecule could be reasonably described in vacuum, a requirement that was already necessary in first principles computational enzymology.

An integrated water system model considering hydrological and biogeochemical processes at basin scale: model construction and application

NASA Astrophysics Data System (ADS)

Zhang, Y. Y.; Shao, Q. X.; Ye, A. Z.; Xing, H. T.

2014-08-01

Integrated water system modeling is a reasonable approach to provide scientific understanding and possible solutions to tackle the severe water crisis faced over the world and to promote the implementation of integrated river basin management. Such a modeling practice becomes more feasible nowadays due to better computing facilities and available data sources. In this study, the process-oriented water system model (HEXM) is developed by integrating multiple water related processes including hydrology, biogeochemistry, environment and ecology, as well as the interference of human activities. The model was tested in the Shaying River Catchment, the largest, highly regulated and heavily polluted tributary of Huai River Basin in China. The results show that: HEXM is well integrated with good performance on the key water related components in the complex catchments. The simulated daily runoff series at all the regulated and less-regulated stations matches observations, especially for the high and low flow events. The average values of correlation coefficient and coefficient of efficiency are 0.81 and 0.63, respectively. The dynamics of observed daily ammonia-nitrogen (NH4N) concentration, as an important index to assess water environmental quality in China, are well captured with average correlation coefficient of 0.66. Furthermore, the spatial patterns of nonpoint source pollutant load and grain yield are also simulated properly, and the outputs have good agreements with the statistics at city scale. Our model shows clear superior performance in both calibration and validation in comparison with the widely used SWAT model. This model is expected to give a strong reference for water system modeling in complex basins, and provide the scientific foundation for the implementation of integrated river basin management all over the world as well as the technical guide for the reasonable regulation of dams and sluices and environmental improvement in river basins.

A prognostic model for temporal courses that combines temporal abstraction and case-based reasoning.

PubMed

Schmidt, Rainer; Gierl, Lothar

2005-03-01

Since clinical management of patients and clinical research are essentially time-oriented endeavours, reasoning about time has become a hot topic in medical informatics. Here we present a method for prognosis of temporal courses, which combines temporal abstractions with case-based reasoning. It is useful for application domains where neither well-known standards, nor known periodicity, nor a complete domain theory exist. We have used our method in two prognostic applications. The first one deals with prognosis of the kidney function for intensive care patients. The idea is to elicit impairments on time, especially to warn against threatening kidney failures. Our second application deals with a completely different domain, namely geographical medicine. Its intention is to compute early warnings against approaching infectious diseases, which are characterised by irregular cyclic occurrences. So far, we have applied our program on influenza and bronchitis. In this paper, we focus on influenza forecast and show first experimental results.

Age-related increase in brain activity during task-related and -negative networks and numerical inductive reasoning

PubMed Central

Sun, Li; Liang, Peipeng; Jia, Xiuqin; Qi, Zhigang; Li, Kuncheng

2014-01-01

Objective: Recent neuroimaging studies have shown that elderly adults exhibit increased and decreased activation on various cognitive tasks, yet little is known about age-related changes in inductive reasoning. Methods: To investigate the neural basis for the aging effect on inductive reasoning, 15 young and 15 elderly subjects performed numerical inductive reasoning while in a magnetic resonance (MR) scanner. Results: Functional magnetic resonance imaging (fMRI) analysis revealed that numerical inductive reasoning, relative to rest, yielded multiple frontal, temporal, parietal, and some subcortical area activations for both age groups. In addition, the younger participants showed significant regions of task-induced deactivation, while no deactivation occurred in the elderly adults. Direct group comparisons showed that elderly adults exhibited greater activity in regions of task-related activation and areas showing task-induced deactivation (TID) in the younger group. Conclusions: Our findings suggest an age-related deficiency in neural function and resource allocation during inductive reasoning. PMID:25337240

Application of Eyring's thermal activation theory to constitutive equations for polymers

NASA Astrophysics Data System (ADS)

Zerilli, Frank J.; Armstrong, Ronald W.

2000-04-01

The application of a constitutive model based on the thermal activation theory of Eyring to the yield stress of polymethylmethacrylate at various temperatures and strain rates, as measured by Bauwens-Crowet, shows that the yield stress may reasonably well be described by a thermal activation equation in which the volume of activation is inversely proportional to the yield stress. It is found that, to obtain an accurate model, the dependence of the cold (T=0 K) yield stress on the shear modulus must be taken into account.

Analytical Performance Modeling and Validation of Intel’s Xeon Phi Architecture

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

Chunduri, Sudheer; Balaprakash, Prasanna; Morozov, Vitali

Modeling the performance of scientific applications on emerging hardware plays a central role in achieving extreme-scale computing goals. Analytical models that capture the interaction between applications and hardware characteristics are attractive because even a reasonably accurate model can be useful for performance tuning before the hardware is made available. In this paper, we develop a hardware model for Intel’s second-generation Xeon Phi architecture code-named Knights Landing (KNL) for the SKOPE framework. We validate the KNL hardware model by projecting the performance of mini-benchmarks and application kernels. The results show that our KNL model can project the performance with prediction errorsmore » of 10% to 20%. The hardware model also provides informative recommendations for code transformations and tuning.« less

Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99

USGS Publications Warehouse

Conrads, Paul; Petkewich, Matthew D.; O'Reilly, Andrew M.; Telis, Pamela A.

2015-01-01

To hindcast and fill data records, 214 empirical models were developed—189 are linear regression models and 25 are artificial neural network models. The coefficient of determination (R2) for 163 of the models is greater than 0.80 and the median percent model error (root mean square error divided by the range of the measured data) is 5 percent. To evaluate the performance of the hindcast models as a group, contour maps of modeled water-level surfaces at 2-centimeter (cm) intervals were generated using the hindcasted data. The 2-cm contour maps were examined for selected days to verify that water surfaces from the EDEN model are consistent with the input data. The biweekly 2-cm contour maps did show a higher number of issues during days in 1990 as compared to days after 1990. May 1990 had the lowest water levels in the Everglades of the 21-year dataset used for the hindcasting study. To hindcast these record low conditions in 1990, many of the hindcast models would require large extrapolations beyond the range of the predictive quality of the models. For these reasons, it was decided to limit the hindcasted data to the period January 1, 1991, to December 31, 1999. Overall, the hindcasted and gap-filled data are assumed to provide reasonable estimates of station-specific water-level data for an extended historical period to inform research and natural resource management in the Everglades.

Preservice Biology Teachers' Conceptions About the Tentative Nature of Theories and Models in Biology

NASA Astrophysics Data System (ADS)

Reinisch, Bianca; Krüger, Dirk

2018-02-01

In research on the nature of science, there is a need to investigate the role and status of different scientific knowledge forms. Theories and models are two of the most important knowledge forms within biology and are the focus of this study. During interviews, preservice biology teachers ( N = 10) were asked about their understanding of theories and models. They were requested to give reasons why they see theories and models as either tentative or certain constructs. Their conceptions were then compared to philosophers' positions (e.g., Popper, Giere). A category system was developed from the qualitative content analysis of the interviews. These categories include 16 conceptions for theories ( n tentative = 11; n certai n = 5) and 18 conceptions for models ( n tentative = 10; n certain = 8). The analysis of the interviews showed that the preservice teachers gave reasons for the tentativeness or certainty of theories and models either due to their understanding of the terms or due to their understanding of the generation or evaluation of theories and models. Therefore, a variety of different terminology, from different sources, should be used in learning-teaching situations. Additionally, an understanding of which processes lead to the generation, evaluation, and refinement or rejection of theories and models should be discussed with preservice teachers. Within philosophy of science, there has been a shift from theories to models. This should be transferred to educational contexts by firstly highlighting the role of models and also their connections to theories.

Quantum Structure in Cognition and the Foundations of Human Reasoning

NASA Astrophysics Data System (ADS)

Aerts, Diederik; Sozzo, Sandro; Veloz, Tomas

2015-12-01

Traditional cognitive science rests on a foundation of classical logic and probability theory. This foundation has been seriously challenged by several findings in experimental psychology on human decision making. Meanwhile, the formalism of quantum theory has provided an efficient resource for modeling these classically problematical situations. In this paper, we start from our successful quantum-theoretic approach to the modeling of concept combinations to formulate a unifying explanatory hypothesis. In it, human reasoning is the superposition of two processes - a conceptual reasoning, whose nature is emergence of new conceptuality, and a logical reasoning, founded on an algebraic calculus of the logical type. In most cognitive processes however, the former reasoning prevails over the latter. In this perspective, the observed deviations from classical logical reasoning should not be interpreted as biases but, rather, as natural expressions of emergence in its deepest form.

Estimation of the monthly average daily solar radiation using geographic information system and advanced case-based reasoning.

PubMed

Koo, Choongwan; Hong, Taehoon; Lee, Minhyun; Park, Hyo Seon

2013-05-07

The photovoltaic (PV) system is considered an unlimited source of clean energy, whose amount of electricity generation changes according to the monthly average daily solar radiation (MADSR). It is revealed that the MADSR distribution in South Korea has very diverse patterns due to the country's climatic and geographical characteristics. This study aimed to develop a MADSR estimation model for the location without the measured MADSR data, using an advanced case based reasoning (CBR) model, which is a hybrid methodology combining CBR with artificial neural network, multiregression analysis, and genetic algorithm. The average prediction accuracy of the advanced CBR model was very high at 95.69%, and the standard deviation of the prediction accuracy was 3.67%, showing a significant improvement in prediction accuracy and consistency. A case study was conducted to verify the proposed model. The proposed model could be useful for owner or construction manager in charge of determining whether or not to introduce the PV system and where to install it. Also, it would benefit contractors in a competitive bidding process to accurately estimate the electricity generation of the PV system in advance and to conduct an economic and environmental feasibility study from the life cycle perspective.

Gender differences in condom use prediction with Theory of Reasoned Action and Planned Behaviour: the role of self-efficacy and control.

PubMed

Muñoz-Silva, A; Sánchez-García, M; Nunes, C; Martins, A

2007-10-01

There is much evidence that demonstrates that programs and interventions based on the theoretical models of the Theory of Reasoned Action (TRA) and the Theory of Planned Behaviour (TPB) have been effective in the prevention of the sexual transmission of HIV. The objective of this work is to compare the effectiveness of both models in the prediction of condom use, distinguishing two components inside the variable Perceived Behavioural Control of the TPB model: self-efficacy and control. The perspective of gender differences is also added. The study was carried out in a sample of 601 Portuguese and Spanish university students. The results show that the females have a higher average in all the TPB variables than males, except in the frequency of condom use: females request the use of condoms less frequently than males. On the other hand, for both females and males the TPB model predicts better condom-use intention than the TRA. However there are no differences between the two models in relation to the prediction of condom-use behaviour. For prediction of intention, the most outstanding variable among females is attitude, while among males they are subjective norm and self-efficacy. Finally, we analyze the implications of these data from a theoretical and practical point of view.

Application of Precipitate Free Zone Growth Kinetics to the β-Phase Depletion Behavior in a CoNiCrAlY Coating Alloy: An Analytical Approach

NASA Astrophysics Data System (ADS)

Chen, H.

2018-06-01

This paper concerns the β-phase depletion kinetics of a thermally sprayed free-standing CoNiCrAlY (Co-31.7 pct Ni-20.8 pct Cr-8.1 pct Al-0.5 pct Y, all in wt pct) coating alloy. An analytical β-phase depletion model based on the precipitate free zone growth kinetics was developed to calculate the β-phase depletion kinetics during isothermal oxidation. This approach, which accounts for the molar volume of the alloy, the interfacial energy of the γ/ β interface, and the Al concentration at γ/ γ + β boundary, requires the Al concentrations in the β-phase depletion zone as the input rather than the oxidation kinetics at the oxide/coating interface. The calculated β-phase depletion zones derived from the current model were compared with experimental results. It is shown that the calculated β-phase depletion zones using the current model are in reasonable agreement with those obtained experimentally. The constant compositional terms used in the model are likely to cause the discrepancies between the model predictions and experimental results. This analytical approach, which shows a reasonable correlation with experimental results, demonstrates a good reliability in the fast evaluation on lifetime prediction of MCrAlY coatings.

Application of Precipitate Free Zone Growth Kinetics to the β-Phase Depletion Behavior in a CoNiCrAlY Coating Alloy: An Analytical Approach

NASA Astrophysics Data System (ADS)

Chen, H.

2018-03-01

This paper concerns the β-phase depletion kinetics of a thermally sprayed free-standing CoNiCrAlY (Co-31.7 pct Ni-20.8 pct Cr-8.1 pct Al-0.5 pct Y, all in wt pct) coating alloy. An analytical β-phase depletion model based on the precipitate free zone growth kinetics was developed to calculate the β-phase depletion kinetics during isothermal oxidation. This approach, which accounts for the molar volume of the alloy, the interfacial energy of the γ/β interface, and the Al concentration at γ/γ + β boundary, requires the Al concentrations in the β-phase depletion zone as the input rather than the oxidation kinetics at the oxide/coating interface. The calculated β-phase depletion zones derived from the current model were compared with experimental results. It is shown that the calculated β-phase depletion zones using the current model are in reasonable agreement with those obtained experimentally. The constant compositional terms used in the model are likely to cause the discrepancies between the model predictions and experimental results. This analytical approach, which shows a reasonable correlation with experimental results, demonstrates a good reliability in the fast evaluation on lifetime prediction of MCrAlY coatings.

The Comparison of Inductive Reasoning under Risk Conditions between Chinese and Japanese Based on Computational Models: Toward the Application to CAE for Foreign Language

ERIC Educational Resources Information Center

Zhang, Yujie; Terai, Asuka; Nakagawa, Masanori

2013-01-01

Inductive reasoning under risk conditions is an important thinking process not only for sciences but also in our daily life. From this viewpoint, it is very useful for language learning to construct computational models of inductive reasoning which realize the CAE for foreign languages. This study proposes the comparison of inductive reasoning…

Massive integration of diverse protein quality assessment methods to improve template based modeling in CASP11.

PubMed

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2016-09-01

Model evaluation and selection is an important step and a big challenge in template-based protein structure prediction. Individual model quality assessment methods designed for recognizing some specific properties of protein structures often fail to consistently select good models from a model pool because of their limitations. Therefore, combining multiple complimentary quality assessment methods is useful for improving model ranking and consequently tertiary structure prediction. Here, we report the performance and analysis of our human tertiary structure predictor (MULTICOM) based on the massive integration of 14 diverse complementary quality assessment methods that was successfully benchmarked in the 11th Critical Assessment of Techniques of Protein Structure prediction (CASP11). The predictions of MULTICOM for 39 template-based domains were rigorously assessed by six scoring metrics covering global topology of Cα trace, local all-atom fitness, side chain quality, and physical reasonableness of the model. The results show that the massive integration of complementary, diverse single-model and multi-model quality assessment methods can effectively leverage the strength of single-model methods in distinguishing quality variation among similar good models and the advantage of multi-model quality assessment methods of identifying reasonable average-quality models. The overall excellent performance of the MULTICOM predictor demonstrates that integrating a large number of model quality assessment methods in conjunction with model clustering is a useful approach to improve the accuracy, diversity, and consequently robustness of template-based protein structure prediction. Proteins 2016; 84(Suppl 1):247-259. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Combinational Reasoning of Quantitative Fuzzy Topological Relations for Simple Fuzzy Regions

PubMed Central

Liu, Bo; Li, Dajun; Xia, Yuanping; Ruan, Jian; Xu, Lili; Wu, Huanyi

2015-01-01

In recent years, formalization and reasoning of topological relations have become a hot topic as a means to generate knowledge about the relations between spatial objects at the conceptual and geometrical levels. These mechanisms have been widely used in spatial data query, spatial data mining, evaluation of equivalence and similarity in a spatial scene, as well as for consistency assessment of the topological relations of multi-resolution spatial databases. The concept of computational fuzzy topological space is applied to simple fuzzy regions to efficiently and more accurately solve fuzzy topological relations. Thus, extending the existing research and improving upon the previous work, this paper presents a new method to describe fuzzy topological relations between simple spatial regions in Geographic Information Sciences (GIS) and Artificial Intelligence (AI). Firstly, we propose a new definition for simple fuzzy line segments and simple fuzzy regions based on the computational fuzzy topology. And then, based on the new definitions, we also propose a new combinational reasoning method to compute the topological relations between simple fuzzy regions, moreover, this study has discovered that there are (1) 23 different topological relations between a simple crisp region and a simple fuzzy region; (2) 152 different topological relations between two simple fuzzy regions. In the end, we have discussed some examples to demonstrate the validity of the new method, through comparisons with existing fuzzy models, we showed that the proposed method can compute more than the existing models, as it is more expressive than the existing fuzzy models. PMID:25775452

Dual Rationality and Deliberative Agents

NASA Astrophysics Data System (ADS)

Debenham, John; Sierra, Carles

Human agents deliberate using models based on reason for only a minute proportion of the decisions that they make. In stark contrast, the deliberation of artificial agents is heavily dominated by formal models based on reason such as game theory, decision theory and logic—despite that fact that formal reasoning will not necessarily lead to superior real-world decisions. Further the Nobel Laureate Friedrich Hayek warns us of the ‘fatal conceit’ in controlling deliberative systems using models based on reason as the particular model chosen will then shape the system’s future and either impede, or eventually destroy, the subtle evolutionary processes that are an integral part of human systems and institutions, and are crucial to their evolution and long-term survival. We describe an architecture for artificial agents that is founded on Hayek’s two rationalities and supports the two forms of deliberation used by mankind.

Modeling the effects of argument length and validity on inductive and deductive reasoning.

PubMed

Rotello, Caren M; Heit, Evan

2009-09-01

In an effort to assess models of inductive reasoning and deductive reasoning, the authors, in 3 experiments, examined the effects of argument length and logical validity on evaluation of arguments. In Experiments 1a and 1b, participants were given either induction or deduction instructions for a common set of stimuli. Two distinct effects were observed: Induction judgments were more affected by argument length, and deduction judgments were more affected by validity. In Experiment 2, fluency was manipulated by displaying the materials in a low-contrast font, leading to increased sensitivity to logical validity. Several variants of 1-process and 2-process models of reasoning were assessed against the results. A 1-process model that assumed the same scale of argument strength underlies induction and deduction was not successful. A 2-process model that assumed separate, continuous informational dimensions of apparent deductive validity and associative strength gave the more successful account. (c) 2009 APA, all rights reserved.

Cohort Differences in Cognitive Aging in the Longitudinal Aging Study Amsterdam.

PubMed

Brailean, Anamaria; Huisman, Martijn; Prince, Martin; Prina, A Matthew; Deeg, Dorly J H; Comijs, Hannie

2016-09-30

This study aims to examine cohort differences in cognitive performance and rates of change in episodic memory, processing speed, inductive reasoning, and general cognitive performance and to investigate whether these cohort effects may be accounted for by education attainment. The first cohort (N = 705) was born between 1920 and 1930, whereas the second cohort (N = 646) was born between 1931 and 1941. Both birth cohorts were aged 65 to 75 years at baseline and were followed up 3 and 6 years later. Data were analyzed using linear mixed models. The later born cohort had better general cognitive performance, inductive reasoning, and processing speed at baseline, but cohort differences in inductive reasoning and general cognitive performance disappeared after adjusting for education. The later born cohort showed steeper decline in processing speed. Memory decline was steeper in the earlier born cohort but only from Time 1 to Time 3 when the same memory test was administered. Education did not account for cohort differences in cognitive decline. The later born cohort showed better initial performance in certain cognitive abilities, but no better preservation of cognitive abilities overtime compared with the earlier born cohort. These findings carry implications for healthy cognitive aging. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America.

Reasoning about instrumental and communicative agency in human infancy.

PubMed

Gergely, György; Jacob, Pierre

2012-01-01

Theoretical rationality and practical rationality are, respectively, properties of an individual's belief system and decision system. While reasoning about instrumental actions complies with practical rationality, understanding communicative actions complies with the principle of relevance. Section 2 reviews the evidence showing that young infants can reason about an agent's instrumental action by representing her subjective motivations and the episodic contents of her epistemic states (including false beliefs). Section 3 reviews the evidence showing special sensitivity in young human infants to some ostensive behavioral signals encoding an agent's communicative intention. We also address the puzzle of imitative learning of novel means actions by 1-year olds and argue that it can be resolved only by assuming that the infant construes the model's demonstration as a communicative, not an instrumental, action. Section 4 reviews the evidence for natural pedagogy, a species-unique social communicative learning mechanism that exploits human infants' receptivity to ostensive-communicative signals and enables infants to acquire kind-wide generalizations from the nonverbal demonstrations of communicative agents. We argue that the essentialist bias that has been shown to be involved in children's concepts of natural kinds also applies to infants' concepts of artifacts. We further examine how natural pedagogy may also boost inductive learning in human infancy.

Philosophical methodology and strikes.

PubMed

Thomasma, David C

1991-01-01

...how do we train residents to employ ethical reasoning? This is a good question, not only for the problem of strikes, but also for all medical training. The best method is inductive, since that most closely parallels the clinical reasoning processes that define the reality of medical practice. The strengths of inductive reasoning are that it most closely matches the realities of practice, it arises from the particular circumstances of the case, and it leads to a casuistic conclusion that applies more directly than abstract reasoning models to the problem at hand. The weaknesses, though, require that inductive models include a check and balance.

Measurement and analysis of chatter in a compliant model of a drillstring equipped with a PDC bit

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

Elsayed, M.A.; Raymond, D.W.

1999-11-09

Typical laboratory testing of Polycrystalline Diamond Compact (PDC) bits is performed on relatively rigid setups. Even in hard rock, PDC bits exhibit reasonable life using such testing schemes. Unfortunately, field experience indicates otherwise. In this paper, the authors show that introducing compliance in testing setups provides better simulation of actual field conditions. Using such a scheme, they show that chatter can be severe even in softer rock, such as sandstone, and very destructive to the cutters in hard rock, such as sierra white granite.

CFD Modeling of Superheated Fuel Sprays

NASA Technical Reports Server (NTRS)

Raju, M. S.

2008-01-01

An understanding of fuel atomization and vaporization behavior at superheat conditions is identified to be a topic of importance in the design of modern supersonic engines. As a part of the NASA aeronautics initiative, we have undertaken an assessment study to establish baseline accuracy of existing CFD models used in the evaluation of a ashing jet. In a first attempt towards attaining this goal, we have incorporated an existing superheat vaporization model into our spray solution procedure but made some improvements to combine the existing models valid at superheated conditions with the models valid at stable (non-superheat) evaporating conditions. Also, the paper reports some validation results based on the experimental data obtained from the literature for a superheated spray generated by the sudden release of pressurized R134A from a cylindrical nozzle. The predicted profiles for both gas and droplet velocities show a reasonable agreement with the measured data and exhibit a self-similar pattern similar to the correlation reported in the literature. Because of the uncertainty involved in the specification of the initial conditions, we have investigated the effect of initial droplet size distribution on the validation results. The predicted results were found to be sensitive to the initial conditions used for the droplet size specification. However, it was shown that decent droplet size comparisons could be achieved with properly selected initial conditions, For the case considered, it is reasonable to assume that the present vaporization models are capable of providing a reasonable qualitative description for the two-phase jet characteristics generated by a ashing jet. However, there remains some uncertainty with regard to the specification of certain initial spray conditions and there is a need for experimental data on separate gas and liquid temperatures in order to validate the vaporization models based on the Adachi correlation for a liquid involving R134A.

Professional development design considerations in climate change education: teacher enactment and student learning

NASA Astrophysics Data System (ADS)

Drewes, Andrea; Henderson, Joseph; Mouza, Chrystalla

2018-01-01

Climate change is one of the most pressing challenges facing society, and climate change educational models are emerging in response. This study investigates the implementation and enactment of a climate change professional development (PD) model for science educators and its impact on student learning. Using an intrinsic case study methodology, we focused analytic attention on how one teacher made particular pedagogical and content decisions, and the implications for student's conceptual learning. Using anthropological theories of conceptual travel, we traced salient ideas through instructional delivery and into student reasoning. Analysis showed that students gained an increased understanding of the enhanced greenhouse effect and the implications of human activity on this enhanced effect at statistically significant levels and with moderate effect sizes. However, students demonstrated a limited, though non-significant gain on the likely effects of climate change. Student reasoning on the tangible actions to deal with these problems also remained underdeveloped, reflecting omissions in both PD and teacher enactment. We discuss implications for the emerging field of climate change education.

Dyslexia and reasoning: the importance of visual processes.

PubMed

Bacon, Alison M; Handley, Simon J

2010-08-01

Recent research has suggested that individuals with dyslexia rely on explicit visuospatial representations for syllogistic reasoning while most non-dyslexics opt for an abstract verbal strategy. This paper investigates the role of visual processes in relational reasoning amongst dyslexic reasoners. Expt 1 presents written and verbal protocol evidence to suggest that reasoners with dyslexia generate detailed representations of relational properties and use these to make a visual comparison of objects. Non-dyslexics use a linear array of objects to make a simple transitive inference. Expt 2 examined evidence for the visual-impedance effect which suggests that visual information detracts from reasoning leading to longer latencies and reduced accuracy. While non-dyslexics showed the impedance effects predicted, dyslexics showed only reduced accuracy on problems designed specifically to elicit imagery. Expt 3 presented problems with less semantically and visually rich content. The non-dyslexic group again showed impedance effects, but dyslexics did not. Furthermore, in both studies, visual memory predicted reasoning accuracy for dyslexic participants, but not for non-dyslexics, particularly on problems with highly visual content. The findings are discussed in terms of the importance of visual and semantic processes in reasoning for individuals with dyslexia, and we argue that these processes play a compensatory role, offsetting phonological and verbal memory deficits.

[Modeling and experimental study on frequency-domain electricity properties of biological materials].

PubMed

Tian, Hua; Luo, Shiqiang; Zhang, Rui; Yang, Gang; Huang, Hua

2009-12-01

Frequency-domain electricity properties of four objects, including bullfrog skin, bullfrog muscle, triply distilled water and 0.9% NaCl, were tested in the range of 100Hz-10MHz using home-made electrode and measuring system. The experimental results showed that the resistance of 0.9% NaCl decreased dramatically, that the amplitude frequency characteristics of bullfrog's muscle and skin were similar, but that of triply distilled water did not change significantly. The frequency dependence of 0.9% NaCl showed that the electrode had great influence on the measuring system, so a new equivalent circuit model based on the electrode system was needed. These findings suggest that the new five-parameter equivalent circuit model, which embodies considerations on the interaction between electrodes and tissues, is a reasonable equivalent circuit for studying the electrical characteristics of biological materials.

Designing an Effective In-School Suspension Program to Change Student Behavior.

ERIC Educational Resources Information Center

Sheets, John

1996-01-01

All in-school suspension (ISS) models can be classified into punitive, problem-solving, academic, and individual models. The individual model is most reasonable, since it assumes that reasons for misbehavior vary from student to student. ISS programs can help modify student misbehavior, protect the overall learning environment by isolating…

Effect of the Implicit Combinatorial Model on Combinatorial Reasoning in Secondary School Pupils.

ERIC Educational Resources Information Center

Batanero, Carmen; And Others

1997-01-01

Elementary combinatorial problems may be classified into three different combinatorial models: (1) selection; (2) partition; and (3) distribution. The main goal of this research was to determine the effect of the implicit combinatorial model on pupils' combinatorial reasoning before and after instruction. Gives an analysis of variance of the…

The Importance of Teaching Methodology in Moral Education of Sport Populations.

ERIC Educational Resources Information Center

Stoll, Sharon Kay; And Others

Three approaches to teaching moral reasoning were implemented by expert teachers in classes at three small colleges and outcomes were compared. Teaching models included the following: Model A, a "good reasoned" approach in which students discussed scenarios and determined the best course of action; Model B, a teacher-centered lecture,…

A Modeling Approach to the Development of Students' Informal Inferential Reasoning

ERIC Educational Resources Information Center

Doerr, Helen M.; Delmas, Robert; Makar, Katie

2017-01-01

Teaching from an informal statistical inference perspective can address the challenge of teaching statistics in a coherent way. We argue that activities that promote model-based reasoning address two additional challenges: providing a coherent sequence of topics and promoting the application of knowledge to novel situations. We take a models and…

Modelling observations of the inner gas and dust coma of comet 67P/Churyumov-Gerasimenko using ROSINA/COPS and OSIRIS data: First results

NASA Astrophysics Data System (ADS)

Marschall, R.; Su, C. C.; Liao, Y.; Thomas, N.; Altwegg, K.; Sierks, H.; Ip, W.-H.; Keller, H. U.; Knollenberg, J.; Kührt, E.; Lai, I. L.; Rubin, M.; Skorov, Y.; Wu, J. S.; Jorda, L.; Preusker, F.; Scholten, F.; Gracia-Berná, A.; Gicquel, A.; Naletto, G.; Shi, X.; Vincent, J.-B.

2016-05-01

Context. This paper describes the initial modelling of gas and dust data acquired in August and September 2014 from the European Space Agency's Rosetta spacecraft when it was in close proximity to the nucleus of comet 67P/Churyumov-Gerasimenko. Aims: This work is an attempt to provide a self-consistent model of the innermost gas and dust coma of the comet, as constrained by the Rosetta Orbiter Spectrometer for Ion and Neutral Analysis (ROSINA) data set for the gas and by the Optical, Spectroscopic, and Infrared Remote Imaging System (OSIRIS) data set for the dust. Methods: The model uses a previously developed shape model for the nucleus, and from this the water sublimation rate and gas temperatures at the surface are computed with a simple thermal model. The gas expansion is modelled with a 3D parallel implementation of a Direct Simulation Monte Carlo algorithm. A dust drag algorithm is then used to produce dust densities in the coma, which are then converted to brightnesses using Mie theory and a line-of-sight integration. Results: We show that a purely insolation-driven model for surface outgassing does not produce a reasonable fit to ROSINA/COPS data. A stronger source in the "neck" region of the nucleus (region Hapi) is needed to match the observed modulation of the gas density in detail. This agrees with OSIRIS data, which shows that the dust emission from the "neck" was dominant in the August-September 2014 time frame. The current model matches this observation reasonably if a power index of 2-3 for the dust size distribution is used. A better match to the OSIRIS data is seen by using a single large particle size for the coma. Conclusions: We have shown possible solutions to the gas and dust distributions in the inner coma, which are consistent with ROSINA and OSIRIS data.

Do Different Mental Models Influence Cybersecurity Behavior? Evaluations via Statistical Reasoning Performance.

PubMed

Brase, Gary L; Vasserman, Eugene Y; Hsu, William

2017-01-01

Cybersecurity research often describes people as understanding internet security in terms of metaphorical mental models (e.g., disease risk, physical security risk, or criminal behavior risk). However, little research has directly evaluated if this is an accurate or productive framework. To assess this question, two experiments asked participants to respond to a statistical reasoning task framed in one of four different contexts (cybersecurity, plus the above alternative models). Each context was also presented using either percentages or natural frequencies, and these tasks were followed by a behavioral likelihood rating. As in previous research, consistent use of natural frequencies promoted correct Bayesian reasoning. There was little indication, however, that any of the alternative mental models generated consistently better understanding or reasoning over the actual cybersecurity context. There was some evidence that different models had some effects on patterns of responses, including the behavioral likelihood ratings, but these effects were small, as compared to the effect of the numerical format manipulation. This points to a need to improve the content of actual internet security warnings, rather than working to change the models users have of warnings.

Do Different Mental Models Influence Cybersecurity Behavior? Evaluations via Statistical Reasoning Performance

PubMed Central

Brase, Gary L.; Vasserman, Eugene Y.; Hsu, William

2017-01-01

Cybersecurity research often describes people as understanding internet security in terms of metaphorical mental models (e.g., disease risk, physical security risk, or criminal behavior risk). However, little research has directly evaluated if this is an accurate or productive framework. To assess this question, two experiments asked participants to respond to a statistical reasoning task framed in one of four different contexts (cybersecurity, plus the above alternative models). Each context was also presented using either percentages or natural frequencies, and these tasks were followed by a behavioral likelihood rating. As in previous research, consistent use of natural frequencies promoted correct Bayesian reasoning. There was little indication, however, that any of the alternative mental models generated consistently better understanding or reasoning over the actual cybersecurity context. There was some evidence that different models had some effects on patterns of responses, including the behavioral likelihood ratings, but these effects were small, as compared to the effect of the numerical format manipulation. This points to a need to improve the content of actual internet security warnings, rather than working to change the models users have of warnings. PMID:29163304

An Improved Cochlea Model with a General User Interface

NASA Astrophysics Data System (ADS)

Duifhuis, H.; Kruseman, J. M.; van Hengel, P. W. J.

2003-02-01

We have developed a flexible 1D cochlea model to test hypotheses and data against physical and mathematical constraints. The model is flexible in the sense that several linear and nonlinear model characteristics can be selected, and different boundary conditions can be tested. The software model runs at a reasonable speed at a modern PC. As an example, we will show the results of the model in comparison with the systematic study of the phase behavior (group delay) of distortion product otoacoustic emissions (DPOAEs) in the guinea pig (S. Schneider, V. Prijs and R. Schoonhoven, [9]). We also will demonstrate the effects of some common non-physical boundary conditions. Finally, we briefly indicate that this model of the auditory periphery provides a superior front end for an ASR (automatic speech recognition)-system.

Inverse reasoning processes in obsessive-compulsive disorder.

PubMed

Wong, Shiu F; Grisham, Jessica R

2017-04-01

The inference-based approach (IBA) is one cognitive model that aims to explain the aetiology and maintenance of obsessive-compulsive disorder (OCD). The model proposes that certain reasoning processes lead an individual with OCD to confuse an imagined possibility with an actual probability, a state termed inferential confusion. One such reasoning process is inverse reasoning, in which hypothetical causes form the basis of conclusions about reality. Although previous research has found associations between a self-report measure of inferential confusion and OCD symptoms, evidence of a specific association between inverse reasoning and OCD symptoms is lacking. In the present study, we developed a task-based measure of inverse reasoning in order to investigate whether performance on this task is associated with OCD symptoms in an online sample. The results provide some evidence for the IBA assertion: greater endorsement of inverse reasoning was significantly associated with OCD symptoms, even when controlling for general distress and OCD-related beliefs. Future research is needed to replicate this result in a clinical sample and to investigate a potential causal role for inverse reasoning in OCD. Copyright © 2016 Elsevier Ltd. All rights reserved.

A method for diagnosing time dependent faults using model-based reasoning systems

NASA Technical Reports Server (NTRS)

Goodrich, Charles H.

1995-01-01

This paper explores techniques to apply model-based reasoning to equipment and systems which exhibit dynamic behavior (that which changes as a function of time). The model-based system of interest is KATE-C (Knowledge based Autonomous Test Engineer) which is a C++ based system designed to perform monitoring and diagnosis of Space Shuttle electro-mechanical systems. Methods of model-based monitoring and diagnosis are well known and have been thoroughly explored by others. A short example is given which illustrates the principle of model-based reasoning and reveals some limitations of static, non-time-dependent simulation. This example is then extended to demonstrate representation of time-dependent behavior and testing of fault hypotheses in that environment.

Sensemaking Strategies for Ethical Decision-making.

PubMed

Caughron, Jay J; Antes, Alison L; Stenmark, Cheryl K; Thiel, Chaise E; Wang, Xiaoqian; Mumford, Michael D

2011-01-01

The current study uses a sensemaking model and thinking strategies identified in earlier research to examine ethical decision-making. Using a sample of 163 undergraduates, a low fidelity simulation approach is used to study the effects personal involvement (in causing the problem and personal involvement in experiencing the outcomes of the problem) could have on the use of cognitive reasoning strategies that have been shown to promote ethical decision-making. A mediated model is presented which suggests that environmental factors influence reasoning strategies, reasoning strategies influence sensemaking, and sensemaking in turn influences ethical decision-making. Findings were mixed but generally supported the hypothesized model. Interestingly, framing the outcomes of ethically charged situations in terms of more global organizational outcomes rather than personal outcomes was found to promote the use of pro-ethical cognitive reasoning strategies.

Sensemaking Strategies for Ethical Decision-making

PubMed Central

Caughron, Jay J.; Antes, Alison L.; Stenmark, Cheryl K.; Thiel, Chaise E.; Wang, Xiaoqian; Mumford, Michael D.

2015-01-01

The current study uses a sensemaking model and thinking strategies identified in earlier research to examine ethical decision-making. Using a sample of 163 undergraduates, a low fidelity simulation approach is used to study the effects personal involvement (in causing the problem and personal involvement in experiencing the outcomes of the problem) could have on the use of cognitive reasoning strategies that have been shown to promote ethical decision-making. A mediated model is presented which suggests that environmental factors influence reasoning strategies, reasoning strategies influence sensemaking, and sensemaking in turn influences ethical decision-making. Findings were mixed but generally supported the hypothesized model. Interestingly, framing the outcomes of ethically charged situations in terms of more global organizational outcomes rather than personal outcomes was found to promote the use of pro-ethical cognitive reasoning strategies. PMID:26257505

Theory of mind broad and narrow: reasoning about social exchange engages ToM areas, precautionary reasoning does not.

PubMed

Ermer, Elsa; Guerin, Scott A; Cosmides, Leda; Tooby, John; Miller, Michael B

2006-01-01

Baron-Cohen (1995) proposed that the theory of mind (ToM) inference system evolved to promote strategic social interaction. Social exchange--a form of co-operation for mutual benefit--involves strategic social interaction and requires ToM inferences about the contents of other individuals' mental states, especially their desires, goals, and intentions. There are behavioral and neuropsychological dissociations between reasoning about social exchange and reasoning about equivalent problems tapping other, more general content domains. It has therefore been proposed that social exchange behavior is regulated by social contract algorithms: a domain-specific inference system that is functionally specialized for reasoning about social exchange. We report an fMRI study using the Wason selection task that provides further support for this hypothesis. Precautionary rules share so many properties with social exchange rules--they are conditional, deontic, and involve subjective utilities--that most reasoning theories claim they are processed by the same neurocomputational machinery. Nevertheless, neuroimaging shows that reasoning about social exchange activates brain areas not activated by reasoning about precautionary rules, and vice versa. As predicted, neural correlates of ToM (anterior and posterior temporal cortex) were activated when subjects interpreted social exchange rules, but not precautionary rules (where ToM inferences are unnecessary). We argue that the interaction between ToM and social contract algorithms can be reciprocal: social contract algorithms requires ToM inferences, but their functional logic also allows ToM inferences to be made. By considering interactions between ToM in the narrower sense (belief-desire reasoning) and all the social inference systems that create the logic of human social interaction--ones that enable as well as use inferences about the content of mental states--a broader conception of ToM may emerge: a computational model embodying a Theory of Human Nature (ToHN).

People Like Logical Truth: Testing the Intuitive Detection of Logical Value in Basic Propositions.

PubMed

Nakamura, Hiroko; Kawaguchi, Jun

2016-01-01

Recent studies on logical reasoning have suggested that people are intuitively aware of the logical validity of syllogisms or that they intuitively detect conflict between heuristic responses and logical norms via slight changes in their feelings. According to logical intuition studies, logically valid or heuristic logic no-conflict reasoning is fluently processed and induces positive feelings without conscious awareness. One criticism states that such effects of logicality disappear when confounding factors such as the content of syllogisms are controlled. The present study used abstract propositions and tested whether people intuitively detect logical value. Experiment 1 presented four logical propositions (conjunctive, biconditional, conditional, and material implications) regarding a target case and asked the participants to rate the extent to which they liked the statement. Experiment 2 tested the effects of matching bias, as well as intuitive logic, on the reasoners' feelings by manipulating whether the antecedent or consequent (or both) of the conditional was affirmed or negated. The results showed that both logicality and matching bias affected the reasoners' feelings, and people preferred logically true targets over logically false ones for all forms of propositions. These results suggest that people intuitively detect what is true from what is false during abstract reasoning. Additionally, a Bayesian mixed model meta-analysis of conditionals indicated that people's intuitive interpretation of the conditional "if p then q" fits better with the conditional probability, q given p.

Identifying the drivers of liking by investigating the reasons for (dis)liking using CATA in cross-cultural context: a case study on barbecue sauce.

PubMed

Choi, Ji-Hye; Gwak, Mi-Jin; Chung, Seo-Jin; Kim, Kwang-Ok; O'Mahony, Michael; Ishii, Rie; Bae, Ye-Won

2015-06-01

The present study cross-culturally investigated the drivers of liking for traditional and ethnic chicken marinades using descriptive analysis and consumer taste tests incorporating the check-all-that-apply (CATA) method. Seventy-three Koreans and 86 US consumers participated. The tested sauces comprised three tomato-based sauces, a teriyaki-based sauce and a Korean spicy seasoning-based sauce. Chicken breasts were marinated with each of the five barbecue sauces, grilled and served for evaluation. Descriptive analysis and consumer taste tests were conducted. Consumers rated the acceptance on a hedonic scale and checked the reasons for (dis)liking by the CATA method for each sauce. A general linear model, multiple factor analysis and chi-square analysis were conducted using the data. The results showed that the preference orders of the samples between Koreans and US consumers were strikingly similar to each other. However, the reasons for (dis)liking the samples differed cross-culturally. The drivers of liking of two sauces sharing relatively similar sensory profiles but differing significantly in hedonic ratings were effectively delineated by reasons of (dis)liking CATA results. Reasons for (dis)liking CATA proved to be a powerful supporting method to understand the internal drivers of liking which can be overlooked by generic descriptive analysis. © 2014 Society of Chemical Industry.

Impact of new particle formation on the concentrations of aerosol number and cloud condensation nuclei around Beijing

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

Matsui, H.; Koike, Makoto; Kondo, Yutaka

New particle formation (NPF) is one of the most important processes in controlling the concentrations of aerosol number (condensation nuclei, CN) and cloud condensation nuclei (CCN) in the atmosphere. In this study, we introduced a new aerosol model representation with 20 size bins between 1 nm and 10 {mu}m and activation-type and kinetic nucleation parameterizations into the WRF-chem model (called NPF-explicit WRF-chem). Model calculations were conducted in the Beijing region in China for the periods during the CARE-Beijing 2006 campaign conducted in August and September 2006. Model calculations successfully reproduced the timing of NPF and no-NPF days in the measurementsmore » (21 of 26 days). Model calculations also reproduced the subsequent rapid growth of new particles with a time scale of half a day. These results suggest that once a reasonable nucleation rate at a diameter of 1 nm is given, explicit calculations of condensation and coagulation processes can reproduce the clear contrast between NPF and no-NPF days as well as further growth up to several tens nanometers. With this reasonable representation of the NPF process, we show that NPF contributed 20-30% of CN concentrations (> 10 nm in diameter) in and around Beijing on average. We also show that NPF increases CCN concentrations at higher supersaturations (S > 0.2%), while it decreases them at lower supersaturations (S < 0.1%). This is likely because NPF suppresses the increases in both the size and hygroscopicity of pre-existing particles through the competition of condensable gases between new particles and pre-existing particles. Sensitivity calculations show that a reduction of primary aerosol emissions, such as black carbon (BC), would not necessarily decrease CCN concentrations because of an increase in NPF. Sensitivity calculations also suggest that the reduction ratio of primary aerosol and SO2 emissions will be key in enhancing or damping the BC mitigation effect.« less

Impact of new particle formation on the concentrations of aerosols and cloud condensation nuclei around Beijing

NASA Astrophysics Data System (ADS)

Matsui, H.; Koike, M.; Kondo, Y.; Takegawa, N.; Wiedensohler, A.; Fast, J. D.; Zaveri, R. A.

2011-10-01

New particle formation (NPF) is one of the most important processes in controlling the concentrations of aerosols (condensation nuclei, CN) and cloud condensation nuclei (CCN) in the atmosphere. In this study, we introduce a new aerosol model representation with 20 size bins between 1 nm and 10 μm and activation-type and kinetic nucleation parameterizations into the WRF-chem model (called NPF-explicit WRF-chem). Model calculations were conducted in the Beijing region in China for the periods during the Campaign of Air Quality Research in Beijing and Surrounding Region 2006 (CARE-Beijing 2006) campaign conducted in August and September 2006. Model calculations successfully reproduced the timing of NPF and no-NPF days in the measurements (21 of 26 days). Model calculations also reproduced the subsequent rapid growth of new particles with a time scale of half a day. These results suggest that once a reasonable nucleation rate at a diameter of 1 nm is given, explicit calculations of condensation and coagulation processes can reproduce the clear contrast between NPF and no-NPF days as well as further growth up to several tens of nanometers. With this reasonable representation of the NPF process, we show that NPF contributed 20%-30% of the CN concentrations (>10 nm in diameter) in and around Beijing on average. We also show that NPF increases CCN concentrations at higher supersaturations (S > 0.2%), while it decreases them at lower supersaturations (S < 0.1%). This is likely because NPF suppresses the increases in both the size and hygroscopicity of preexisting particles through the competition of condensable gases between new particles and preexisting particles. Sensitivity calculations show that a reduction of primary aerosol emissions, such as black carbon (BC), would not necessarily decrease CCN concentrations because of an increase in NPF. Sensitivity calculations also suggest that the reduction ratio of primary aerosol and SO2 emissions will be key in enhancing or damping the BC mitigation effect.

Naturalistic Model of Causal Reasoning: Developing an Experiential User Guide (EUG) to Understand Fusion Algorithms and Simulation Models

DTIC Science & Technology

2010-09-01

achieved; the causal reasoning involved in understanding diseases such as AIDS, yellow fever, and cholera , and the causal reasoning in understanding a...and malaria, we could start to implement prevention strategies. Once we determined that contaminated water led to cholera , we could impose...sanitation measures to prevent further outbreaks . However, when dealing with indeterminate, multi-causal situations, the picture is not so easy. We may

Parallel Critical Field in Thin Niobium Films: Comparison to Theory

NASA Astrophysics Data System (ADS)

Broussard, P. R.

2017-10-01

For the first time, a comparison to the predicted behavior for parallel critical field is carried out for the model of Kogan and the model of Hara and Nagai. In this study, thin niobium films in the moderately dirty regime were considered. Experimental values of the -C2 term are seen to be lower than those from the model of Hara and Nagai. A possible reason for this could be not including the non-spherical Fermi surface of niobium into the model. There is clearly disagreement with the model of Kogan as the films get cleaner and thinner, and two films which should be below his critical thickness still show positive values of -C2, in disagreement with his theory.

Development of constructivist theory of mind from middle childhood to early adulthood and its relation to social cognition and behavior.

PubMed

Weimer, Amy A; Parault Dowds, Susan J; Fabricius, William V; Schwanenflugel, Paula J; Suh, Go Woon

2017-02-01

Two studies examined the development of constructivist theory of mind (ToM) during late childhood and early adolescence. In Study 1, a new measure was developed to assess participants' understanding of the interpretive and constructive processes embedded in memory, comprehension, attention, comparison, planning, and inference. Using this measure, Study 2 tested a mediational model in which prosocial reasoning about conflict mediated the relation between constructivist ToM and behavior problems in high school. Results showed that the onset of constructivist ToM occurs between late childhood and early adolescence and that adolescents who have more advanced constructivist ToM have more prosocial reasoning about conflict, which in turn mediated the relation with fewer serious behavior problems in high school, after controlling for academic performance and sex. In both studies, girls showed more advanced constructivist ToM than boys in high school. Copyright © 2016 Elsevier Inc. All rights reserved.

Teaching Statistics--Despite Its Applications

ERIC Educational Resources Information Center

Ridgway, Jim; Nicholson, James; McCusker, Sean

2007-01-01

Evidence-based policy requires sophisticated modelling and reasoning about complex social data. The current UK statistics curricula do not equip tomorrow's citizens to understand such reasoning. We advocate radical curriculum reform, designed to require students to reason from complex data.

Modelling variable dropout in randomised controlled trials with longitudinal outcomes: application to the MAGNETIC study.

PubMed

Kolamunnage-Dona, Ruwanthi; Powell, Colin; Williamson, Paula Ruth

2016-04-28

Clinical trials with longitudinally measured outcomes are often plagued by missing data due to patients withdrawing or dropping out from the trial before completing the measurement schedule. The reasons for dropout are sometimes clearly known and recorded during the trial, but in many instances these reasons are unknown or unclear. Often such reasons for dropout are non-ignorable. However, the standard methods for analysing longitudinal outcome data assume that missingness is non-informative and ignore the reasons for dropout, which could result in a biased comparison between the treatment groups. In this article, as a post hoc analysis, we explore the impact of informative dropout due to competing reasons on the evaluation of treatment effect in the MAGNETIC trial, the largest randomised placebo-controlled study to date comparing the addition of nebulised magnesium sulphate to standard treatment in acute severe asthma in children. We jointly model longitudinal outcome and informative dropout process to incorporate the information regarding the reasons for dropout by treatment group. The effect of nebulised magnesium sulphate compared with standard treatment is evaluated more accurately using a joint longitudinal-competing risk model by taking account of such complexities. The corresponding estimates indicate that the rate of dropout due to good prognosis is about twice as high in the magnesium group compared with standard treatment. We emphasise the importance of identifying reasons for dropout and undertaking an appropriate statistical analysis accounting for such dropout. The joint modelling approach accounting for competing reasons for dropout is proposed as a general approach for evaluating the sensitivity of conclusions to assumptions regarding missing data in clinical trials with longitudinal outcomes. EudraCT number 2007-006227-12 . Registration date 18 Mar 2008.

Calibration of the Test of Relational Reasoning.

PubMed

Dumas, Denis; Alexander, Patricia A

2016-10-01

Relational reasoning, or the ability to discern meaningful patterns within a stream of information, is a critical cognitive ability associated with academic and professional success. Importantly, relational reasoning has been described as taking multiple forms, depending on the type of higher order relations being drawn between and among concepts. However, the reliable and valid measurement of such a multidimensional construct of relational reasoning has been elusive. The Test of Relational Reasoning (TORR) was designed to tap 4 forms of relational reasoning (i.e., analogy, anomaly, antinomy, and antithesis). In this investigation, the TORR was calibrated and scored using multidimensional item response theory in a large, representative undergraduate sample. The bifactor model was identified as the best-fitting model, and used to estimate item parameters and construct reliability. To improve the usefulness of the TORR to educators, scaled scores were also calculated and presented. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Intertwining evidence- and model-based reasoning in physics sensemaking: An example from electrostatics

NASA Astrophysics Data System (ADS)

Russ, Rosemary S.; Odden, Tor Ole B.

2017-12-01

Our field has long valued the goal of teaching students not just the facts of physics, but also the thinking and reasoning skills of professional physicists. The complexity inherent in scientific reasoning demands that we think carefully about how we conceptualize for ourselves, enact in our classes, and encourage in our students the relationship between the multifaceted practices of professional science. The current study draws on existing research in the philosophy of science and psychology to advocate for intertwining two important aspects of scientific reasoning: using evidence from experimentation and modeling. We present a case from an undergraduate physics course to illustrate how these aspects can be intertwined productively and describe specific ways in which these aspects of reasoning can mutually reinforce one another in student learning. We end by discussing implications for this work for instruction in introductory physics courses and for research on scientific reasoning at the undergraduate level.

A robot sets a table: a case for hybrid reasoning with different types of knowledge

NASA Astrophysics Data System (ADS)

Mansouri, Masoumeh; Pecora, Federico

2016-09-01

An important contribution of AI to Robotics is the model-centred approach, whereby competent robot behaviour stems from automated reasoning in models of the world which can be changed to suit different environments, physical capabilities and tasks. However models need to capture diverse (and often application-dependent) aspects of the robot's environment and capabilities. They must also have good computational properties, as robots need to reason while they act in response to perceived context. In this article, we investigate the use of a meta-CSP-based technique to interleave reasoning in diverse knowledge types. We reify the approach through a robotic waiter case study, for which a particular selection of spatial, temporal, resource and action KR formalisms is made. Using this case study, we discuss general principles pertaining to the selection of appropriate KR formalisms and jointly reasoning about them. The resulting integration is evaluated both formally and experimentally on real and simulated robotic platforms.

A concise guide to clinical reasoning.

PubMed

Daly, Patrick

2018-04-30

What constitutes clinical reasoning is a disputed subject regarding the processes underlying accurate diagnosis, the importance of patient-specific versus population-based data, and the relation between virtue and expertise in clinical practice. In this paper, I present a model of clinical reasoning that identifies and integrates the processes of diagnosis, prognosis, and therapeutic decision making. The model is based on the generalized empirical method of Bernard Lonergan, which approaches inquiry with equal attention to the subject who investigates and the object under investigation. After identifying the structured operations of knowing and doing and relating these to a self-correcting cycle of learning, I correlate levels of inquiry regarding what-is-going-on and what-to-do to the practical and theoretical elements of clinical reasoning. I conclude that this model provides a methodical way to study questions regarding the operations of clinical reasoning as well as what constitute significant clinical data, clinical expertise, and virtuous health care practice. © 2018 John Wiley & Sons, Ltd.

Agent based reasoning for the non-linear stochastic models of long-range memory

NASA Astrophysics Data System (ADS)

Kononovicius, A.; Gontis, V.

2012-02-01

We extend Kirman's model by introducing variable event time scale. The proposed flexible time scale is equivalent to the variable trading activity observed in financial markets. Stochastic version of the extended Kirman's agent based model is compared to the non-linear stochastic models of long-range memory in financial markets. The agent based model providing matching macroscopic description serves as a microscopic reasoning of the earlier proposed stochastic model exhibiting power law statistics.

Applying a Multiple Group Causal Indicator Modeling Framework to the Reading Comprehension Skills of Third, Seventh, and Tenth Grade Students

PubMed Central

Tighe, Elizabeth L.; Wagner, Richard K.; Schatschneider, Christopher

2015-01-01

This study demonstrates the utility of applying a causal indicator modeling framework to investigate important predictors of reading comprehension in third, seventh, and tenth grade students. The results indicated that a 4-factor multiple indicator multiple indicator cause (MIMIC) model of reading comprehension provided adequate fit at each grade level. This model included latent predictor constructs of decoding, verbal reasoning, nonverbal reasoning, and working memory and accounted for a large portion of the reading comprehension variance (73% to 87%) across grade levels. Verbal reasoning contributed the most unique variance to reading comprehension at all grade levels. In addition, we fit a multiple group 4-factor MIMIC model to investigate the relative stability (or variability) of the predictor contributions to reading comprehension across development (i.e., grade levels). The results revealed that the contributions of verbal reasoning, nonverbal reasoning, and working memory to reading comprehension were stable across the three grade levels. Decoding was the only predictor that could not be constrained to be equal across grade levels. The contribution of decoding skills to reading comprehension was higher in third grade and then remained relatively stable between seventh and tenth grade. These findings illustrate the feasibility of using MIMIC models to explain individual differences in reading comprehension across the development of reading skills. PMID:25821346

The inference-based approach to obsessive-compulsive disorder: A comprehensive review of its etiological model, treatment efficacy, and model of change.

PubMed

Julien, Dominic; O'Connor, Kieron; Aardema, Frederick

2016-09-15

The inference-based approach (IBA) postulates that individuals with obsessive-compulsive disorder (OCD) confuse a possibility with reality (inferential confusion) according to specific inductive reasoning devices and act as if this possibility were true. A new treatment modality, the inference-based therapy (IBT), was developed. The aim of this study was to critically review empirical evidence regarding the etiological model, treatment efficacy, and model of change of IBA. A search of the literature was conducted using PsycINFO and Medline. Thirty-four articles were included in the review. The review reveals that intrusive thoughts of non-clinical and OCD individuals may occur in different contexts. There is support for a specific inductive reasoning style in OCD. Inferential confusion is associated with OCD symptoms. There is good evidence that IBT is an efficacious treatment for OCD, including two randomized controlled trials showing that IBT was as efficacious as cognitive-behavior therapy. There is some but limited evidence that the process of change during treatment is coherent with IBA's assumptions. Key premises were investigated in only a few studies. Some of these studies were conducted in non-clinical samples or did not include an anxious control group. IBA's etiological model, treatment modality, and model of change make a significant contribution to OCD. Copyright © 2016 Elsevier B.V. All rights reserved.

Study of tissue oxygen supply rate in a macroscopic photodynamic therapy singlet oxygen model

NASA Astrophysics Data System (ADS)

Zhu, Timothy C.; Liu, Baochang; Penjweini, Rozhin

2015-03-01

An appropriate expression for the oxygen supply rate (Γs) is required for the macroscopic modeling of the complex mechanisms of photodynamic therapy (PDT). It is unrealistic to model the actual heterogeneous tumor microvascular networks coupled with the PDT processes because of the large computational requirement. In this study, a theoretical microscopic model based on uniformly distributed Krogh cylinders is used to calculate Γs=g (1-[O]/[]0) that can replace the complex modeling of blood vasculature while maintaining a reasonable resemblance to reality; g is the maximum oxygen supply rate and [O]/[]0 is the volume-average tissue oxygen concentration normalized to its value prior to PDT. The model incorporates kinetic equations of oxygen diffusion and convection within capillaries and oxygen saturation from oxyhemoglobin. Oxygen supply to the tissue is via diffusion from the uniformly distributed blood vessels. Oxygen can also diffuse along the radius and the longitudinal axis of the cylinder within tissue. The relations of Γs to [3O2]/] are examined for a biologically reasonable range of the physiological parameters for the microvasculature and several light fluence rates (ϕ). The results show a linear relationship between Γs and [3O2]/], independent of ϕ and photochemical parameters; the obtained g ranges from 0.4 to 1390 μM/s.

Diagnosing a Strong-Fault Model by Conflict and Consistency

PubMed Central

Zhou, Gan; Feng, Wenquan

2018-01-01

The diagnosis method for a weak-fault model with only normal behaviors of each component has evolved over decades. However, many systems now demand a strong-fault models, the fault modes of which have specific behaviors as well. It is difficult to diagnose a strong-fault model due to its non-monotonicity. Currently, diagnosis methods usually employ conflicts to isolate possible fault and the process can be expedited when some observed output is consistent with the model’s prediction where the consistency indicates probably normal components. This paper solves the problem of efficiently diagnosing a strong-fault model by proposing a novel Logic-based Truth Maintenance System (LTMS) with two search approaches based on conflict and consistency. At the beginning, the original a strong-fault model is encoded by Boolean variables and converted into Conjunctive Normal Form (CNF). Then the proposed LTMS is employed to reason over CNF and find multiple minimal conflicts and maximal consistencies when there exists fault. The search approaches offer the best candidate efficiency based on the reasoning result until the diagnosis results are obtained. The completeness, coverage, correctness and complexity of the proposals are analyzed theoretically to show their strength and weakness. Finally, the proposed approaches are demonstrated by applying them to a real-world domain—the heat control unit of a spacecraft—where the proposed methods are significantly better than best first and conflict directly with A* search methods. PMID:29596302

The NASA/industry Design Analysis Methods for Vibrations (DAMVIBS) program: Boeing Helicopters airframe finite element modeling

NASA Technical Reports Server (NTRS)

Gabel, R.; Lang, P.; Reed, D.

1993-01-01

Mathematical models based on the finite element method of structural analysis, as embodied in the NASTRAN computer code, are routinely used by the helicopter industry to calculate airframe static internal loads used for sizing structural members. Historically, less reliance has been placed on the vibration predictions based on these models. Beginning in the early 1980's NASA's Langley Research Center initiated an industry wide program with the objective of engendering the needed trust in vibration predictions using these models and establishing a body of modeling guides which would enable confident future prediction of airframe vibration as part of the regular design process. Emphasis in this paper is placed on the successful modeling of the Army/Boeing CH-47D which showed reasonable correlation with test data. A principal finding indicates that improved dynamic analysis requires greater attention to detail and perhaps a finer mesh, especially the mass distribution, than the usual stress model. Post program modeling efforts show improved correlation placing key modal frequencies in the b/rev range with 4 percent of the test frequencies.

Neurobiological and memory models of risky decision making in adolescents versus young adults.

PubMed

Reyna, Valerie F; Estrada, Steven M; DeMarinis, Jessica A; Myers, Regina M; Stanisz, Janine M; Mills, Britain A

2011-09-01

Predictions of fuzzy-trace theory and neurobiological approaches are examined regarding risk taking in a classic decision-making task--the framing task--as well as in the context of real-life risk taking. We report the 1st study of framing effects in adolescents versus adults, varying risk and reward, and relate choices to individual differences, sexual behavior, and behavioral intentions. As predicted by fuzzy-trace theory, adolescents modulated risk taking according to risk and reward. Adults showed standard framing, reflecting greater emphasis on gist-based (qualitative) reasoning, but adolescents displayed reverse framing when potential gains for risk taking were high, reflecting greater emphasis on verbatim-based (quantitative) reasoning. Reverse framing signals a different way of thinking compared with standard framing (reverse framing also differs from simply choosing the risky option). Measures of verbatim- and gist-based reasoning about risk, sensation seeking, behavioral activation, and inhibition were used to extract dimensions of risk proneness: Sensation seeking increased and then decreased, whereas inhibition increased from early adolescence to young adulthood, predicted by neurobiological theories. Two additional dimensions, verbatim- and gist-based reasoning about risk, loaded separately and predicted unique variance in risk taking. Importantly, framing responses predicted real-life risk taking. Reasoning was the most consistent predictor of real-life risk taking: (a) Intentions to have sex, sexual behavior, and number of partners decreased when gist-based reasoning was triggered by retrieval cues in questions about perceived risk, whereas (b) intentions to have sex and number of partners increased when verbatim-based reasoning was triggered by different retrieval cues in questions about perceived risk. (c) 2011 APA, all rights reserved.

Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI).

PubMed

Deane, Thomas; Nomme, Kathy; Jeffery, Erica; Pollock, Carol; Birol, Gülnur

2016-01-01

We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non-expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI's robustness and sensitivity in capturing useful data relating to the students' conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. © 2016 T. Deane et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Wind-Tunnel Investigation of the Low-Speed Static Stability and Control Characteristics of a Model of the Bell MX-776 (RASCAL) in Combined Angle of Attack and Sideslip

NASA Technical Reports Server (NTRS)

Letko, William

1949-01-01

An investigation has been made in the Langley stability tunnel to determine the low-speed static stability and control characteristics of a model of the Bell MX-776. The results show the model to be longitudinally unstable in the angle-of-attack range around zero angle of attack and to become stable at moderate angles of attack. The results of the present investigation agree reasonably well with results obtained in other facilities at low speed. The present pitching-moment results at low Mach numbers also agree reasonably well with unpublished results of tests of the model at supersonic Mach numbers (up to Mach number 1.86). Unpublished results at moderate and high subsonic speeds, however, indicate considerably greater instability at low angles of attack than is indicated by low-speed results. The results of the present tests also showed that the pitching-moment coefficients for angles of attack up to 12deg remained fairly constant with sideslip angle up to 12deg. The elevators tested produced relatively large pitching moments at zero angle of attack but, as the angle of attack was increased, the elevator effectiveness decreased. The rate of decrease of elevator effectiveness with angle of attack was less for 8deg than for 20deg elevator deflection. Therefore although 8deg deflection caused an appreciable change in longitudinal trim angle and trim lift coefficient a deflection of 20deg caused only a small additional increase in trim angle and trim lift coefficient.

One-dimensional turbulence modeling of a turbulent counterflow flame with comparison to DNS

DOE PAGES

Jozefik, Zoltan; Kerstein, Alan R.; Schmidt, Heiko; ...

2015-06-01

The one-dimensional turbulence (ODT) model is applied to a reactant-to-product counterflow configuration and results are compared with DNS data. The model employed herein solves conservation equations for momentum, energy, and species on a one dimensional (1D) domain corresponding to the line spanning the domain between nozzle orifice centers. The effects of turbulent mixing are modeled via a stochastic process, while the Kolmogorov and reactive length and time scales are explicitly resolved and a detailed chemical kinetic mechanism is used. Comparisons between model and DNS results for spatial mean and root-mean-square (RMS) velocity, temperature, and major and minor species profiles aremore » shown. The ODT approach shows qualitatively and quantitatively reasonable agreement with the DNS data. Scatter plots and statistics conditioned on temperature are also compared for heat release rate and all species. ODT is able to capture the range of results depicted by DNS. As a result, conditional statistics show signs of underignition.« less

Microbiology, philosophy and education.

PubMed

O'Malley, Maureen A

2016-09-01

There are not only many links between microbiological and philosophical topics, but good educational reasons for microbiologists to explore the philosophical issues in their fields. I examine three broad issues of classification, causality and model systems, showing how these philosophical dimensions have practical implications. I conclude with a discussion of the educational benefits for recognising the philosophy in microbiology. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Laser induced heat source distribution in bio-tissues

NASA Astrophysics Data System (ADS)

Li, Xiaoxia; Fan, Shifu; Zhao, Youquan

2006-09-01

During numerical simulation of laser and tissue thermal interaction, the light fluence rate distribution should be formularized and constituted to the source term in the heat transfer equation. Usually the solution of light irradiative transport equation is given in extreme conditions such as full absorption (Lambert-Beer Law), full scattering (Lubelka-Munk theory), most scattering (Diffusion Approximation) et al. But in specific conditions, these solutions will induce different errors. The usually used Monte Carlo simulation (MCS) is more universal and exact but has difficulty to deal with dynamic parameter and fast simulation. Its area partition pattern has limits when applying FEM (finite element method) to solve the bio-heat transfer partial differential coefficient equation. Laser heat source plots of above methods showed much difference with MCS. In order to solve this problem, through analyzing different optical actions such as reflection, scattering and absorption on the laser induced heat generation in bio-tissue, a new attempt was made out which combined the modified beam broaden model and the diffusion approximation model. First the scattering coefficient was replaced by reduced scattering coefficient in the beam broaden model, which is more reasonable when scattering was treated as anisotropic scattering. Secondly the attenuation coefficient was replaced by effective attenuation coefficient in scattering dominating turbid bio-tissue. The computation results of the modified method were compared with Monte Carlo simulation and showed the model provided reasonable predictions of heat source term distribution than past methods. Such a research is useful for explaining the physical characteristics of heat source in the heat transfer equation, establishing effective photo-thermal model, and providing theory contrast for related laser medicine experiments.

Scientific Reasoning in Elementary School: Developmental and Individual Differences.

ERIC Educational Resources Information Center

Bullock, Merry

Pre-adolescent children are generally characterized as incapable of applying scientific reasoning to test a causal relation. This paper describes research on children's scientific reasoning which shows that pre-adolescent children do have some systematic scientific reasoning skills. The subjects of this study were 260 second through fourth grade…

Why are some medical specialists working part-time, while others work full-time?

PubMed

de Jong, Judith D; Heiligers, Phil; Groenewegen, Peter P; Hingstman, Lammert

2006-10-01

Although medical specialists primarily work full-time, part-time work is on the increase, a trend that can be found worldwide. This article seeks to answer the question why some medical specialists work part-time, while others do not although they are willing to work part-time. Two approaches are used. First, we studied reported reasons and as a second approach we used a theoretical model, based on goal-directed behavior and restrictions. A questionnaire was sent to all internists (N=817), surgeons (N=693) and radiologists (N=621) working in general hospitals in The Netherlands. Questions were asked about personal traits, characteristics of the work situation, and motives for working full-time or part-time. Frequencies were reported for the reasons given, and multilevel analysis was used to test the theoretical model. The results show that the reported reasons for working part-time and being willing to work part-time are the same: the importance of family and leisure pursuits. The second approach showed that medical specialists working part-time tend to be female, older, and have children below the age of five. Surgeons are least likely to work part-time. A willingness to work part-time is purely individual and not related to any of the explanatory variables. We conclude that working part-time is related to both professional and personal circumstances. Policy should be aimed at removing the organizational difficulties that obstruct the realization of part-time work. Alternatively, perhaps there should be a change in working hours for all medical specialists. As the majority of all full-time working medical specialists are willing to work part-time, this might indicate that most medical specialists actually prefer "normal" working hours.

TrhOnt: building an ontology to assist rehabilitation processes.

PubMed

Berges, Idoia; Antón, David; Bermúdez, Jesús; Goñi, Alfredo; Illarramendi, Arantza

2016-10-04

One of the current research efforts in the area of biomedicine is the representation of knowledge in a structured way so that reasoning can be performed on it. More precisely, in the field of physiotherapy, information such as the physiotherapy record of a patient or treatment protocols for specific disorders must be adequately modeled, because they play a relevant role in the management of the evolutionary recovery process of a patient. In this scenario, we introduce TRHONT, an application ontology that can assist physiotherapists in the management of the patients' evolution via reasoning supported by semantic technology. The ontology was developed following the NeOn Methodology. It integrates knowledge from ontological (e.g. FMA ontology) and non-ontological resources (e.g. a database of movements, exercises and treatment protocols) as well as additional physiotherapy-related knowledge. We demonstrate how the ontology fulfills the purpose of providing a reference model for the representation of the physiotherapy-related information that is needed for the whole physiotherapy treatment of patients, since they step for the first time into the physiotherapist's office, until they are discharged. More specifically, we present the results for each of the intended uses of the ontology listed in the document that specifies its requirements, and show how TRHONT can answer the competency questions defined within that document. Moreover, we detail the main steps of the process followed to build the TRHONT ontology in order to facilitate its reproducibility in a similar context. Finally, we show an evaluation of the ontology from different perspectives. TRHONT has achieved the purpose of allowing for a reasoning process that changes over time according to the patient's state and performance.

Improving Hydrological Simulations by Incorporating GRACE Data for Parameter Calibration

NASA Astrophysics Data System (ADS)

Bai, P.

2017-12-01

Hydrological model parameters are commonly calibrated by observed streamflow data. This calibration strategy is questioned when the modeled hydrological variables of interest are not limited to streamflow. Well-performed streamflow simulations do not guarantee the reliable reproduction of other hydrological variables. One of the reasons is that hydrological model parameters are not reasonably identified. The Gravity Recovery and Climate Experiment (GRACE) satellite-derived total water storage change (TWSC) data provide an opportunity to constrain hydrological model parameterizations in combination with streamflow observations. We constructed a multi-objective calibration scheme based on GRACE-derived TWSC and streamflow observations, with the aim of improving the parameterizations of hydrological models. The multi-objective calibration scheme was compared with the traditional single-objective calibration scheme, which is based only on streamflow observations. Two monthly hydrological models were employed on 22 Chinese catchments with different hydroclimatic conditions. The model evaluation was performed using observed streamflows, GRACE-derived TWSC, and evapotranspiraiton (ET) estimates from flux towers and from the water balance approach. Results showed that the multi-objective calibration provided more reliable TWSC and ET simulations without significant deterioration in the accuracy of streamflow simulations than the single-objective calibration. In addition, the improvements of TWSC and ET simulations were more significant in relatively dry catchments than in relatively wet catchments. This study highlights the importance of including additional constraints besides streamflow observations in the parameter estimation to improve the performances of hydrological models.

The Identification and Validation Process of Proportional Reasoning Attributes: An Application of a Proportional Reasoning Modeling Framework

ERIC Educational Resources Information Center

Tjoe, Hartono; de la Torre, Jimmy

2014-01-01

In this paper, we discuss the process of identifying and validating students' abilities to think proportionally. More specifically, we describe the methodology we used to identify these proportional reasoning attributes, beginning with the selection and review of relevant literature on proportional reasoning. We then continue with the…

High-School Students' Reasoning while Constructing Plant Growth Models in a Computer-Supported Educational Environment. Research Report

ERIC Educational Resources Information Center

Ergazaki, Marida; Komis, Vassilis; Zogza, Vassiliki

2005-01-01

This paper highlights specific aspects of high-school students' reasoning while coping with a modeling task of plant growth in a computer-supported educational environment. It is particularly concerned with the modeling levels ('macro-phenomenological' and 'micro-conceptual' level) activated by peers while exploring plant growth and with their…

Model Analysis of Fine Structures of Student Models: An Example with Newton's Third Law.

ERIC Educational Resources Information Center

Bao, Lei; Hogg, Kirsten; Zollman, Dean

2002-01-01

Studies the role of context in students' uses of alternative conceptual models by using Newton's third law. Identifies four contextual features that are frequently used by students in their reasoning. Probes the effects of specific contextual features on student reasoning using a multiple-choice survey. (Contains 39 references.) (Author/YDS)

Acquiring, Representing, and Evaluating a Competence Model of Diagnostic Strategy.

ERIC Educational Resources Information Center

Clancey, William J.

This paper describes NEOMYCIN, a computer program that models one physician's diagnostic reasoning within a limited area of medicine. NEOMYCIN's knowledge base and reasoning procedure constitute a model of how human knowledge is organized and how it is used in diagnosis. The hypothesis is tested that such a procedure can be used to simulate both…

Reasoning with Conditionals: A Test of Formal Models of Four Theories

ERIC Educational Resources Information Center

Oberauer, Klaus

2006-01-01

The four dominant theories of reasoning from conditionals are translated into formal models: The theory of mental models (Johnson-Laird, P. N., & Byrne, R. M. J. (2002). Conditionals: a theory of meaning, pragmatics, and inference. "Psychological Review," 109, 646-678), the suppositional theory (Evans, J. S. B. T., & Over, D. E. (2004). "If."…

Cultural Commonalities and Differences in Spatial Problem-Solving: A Computational Analysis

ERIC Educational Resources Information Center

Lovett, Andrew; Forbus, Kenneth

2011-01-01

A fundamental question in human cognition is how people reason about space. We use a computational model to explore cross-cultural commonalities and differences in spatial cognition. Our model is based upon two hypotheses: (1) the structure-mapping model of analogy can explain the visual comparisons used in spatial reasoning; and (2) qualitative,…

Corequisite Model: An Effective Strategy for Remediation in Freshmen Level Quantitative Reasoning Course

ERIC Educational Resources Information Center

Kashyap, Upasana; Mathew, Santhosh

2017-01-01

The purpose of this study was to compare students' performances in a freshmen level quantitative reasoning course (QR) under three different instructional models. A cohort of 155 freshmen students was placed in one of the three models: needing a prerequisite course, corequisite (students enroll simultaneously in QR course and a course that…

Differentiating between precursor and control variables when analyzing reasoned action theories.

PubMed

Hennessy, Michael; Bleakley, Amy; Fishbein, Martin; Brown, Larry; Diclemente, Ralph; Romer, Daniel; Valois, Robert; Vanable, Peter A; Carey, Michael P; Salazar, Laura

2010-02-01

This paper highlights the distinction between precursor and control variables in the context of reasoned action theory. Here the theory is combined with structural equation modeling to demonstrate how age and past sexual behavior should be situated in a reasoned action analysis. A two wave longitudinal survey sample of African-American adolescents is analyzed where the target behavior is having vaginal sex. Results differ when age and past behavior are used as control variables and when they are correctly used as precursors. Because control variables do not appear in any form of reasoned action theory, this approach to including background variables is not correct when analyzing data sets based on the theoretical axioms of the Theory of Reasoned Action, the Theory of Planned Behavior, or the Integrative Model.

Differentiating Between Precursor and Control Variables When Analyzing Reasoned Action Theories

PubMed Central

Hennessy, Michael; Bleakley, Amy; Fishbein, Martin; Brown, Larry; DiClemente, Ralph; Romer, Daniel; Valois, Robert; Vanable, Peter A.; Carey, Michael P.; Salazar, Laura

2010-01-01

This paper highlights the distinction between precursor and control variables in the context of reasoned action theory. Here the theory is combined with structural equation modeling to demonstrate how age and past sexual behavior should be situated in a reasoned action analysis. A two wave longitudinal survey sample of African-American adolescents is analyzed where the target behavior is having vaginal sex. Results differ when age and past behavior are used as control variables and when they are correctly used as precursors. Because control variables do not appear in any form of reasoned action theory, this approach to including background variables is not correct when analyzing data sets based on the theoretical axioms of the Theory of Reasoned Action, the Theory of Planned Behavior, or the Integrative Model PMID:19370408

Modelling the mid-Pliocene Warm Period with the IPSLGCM: contribution to PlioMIP and feedback mechanisms from the presence of mega-lakes

NASA Astrophysics Data System (ADS)

Contoux, C.; Jost, A.; Sepulchre, P.; Ramstein, G.

2012-04-01

The mid-Pliocene Warm Period (mPWP, ca. 3.3 -3 Ma) is the last geological period showing a warmer climate than the preindustrial during a sustained period of time, much longer than interglacial periods of the last million years. Moreover, mPWP position of the continents and atmospheric pCO2 are very close to present-day, both conditions making the mPWP a relevant analogue for future global warming. For these reasons, the mPWP has been the focus of Pliocene Modelling Intercomparison Project (PlioMIP), which associates data analysis and modelling. We use the IPSLCM5 Earth System model and its atmospheric component alone (LMDZ), to simulate the climate of the mPWP. Boundary conditions such as sea surface temperatures (SSTs), topography, ice sheet extent and vegetation are the ones used within the PlioMIP framework. On a global scale we show the impact of different boundary conditions with LMDZ, and of a global coupling on the simulated climate. Results from the Earth System model are also compared to SST reconstructions, particularly in the North Atlantic Ocean, where an important warming occurs, generally poorly reproduced by models. These results will then be part of the multi-model analysis for the Pliocene. The PlioMIP exercise is also about better understanding model/data mismatches. In the present-day desertic regions of Lake Chad (Africa) and Lake Eyre (Australia), vegetation data show the presence of tropical savanna at the expense of deserts during the mPWP. Vegetation models forced by mPWP climatic simulations fail to reproduce more humid vegetation in these locations. There might be a reason for this model/data discrepancy: geological data stand for the presence of mega-lakes in these two regions during the mPWP that are not accounted for in previous simulations. Such extended waterbodies could have important feedbacks on the hydrological cycle and regional climate. We use the LMDZ4 atmospheric model imbedding explicitly resolved lake surfaces to simulate the climate under mega-lake conditions, using a zoom on the regions of interest. This allows us to determine the viability of such waterbodies under mid-Pliocene climatic conditions as well as their feedbacks on the climate system.

Beyond semantic accuracy: preschoolers evaluate a speaker's reasons.

PubMed

Koenig, Melissa A

2012-01-01

Children's sensitivity to the quality of epistemic reasons and their selective trust in the more reasonable of 2 informants was investigated in 2 experiments. Three-, 4-, and 5-year-old children (N = 90) were presented with speakers who stated different kinds of evidence for what they believed. Experiment 1 showed that children of all age groups appropriately judged looking, reliable testimony, and inference as better reasons for belief than pretense, guessing, and desiring. Experiment 2 showed that 3- and 4-year-old children preferred to seek and accept new information from a speaker who was previously judged to use the "best" way of thinking. The findings demonstrate that children distinguish certain good from bad reasons and prefer to learn from those who showcased good reasoning in the past. © 2012 The Author. Child Development © 2012 Society for Research in Child Development, Inc.

Comparison of NGA-West2 directivity models

USGS Publications Warehouse

Spudich, Paul A.; Rowshandel, Badie; Shahi, Shrey; Baker, Jack W.; Chiou, Brian S-J

2014-01-01

Five directivity models have been developed based on data from the NGA-West2 database and based on numerical simulations of large strike-slip and reverse-slip earthquakes. All models avoid the use of normalized rupture dimension, enabling them to scale up to the largest earthquakes in a physically reasonable way. Four of the five models are explicitly “narrow-band” (in which the effect of directivity is maximum at a specific period that is a function of earthquake magnitude). Several strategies for determining the zero-level for directivity have been developed. We show comparisons of maps of the directivity amplification. This comparison suggests that the predicted geographic distributions of directivity amplification are dominated by effects of the models' assumptions, and more than one model should be used for ruptures dipping less than about 65 degrees.

Safety model assessment and two-lane urban crash model

DOT National Transportation Integrated Search

2008-10-01

There are many reasons to be concerned with estimating the frequency and social costs of highway accidents, but most reasons are motivated by a desire to minimize these costs to the extent feasible. Competition for scarce resources is a practical nec...

Research of Uncertainty Reasoning in Pineapple Disease Identification System

NASA Astrophysics Data System (ADS)

Liu, Liqun; Fan, Haifeng

In order to deal with the uncertainty of evidences mostly existing in pineapple disease identification system, a reasoning model based on evidence credibility factor was established. The uncertainty reasoning method is discussed,including: uncertain representation of knowledge, uncertain representation of rules, uncertain representation of multi-evidences and update of reasoning rules. The reasoning can fully reflect the uncertainty in disease identification and reduce the influence of subjective factors on the accuracy of the system.

A comparative study of mixed exponential and Weibull distributions in a stochastic model replicating a tropical rainfall process

NASA Astrophysics Data System (ADS)

Abas, Norzaida; Daud, Zalina M.; Yusof, Fadhilah

2014-11-01

A stochastic rainfall model is presented for the generation of hourly rainfall data in an urban area in Malaysia. In view of the high temporal and spatial variability of rainfall within the tropical rain belt, the Spatial-Temporal Neyman-Scott Rectangular Pulse model was used. The model, which is governed by the Neyman-Scott process, employs a reasonable number of parameters to represent the physical attributes of rainfall. A common approach is to attach each attribute to a mathematical distribution. With respect to rain cell intensity, this study proposes the use of a mixed exponential distribution. The performance of the proposed model was compared to a model that employs the Weibull distribution. Hourly and daily rainfall data from four stations in the Damansara River basin in Malaysia were used as input to the models, and simulations of hourly series were performed for an independent site within the basin. The performance of the models was assessed based on how closely the statistical characteristics of the simulated series resembled the statistics of the observed series. The findings obtained based on graphical representation revealed that the statistical characteristics of the simulated series for both models compared reasonably well with the observed series. However, a further assessment using the AIC, BIC and RMSE showed that the proposed model yields better results. The results of this study indicate that for tropical climates, the proposed model, using a mixed exponential distribution, is the best choice for generation of synthetic data for ungauged sites or for sites with insufficient data within the limit of the fitted region.

Analysis of students’ mathematical reasoning

NASA Astrophysics Data System (ADS)

Sukirwan; Darhim; Herman, T.

2018-01-01

The reasoning is one of the mathematical abilities that have very complex implications. This complexity causes reasoning including abilities that are not easily attainable by students. Similarly, studies dealing with reason are quite diverse, primarily concerned with the quality of mathematical reasoning. The objective of this study was to determine the quality of mathematical reasoning based perspective Lithner. Lithner looked at how the environment affects the mathematical reasoning. In this regard, Lithner made two perspectives, namely imitative reasoning and creative reasoning. Imitative reasoning can be memorized and algorithmic reasoning. The Result study shows that although the students generally still have problems in reasoning. Students tend to be on imitative reasoning which means that students tend to use a routine procedure when dealing with reasoning. It is also shown that the traditional approach still dominates on the situation of students’ daily learning.

Spatial and Visual Reasoning: Do These Abilities Improve in First-Year Veterinary Medical Students Exposed to an Integrated Curriculum?

PubMed

Gutierrez, J Claudio; Chigerwe, Munashe; Ilkiw, Jan E; Youngblood, Patricia; Holladay, Steven D; Srivastava, Sakti

Spatial visualization ability refers to the human cognitive ability to form, retrieve, and manipulate mental models of spatial nature. Visual reasoning ability has been linked to spatial ability. There is currently limited information about how entry-level spatial and visual reasoning abilities may predict veterinary anatomy performance or may be enhanced with progression through the veterinary anatomy content in an integrated curriculum. The present study made use of two tests that measure spatial ability and one test that measures visual reasoning ability in veterinary students: Guay's Visualization of Views Test, adapted version (GVVT), the Mental Rotations Test (MRT), and Raven's Advanced Progressive Matrices Test, short form (RavenT). The tests were given to the entering class of veterinary students during their orientation week and at week 32 in the veterinary medical curriculum. Mean score on the MRT significantly increased from 15.2 to 20.1, and on the RavenT significantly increased from 7.5 to 8.8. When females only were evaluated, results were similar to the total class outcome; however, all three tests showed significant increases in mean scores. A positive correlation between the pre- and post-test scores was found for all three tests. The present results should be considered preliminary at best for associating anatomic learning in an integrated curriculum with spatial and visual reasoning abilities. Other components of the curriculum, for instance histology or physiology, could also influence the improved spatial visualization and visual reasoning test scores at week 32.

Answer first: Applying the heuristic-analytic theory of reasoning to examine student intuitive thinking in the context of physics

NASA Astrophysics Data System (ADS)

Kryjevskaia, Mila; Stetzer, MacKenzie R.; Grosz, Nathaniel

2014-12-01

We have applied the heuristic-analytic theory of reasoning to interpret inconsistencies in student reasoning approaches to physics problems. This study was motivated by an emerging body of evidence that suggests that student conceptual and reasoning competence demonstrated on one task often fails to be exhibited on another. Indeed, even after instruction specifically designed to address student conceptual and reasoning difficulties identified by rigorous research, many undergraduate physics students fail to build reasoning chains from fundamental principles even though they possess the required knowledge and skills to do so. Instead, they often rely on a variety of intuitive reasoning strategies. In this study, we developed and employed a methodology that allowed for the disentanglement of student conceptual understanding and reasoning approaches through the use of sequences of related questions. We have shown that the heuristic-analytic theory of reasoning can be used to account for, in a mechanistic fashion, the observed inconsistencies in student responses. In particular, we found that students tended to apply their correct ideas in a selective manner that supported a specific and likely anticipated conclusion while neglecting to employ the same ideas to refute an erroneous intuitive conclusion. The observed reasoning patterns were consistent with the heuristic-analytic theory, according to which reasoners develop a "first-impression" mental model and then construct an argument in support of the answer suggested by this model. We discuss implications for instruction and argue that efforts to improve student metacognition, which serves to regulate the interaction between intuitive and analytical reasoning, is likely to lead to improved student reasoning.

Contact angle adjustment in equation-of-state-based pseudopotential model.

PubMed

Hu, Anjie; Li, Longjian; Uddin, Rizwan; Liu, Dong

2016-05-01

The single component pseudopotential lattice Boltzmann model has been widely applied in multiphase simulation due to its simplicity and stability. In many studies, it has been claimed that this model can be stable for density ratios larger than 1000. However, the application of the model is still limited to small density ratios when the contact angle is considered. The reason is that the original contact angle adjustment method influences the stability of the model. Moreover, simulation results in the present work show that, by applying the original contact angle adjustment method, the density distribution near the wall is artificially changed, and the contact angle is dependent on the surface tension. Hence, it is very inconvenient to apply this method with a fixed contact angle, and the accuracy of the model cannot be guaranteed. To solve these problems, a contact angle adjustment method based on the geometry analysis is proposed and numerically compared with the original method. Simulation results show that, with our contact angle adjustment method, the stability of the model is highly improved when the density ratio is relatively large, and it is independent of the surface tension.

Contact angle adjustment in equation-of-state-based pseudopotential model

NASA Astrophysics Data System (ADS)

Hu, Anjie; Li, Longjian; Uddin, Rizwan; Liu, Dong

2016-05-01

The single component pseudopotential lattice Boltzmann model has been widely applied in multiphase simulation due to its simplicity and stability. In many studies, it has been claimed that this model can be stable for density ratios larger than 1000. However, the application of the model is still limited to small density ratios when the contact angle is considered. The reason is that the original contact angle adjustment method influences the stability of the model. Moreover, simulation results in the present work show that, by applying the original contact angle adjustment method, the density distribution near the wall is artificially changed, and the contact angle is dependent on the surface tension. Hence, it is very inconvenient to apply this method with a fixed contact angle, and the accuracy of the model cannot be guaranteed. To solve these problems, a contact angle adjustment method based on the geometry analysis is proposed and numerically compared with the original method. Simulation results show that, with our contact angle adjustment method, the stability of the model is highly improved when the density ratio is relatively large, and it is independent of the surface tension.

Kaiser Permanente/Sandia National health care model. Phase I prototype final report. Part 1 - model overview

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

Edwards, D.; Yoshimura, A.; Butler, D.

1996-11-01

This report describes the results of a Cooperative Research and Development Agreement between Sandia National Laboratories and Kaiser Permanente Southern California to develop a prototype computer model of Kaiser Permanente`s health care delivery system. As a discrete event simulation, SimHCO models for each of 100,000 patients the progression of disease, individual resource usage, and patient choices in a competitive environment. SimHCO is implemented in the object-oriented programming language C++, stressing reusable knowledge and reusable software components. The versioned implementation of SimHCO showed that the object-oriented framework allows the program to grow in complexity in an incremental way. Furthermore, timing calculationsmore » showed that SimHCO runs in a reasonable time on typical workstations, and that a second phase model will scale proportionally and run within the system constraints of contemporary computer technology. This report is published as two documents: Model Overview and Domain Analysis. A separate Kaiser-proprietary report contains the Disease and Health Care Organization Selection Models.« less

Decision-making in healthcare: a practical application of partial least square path modelling to coverage of newborn screening programmes.

PubMed

Fischer, Katharina E

2012-08-02

Decision-making in healthcare is complex. Research on coverage decision-making has focused on comparative studies for several countries, statistical analyses for single decision-makers, the decision outcome and appraisal criteria. Accounting for decision processes extends the complexity, as they are multidimensional and process elements need to be regarded as latent constructs (composites) that are not observed directly. The objective of this study was to present a practical application of partial least square path modelling (PLS-PM) to evaluate how it offers a method for empirical analysis of decision-making in healthcare. Empirical approaches that applied PLS-PM to decision-making in healthcare were identified through a systematic literature search. PLS-PM was used as an estimation technique for a structural equation model that specified hypotheses between the components of decision processes and the reasonableness of decision-making in terms of medical, economic and other ethical criteria. The model was estimated for a sample of 55 coverage decisions on the extension of newborn screening programmes in Europe. Results were evaluated by standard reliability and validity measures for PLS-PM. After modification by dropping two indicators that showed poor measures in the measurement models' quality assessment and were not meaningful for newborn screening, the structural equation model estimation produced plausible results. The presence of three influences was supported: the links between both stakeholder participation or transparency and the reasonableness of decision-making; and the effect of transparency on the degree of scientific rigour of assessment. Reliable and valid measurement models were obtained to describe the composites of 'transparency', 'participation', 'scientific rigour' and 'reasonableness'. The structural equation model was among the first applications of PLS-PM to coverage decision-making. It allowed testing of hypotheses in situations where there are links between several non-observable constructs. PLS-PM was compatible in accounting for the complexity of coverage decisions to obtain a more realistic perspective for empirical analysis. The model specification can be used for hypothesis testing by using larger sample sizes and for data in the full domain of health technologies.

Reasoning about real-time systems with temporal interval logic constraints on multi-state automata

NASA Technical Reports Server (NTRS)

Gabrielian, Armen

1991-01-01

Models of real-time systems using a single paradigm often turn out to be inadequate, whether the paradigm is based on states, rules, event sequences, or logic. A model-based approach to reasoning about real-time systems is presented in which a temporal interval logic called TIL is employed to define constraints on a new type of high level automata. The combination, called hierarchical multi-state (HMS) machines, can be used to model formally a real-time system, a dynamic set of requirements, the environment, heuristic knowledge about planning-related problem solving, and the computational states of the reasoning mechanism. In this framework, mathematical techniques were developed for: (1) proving the correctness of a representation; (2) planning of concurrent tasks to achieve goals; and (3) scheduling of plans to satisfy complex temporal constraints. HMS machines allow reasoning about a real-time system from a model of how truth arises instead of merely depending of what is true in a system.

Experimental validation of finite element modelling of a modular metal-on-polyethylene total hip replacement.

PubMed

Hua, Xijin; Wang, Ling; Al-Hajjar, Mazen; Jin, Zhongmin; Wilcox, Ruth K; Fisher, John

2014-07-01

Finite element models are becoming increasingly useful tools to conduct parametric analysis, design optimisation and pre-clinical testing for hip joint replacements. However, the verification of the finite element model is critically important. The purposes of this study were to develop a three-dimensional anatomic finite element model for a modular metal-on-polyethylene total hip replacement for predicting its contact mechanics and to conduct experimental validation for a simple finite element model which was simplified from the anatomic finite element model. An anatomic modular metal-on-polyethylene total hip replacement model (anatomic model) was first developed and then simplified with reasonable accuracy to a simple modular total hip replacement model (simplified model) for validation. The contact areas on the articulating surface of three polyethylene liners of modular metal-on-polyethylene total hip replacement bearings with different clearances were measured experimentally in the Leeds ProSim hip joint simulator under a series of loading conditions and different cup inclination angles. The contact areas predicted from the simplified model were then compared with that measured experimentally under the same conditions. The results showed that the simplification made for the anatomic model did not change the predictions of contact mechanics of the modular metal-on-polyethylene total hip replacement substantially (less than 12% for contact stresses and contact areas). Good agreements of contact areas between the finite element predictions from the simplified model and experimental measurements were obtained, with maximum difference of 14% across all conditions considered. This indicated that the simplification and assumptions made in the anatomic model were reasonable and the finite element predictions from the simplified model were valid. © IMechE 2014.

Fluid reasoning predicts future mathematics among children and adolescents

PubMed Central

Green, Chloe T.; Bunge, Silvia A.; Chiongbian, Victoria Briones; Barrow, Maia; Ferrer, Emilio

2017-01-01

The aim of this longitudinal study was to determine whether fluid reasoning (FR) plays a significant role in the acquisition of mathematics skills, above and beyond the effects of other cognitive and numerical abilities. Using a longitudinal cohort sequential design, we examined how FR measured at three assessment occasions, spaced approximately 1.5 years apart, predicted math outcomes for a group of 69 participants between ages 6 and 21 across all three assessment occasions. We used structural equation modeling (SEM) to examine the direct and indirect relations between children's prior cognitive abilities and their future math achievement. A model including age, FR, vocabulary, and spatial skills accounted for 90% of the variance in future math achievement. In this model, FR was the only significant predictor of future math achievement; neither age, vocabulary, nor spatial skills were significant predictors. Thus, FR was the only predictor of future math achievement across a wide age range that spanned primary and secondary school. These findings build on Cattell's conceptualization of FR (Cattell, 1987) as a scaffold for learning, showing that this domain-general ability supports the acquisition of rudimentary math skills as well as the ability to solve more complex mathematical problems. PMID:28152390

The seats of reason? An imaging study of deductive and inductive reasoning.

PubMed

Goel, V; Gold, B; Kapur, S; Houle, S

1997-03-24

We carried out a neuroimaging study to test the neurophysiological predictions made by different cognitive models of reasoning. Ten normal volunteers performed deductive and inductive reasoning tasks while their regional cerebral blood flow pattern was recorded using [15O]H2O PET imaging. In the control condition subjects semantically comprehended sets of three sentences. In the deductive reasoning condition subjects determined whether the third sentence was entailed by the first two sentences. In the inductive reasoning condition subjects reported whether the third sentence was plausible given the first two sentences. The deduction condition resulted in activation of the left inferior frontal gyrus (Brodmann areas 45, 47). The induction condition resulted in activation of a large area comprised of the left medial frontal gyrus, the left cingulate gyrus, and the left superior frontal gyrus (Brodmann areas 8, 9, 24, 32). Induction was distinguished from deduction by the involvement of the medial aspect of the left superior frontal gyrus (Brodmann areas 8, 9). These results are consistent with cognitive models of reasoning that postulate different mechanisms for inductive and deductive reasoning and view deduction as a formal rule-based process.

Information Uncertainty to Compare Qualitative Reasoning Security Risk Assessment Results

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

Chavez, Gregory M; Key, Brian P; Zerkle, David K

2009-01-01

The security risk associated with malevolent acts such as those of terrorism are often void of the historical data required for a traditional PRA. Most information available to conduct security risk assessments for these malevolent acts is obtained from subject matter experts as subjective judgements. Qualitative reasoning approaches such as approximate reasoning and evidential reasoning are useful for modeling the predicted risk from information provided by subject matter experts. Absent from these approaches is a consistent means to compare the security risk assessment results. Associated with each predicted risk reasoning result is a quantifiable amount of information uncertainty which canmore » be measured and used to compare the results. This paper explores using entropy measures to quantify the information uncertainty associated with conflict and non-specificity in the predicted reasoning results. The measured quantities of conflict and non-specificity can ultimately be used to compare qualitative reasoning results which are important in triage studies and ultimately resource allocation. Straight forward extensions of previous entropy measures are presented here to quantify the non-specificity and conflict associated with security risk assessment results obtained from qualitative reasoning models.« less

A Variational Bayes Genomic-Enabled Prediction Model with Genotype × Environment Interaction

PubMed Central

Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José Cricelio; Luna-Vázquez, Francisco Javier; Salinas-Ruiz, Josafhat; Herrera-Morales, José R.; Buenrostro-Mariscal, Raymundo

2017-01-01

There are Bayesian and non-Bayesian genomic models that take into account G×E interactions. However, the computational cost of implementing Bayesian models is high, and becomes almost impossible when the number of genotypes, environments, and traits is very large, while, in non-Bayesian models, there are often important and unsolved convergence problems. The variational Bayes method is popular in machine learning, and, by approximating the probability distributions through optimization, it tends to be faster than Markov Chain Monte Carlo methods. For this reason, in this paper, we propose a new genomic variational Bayes version of the Bayesian genomic model with G×E using half-t priors on each standard deviation (SD) term to guarantee highly noninformative and posterior inferences that are not sensitive to the choice of hyper-parameters. We show the complete theoretical derivation of the full conditional and the variational posterior distributions, and their implementations. We used eight experimental genomic maize and wheat data sets to illustrate the new proposed variational Bayes approximation, and compared its predictions and implementation time with a standard Bayesian genomic model with G×E. Results indicated that prediction accuracies are slightly higher in the standard Bayesian model with G×E than in its variational counterpart, but, in terms of computation time, the variational Bayes genomic model with G×E is, in general, 10 times faster than the conventional Bayesian genomic model with G×E. For this reason, the proposed model may be a useful tool for researchers who need to predict and select genotypes in several environments. PMID:28391241

A Variational Bayes Genomic-Enabled Prediction Model with Genotype × Environment Interaction.

PubMed

Montesinos-López, Osval A; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José Cricelio; Luna-Vázquez, Francisco Javier; Salinas-Ruiz, Josafhat; Herrera-Morales, José R; Buenrostro-Mariscal, Raymundo

2017-06-07

There are Bayesian and non-Bayesian genomic models that take into account G×E interactions. However, the computational cost of implementing Bayesian models is high, and becomes almost impossible when the number of genotypes, environments, and traits is very large, while, in non-Bayesian models, there are often important and unsolved convergence problems. The variational Bayes method is popular in machine learning, and, by approximating the probability distributions through optimization, it tends to be faster than Markov Chain Monte Carlo methods. For this reason, in this paper, we propose a new genomic variational Bayes version of the Bayesian genomic model with G×E using half-t priors on each standard deviation (SD) term to guarantee highly noninformative and posterior inferences that are not sensitive to the choice of hyper-parameters. We show the complete theoretical derivation of the full conditional and the variational posterior distributions, and their implementations. We used eight experimental genomic maize and wheat data sets to illustrate the new proposed variational Bayes approximation, and compared its predictions and implementation time with a standard Bayesian genomic model with G×E. Results indicated that prediction accuracies are slightly higher in the standard Bayesian model with G×E than in its variational counterpart, but, in terms of computation time, the variational Bayes genomic model with G×E is, in general, 10 times faster than the conventional Bayesian genomic model with G×E. For this reason, the proposed model may be a useful tool for researchers who need to predict and select genotypes in several environments. Copyright © 2017 Montesinos-López et al.

Ragweed pollen production and dispersion modelling within a regional climate system, calibration and application over Europe

NASA Astrophysics Data System (ADS)

Liu, Li; Solmon, Fabien; Vautard, Robert; Hamaoui-Laguel, Lynda; Zsolt Torma, Csaba; Giorgi, Filippo

2016-05-01

Common ragweed (Ambrosia artemisiifolia L.) is a highly allergenic and invasive plant in Europe. Its pollen can be transported over large distances and has been recognized as a significant cause of hay fever and asthma (D'Amato et al., 2007; Burbach et al., 2009). To simulate production and dispersion of common ragweed pollen, we implement a pollen emission and transport module in the Regional Climate Model (RegCM) version 4 using the framework of the Community Land Model (CLM) version 4.5. In this online approach pollen emissions are calculated based on the modelling of plant distribution, pollen production, species-specific phenology, flowering probability, and flux response to meteorological conditions. A pollen tracer model is used to describe pollen advective transport, turbulent mixing, dry and wet deposition. The model is then applied and evaluated on a European domain for the period 2000-2010. To reduce the large uncertainties notably due to the lack of information on ragweed density distribution, a calibration based on airborne pollen observations is used. Accordingly a cross validation is conducted and shows reasonable error and sensitivity of the calibration. Resulting simulations show that the model captures the gross features of the pollen concentrations found in Europe, and reproduce reasonably both the spatial and temporal patterns of flowering season and associated pollen concentrations measured over Europe. The model can explain 68.6, 39.2, and 34.3 % of the observed variance in starting, central, and ending dates of the pollen season with associated root mean square error (RMSE) equal to 4.7, 3.9, and 7.0 days, respectively. The correlation between simulated and observed daily concentrations time series reaches 0.69. Statistical scores show that the model performs better over the central Europe source region where pollen loads are larger and the model is better constrained. From these simulations health risks associated to common ragweed pollen spread are evaluated through calculation of exposure time above health-relevant threshold levels. The total risk area with concentration above 5 grains m-3 takes up 29.5 % of domain. The longest exposure time occurs on Pannonian Plain, where the number of days per year with the daily concentration above 20 grains m-3 exceeds 30.

Modeling the kinetics of survival of Staphylococcus aureus in regional yogurt from goat's milk.

PubMed

Bednarko-Młynarczyk, E; Szteyn, J; Białobrzewski, I; Wiszniewska-Łaszczych, A; Liedtke, K

2015-01-01

The aim of this study was to determine the kinetics of the survival of the test strain of Staphylococcus aureus in the product investigated. Yogurt samples were contaminated with S. aure to an initial level of 10(3)-10(4) cfu/g. The samples were then stored at four temperatures: 4, 6, 20, 22°C. During storage, the number of S. aureus forming colonies in a gram of yogurt was determined every two hours. Based on the results of the analysis culture the curves of survival were plotted. Three primary models were selected to describe the kinetics of changes in the count of bacteria: Cole's model, a modified model of Gompertz and the model of Baranyi and Roberts. Analysis of the model fit carried out based on the average values of Pearson's correlation coefficient, between the modeled and measured values, showed that the Cole's model had the worst fit. The modified Gompertz model showed the count of S. aureus as a negative value. These drawbacks were not observed in the model of Baranyi and Roberts. For this reason, this model best reflects the kinetics of changes in the number of staphylococci in yogurt.

The Application of the Theory of Reasoned Action and Planned Behavior to Prevention Science in Counseling Psychology

ERIC Educational Resources Information Center

Romano, John L.; Netland, Jason D.

2008-01-01

The theory of reasoned action and planned behavior (TRA/PB) is a model of behavior change that has been extensively studied in the health sciences but has had limited exposure in the counseling psychology literature. The model offers counseling psychologists a framework to conceptualize prevention research and practice. The model is important to…

Diagnosis by integrating model-based reasoning with knowledge-based reasoning

NASA Technical Reports Server (NTRS)

Bylander, Tom

1988-01-01

Our research investigates how observations can be categorized by integrating a qualitative physical model with experiential knowledge. Our domain is diagnosis of pathologic gait in humans, in which the observations are the gait motions, muscle activity during gait, and physical exam data, and the diagnostic hypotheses are the potential muscle weaknesses, muscle mistimings, and joint restrictions. Patients with underlying neurological disorders typically have several malfunctions. Among the problems that need to be faced are: the ambiguity of the observations, the ambiguity of the qualitative physical model, correspondence of the observations and hypotheses to the qualitative physical model, the inherent uncertainty of experiential knowledge, and the combinatorics involved in forming composite hypotheses. Our system divides the work so that the knowledge-based reasoning suggests which hypotheses appear more likely than others, the qualitative physical model is used to determine which hypotheses explain which observations, and another process combines these functionalities to construct a composite hypothesis based on explanatory power and plausibility. We speculate that the reasoning architecture of our system is generally applicable to complex domains in which a less-than-perfect physical model and less-than-perfect experiential knowledge need to be combined to perform diagnosis.

A UML-based ontology for describing hospital information system architectures.

PubMed

Winter, A; Brigl, B; Wendt, T

2001-01-01

To control the heterogeneity inherent to hospital information systems the information management needs appropriate hospital information systems modeling methods or techniques. This paper shows that, for several reasons, available modeling approaches are not able to answer relevant questions of information management. To overcome this major deficiency we offer an UML-based ontology for describing hospital information systems architectures. This ontology views at three layers: the domain layer, the logical tool layer, and the physical tool layer, and defines the relevant components. The relations between these components, especially between components of different layers make the answering of our information management questions possible.

Sensitivity of climate and atmospheric CO2 to deep-ocean and shallow-ocean carbonate burial

NASA Technical Reports Server (NTRS)

Volk, Tyler

1989-01-01

A model of the carbonate-silicate geochemical cycle is presented that distinguishes carbonate masses produced by shallow-ocean and deep-ocean carbonate burial and shows that reasonable increases in deep-ocean burial could produce substantial warmings over a few hundred million years. The model includes exchanges between crust and mantle; transients from burial shifts are found to be sensitive to the fraction of nondegassed carbonates subducted into the mantle. Without the habitation of the open ocean by plankton such as foraminifera and coccolithophores, today's climate would be substantially colder.

The continuous UV flux of Alpha Lyrae - Non-LTE results

NASA Technical Reports Server (NTRS)

Snijders, M. A. J.

1977-01-01

Non-LTE calculations for the ultraviolet C I and Si I continuous opacity show that LTE results overestimate the importance of these sources of opacity and underestimate the emergent flux in Alpha Lyr. The largest errors occur between 1100 and 1160 A, where the predicted flux in non-LTE is as much as 50 times larger than in LTE, in reasonable accord with Copernicus observations. The discrepancy between LTE models and observations has been interpreted to result from the existence of a chromosphere. Until a self-consistent non-LTE model atmosphere becomes available, such an interpretation is premature.

Nonthermal steady states after an interaction quench in the Falicov-Kimball model.

PubMed

Eckstein, Martin; Kollar, Marcus

2008-03-28

We present the exact solution of the Falicov-Kimball model after a sudden change of its interaction parameter using nonequilibrium dynamical mean-field theory. For different interaction quenches between the homogeneous metallic and insulating phases the system relaxes to a nonthermal steady state on time scales on the order of variant Planck's over 2pi/bandwidth, showing collapse and revival with an approximate period of h/interaction if the interaction is large. We discuss the reasons for this behavior and provide a statistical description of the final steady state by means of generalized Gibbs ensembles.

Observation of universality for high pT distribution at LHC energies

NASA Astrophysics Data System (ADS)

Tabassam, U.; Ali, Y.; Ullah, S.; Ajaz, M.; Ali, Q.; Suleymanov, M.; Bhatti, A. S.; Suleymanov, R.

We have studied the distributions of the yield of primary charged particles produced in the asymmetric p-Pb collisions at sNN = 5.02TeV for the three pseudorapidity regions: 0.3 < η < 0.8, 0.8 < η < 1.3 and 1.3 < η < 1.8 and the transverse momentum range of 0.5

Experiment and simulation study on unidirectional carbon fiber composite component under dynamic 3 point bending loading

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

Zhou, Guowei; Sun, Qingping; Zeng, Danielle

In current work, unidirectional (UD) carbon fiber composite hatsection component with two different layups are studied under dynamic 3 point bending loading. The experiments are performed at various impact velocities, and the effects of impactor velocity and layup on acceleration histories are compared. A macro model is established with LS-Dyna for more detailed study. The simulation results show that the delamination plays an important role during dynamic 3 point bending test. Based on the analysis with high speed camera, the sidewall of hatsection shows significant buckling rather than failure. Without considering the delamination, current material model cannot capture the postmore » failure phenomenon correctly. The sidewall delamination is modeled by assumption of larger failure strain together with slim parameters, and the simulation results of different impact velocities and layups match the experimental results reasonable well.« less

Preferred mental models in reasoning about spatial relations.

PubMed

Jahn, Georg; Knauff, Markus; Johnson-Laird, P N

2007-12-01

The theory of mental models postulates that individuals infer that a spatial description is consistent only if they can construct a model in which all the assertions in the description are true. Individuals prefer a parsimonious representation, and so, when a description is consistent with more than one possible layout of entities on the left-right dimension, individuals in our culture prefer to construct models working from left to right. They also prefer to locate entities referred to in the same assertion as adjacent to one another in a model. And, if possible, they tend to chunk entities into a single unit in order to capture several possibilities in a single model. We report four experiments corroborating these predictions. The results shed light on the integration of relational assertions, and they show that participants exploit implicit constraints in building models of spatial relations.

LEARNING SEMANTICS-ENHANCED LANGUAGE MODELS APPLIED TO UNSUEPRVISED WSD

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

VERSPOOR, KARIN; LIN, SHOU-DE

An N-gram language model aims at capturing statistical syntactic word order information from corpora. Although the concept of language models has been applied extensively to handle a variety of NLP problems with reasonable success, the standard model does not incorporate semantic information, and consequently limits its applicability to semantic problems such as word sense disambiguation. We propose a framework that integrates semantic information into the language model schema, allowing a system to exploit both syntactic and semantic information to address NLP problems. Furthermore, acknowledging the limited availability of semantically annotated data, we discuss how the proposed model can be learnedmore » without annotated training examples. Finally, we report on a case study showing how the semantics-enhanced language model can be applied to unsupervised word sense disambiguation with promising results.« less

Critical analysis of partial discharge dynamics in air filled spherical voids

NASA Astrophysics Data System (ADS)

Callender, G.; Golosnoy, I. O.; Rapisarda, P.; Lewin, P. L.

2018-03-01

In this paper partial discharge (PD) is investigated inside a spherical air filled void at atmospheric pressure using a drift diffusion model. Discharge dynamics consisted of an electron avalanche transitioning into positive streamer, in agreement with earlier work on dielectric barrier discharges. Different model configurations were utilised to test many of the concepts employed in semi-analytical PD activity models, which use simplistic descriptions of the discharge dynamics. The results showed that many of these concepts may be erroneous, with significant discrepancies between the canonical reasoning and the simulation results. For example, the residual electric field, the electric field after a discharge, is significantly lower than the estimates used by classical PD activity models in the literature.

Estimation of pharmacokinetic parameters from non-compartmental variables using Microsoft Excel.

PubMed

Dansirikul, Chantaratsamon; Choi, Malcolm; Duffull, Stephen B

2005-06-01

This study was conducted to develop a method, termed 'back analysis (BA)', for converting non-compartmental variables to compartment model dependent pharmacokinetic parameters for both one- and two-compartment models. A Microsoft Excel spreadsheet was implemented with the use of Solver and visual basic functions. The performance of the BA method in estimating pharmacokinetic parameter values was evaluated by comparing the parameter values obtained to a standard modelling software program, NONMEM, using simulated data. The results show that the BA method was reasonably precise and provided low bias in estimating fixed and random effect parameters for both one- and two-compartment models. The pharmacokinetic parameters estimated from the BA method were similar to those of NONMEM estimation.

A composition joint PDF method for the modeling of spray flames

NASA Technical Reports Server (NTRS)

Raju, M. S.

1995-01-01

This viewgraph presentation discusses an extension of the probability density function (PDF) method to the modeling of spray flames to evaluate the limitations and capabilities of this method in the modeling of gas-turbine combustor flows. The comparisons show that the general features of the flowfield are correctly predicted by the present solution procedure. The present solution appears to provide a better representation of the temperature field, particularly, in the reverse-velocity zone. The overpredictions in the centerline velocity could be attributed to the following reasons: (1) the use of k-epsilon turbulence model is known to be less precise in highly swirling flows and (2) the swirl number used here is reported to be estimated rather than measured.

Stochastic dynamics of cholera epidemics

NASA Astrophysics Data System (ADS)

Azaele, Sandro; Maritan, Amos; Bertuzzo, Enrico; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2010-05-01

We describe the predictions of an analytically tractable stochastic model for cholera epidemics following a single initial outbreak. The exact model relies on a set of assumptions that may restrict the generality of the approach and yet provides a realm of powerful tools and results. Without resorting to the depletion of susceptible individuals, as usually assumed in deterministic susceptible-infected-recovered models, we show that a simple stochastic equation for the number of ill individuals provides a mechanism for the decay of the epidemics occurring on the typical time scale of seasonality. The model is shown to provide a reasonably accurate description of the empirical data of the 2000/2001 cholera epidemic which took place in the Kwa Zulu-Natal Province, South Africa, with possibly notable epidemiological implications.

Analytic drain current model for III-V cylindrical nanowire transistors

NASA Astrophysics Data System (ADS)

Marin, E. G.; Ruiz, F. G.; Schmidt, V.; Godoy, A.; Riel, H.; Gámiz, F.

2015-07-01

An analytical model is proposed to determine the drain current of III-V cylindrical nanowires (NWs). The model uses the gradual channel approximation and takes into account the complete analytical solution of the Poisson and Schrödinger equations for the Γ-valley and for an arbitrary number of subbands. Fermi-Dirac statistics are considered to describe the 1D electron gas in the NWs, being the resulting recursive Fermi-Dirac integral of order -1/2 successfully integrated under reasonable assumptions. The model has been validated against numerical simulations showing excellent agreement for different semiconductor materials, diameters up to 40 nm, gate overdrive biases up to 0.7 V, and densities of interface states up to 1013eV-1cm-2 .

An analysis of the booster plume impingement environment during the space shuttle nominal staging maneuver

NASA Technical Reports Server (NTRS)

Wojciechowski, C. J.; Penny, M. M.; Greenwood, T. F.; Fossler, I. H.

1972-01-01

An experimental study of the plume impingement heating on the space shuttle booster afterbody resulting from the space shuttle orbiter engine plumes was conducted. The 1/100-scale model tests consisted of one and two orbiter engine firings on a flat plate, a flat plate with a fin, and a cylinder model. The plume impingement heating rates on these surfaces were measured using thin film heat transfer gages. Results indicate the engine simulation is a reasonable approximation to the two engine configuration, but more tests are needed to verify the plume model of the main engine configuration. For impingment, results show models experienced laminar boundary layer convective heating. Therefore, tests at higher Reynolds numbers are needed to determine impingment heating.

Representing Learning With Graphical Models

NASA Technical Reports Server (NTRS)

Buntine, Wray L.; Lum, Henry, Jr. (Technical Monitor)

1994-01-01

Probabilistic graphical models are being used widely in artificial intelligence, for instance, in diagnosis and expert systems, as a unified qualitative and quantitative framework for representing and reasoning with probabilities and independencies. Their development and use spans several fields including artificial intelligence, decision theory and statistics, and provides an important bridge between these communities. This paper shows by way of example that these models can be extended to machine learning, neural networks and knowledge discovery by representing the notion of a sample on the graphical model. Not only does this allow a flexible variety of learning problems to be represented, it also provides the means for representing the goal of learning and opens the way for the automatic development of learning algorithms from specifications.

Health belief model and reasoned action theory in predicting water saving behaviors in yazd, iran.

PubMed

Morowatisharifabad, Mohammad Ali; Momayyezi, Mahdieh; Ghaneian, Mohammad Taghi

2012-01-01

People's behaviors and intentions about healthy behaviors depend on their beliefs, values, and knowledge about the issue. Various models of health education are used in deter¬mining predictors of different healthy behaviors but their efficacy in cultural behaviors, such as water saving behaviors, are not studied. The study was conducted to explain water saving beha¬viors in Yazd, Iran on the basis of Health Belief Model and Reasoned Action Theory. The cross-sectional study used random cluster sampling to recruit 200 heads of households to collect the data. The survey questionnaire was tested for its content validity and reliability. Analysis of data included descriptive statistics, simple correlation, hierarchical multiple regression. Simple correlations between water saving behaviors and Reasoned Action Theory and Health Belief Model constructs were statistically significant. Health Belief Model and Reasoned Action Theory constructs explained 20.80% and 8.40% of the variances in water saving beha-viors, respectively. Perceived barriers were the strongest Predictor. Additionally, there was a sta¬tistically positive correlation between water saving behaviors and intention. In designing interventions aimed at water waste prevention, barriers of water saving behaviors should be addressed first, followed by people's attitude towards water saving. Health Belief Model constructs, with the exception of perceived severity and benefits, is more powerful than is Reasoned Action Theory in predicting water saving behavior and may be used as a framework for educational interventions aimed at improving water saving behaviors.

Health Belief Model and Reasoned Action Theory in Predicting Water Saving Behaviors in Yazd, Iran

PubMed Central

Morowatisharifabad, Mohammad Ali; Momayyezi, Mahdieh; Ghaneian, Mohammad Taghi

2012-01-01

Background: People's behaviors and intentions about healthy behaviors depend on their beliefs, values, and knowledge about the issue. Various models of health education are used in deter¬mining predictors of different healthy behaviors but their efficacy in cultural behaviors, such as water saving behaviors, are not studied. The study was conducted to explain water saving beha¬viors in Yazd, Iran on the basis of Health Belief Model and Reasoned Action Theory. Methods: The cross-sectional study used random cluster sampling to recruit 200 heads of households to collect the data. The survey questionnaire was tested for its content validity and reliability. Analysis of data included descriptive statistics, simple correlation, hierarchical multiple regression. Results: Simple correlations between water saving behaviors and Reasoned Action Theory and Health Belief Model constructs were statistically significant. Health Belief Model and Reasoned Action Theory constructs explained 20.80% and 8.40% of the variances in water saving beha-viors, respectively. Perceived barriers were the strongest Predictor. Additionally, there was a sta¬tistically positive correlation between water saving behaviors and intention. Conclusion: In designing interventions aimed at water waste prevention, barriers of water saving behaviors should be addressed first, followed by people's attitude towards water saving. Health Belief Model constructs, with the exception of perceived severity and benefits, is more powerful than is Reasoned Action Theory in predicting water saving behavior and may be used as a framework for educational interventions aimed at improving water saving behaviors. PMID:24688927

Reasoning=working Memory<>attention

ERIC Educational Resources Information Center

Buehner, M.; Krumm, S.; Pick, M.

2005-01-01

The purpose of this study was to clarify the relationship between attention, components of working memory, and reasoning. Therefore, twenty working memory tests, two attention tests, and nine intelligence subtests were administered to 135 students. Using structural equation modeling, we were able to replicate a functional model of working memory…

The Consolidation/Transition Model in Moral Reasoning Development.

ERIC Educational Resources Information Center

Walker, Lawrence J.; Gustafson, Paul; Hennig, Karl H.

2001-01-01

This longitudinal study with 62 children and adolescents examined the validity of the consolidation/transition model in the context of moral reasoning development. Results of standard statistical and Bayesian techniques supported the hypotheses regarding cyclical patterns of change and predictors of stage transition, and demonstrated the utility…

Coupled carbon-water exchange of the Amazon rain forest, I. Model description, parameterization and sensitivity analysis

NASA Astrophysics Data System (ADS)

Simon, E.; Meixner, F. X.; Ganzeveld, L.; Kesselmeier, J.

2005-04-01

Detailed one-dimensional multilayer biosphere-atmosphere models, also referred to as CANVEG models, are used for more than a decade to describe coupled water-carbon exchange between the terrestrial vegetation and the lower atmosphere. Within the present study, a modified CANVEG scheme is described. A generic parameterization and characterization of biophysical properties of Amazon rain forest canopies is inferred using available field measurements of canopy structure, in-canopy profiles of horizontal wind speed and radiation, canopy albedo, soil heat flux and soil respiration, photosynthetic capacity and leaf nitrogen as well as leaf level enclosure measurements made on sunlit and shaded branches of several Amazonian tree species during the wet and dry season. The sensitivity of calculated canopy energy and CO2 fluxes to the uncertainty of individual parameter values is assessed. In the companion paper, the predicted seasonal exchange of energy, CO2, ozone and isoprene is compared to observations.

A bi-modal distribution of leaf area density with a total leaf area index of 6 is inferred from several observations in Amazonia. Predicted light attenuation within the canopy agrees reasonably well with observations made at different field sites. A comparison of predicted and observed canopy albedo shows a high model sensitivity to the leaf optical parameters for near-infrared short-wave radiation (NIR). The predictions agree much better with observations when the leaf reflectance and transmission coefficients for NIR are reduced by 25-40%. Available vertical distributions of photosynthetic capacity and leaf nitrogen concentration suggest a low but significant light acclimation of the rain forest canopy that scales nearly linearly with accumulated leaf area.

Evaluation of the biochemical leaf model, using the enclosure measurements, showed that recommended parameter values describing the photosynthetic light response, have to be optimized. Otherwise, predicted net assimilation is overestimated by 30-50%. Two stomatal models have been tested, which apply a well established semi-empirical relationship between stomatal conductance and net assimilation. Both models differ in the way they describe the influence of humidity on stomatal response. However, they show a very similar performance within the range of observed environmental conditions. The agreement between predicted and observed stomatal conductance rates is reasonable. In general, the leaf level data suggests seasonal physiological changes, which can be reproduced reasonably well by assuming increased stomatal conductance rates during the wet season, and decreased assimilation rates during the dry season.

The sensitivity of the predicted canopy fluxes of energy and CO2 to the parameterization of canopy structure, the leaf optical parameters, and the scaling of photosynthetic parameters is relatively low (1-12%), with respect to parameter uncertainty. In contrast, modifying leaf model parameters within their uncertainty range results in much larger changes of the predicted canopy net fluxes (5-35%).

Coupled carbon-water exchange of the Amazon rain forest, I. Model description, parameterization and sensitivity analysis

NASA Astrophysics Data System (ADS)

Simon, E.; Meixner, F. X.; Ganzeveld, L.; Kesselmeier, J.

2005-09-01

Detailed one-dimensional multilayer biosphere-atmosphere models, also referred to as CANVEG models, are used for more than a decade to describe coupled water-carbon exchange between the terrestrial vegetation and the lower atmosphere. Within the present study, a modified CANVEG scheme is described. A generic parameterization and characterization of biophysical properties of Amazon rain forest canopies is inferred using available field measurements of canopy structure, in-canopy profiles of horizontal wind speed and radiation, canopy albedo, soil heat flux and soil respiration, photosynthetic capacity and leaf nitrogen as well as leaf level enclosure measurements made on sunlit and shaded branches of several Amazonian tree species during the wet and dry season. The sensitivity of calculated canopy energy and CO2 fluxes to the uncertainty of individual parameter values is assessed. In the companion paper, the predicted seasonal exchange of energy, CO2, ozone and isoprene is compared to observations.

A bi-modal distribution of leaf area density with a total leaf area index of 6 is inferred from several observations in Amazonia. Predicted light attenuation within the canopy agrees reasonably well with observations made at different field sites. A comparison of predicted and observed canopy albedo shows a high model sensitivity to the leaf optical parameters for near-infrared short-wave radiation (NIR). The predictions agree much better with observations when the leaf reflectance and transmission coefficients for NIR are reduced by 25-40%. Available vertical distributions of photosynthetic capacity and leaf nitrogen concentration suggest a low but significant light acclimation of the rain forest canopy that scales nearly linearly with accumulated leaf area.

Evaluation of the biochemical leaf model, using the enclosure measurements, showed that recommended parameter values describing the photosynthetic light response, have to be optimized. Otherwise, predicted net assimilation is overestimated by 30-50%. Two stomatal models have been tested, which apply a well established semi-empirical relationship between stomatal conductance and net assimilation. Both models differ in the way they describe the influence of humidity on stomatal response. However, they show a very similar performance within the range of observed environmental conditions. The agreement between predicted and observed stomatal conductance rates is reasonable. In general, the leaf level data suggests seasonal physiological changes, which can be reproduced reasonably well by assuming increased stomatal conductance rates during the wet season, and decreased assimilation rates during the dry season.

The sensitivity of the predicted canopy fluxes of energy and CO2 to the parameterization of canopy structure, the leaf optical parameters, and the scaling of photosynthetic parameters is relatively low (1-12%), with respect to parameter uncertainty. In contrast, modifying leaf model parameters within their uncertainty range results in much larger changes of the predicted canopy net fluxes (5-35%).

Scientific reasoning in early and middle childhood: the development of domain-general evidence evaluation, experimentation, and hypothesis generation skills.

PubMed

Piekny, Jeanette; Maehler, Claudia

2013-06-01

According to Klahr's (2000, 2005; Klahr & Dunbar, 1988) Scientific Discovery as Dual Search model, inquiry processes require three cognitive components: hypothesis generation, experimentation, and evidence evaluation. The aim of the present study was to investigate (a) when the ability to evaluate perfect covariation, imperfect covariation, and non-covariation evidence emerges, (b) when experimentation emerges, (c) when hypothesis generation skills emerge, and (d), whether these abilities develop synchronously during childhood. We administered three scientific reasoning tasks referring to the three components to 223 children of five age groups (from age 4.0 to 13.5 years). Our results show that the three cognitive components of domain-general scientific reasoning emerge asynchronously. The development of domain-general scientific reasoning begins with the ability to handle unambiguous data, progresses to the interpretation of ambiguous data, and leads to a flexible adaptation of hypotheses according to the sufficiency of evidence. When children understand the relation between the level of ambiguity of evidence and the level of confidence in hypotheses, the ability to differentiate conclusive from inconclusive experiments accompanies this development. Implications of these results for designing science education concepts for young children are briefly discussed. © 2012 The British Psychological Society.

Reasoning, learning, and creativity: frontal lobe function and human decision-making.

PubMed

Collins, Anne; Koechlin, Etienne

2012-01-01

The frontal lobes subserve decision-making and executive control--that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior.

Assessing State Nuclear Weapons Proliferation: Using Bayesian Network Analysis of Social Factors

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

Coles, Garill A.; Brothers, Alan J.; Olson, Jarrod

A Bayesian network (BN) model of social factors can support proliferation assessments by estimating the likelihood that a state will pursue a nuclear weapon. Social factors including political, economic, nuclear capability, security, and national identity and psychology factors may play as important a role in whether a State pursues nuclear weapons as more physical factors. This paper will show how using Bayesian reasoning on a generic case of a would-be proliferator State can be used to combine evidence that supports proliferation assessment. Theories and analysis by political scientists can be leveraged in a quantitative and transparent way to indicate proliferationmore » risk. BN models facilitate diagnosis and inference in a probabilistic environment by using a network of nodes and acyclic directed arcs between the nodes whose connections, or absence of, indicate probabilistic relevance, or independence. We propose a BN model that would use information from both traditional safeguards and the strengthened safeguards associated with the Additional Protocol to indicate countries with a high risk of proliferating nuclear weapons. This model could be used in a variety of applications such a prioritization tool and as a component of state safeguards evaluations. This paper will discuss the benefits of BN reasoning, the development of Pacific Northwest National Laboratory’s (PNNL) BN state proliferation model and how it could be employed as an analytical tool.« less

Reasoning, Learning, and Creativity: Frontal Lobe Function and Human Decision-Making

PubMed Central

Collins, Anne; Koechlin, Etienne

2012-01-01

The frontal lobes subserve decision-making and executive control—that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior. PMID:22479152

Canopy reflectance modeling in a tropical wooded grassland

NASA Technical Reports Server (NTRS)

Simonett, David

1988-01-01

The Li-Strahler canopy reflectance model, driven by LANDSAT Thematic Mapper (TM) data, provided regional estimates of tree size and density in two bioclimatic zones in Africa. This model exploits tree geometry in an inversion technique to predict average tree size and density from reflectance data using a few simple patameters measured in the field and in the imagery. Reflectance properties of the trees were measured in the study sites using a pole-mounted radiometer. The measurements showed that the assumptions of the simple Li-Strahler model are reasonable for these woodlands. The field radiometer measurements were used to calculate the normalized difference vegetation index (NDVI), and the integrated NDVI over the canopy was related to crown volume. Predictions of tree size and density from the canopy model were used with allometric equations from the literature to estimate woody biomass and potential foliar biomass for the sites and for the regions. Estimates were compared with independent measurements made in the Sahelian sites, and to typical values from the literature for these regions and for similar woodlands. In order to apply the inversion procedure regionally, an area must first be stratified into woodland cover classes, and dry-season TM data were used to generate a stratum map of the study areas with reasonable accuracy. The method used was unsupervised classification of multi-data principal components images.

Dental care and treatments provided under general anaesthesia in the Helsinki Public Dental Service

PubMed Central

2012-01-01

Background Dental general anaesthesia (DGA) is a very efficient treatment modality, but is considered only in the last resort because of the risks posed by general anaesthesia to patients’ overall health. Health services and their treatment policies regarding DGA vary from country to country. The aims of this work were to determine the reasons for DGA in the Helsinki Public Dental Service (PDS) and to assess the role of patient characteristics in the variation in reasons and in the treatments given with special focus on preventive care. Methods The data covered all DGA patients treated in the PDS in Helsinki in 2010. The data were collected from patient documents and included personal background: age (<6, 6–12, 13–17, 18–68), gender, immigration, previous conscious sedation and previous DGA; medical background; reasons for DGA and treatments provided. Chi-square tests, Fisher’s exact test, and logistic regression modelling were employed in the statistical analyses. Results The DGA patients (n=349) were aged 2.3 to 67.2 years. Immigrants predominated in the youngest age group (p<0.001) and medically compromised patients among the adults (p<0.001) relative to the other age groups. The main reason for DGA was extreme non-cooperation (65%) followed by dental fear (37%) and an excessive need for treatment (26%). In total, 3435 treatments were performed under DGA, 57% of which were restorations, 24% tooth extractions, 5% preventive measures, 5% radiography, 4% endodontics and the remaining 5% periodontics, surgical procedures and miscellaneous. The reasons for DGA and the treatments provided varied according to age, immigration, previous sedation and DGA and medical background. The logistic regression model showed that previous sedation (OR 2.3; 95%CI 1.3-4.1; p=0.005) and extreme non-cooperation (OR 1.7; 95%CI 0.9-3.2; p=0.103) were most indicative of preventive measures given. Conclusions Extreme non-cooperation, dental fear and an excessive need for treatment were the main reasons for the use of comprehensive, conservative DGA in the Helsinki PDS. The reasons for the use of DGA and the treatments provided varied according to personal and medical background, and immigration status with no gender-differences. Preventive measures formed only a minor part of the dental care given under DGA. PMID:23102205

Dental care and treatments provided under general anaesthesia in the Helsinki Public Dental Service.

PubMed

Savanheimo, Nora; Sundberg, Sari A; Virtanen, Jorma I; Vehkalahti, Miira M

2012-10-27

Dental general anaesthesia (DGA) is a very efficient treatment modality, but is considered only in the last resort because of the risks posed by general anaesthesia to patients' overall health. Health services and their treatment policies regarding DGA vary from country to country. The aims of this work were to determine the reasons for DGA in the Helsinki Public Dental Service (PDS) and to assess the role of patient characteristics in the variation in reasons and in the treatments given with special focus on preventive care. The data covered all DGA patients treated in the PDS in Helsinki in 2010. The data were collected from patient documents and included personal background: age (<6, 6-12, 13-17, 18-68), gender, immigration, previous conscious sedation and previous DGA; medical background; reasons for DGA and treatments provided. Chi-square tests, Fisher's exact test, and logistic regression modelling were employed in the statistical analyses. The DGA patients (n=349) were aged 2.3 to 67.2 years. Immigrants predominated in the youngest age group (p<0.001) and medically compromised patients among the adults (p<0.001) relative to the other age groups. The main reason for DGA was extreme non-cooperation (65%) followed by dental fear (37%) and an excessive need for treatment (26%). In total, 3435 treatments were performed under DGA, 57% of which were restorations, 24% tooth extractions, 5% preventive measures, 5% radiography, 4% endodontics and the remaining 5% periodontics, surgical procedures and miscellaneous. The reasons for DGA and the treatments provided varied according to age, immigration, previous sedation and DGA and medical background. The logistic regression model showed that previous sedation (OR 2.3; 95%CI 1.3-4.1; p=0.005) and extreme non-cooperation (OR 1.7; 95%CI 0.9-3.2; p=0.103) were most indicative of preventive measures given. Extreme non-cooperation, dental fear and an excessive need for treatment were the main reasons for the use of comprehensive, conservative DGA in the Helsinki PDS. The reasons for the use of DGA and the treatments provided varied according to personal and medical background, and immigration status with no gender-differences. Preventive measures formed only a minor part of the dental care given under DGA.

Evaluation of three energy balance-based evaporation models for estimating monthly evaporation for five lakes using derived heat storage changes from a hysteresis model

NASA Astrophysics Data System (ADS)

Duan, Zheng; Bastiaanssen, W. G. M.

2017-02-01

The heat storage changes (Q t) can be a significant component of the energy balance in lakes, and it is important to account for Q t for reasonable estimation of evaporation at monthly and finer timescales if the energy balance-based evaporation models are used. However, Q t has been often neglected in many studies due to the lack of required water temperature data. A simple hysteresis model (Q t = a*Rn + b + c* dRn/dt) has been demonstrated to reasonably estimate Q t from the readily available net all wave radiation (Rn) and three locally calibrated coefficients (a-c) for lakes and reservoirs. As a follow-up study, we evaluated whether this hysteresis model could enable energy balance-based evaporation models to yield good evaporation estimates. The representative monthly evaporation data were compiled from published literature and used as ground-truth to evaluate three energy balance-based evaporation models for five lakes. The three models in different complexity are De Bruin-Keijman (DK), Penman, and a new model referred to as Duan-Bastiaanssen (DB). All three models require Q t as input. Each model was run in three scenarios differing in the input Q t (S1: measured Q t; S2: modelled Q t from the hysteresis model; S3: neglecting Q t) to evaluate the impact of Q t on the modelled evaporation. Evaluation showed that the modelled Q t agreed well with measured counterparts for all five lakes. It was confirmed that the hysteresis model with locally calibrated coefficients can predict Q t with good accuracy for the same lake. Using modelled Q t as inputs all three evaporation models yielded comparably good monthly evaporation to those using measured Q t as inputs and significantly better than those neglecting Q t for the five lakes. The DK model requiring minimum data generally performed the best, followed by the Penman and DB model. This study demonstrated that once three coefficients are locally calibrated using historical data the simple hysteresis model can offer reasonable Q t to force energy balance-based evaporation models to improve evaporation modelling at monthly timescales for conditions and long-term periods when measured Q t are not available. We call on scientific community to further test and refine the hysteresis model in more lakes in different geographic locations and environments.

Evidential reasoning research on intrusion detection

NASA Astrophysics Data System (ADS)

Wang, Xianpei; Xu, Hua; Zheng, Sheng; Cheng, Anyu

2003-09-01

In this paper, we mainly aim at D-S theory of evidence and the network intrusion detection these two fields. It discusses the method how to apply this probable reasoning as an AI technology to the Intrusion Detection System (IDS). This paper establishes the application model, describes the new mechanism of reasoning and decision-making and analyses how to implement the model based on the synscan activities detection on the network. The results suggest that if only rational probability values were assigned at the beginning, the engine can, according to the rules of evidence combination and hierarchical reasoning, compute the values of belief and finally inform the administrators of the qualities of the traced activities -- intrusions, normal activities or abnormal activities.

Inductive reasoning 2.0.

PubMed

Hayes, Brett K; Heit, Evan

2018-05-01

Inductive reasoning entails using existing knowledge to make predictions about novel cases. The first part of this review summarizes key inductive phenomena and critically evaluates theories of induction. We highlight recent theoretical advances, with a special emphasis on the structured statistical approach, the importance of sampling assumptions in Bayesian models, and connectionist modeling. A number of new research directions in this field are identified including comparisons of inductive and deductive reasoning, the identification of common core processes in induction and memory tasks and induction involving category uncertainty. The implications of induction research for areas as diverse as complex decision-making and fear generalization are discussed. This article is categorized under: Psychology > Reasoning and Decision Making Psychology > Learning. © 2017 Wiley Periodicals, Inc.

A National Model for Diabetes Prevention and Treatment Program in Civilian and Military Beneficiary Populations (FY07)

DTIC Science & Technology

2013-09-24

examination was performed by one of the investigators (medical doctors) or certified nurse practitioners. Prior to initiating the intervention...3 days before their scheduled appointment. If a patient did not show or cancelled their appointment without rescheduling , the study team...additionally tried to reach them by phone to identify the reason for missing an appointment and to attempt to reschedule another appointment. It was

Particle Size, Bed Properties, and Transport of Sediment on European Epicontinental Shelves

DTIC Science & Technology

2004-09-30

hundreds of kilometers to depocenters north of the Gargano promontory. The western Adriatic coastal current ( WACC ) is partially buoyancy driven, a forcing...western Adriatic and enhance flow in the WACC , so it is reasonable to expect that correlated wave resuspension and stronger-than-average southward...flow in the WACC combine to generate southward sediment flux. However, our data and model results show only a weak correlation between wave height