A demonstrative model of a lunar base simulation on a personal computer

NASA Technical Reports Server (NTRS)

1985-01-01

The initial demonstration model of a lunar base simulation is described. This initial model was developed on the personal computer level to demonstrate feasibility and technique before proceeding to a larger computer-based model. Lotus Symphony Version 1.1 software was used to base the demonstration model on an personal computer with an MS-DOS operating system. The personal computer-based model determined the applicability of lunar base modeling techniques developed at an LSPI/NASA workshop. In addition, the personnal computer-based demonstration model defined a modeling structure that could be employed on a larger, more comprehensive VAX-based lunar base simulation. Refinement of this personal computer model and the development of a VAX-based model is planned in the near future.

A simple computational algorithm of model-based choice preference.

PubMed

Toyama, Asako; Katahira, Kentaro; Ohira, Hideki

2017-08-01

A broadly used computational framework posits that two learning systems operate in parallel during the learning of choice preferences-namely, the model-free and model-based reinforcement-learning systems. In this study, we examined another possibility, through which model-free learning is the basic system and model-based information is its modulator. Accordingly, we proposed several modified versions of a temporal-difference learning model to explain the choice-learning process. Using the two-stage decision task developed by Daw, Gershman, Seymour, Dayan, and Dolan (2011), we compared their original computational model, which assumes a parallel learning process, and our proposed models, which assume a sequential learning process. Choice data from 23 participants showed a better fit with the proposed models. More specifically, the proposed eligibility adjustment model, which assumes that the environmental model can weight the degree of the eligibility trace, can explain choices better under both model-free and model-based controls and has a simpler computational algorithm than the original model. In addition, the forgetting learning model and its variation, which assume changes in the values of unchosen actions, substantially improved the fits to the data. Overall, we show that a hybrid computational model best fits the data. The parameters used in this model succeed in capturing individual tendencies with respect to both model use in learning and exploration behavior. This computational model provides novel insights into learning with interacting model-free and model-based components.

Reliability modeling of fault-tolerant computer based systems

NASA Technical Reports Server (NTRS)

Bavuso, Salvatore J.

1987-01-01

Digital fault-tolerant computer-based systems have become commonplace in military and commercial avionics. These systems hold the promise of increased availability, reliability, and maintainability over conventional analog-based systems through the application of replicated digital computers arranged in fault-tolerant configurations. Three tightly coupled factors of paramount importance, ultimately determining the viability of these systems, are reliability, safety, and profitability. Reliability, the major driver affects virtually every aspect of design, packaging, and field operations, and eventually produces profit for commercial applications or increased national security. However, the utilization of digital computer systems makes the task of producing credible reliability assessment a formidable one for the reliability engineer. The root of the problem lies in the digital computer's unique adaptability to changing requirements, computational power, and ability to test itself efficiently. Addressed here are the nuances of modeling the reliability of systems with large state sizes, in the Markov sense, which result from systems based on replicated redundant hardware and to discuss the modeling of factors which can reduce reliability without concomitant depletion of hardware. Advanced fault-handling models are described and methods of acquiring and measuring parameters for these models are delineated.

An Evaluation of Alternative Functional Models of Narrative Schemata,

DTIC Science & Technology

1980-07-01

proposi- tions. This model, like models 2L-5L, predicts a levels effect for both recall and recognition due to differential initial encoding of...Table 1. Model 7L. Model 7L differs from 6L in assuming top-down search. This model thus predicts a levels effect in recall based on probabilis- tic...Bower (1980) failed to find a levels effect in recall of narratives. To compare our results to -20- .70- 501 A I iMMED IATE 0 40 1--- 0c. 3 0 1 020 .00

Coherence of Personal Narratives across the Lifespan: A Multidimensional Model and Coding Method

PubMed Central

Reese, Elaine; Haden, Catherine A.; Baker-Ward, Lynne; Bauer, Patricia; Fivush, Robyn; Ornstein, Peter A.

2012-01-01

Personal narratives are integral to autobiographical memory and to identity, with coherent personal narratives being linked to positive developmental outcomes across the lifespan. In this article, we review the theoretical and empirical literature that sets the stage for a new lifespan model of personal narrative coherence. This new model integrates context, chronology, and theme as essential dimensions of personal narrative coherence, each of which relies upon different developmental achievements and has a different developmental trajectory across the lifespan. A multidimensional method of coding narrative coherence (the Narrative Coherence Coding Scheme or NaCCS) was derived from the model and is described here. The utility of this approach is demonstrated by its application to 498 narratives that were collected in six laboratories from participants ranging in age from 3 years to adulthood. The value of the model is illustrated further by a discussion of its potential to guide future research on the developmental foundations of narrative coherence and on the benefits of personal narrative coherence for different aspects of psychological functioning. PMID:22754399

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.

Limitations of Language: Developing Arts-Based Creative Narrative in Stories of Teachers' Identities

ERIC Educational Resources Information Center

Leitch, Ruth

2006-01-01

This paper is based on a multidimensional study employing a heuristic methodology termed "creative narrative" that combines arts-based methods with narrative inquiry. Six female teachers' narratives of identity are explored through artistic, visual images to illuminate if and how they story "unconscious". The creative narratives, illuminated…

Chapter 3. A multidimensional model for narrative analysis of substance use-related dependency.

PubMed

Larsson, Sam; von Braun, Therese; Lilja, John

2013-11-01

This chapter examines the possibilities and limitations of using a narrative method as a framework within a multidimensional model for exploring and analyzing the use and misuse of alcohol and drugs. It is posited that a multidimensional model, based on narrative reasoning, can give a more detailed and specific understanding of substance users, who represent a heterogeneous population of people, and of substance use-related dependency problems. Such a model describes and analyses the drug-use related problems in a manner that provides holistic and important information and knowledge about the person by contextual and situation interaction processes which are involved in the use/misuse of alcohol and drugs. Tentative conclusions and unresolved critical issues are considered.

Computer-Based Molecular Modelling: Finnish School Teachers' Experiences and Views

ERIC Educational Resources Information Center

Aksela, Maija; Lundell, Jan

2008-01-01

Modern computer-based molecular modelling opens up new possibilities for chemistry teaching at different levels. This article presents a case study seeking insight into Finnish school teachers' use of computer-based molecular modelling in teaching chemistry, into the different working and teaching methods used, and their opinions about necessary…

Teacher Narratives and Student Engagement: Testing Narrative Engagement Theory in Drug Prevention Education

PubMed Central

Miller-Day, Michelle; Hecht, Michael L.; Krieger, Janice L.; Pettigrew, Jonathan; Shin, YoungJu; Graham, John

2015-01-01

Testing narrative engagement theory, this study examines student engagement and teachers’ spontaneous narratives told in a narrative-based drug prevention curriculum. The study describes the extent to which teachers share their own narratives in a narrative-based curriculum, identifies dominant narrative elements, forms and functions, and assesses the relationships among teacher narratives, overall lesson narrative quality, and student engagement. One hundred videotaped lessons of the keepin’ it REAL drug prevention curriculum were coded and the results supported the claim that increased narrative quality of a prevention lesson would be associated with increased student engagement. The quality of narrativity, however, varied widely. Implications of these results for narrative-based prevention interventions and narrative pedagogy are discussed. PMID:26690668

Young Readers' Narratives Based on a Picture Book: Model Readers and Empirical Readers

ERIC Educational Resources Information Center

Hoel, Trude

2015-01-01

The article present parts of a research project where the aim is to investigate six- to seven-year-old children's language use in storytelling. The children's oral texts are based on the wordless picture book "Frog, Where Are You?" Which has been, and still remains, a frequent tool for collecting narratives from children. The Frog story…

Disrupted narrative and narrative symbol.

PubMed

Vuletić, Georgije

2018-02-01

In this article a specific type of narrative, which often appears in analytic sessions, is discussed. It is characterized by a seemingly ordinary, everyday topic and by a peculiar disruption of the narrative flow. The threefold structure of this type of narrative is described, along with its main characteristics. One element of this type of narrative is very similar to symbolic content or complex symbolic structures, e.g. dreams, the sort of material that can be used for the purpose of interpretation. The similarities as well as the differences are elaborated in the article. Thanks to the observed general structure and 'symbolic' nature of some parts of the narrative, it is easy to notice some of the unconscious elements, which are not familiar to the patient's ego, and to make an interpretation. Because these elements are close to the threshold of consciousness, the patient willingly accepts an interpretation based on them. This is especially true for patients whose dominant function is thinking. A temporary, working name for this type of narrative is proposed in the article: 'disrupted narrative' - and for its disruptive part 'narrative symbol'. © 2018, The Society of Analytical Psychology.

Computer Games versus Maps before Reading Stories: Priming Readers' Spatial Situation Models

ERIC Educational Resources Information Center

Smith, Glenn Gordon; Majchrzak, Dan; Hayes, Shelley; Drobisz, Jack

2011-01-01

The current study investigated how computer games and maps compare as preparation for readers to comprehend and retain spatial relations in text narratives. Readers create situation models of five dimensions: spatial, temporal, causal, goal, and protagonist (Zwaan, Langston, & Graesser 1995). Of these five, readers mentally model the spatial…

Computing Models for FPGA-Based Accelerators

PubMed Central

Herbordt, Martin C.; Gu, Yongfeng; VanCourt, Tom; Model, Josh; Sukhwani, Bharat; Chiu, Matt

2011-01-01

Field-programmable gate arrays are widely considered as accelerators for compute-intensive applications. A critical phase of FPGA application development is finding and mapping to the appropriate computing model. FPGA computing enables models with highly flexible fine-grained parallelism and associative operations such as broadcast and collective response. Several case studies demonstrate the effectiveness of using these computing models in developing FPGA applications for molecular modeling. PMID:21603152

The use of natural language processing on narrative medication schedules to compute average weekly dose.

PubMed

Lu, Chao-Chin; Leng, Jianwei; Cannon, Grant W; Zhou, Xi; Egger, Marlene; South, Brett; Burningham, Zach; Zeng, Qing; Sauer, Brian C

2016-12-01

Medications with non-standard dosing and unstandardized units of measurement make the estimation of prescribed dose difficult from pharmacy dispensing data. A natural language processing tool named the SIG extractor was developed to identify and extract elements from narrative medication instructions to compute average weekly doses (AWDs) for disease-modifying antirheumatic drugs. The goal of this paper is to evaluate the performance of the SIG extractor. This agreement study utilized Veterans Health Affairs pharmacy data from 2008 to 2012. The SIG extractor was designed to extract key elements from narrative medication schedules (SIGs) for 17 select medications to calculate AWD, and these medications were categorized by generic name and route of administration. The SIG extractor was evaluated against an annotator-derived reference standard for accuracy, which is the fraction of AWDs accurately computed. The overall accuracy was 89% [95% confidence interval (CI) 88%, 90%]. The accuracy was ≥85% for all medications and route combinations, except for cyclophosphamide (oral) and cyclosporine (oral), which were 79% (95%CI 72%, 85%) and 66% (95%CI 58%, 73%), respectively. The SIG extractor performed well on the majority of medications, indicating that AWD calculated by the SIG extractor can be used to improve estimation of AWD when dispensed quantity or days' supply is questionable or improbable. The working model for annotating SIGs and the SIG extractor are generalized and can easily be applied to other medications. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Becoming a teller of tales: Associations between children’s fictional narratives and parent-child reminiscence narratives

PubMed Central

Wenner, Jennifer A.; Burch, Melissa M.; Lynch, Julie S.; Bauer, Patricia J.

2008-01-01

Previous research has revealed a connection between the contributions parents make while reminiscing and their children’s narratives for personally experienced events. The present research expands the literature by focusing on the connection between parental reminiscing and children’s production of fictional narratives. Four- to 9-year-olds and their parents reminisced about past shared events and then, with an experimenter, the children produced narratives based on wordless picture books. The results revealed that the overall quality of the fictional narratives was correlated with parents’ provision statements that emphasized orientation and evaluation in the reminiscence narrative. For younger children, correlations held for reminiscence narratives about recent events. For older children, correlations held for reminiscence narratives about events from the distant past. The results are consistent with the suggestion that children learn general storytelling skills from adult models. PMID:18062986

Narrative change, narrative stability, and structural constraint: The case of prisoner reentry narratives

PubMed Central

Harding, David J.; Dobson, Cheyney C.; Wyse, Jessica J. B.; Morenoff, Jeffrey D.

2016-01-01

Cultural sociologists and other social scientists have increasingly used the concept of narrative as a theoretical tool to understand how individuals make sense of the links between their past, present, and future, how individuals construct social identities from cultural building blocks, and how culture shapes social action and individual behavior. Despite its richness, we contend that the narratives literature has yet to grapple with narrative change and stability when structural constraints or barriers challenge personal narratives and narrative identities. Particularly for marginalized groups, the potential incompatibility of personal narratives with daily experiences raises questions about the capacity of narratives to influence behavior and decision-making. In this study we draw on prospective longitudinal data on the reentry narratives and narrative identities of former prisoners to understand how narratives do and not change when confronted with contradictory experiences and structural constraints. We identify and describe the processes generating narrative change and stability among our subjects. These findings inform a framework for studying narrative change and stability based on four factors: the content of the narrative itself, the structural circumstances experienced by the individual, the institutional contexts in which the individual is embedded, and the social networks in which the individual is embedded. PMID:28316785

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…

Synchronous Computer-Mediated Dynamic Assessment: A Case Study of L2 Spanish Past Narration

ERIC Educational Resources Information Center

Darhower, Mark Anthony

2014-01-01

In this study, dynamic assessment is employed to help understand the developmental processes of two university Spanish learners as they produce a series of past narrations in a synchronous computer mediated environment. The assessments were conducted in six weekly one-hour chat sessions about various scenes of a Spanish language film. The analysis…

Learning with Artificial Worlds: Computer-Based Modelling in the Curriculum.

ERIC Educational Resources Information Center

Mellar, Harvey, Ed.; And Others

With the advent of the British National Curriculum, computer-based modeling has become an integral part of the school curriculum. This book is about modeling in education and providing children with computer tools to create and explore representations of the world. Members of the London Mental Models Group contributed their research: (1)…

The Role of Narratives in Sociohydrological Models of Flood Behaviors

NASA Astrophysics Data System (ADS)

Leong, Ching

2018-04-01

While current efforts to model sociohydrologic phenomena provide crucial insight, critics argue that these do not fully reflect the complexity one observes empirically in the real world. The policy sciences, with its focus on the interaction between human agency and the institutions that constrain public choice, can complement such efforts by providing a narrative approach. This paper demonstrates this complementarity by investigating the idea of resilience in a community response to floods. Using the quantitative Q methodology, we trace the dynamics of a common sociohydrologic hypothesis—the "memory effect" and how it decreases vulnerability and, more crucially, the instances when such memory effects do not obtain. Our analysis of a floodprone maladaptive community in Assam, India, finds four distinct narrative types: the Hardened Preparer, the Engineer, Discontent, and the Pessimist. This paper put forward an explicitly sociohydrological conception of resilience which takes into account the role of sociological indicators such as narrative types and perceptions. Such contextual understandings and narrative types can form the basis of generic resilience indicators which complement the anticipated outcomes of sociohydrologic models generally.

Criminal Narrative Experience: Relating Emotions to Offence Narrative Roles During Crime Commission.

PubMed

Ioannou, Maria; Canter, David; Youngs, Donna

2017-10-01

A neglected area of research within criminality has been that of the experience of the offence for the offender. The present study investigates the emotions and narrative roles that are experienced by an offender while committing a broad range of crimes and proposes a model of criminal narrative experience (CNE). Hypotheses were derived from the circumplex of emotions, Frye, narrative theory, and its link with investigative psychology. The analysis was based on 120 cases. Convicted for a variety of crimes, incarcerated criminals were interviewed and the data were subjected to smallest space analysis (SSA). Four themes of CNE were identified: Elated Hero, Calm Professional, Distressed Revenger, and Depressed Victim in line with the recent theoretical framework posited for narrative offence roles. The theoretical implications for understanding crime on the basis of the CNE as well as practical implications are discussed.

Evidence-based narratives to improve recall of opioid prescribing guidelines: a randomized experiment.

PubMed

Kilaru, Austin S; Perrone, Jeanmarie; Auriemma, Catherine L; Shofer, Frances S; Barg, Frances K; Meisel, Zachary F

2014-03-01

Physicians adopt evidence-based guidelines with variable consistency. Narratives, or stories, offer a novel dissemination strategy for clinical recommendations. The study objective was to compare whether evidence-based narrative versus traditional summary improved recall of opioid prescribing guidelines from the American College of Emergency Physicians (ACEP). This was a prospective, randomized controlled experiment to compare whether narrative versus summary promoted short-term recall of six themes contained in the ACEP opioid guideline. The experiment was modeled after the free-recall test, an established technique in studies of memory. At a regional conference, emergency physicians (EPs) were randomized to read either a summary of the guideline (control) or a narrative (intervention). The fictional narrative was constructed to match the summary in content and length. One hour after reading the text, participants listed all content that they could recall. Two reviewers independently scored the responses to assess recall of the six themes. The primary outcome was the total number of themes recalled per participant. Secondary outcomes included the proportion of responses in each study arm that recalled individual themes and the proportion of responses in each arm that contained falsely recalled or extraneous information. Ninety-five physicians were randomized. Eighty-two physicians completed the experiment, for a response rate of 86%. The mean of the total number of themes recalled per participant was 3.1 in the narrative arm versus 2.0 in the summary arm (difference = 1.1, 95% confidence interval [CI] = 0.6 to 1.7). For three themes, the proportion of responses that recalled the theme was significantly greater in the narrative arm compared to the summary arm, with the differences ranging from 20% to 51%. For one theme, recall was significantly greater in the summary arm. For two themes, there was no statistically significant difference in recall between the arms

Evidence-based Narratives to Improve Recall of Opioid Prescribing Guidelines: A Randomized Experiment

PubMed Central

Kilaru, Austin S.; Perrone, Jeanmarie; Auriemma, Catherine L.; Shofer, Frances S.; Barg, Frances K.; Meisel, Zachary F.

2014-01-01

Objectives Physicians adopt evidence-based guidelines with variable consistency. Narratives, or stories, offer a novel dissemination strategy for clinical recommendations. The study objective was to compare whether evidence-based narrative versus traditional summary improved recall of opioid prescribing guidelines from the American College of Emergency Physicians (ACEP). Methods This was a prospective, randomized controlled experiment to compare whether narrative versus summary promoted short-term recall of six themes contained in the ACEP opioid guideline. The experiment was modeled after the free-recall test, an established technique in studies of memory. At a regional conference, emergency physicians were randomized to read either a summary of the guideline (control) or a narrative (intervention). The fictional narrative was constructed to match the summary in content and length. One hour after reading the text, participants listed all content that they could recall. Two reviewers independently scored the responses to assess recall of the six themes. The primary outcome was the total number of themes recalled per participant. Secondary outcomes included the proportion of responses in each study arm that recalled individual themes and the proportion of responses in each arm that contained falsely recalled or extraneous information. Results Ninety-five physicians were randomized. Eighty-two physicians completed the experiment, for a response rate of 86%. The mean of the total number of themes recalled per participant was 3.1 in the narrative arm versus 2.0 in the summary arm (difference = 1.1, 95% confidence interval [CI] = 0.6 to 1.7). For three themes, the proportion of responses that recalled the theme was significantly greater in the narrative arm compared to the summary arm, with the differences ranging from 20% to 51%. For one theme, recall was significantly greater in the summary arm. For two themes, there was no statistically significant difference in

THE FUTURE OF COMPUTER-BASED TOXICITY PREDICTION: MECHANISM-BASED MODELS VS. INFORMATION MINING APPROACHES

EPA Science Inventory

The Future of Computer-Based Toxicity Prediction:
Mechanism-Based Models vs. Information Mining Approaches

When we speak of computer-based toxicity prediction, we are generally referring to a broad array of approaches which rely primarily upon chemical structure ...

A partnership model for a reflective narrative for researcher and participant.

PubMed

Murphy, Gill; Peters, Kath; Wilkes, Lesley; Jackson, Debra

2016-09-01

Background Conceptual frameworks are important to ensure a clear underpinning research philosophy. Further, the use of conceptual frameworks can support structured research processes. Aim To present a partnership model for a reflective narrative for researcher and participant. Discussion This paper positions the underpinning philosophical framework of the model in social constructionism (the idea that jointly constructed understandings form the basis for shared assumptions) and narrative enquiry. The model has five stages - study design, invitation to share a research space and partnership, a metaphorical research space, building a community story, and reading the community story to others. Core principles of the partnership model are continual reflection by the researcher, potential reflections by participants, reciprocal sharing, and partnership in research. Conclusion A 'trajectory of self' for both participants and researchers can be enhanced within reflective partnerships. Implications for practice This model can be applied to studies that use narrative enquiry and are seeking a humanistic approach with participant engagement.

Design Of Computer Based Test Using The Unified Modeling Language

NASA Astrophysics Data System (ADS)

Tedyyana, Agus; Danuri; Lidyawati

2017-12-01

The Admission selection of Politeknik Negeri Bengkalis through interest and talent search (PMDK), Joint Selection of admission test for state Polytechnics (SB-UMPN) and Independent (UM-Polbeng) were conducted by using paper-based Test (PBT). Paper Based Test model has some weaknesses. They are wasting too much paper, the leaking of the questios to the public, and data manipulation of the test result. This reasearch was Aimed to create a Computer-based Test (CBT) models by using Unified Modeling Language (UML) the which consists of Use Case diagrams, Activity diagram and sequence diagrams. During the designing process of the application, it is important to pay attention on the process of giving the password for the test questions before they were shown through encryption and description process. RSA cryptography algorithm was used in this process. Then, the questions shown in the questions banks were randomized by using the Fisher-Yates Shuffle method. The network architecture used in Computer Based test application was a client-server network models and Local Area Network (LAN). The result of the design was the Computer Based Test application for admission to the selection of Politeknik Negeri Bengkalis.

What is narrative-based medicine?

PubMed Central

Zaharias, George

2018-01-01

Abstract Objective To raise awareness of narrative-based medicine (NBM) as a valuable approach to the consultation, which, if practised more widely by GPs, would convey considerable benefits to both patients and physicians. Sources of information Principally, the perspectives of 2 of NBM’s key proponents, Rita Charon and John Launer. Main message This first in a series of 3 articles outlines what NBM is and its benefits. In holding the patient story as central, NBM shifts the doctor’s focus from the need to problem solve to the need to understand. As a result, the patient-doctor relationship is strengthened and the patient’s needs and concerns are addressed more effectively and with improved health outcomes. Conclusion The healing power of narrative is repeatedly attested to but the scientific evidence is sparse. If NBM is to be incorporated more broadly in clinical practice, more research is needed to better define NBM’s role, understand the specific skills required for practice, and determine NBM’s outcomes with respect to illness and disease. PMID:29540381

An ontology model for nursing narratives with natural language generation technology.

PubMed

Min, Yul Ha; Park, Hyeoun-Ae; Jeon, Eunjoo; Lee, Joo Yun; Jo, Soo Jung

2013-01-01

The purpose of this study was to develop an ontology model to generate nursing narratives as natural as human language from the entity-attribute-value triplets of a detailed clinical model using natural language generation technology. The model was based on the types of information and documentation time of the information along the nursing process. The typesof information are data characterizing the patient status, inferences made by the nurse from the patient data, and nursing actions selected by the nurse to change the patient status. This information was linked to the nursing process based on the time of documentation. We describe a case study illustrating the application of this model in an acute-care setting. The proposed model provides a strategy for designing an electronic nursing record system.

Computational-Model-Based Analysis of Context Effects on Harmonic Expectancy.

PubMed

Morimoto, Satoshi; Remijn, Gerard B; Nakajima, Yoshitaka

2016-01-01

Expectancy for an upcoming musical chord, harmonic expectancy, is supposedly based on automatic activation of tonal knowledge. Since previous studies implicitly relied on interpretations based on Western music theory, the underlying computational processes involved in harmonic expectancy and how it relates to tonality need further clarification. In particular, short chord sequences which cannot lead to unique keys are difficult to interpret in music theory. In this study, we examined effects of preceding chords on harmonic expectancy from a computational perspective, using stochastic modeling. We conducted a behavioral experiment, in which participants listened to short chord sequences and evaluated the subjective relatedness of the last chord to the preceding ones. Based on these judgments, we built stochastic models of the computational process underlying harmonic expectancy. Following this, we compared the explanatory power of the models. Our results imply that, even when listening to short chord sequences, internally constructed and updated tonal assumptions determine the expectancy of the upcoming chord.

Computational-Model-Based Analysis of Context Effects on Harmonic Expectancy

PubMed Central

Morimoto, Satoshi; Remijn, Gerard B.; Nakajima, Yoshitaka

2016-01-01

Expectancy for an upcoming musical chord, harmonic expectancy, is supposedly based on automatic activation of tonal knowledge. Since previous studies implicitly relied on interpretations based on Western music theory, the underlying computational processes involved in harmonic expectancy and how it relates to tonality need further clarification. In particular, short chord sequences which cannot lead to unique keys are difficult to interpret in music theory. In this study, we examined effects of preceding chords on harmonic expectancy from a computational perspective, using stochastic modeling. We conducted a behavioral experiment, in which participants listened to short chord sequences and evaluated the subjective relatedness of the last chord to the preceding ones. Based on these judgments, we built stochastic models of the computational process underlying harmonic expectancy. Following this, we compared the explanatory power of the models. Our results imply that, even when listening to short chord sequences, internally constructed and updated tonal assumptions determine the expectancy of the upcoming chord. PMID:27003807

Towards Modeling False Memory With Computational Knowledge Bases.

PubMed

Li, Justin; Kohanyi, Emma

2017-01-01

One challenge to creating realistic cognitive models of memory is the inability to account for the vast common-sense knowledge of human participants. Large computational knowledge bases such as WordNet and DBpedia may offer a solution to this problem but may pose other challenges. This paper explores some of these difficulties through a semantic network spreading activation model of the Deese-Roediger-McDermott false memory task. In three experiments, we show that these knowledge bases only capture a subset of human associations, while irrelevant information introduces noise and makes efficient modeling difficult. We conclude that the contents of these knowledge bases must be augmented and, more important, that the algorithms must be refined and optimized, before large knowledge bases can be widely used for cognitive modeling. Copyright © 2016 Cognitive Science Society, Inc.

When static media promote active learning: annotated illustrations versus narrated animations in multimedia instruction.

PubMed

Mayer, Richard E; Hegarty, Mary; Mayer, Sarah; Campbell, Julie

2005-12-01

In 4 experiments, students received a lesson consisting of computer-based animation and narration or a lesson consisting of paper-based static diagrams and text. The lessons used the same words and graphics in the paper-based and computer-based versions to explain the process of lightning formation (Experiment 1), how a toilet tank works (Experiment 2), how ocean waves work (Experiment 3), and how a car's braking system works (Experiment 4). On subsequent retention and transfer tests, the paper group performed significantly better than the computer group on 4 of 8 comparisons, and there was no significant difference on the rest. These results support the static media hypothesis, in which static illustrations with printed text reduce extraneous processing and promote germane processing as compared with narrated animations.

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.

Narrative medicine in surgical education.

PubMed

Pearson, A Scott; McTigue, Michael P; Tarpley, John L

2008-01-01

Narrative medicine is a patient-centered approach to the practice of medicine that rescues the patients' stories and integrates what is important to them into decisions regarding their health care. Our hypothesis is that narrative understanding enhances the patient-provider relationship and contributes to optimizing patient care. We propose to use written narrative reflection to capture and measure the general competencies of systems-based practice, practice-based learning, communication skills, and professionalism. DEVELOPMENT/METHODS: The development of this narrative-based project is based on a pilot study that we conducted at our institution with third-year surgical clerkship students. In the pilot, students produced in-depth narrative write-ups on a patient they had had the opportunity to "know." We plan a similar approach for surgical resident education. After a brief discussion of narrative medicine during our scheduled didactic conference, the residents are asked to initiate a written narrative reflection on a patient of their choosing. The narratives will be collected 1 week later. Our plan is to repeat this assessment quarterly so that 4 narratives will be generated annually from internship through the chief resident year. The narratives will be analyzed for content and recurring themes that capture the resident's communication skills, professionalism, as well as self-critique (practice-based learning) and value attributed to health-care teams (systems-based practice). After completion of the narratives, a 5-point Likert response survey will be given to the residents to assess their experience and the perceived value of written reflection. The written narratives will become part of the resident's ongoing portfolio. IMPLEMENTATION/EXPERIENCE TO DATE: Feedback from the medical student pilot study was favorable. When asked in a follow-up questionnaire, most students reported the experience to be valuable and recommended the use of narrative reflection in

Image based Monte Carlo Modeling for Computational Phantom

NASA Astrophysics Data System (ADS)

Cheng, Mengyun; Wang, Wen; Zhao, Kai; Fan, Yanchang; Long, Pengcheng; Wu, Yican

2014-06-01

The evaluation on the effects of ionizing radiation and the risk of radiation exposure on human body has been becoming one of the most important issues for radiation protection and radiotherapy fields, which is helpful to avoid unnecessary radiation and decrease harm to human body. In order to accurately evaluate the dose on human body, it is necessary to construct more realistic computational phantom. However, manual description and verfication of the models for Monte carlo(MC)simulation are very tedious, error-prone and time-consuming. In addiation, it is difficult to locate and fix the geometry error, and difficult to describe material information and assign it to cells. MCAM (CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport Simulation) was developed as an interface program to achieve both CAD- and image-based automatic modeling by FDS Team (Advanced Nuclear Energy Research Team, http://www.fds.org.cn). The advanced version (Version 6) of MCAM can achieve automatic conversion from CT/segmented sectioned images to computational phantoms such as MCNP models. Imaged-based automatic modeling program(MCAM6.0) has been tested by several medical images and sectioned images. And it has been applied in the construction of Rad-HUMAN. Following manual segmentation and 3D reconstruction, a whole-body computational phantom of Chinese adult female called Rad-HUMAN was created by using MCAM6.0 from sectioned images of a Chinese visible human dataset. Rad-HUMAN contains 46 organs/tissues, which faithfully represented the average anatomical characteristics of the Chinese female. The dose conversion coefficients(Dt/Ka) from kerma free-in-air to absorbed dose of Rad-HUMAN were calculated. Rad-HUMAN can be applied to predict and evaluate dose distributions in the Treatment Plan System (TPS), as well as radiation exposure for human body in radiation protection.

Evaluating Emulation-based Models of Distributed Computing Systems

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

Jones, Stephen T.; Gabert, Kasimir G.; Tarman, Thomas D.

Emulation-based models of distributed computing systems are collections of virtual ma- chines, virtual networks, and other emulation components configured to stand in for oper- ational systems when performing experimental science, training, analysis of design alterna- tives, test and evaluation, or idea generation. As with any tool, we should carefully evaluate whether our uses of emulation-based models are appropriate and justified. Otherwise, we run the risk of using a model incorrectly and creating meaningless results. The variety of uses of emulation-based models each have their own goals and deserve thoughtful evaluation. In this paper, we enumerate some of these uses andmore » describe approaches that one can take to build an evidence-based case that a use of an emulation-based model is credible. Predictive uses of emulation-based models, where we expect a model to tell us something true about the real world, set the bar especially high and the principal evaluation method, called validation , is comensurately rigorous. We spend the majority of our time describing and demonstrating the validation of a simple predictive model using a well-established methodology inherited from decades of development in the compuational science and engineering community.« less

Enhancing Evidence-Based Public Health Policy: Developing and Using Policy Narratives.

PubMed

Troy, Lisa M; Kietzman, Kathryn G

2016-06-01

Academic researchers and clinicians have a critical role in shaping public policies to improve the health of an aging America. Policy narratives that pair personal stories with research statistics are a powerful tool to share knowledge generated in academic and clinical settings with policymakers. Effective policy narratives rely on a trustworthy and competent narrator and a compelling story that highlights the personal impact of policies under consideration and academic research that bolsters the story. Awareness of the cultural differences in the motivations, expectations, and institutional constraints of academic researchers and clinicians as information producers and U.S. Congress and federal agencies as information users is critical to the development of policy narratives that impact policy decisions. The current article describes the development and use of policy narratives to bridge cultures and enhance evidence-based public health policies that better meet the needs of older adults. [Journal of Gerontological Nursing, 42(6), 11-17.]. Copyright 2016, SLACK Incorporated.

When Static Media Promote Active Learning: Annotated Illustrations Versus Narrated Animations in Multimedia Instruction

ERIC Educational Resources Information Center

Mayer, Richard E.; Hegarty, Mary; Mayer, Sarah; Campbell, Julie

2005-01-01

In 4 experiments, students received a lesson consisting of computer-based animation and narration or a lesson consisting of paper-based static diagrams and text. The lessons used the same words and graphics in the paper-based and computer-based versions to explain the process of lightning formation (Experiment 1), how a toilet tank works…

Emohawk: Searching for a "Good" Emergent Narrative

NASA Astrophysics Data System (ADS)

Brom, Cyril; Bída, Michal; Gemrot, Jakub; Kadlec, Rudolf; Plch, Tomáš

We report on the progress we have achieved in development of Emohawk, a 3D virtual reality application with an emergent narrative for teaching high-school students and undergraduates the basics of virtual characters control, emotion modelling, and narrative generation. Besides, we present a new methodology, used in Emohawk, for purposeful authoring of emergent narratives of Façade's complexity. The methodology is based on massive automatic search for stories that are appealing to the audience whilst forbidding the unappealing ones during the design phase.

An evaluation method of computer usability based on human-to-computer information transmission model.

PubMed

Ogawa, K

1992-01-01

This paper proposes a new evaluation and prediction method for computer usability. This method is based on our two previously proposed information transmission measures created from a human-to-computer information transmission model. The model has three information transmission levels: the device, software, and task content levels. Two measures, called the device independent information measure (DI) and the computer independent information measure (CI), defined on the software and task content levels respectively, are given as the amount of information transmitted. Two information transmission rates are defined as DI/T and CI/T, where T is the task completion time: the device independent information transmission rate (RDI), and the computer independent information transmission rate (RCI). The method utilizes the RDI and RCI rates to evaluate relatively the usability of software and device operations on different computer systems. Experiments using three different systems, in this case a graphical information input task, confirm that the method offers an efficient way of determining computer usability.

Coherence and content of conflict-based narratives: associations to family risk and maladjustment.

PubMed

Müller, Eva; Perren, Sonja; Wustmann Seiler, Corina

2014-10-01

This study examined the role of structural and content characteristics of children's conflict-based narratives (coherence, positive and aggressive themes) in the association between early childhood family risk and children's internalizing and externalizing problems in a sample of 193 children (97 girls, 96 boys) aged 3 to 5 years (M = 3.85, SD = .48). Parents participated in an interview on family related risk factors; teachers and parents completed the Strengths and Difficulties Questionnaire; children completed conflict-based narratives based on the MacArthur Story Stem Battery (MSSB). We specifically investigated the mediating and moderating role of narrative coherence and content themes in the association between family risk and children's internalizing and externalizing problems. Children's narrative coherence was associated with better adjustment, and had a buffering effect on the negative relation between family risk on children's internalizing problems. Positive themes were negatively associated with externalizing problems. Telling narratives with many positive and negative themes buffered the negative association of family risk and teacher-reported externalizing problems. In sum, the findings suggest that in children, being able to tell coherent and enriched narratives may buffer the impact of family risk on their symptoms, and being able to produce positive themes rather than aggressive themes is associated with lower externalizing problems. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Full 3-D OCT-based pseudophakic custom computer eye model

PubMed Central

Sun, M.; Pérez-Merino, P.; Martinez-Enriquez, E.; Velasco-Ocana, M.; Marcos, S.

2016-01-01

We compared measured wave aberrations in pseudophakic eyes implanted with aspheric intraocular lenses (IOLs) with simulated aberrations from numerical ray tracing on customized computer eye models, built using quantitative 3-D OCT-based patient-specific ocular geometry. Experimental and simulated aberrations show high correlation (R = 0.93; p<0.0001) and similarity (RMS for high order aberrations discrepancies within 23.58%). This study shows that full OCT-based pseudophakic custom computer eye models allow understanding the relative contribution of optical geometrical and surgically-related factors to image quality, and are an excellent tool for characterizing and improving cataract surgery. PMID:27231608

Advanced reliability modeling of fault-tolerant computer-based systems

NASA Technical Reports Server (NTRS)

Bavuso, S. J.

1982-01-01

Two methodologies for the reliability assessment of fault tolerant digital computer based systems are discussed. The computer-aided reliability estimation 3 (CARE 3) and gate logic software simulation (GLOSS) are assessment technologies that were developed to mitigate a serious weakness in the design and evaluation process of ultrareliable digital systems. The weak link is based on the unavailability of a sufficiently powerful modeling technique for comparing the stochastic attributes of one system against others. Some of the more interesting attributes are reliability, system survival, safety, and mission success.

Overview of Computer-Based Models Applicable to Freight Car Utilization

DOT National Transportation Integrated Search

1977-10-01

This report documents a study performed to identify and analyze twenty-two of the important computer-based models of railroad operations. The models are divided into three categories: network simulations, yard simulations, and network optimizations. ...

A combined Fuzzy and Naive Bayesian strategy can be used to assign event codes to injury narratives.

PubMed

Marucci-Wellman, H; Lehto, M; Corns, H

2011-12-01

Bayesian methods show promise for classifying injury narratives from large administrative datasets into cause groups. This study examined a combined approach where two Bayesian models (Fuzzy and Naïve) were used to either classify a narrative or select it for manual review. Injury narratives were extracted from claims filed with a worker's compensation insurance provider between January 2002 and December 2004. Narratives were separated into a training set (n=11,000) and prediction set (n=3,000). Expert coders assigned two-digit Bureau of Labor Statistics Occupational Injury and Illness Classification event codes to each narrative. Fuzzy and Naïve Bayesian models were developed using manually classified cases in the training set. Two semi-automatic machine coding strategies were evaluated. The first strategy assigned cases for manual review if the Fuzzy and Naïve models disagreed on the classification. The second strategy selected additional cases for manual review from the Agree dataset using prediction strength to reach a level of 50% computer coding and 50% manual coding. When agreement alone was used as the filtering strategy, the majority were coded by the computer (n=1,928, 64%) leaving 36% for manual review. The overall combined (human plus computer) sensitivity was 0.90 and positive predictive value (PPV) was >0.90 for 11 of 18 2-digit event categories. Implementing the 2nd strategy improved results with an overall sensitivity of 0.95 and PPV >0.90 for 17 of 18 categories. A combined Naïve-Fuzzy Bayesian approach can classify some narratives with high accuracy and identify others most beneficial for manual review, reducing the burden on human coders.

Dopamine selectively remediates 'model-based' reward learning: a computational approach.

PubMed

Sharp, Madeleine E; Foerde, Karin; Daw, Nathaniel D; Shohamy, Daphna

2016-02-01

Patients with loss of dopamine due to Parkinson's disease are impaired at learning from reward. However, it remains unknown precisely which aspect of learning is impaired. In particular, learning from reward, or reinforcement learning, can be driven by two distinct computational processes. One involves habitual stamping-in of stimulus-response associations, hypothesized to arise computationally from 'model-free' learning. The other, 'model-based' learning, involves learning a model of the world that is believed to support goal-directed behaviour. Much work has pointed to a role for dopamine in model-free learning. But recent work suggests model-based learning may also involve dopamine modulation, raising the possibility that model-based learning may contribute to the learning impairment in Parkinson's disease. To directly test this, we used a two-step reward-learning task which dissociates model-free versus model-based learning. We evaluated learning in patients with Parkinson's disease tested ON versus OFF their dopamine replacement medication and in healthy controls. Surprisingly, we found no effect of disease or medication on model-free learning. Instead, we found that patients tested OFF medication showed a marked impairment in model-based learning, and that this impairment was remediated by dopaminergic medication. Moreover, model-based learning was positively correlated with a separate measure of working memory performance, raising the possibility of common neural substrates. Our results suggest that some learning deficits in Parkinson's disease may be related to an inability to pursue reward based on complete representations of the environment. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Customizing clinical narratives for the electronic medical record interface using cognitive methods.

PubMed

Sharda, Pallav; Das, Amar K; Cohen, Trevor A; Patel, Vimla

2006-05-01

As healthcare practice transitions from paper-based to computer-based records, there is increasing need to determine an effective electronic format for clinical narratives. Our research focuses on utilizing a cognitive science methodology to guide the conversion of medical texts to a more structured, user-customized presentation in the electronic medical record (EMR). We studied the use of discharge summaries by psychiatrists with varying expertise-experts, intermediates, and novices. Experts were given two hypothetical emergency care scenarios with narrative discharge summaries and asked to verbalize their clinical assessment. Based on the results, the narratives were presented in a more structured form. Intermediate and novice subjects received a narrative and a structured discharge summary, and were asked to verbalize their assessments of each. A qualitative comparison of the interview transcripts of all subjects was done by analysis of recall and inference made with respect to level of expertise. For intermediate and novice subjects, recall was greater with the structured form than with the narrative. Novices were also able to make more inferences (not always accurate) from the structured form than with the narrative. Errors occurred in assessments using the narrative form but not the structured form. Our cognitive methods to study discharge summary use enabled us to extract a conceptual representation of clinical narratives from end-users. This method allowed us to identify clinically relevant information that can be used to structure medical text for the EMR and potentially improve recall and reduce errors.

An agent-based computational model for tuberculosis spreading on age-structured populations

NASA Astrophysics Data System (ADS)

Graciani Rodrigues, C. C.; Espíndola, Aquino L.; Penna, T. J. P.

2015-06-01

In this work we present an agent-based computational model to study the spreading of the tuberculosis (TB) disease on age-structured populations. The model proposed is a merge of two previous models: an agent-based computational model for the spreading of tuberculosis and a bit-string model for biological aging. The combination of TB with the population aging, reproduces the coexistence of health states, as seen in real populations. In addition, the universal exponential behavior of mortalities curves is still preserved. Finally, the population distribution as function of age shows the prevalence of TB mostly in elders, for high efficacy treatments.

A singlechip-computer-controlled conductivity meter based on conductance-frequency transformation

NASA Astrophysics Data System (ADS)

Chen, Wenxiang; Hong, Baocai

2005-02-01

A portable conductivity meter controlled by singlechip computer was designed. The instrument uses conductance-frequency transformation method to measure the conductivity of solution. The circuitry is simple and reliable. Another feature of the instrument is that the temperature compensation is realised by changing counting time of the timing counter. The theoretical based and the usage of temperature compensation are narrated.

Impact of audio narrated animation on students' understanding and learning environment based on gender

NASA Astrophysics Data System (ADS)

Nasrudin, Ajeng Ratih; Setiawan, Wawan; Sanjaya, Yayan

2017-05-01

This study is titled the impact of audio narrated animation on students' understanding in learning humanrespiratory system based on gender. This study was conducted in eight grade of junior high school. This study aims to investigate the difference of students' understanding and learning environment at boys and girls classes in learning human respiratory system using audio narrated animation. Research method that is used is quasy experiment with matching pre-test post-test comparison group design. The procedures of study are: (1) preliminary study and learning habituation using audio narrated animation; (2) implementation of learning using audio narrated animation and taking data; (3) analysis and discussion. The result of analysis shows that there is significant difference on students' understanding and learning environment at boys and girls classes in learning human respiratory system using audio narrated animation, both in general and specifically in achieving learning indicators. The discussion related to the impact of audio narrated animation, gender characteristics, and constructivist learning environment. It can be concluded that there is significant difference of students' understanding at boys and girls classes in learning human respiratory system using audio narrated animation. Additionally, based on interpretation of students' respond, there is the difference increment of agreement level in learning environment.

Narratives of psychiatric malingering in works of fiction.

PubMed

Kuperman, V

2006-12-01

This paper argues that the representation of psychiatric malingering in literary and cinematographic narratives informs societal stereotypes, and thus influences the clinical phenomenology of malingering. The study aims to identify sociocultural models of malingering in contemporary Western society based on the narrative analysis of about 60 fictional and non-fiction texts. Two behavioural patterns derived from the Foucauldian categories folly and madness are recognisable in naïve conceptualisations of fake insanity. Fabricated significations of deviation originate in grand societal narratives rather than in medical discourse, and construct characters such as animal like underdeveloped simpletons or detached, irrational, violent madmen. Each pattern stems from its own archaic conceptual basis and dictates a distinct framework for strategies of malingering. The semiotic structure of artistic narratives of malingering is discussed in comparison with the symptomatology of existing psychiatric models.

Evaluating Mediated Perception of Narrative Health Messages: The Perception of Narrative Performance Scale

PubMed Central

Lee, Jeong Kyu; Hecht, Michael L.; Miller-Day, Michelle; Elek, Elvira

2011-01-01

Narrative media health messages have proven effective in preventing adolescents’ substance use but as yet few measures exist to assess perceptions of them. Without such a measure it is difficult to evaluate the role these messages play in health promotion or to differentiate them from other message forms. In response to this need, a study was conducted to evaluate the Perception of Narrative Performance Scale that assesses perceptions of narrative health messages. A sample of 1185 fifth graders in public schools at Phoenix, Arizona completed a questionnaire rating of two videos presenting narrative substance use prevention messages. Confirmatory factor analyses were computed to identify the factor structure of the scale. Consistent with prior studies, results suggest a 3 factor structure for the Perception of Narrative Performance Scale: interest, realism, and identification (with characters). In addition, a path analysis was performed to test the predictive power of the scale. The analysis shows that the scale proves useful in predicting intent to use substances. Finally, practical implications and limitations are discussed. PMID:21822459

A ferrofluid based energy harvester: Computational modeling, analysis, and experimental validation

NASA Astrophysics Data System (ADS)

Liu, Qi; Alazemi, Saad F.; Daqaq, Mohammed F.; Li, Gang

2018-03-01

A computational model is described and implemented in this work to analyze the performance of a ferrofluid based electromagnetic energy harvester. The energy harvester converts ambient vibratory energy into an electromotive force through a sloshing motion of a ferrofluid. The computational model solves the coupled Maxwell's equations and Navier-Stokes equations for the dynamic behavior of the magnetic field and fluid motion. The model is validated against experimental results for eight different configurations of the system. The validated model is then employed to study the underlying mechanisms that determine the electromotive force of the energy harvester. Furthermore, computational analysis is performed to test the effect of several modeling aspects, such as three-dimensional effect, surface tension, and type of the ferrofluid-magnetic field coupling on the accuracy of the model prediction.

Evidence for Model-based Computations in the Human Amygdala during Pavlovian Conditioning

PubMed Central

Prévost, Charlotte; McNamee, Daniel; Jessup, Ryan K.; Bossaerts, Peter; O'Doherty, John P.

2013-01-01

Contemporary computational accounts of instrumental conditioning have emphasized a role for a model-based system in which values are computed with reference to a rich model of the structure of the world, and a model-free system in which values are updated without encoding such structure. Much less studied is the possibility of a similar distinction operating at the level of Pavlovian conditioning. In the present study, we scanned human participants while they participated in a Pavlovian conditioning task with a simple structure while measuring activity in the human amygdala using a high-resolution fMRI protocol. After fitting a model-based algorithm and a variety of model-free algorithms to the fMRI data, we found evidence for the superiority of a model-based algorithm in accounting for activity in the amygdala compared to the model-free counterparts. These findings support an important role for model-based algorithms in describing the processes underpinning Pavlovian conditioning, as well as providing evidence of a role for the human amygdala in model-based inference. PMID:23436990

Virtual Heritage Tours: Developing Interactive Narrative-Based Environments for Historical Sites

NASA Astrophysics Data System (ADS)

Tuck, Deborah; Kuksa, Iryna

In the last decade there has been a noticeable growth in the use of virtual reality (VR) technologies for reconstructing cultural heritage sites. However, many of these virtual reconstructions evidence little of sites' social histories. Narrating the Past is a research project that aims to re-address this issue by investigating methods for embedding social histories within cultural heritage sites and by creating narrative based virtual environments (VEs) within them. The project aims to enhance the visitor's knowledge and understanding by developing a navigable 3D story space, in which participants are immersed. This has the potential to create a malleable virtual environment allowing the visitor to configure their own narrative paths.

Drama and Imagination: A Cognitive Theory of Drama's Effect on Narrative Comprehension and Narrative Production

ERIC Educational Resources Information Center

Mages, Wendy K.

2006-01-01

This article proposes a cognitive theory of how drama affects two aspects of language development: narrative comprehension and narrative production. It is a theoretical model that explicitly posits the role of the imagination in drama's potential to enhance the development of both narrative comprehension and narrative production. (Contains 2…

The Impact of Narrative-Based Learning in Classroom

ERIC Educational Resources Information Center

Marunda-Piki, Chipo J.

2018-01-01

Narrative and story play a central role in cognitive and cultural development of children. In this article, I explore a narrative-centred pedagogy used to address the teaching and learning concerns of my pupils from Helena infant school, Zimbabwe. I document how, as a novice teacher, I deployed narrative learning in my teaching of English as a…

An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology.

PubMed

Deodhar, Suruchi; Bisset, Keith R; Chen, Jiangzhuo; Ma, Yifei; Marathe, Madhav V

2014-07-01

We present an integrated interactive modeling environment to support public health epidemiology. The environment combines a high resolution individual-based model with a user-friendly web-based interface that allows analysts to access the models and the analytics back-end remotely from a desktop or a mobile device. The environment is based on a loosely-coupled service-oriented-architecture that allows analysts to explore various counter factual scenarios. As the modeling tools for public health epidemiology are getting more sophisticated, it is becoming increasingly hard for non-computational scientists to effectively use the systems that incorporate such models. Thus an important design consideration for an integrated modeling environment is to improve ease of use such that experimental simulations can be driven by the users. This is achieved by designing intuitive and user-friendly interfaces that allow users to design and analyze a computational experiment and steer the experiment based on the state of the system. A key feature of a system that supports this design goal is the ability to start, stop, pause and roll-back the disease propagation and intervention application process interactively. An analyst can access the state of the system at any point in time and formulate dynamic interventions based on additional information obtained through state assessment. In addition, the environment provides automated services for experiment set-up and management, thus reducing the overall time for conducting end-to-end experimental studies. We illustrate the applicability of the system by describing computational experiments based on realistic pandemic planning scenarios. The experiments are designed to demonstrate the system's capability and enhanced user productivity.

An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology

PubMed Central

Deodhar, Suruchi; Bisset, Keith R.; Chen, Jiangzhuo; Ma, Yifei; Marathe, Madhav V.

2014-01-01

We present an integrated interactive modeling environment to support public health epidemiology. The environment combines a high resolution individual-based model with a user-friendly web-based interface that allows analysts to access the models and the analytics back-end remotely from a desktop or a mobile device. The environment is based on a loosely-coupled service-oriented-architecture that allows analysts to explore various counter factual scenarios. As the modeling tools for public health epidemiology are getting more sophisticated, it is becoming increasingly hard for non-computational scientists to effectively use the systems that incorporate such models. Thus an important design consideration for an integrated modeling environment is to improve ease of use such that experimental simulations can be driven by the users. This is achieved by designing intuitive and user-friendly interfaces that allow users to design and analyze a computational experiment and steer the experiment based on the state of the system. A key feature of a system that supports this design goal is the ability to start, stop, pause and roll-back the disease propagation and intervention application process interactively. An analyst can access the state of the system at any point in time and formulate dynamic interventions based on additional information obtained through state assessment. In addition, the environment provides automated services for experiment set-up and management, thus reducing the overall time for conducting end-to-end experimental studies. We illustrate the applicability of the system by describing computational experiments based on realistic pandemic planning scenarios. The experiments are designed to demonstrate the system's capability and enhanced user productivity. PMID:25530914

Murder on Grimm Isle: The Impact of Game Narrative Design in an Educational Game-Based Learning Environment

ERIC Educational Resources Information Center

Dickey, Michele D.

2011-01-01

The purpose of this research is to investigate the impact of narrative design in a game-based learning environment. Specifically, this investigation focuses the narrative design in an adventure-styled, game-based learning environment for fostering argumentation writing by looking at how the game narrative impacted player/learner (1) intrinsic…

"Could I return to my life?" Integrated Narrative Nursing Model in Education (INNE).

PubMed

Artioli, Giovanna; Foà, Chiara; Cosentino, Chiara; Sulla, Francesco; Sollami, Alfonso; Taffurelli, Chiara

2018-03-28

The Integrated Narrative Nursing Model (INNM) is an approach that integrates the qualitative methodology typical of the human sciences, with the quantitative methodology more often associated with the natural sciences. This complex model, which combines a focus on narrative with quantitative measures, has recently been effectively applied to the assessment of chronic patients. In this study, the model is applied to the planning phase of education (Integrated Narrative Nursing Education, INNE), and proves to be a valid instrument for the promotion of the current educational paradigm that is centered on the engagement of both the patient and the caregiver in their own path of care. The aim of this study is therefore to describe the nurse's strategy in the planning of an educational intervention by using the INNE model. The case of a 70-year-old woman with pulmonary neoplasm is described at her first admission to Hospice. Each step conducted by the reference nurse, who uses INNE to record the nurse-patient narrative and collect subsequent questionnaires in order to create a shared educational plan, is also described. The information collected was submitted, starting from a grounded methodology to the following four levels of analysis: I. Needs Assessment, II. Narrative Diagnosis, III. Quantitative Outcome, IV. Integrated Outcome. Step IV, which is derived from the integration of all levels of analysis, allows a nurse to define, even graphically, the conceptual map of a patient's needs, resources and perspectives, in a completely tailored manner. The INNE model offers a valid methodological support for the professional who intends to educate the patient through an inter-subjective and engaged pathway, between the professional, their patient and the socio-relational context. It is a matter of adopting a complex vision that combines processes and methods that require a steady scientific basis and advanced methodological expertise with active listening and empathy

Narrative Means to Preventative Ends: A Narrative Engagement Framework for Designing Prevention Interventions

PubMed Central

Miller-Day, Michelle; Hecht, Michael L.

2013-01-01

This paper describes a Narrative Engagement Framework (NEF) for guiding communication-based prevention efforts. This framework suggests that personal narratives have distinctive capabilities in prevention. The paper discusses the concept of narrative, links narrative to prevention, and discusses the central role of youth in developing narrative interventions. As illustration, the authors describe how the NEF is applied in the keepin’ it REAL adolescent drug prevention curriculum, pose theoretical directions, and offer suggestions for future work in prevention communication. PMID:23980613

Comparison of the Effects of Video Modeling with Narration vs. Video Modeling on the Functional Skill Acquisition of Adolescents with Autism

ERIC Educational Resources Information Center

Smith, Molly; Ayres, Kevin; Mechling, Linda; Smith, Katie

2013-01-01

The purpose of this study was to compare the effects of two forms of video modeling: video modeling that includes narration (VMN) and video models without narration (VM) on skill acquisition of four adolescent boys with a primary diagnosis of autism enrolled in an Extended School Year (ESY) summer program. An adapted alternating treatment design…

Facebook, Political Narrative, and Political Change: A Case Study of Palestinian Youth

ERIC Educational Resources Information Center

Kenderes, Amanda M.

2012-01-01

In this dissertation I aim to advance political narrative theory by exploring the use of political narrative on Facebook and the possibility for Facebook to be used among Palestinian youth for political change. To examine the concepts of political narrative and political change, I developed a model for political change based on the changing…

On the design of computer-based models for integrated environmental science.

PubMed

McIntosh, Brian S; Jeffrey, Paul; Lemon, Mark; Winder, Nick

2005-06-01

The current research agenda in environmental science is dominated by calls to integrate science and policy to better understand and manage links between social (human) and natural (nonhuman) processes. Freshwater resource management is one area where such calls can be heard. Designing computer-based models for integrated environmental science poses special challenges to the research community. At present it is not clear whether such tools, or their outputs, receive much practical policy or planning application. It is argued that this is a result of (1) a lack of appreciation within the research modeling community of the characteristics of different decision-making processes including policy, planning, and (2) participation, (3) a lack of appreciation of the characteristics of different decision-making contexts, (4) the technical difficulties in implementing the necessary support tool functionality, and (5) the socio-technical demands of designing tools to be of practical use. This article presents a critical synthesis of ideas from each of these areas and interprets them in terms of design requirements for computer-based models being developed to provide scientific information support for policy and planning. Illustrative examples are given from the field of freshwater resources management. Although computer-based diagramming and modeling tools can facilitate processes of dialogue, they lack adequate simulation capabilities. Component-based models and modeling frameworks provide such functionality and may be suited to supporting problematic or messy decision contexts. However, significant technical (implementation) and socio-technical (use) challenges need to be addressed before such ambition can be realized.

A Model-based Framework for Risk Assessment in Human-Computer Controlled Systems

NASA Technical Reports Server (NTRS)

Hatanaka, Iwao

2000-01-01

The rapid growth of computer technology and innovation has played a significant role in the rise of computer automation of human tasks in modem production systems across all industries. Although the rationale for automation has been to eliminate "human error" or to relieve humans from manual repetitive tasks, various computer-related hazards and accidents have emerged as a direct result of increased system complexity attributed to computer automation. The risk assessment techniques utilized for electromechanical systems are not suitable for today's software-intensive systems or complex human-computer controlled systems. This thesis will propose a new systemic model-based framework for analyzing risk in safety-critical systems where both computers and humans are controlling safety-critical functions. A new systems accident model will be developed based upon modem systems theory and human cognitive processes to better characterize system accidents, the role of human operators, and the influence of software in its direct control of significant system functions. Better risk assessments will then be achievable through the application of this new framework to complex human-computer controlled systems.

An u-Service Model Based on a Smart Phone for Urban Computing Environments

NASA Astrophysics Data System (ADS)

Cho, Yongyun; Yoe, Hyun

In urban computing environments, all of services should be based on the interaction between humans and environments around them, which frequently and ordinarily in home and office. This paper propose an u-service model based on a smart phone for urban computing environments. The suggested service model includes a context-aware and personalized service scenario development environment that can instantly describe user's u-service demand or situation information with smart devices. To do this, the architecture of the suggested service model consists of a graphical service editing environment for smart devices, an u-service platform, and an infrastructure with sensors and WSN/USN. The graphic editor expresses contexts as execution conditions of a new service through a context model based on ontology. The service platform deals with the service scenario according to contexts. With the suggested service model, an user in urban computing environments can quickly and easily make u-service or new service using smart devices.

Metrics for Electronic-Nursing-Record-Based Narratives: cross-sectional analysis.

PubMed

Kim, Kidong; Jeong, Suyeon; Lee, Kyogu; Park, Hyeoun-Ae; Min, Yul Ha; Lee, Joo Yun; Kim, Yekyung; Yoo, Sooyoung; Doh, Gippeum; Ahn, Soyeon

2016-11-30

We aimed to determine the characteristics of quantitative metrics for nursing narratives documented in electronic nursing records and their association with hospital admission traits and diagnoses in a large data set not limited to specific patient events or hypotheses. We collected 135,406,873 electronic, structured coded nursing narratives from 231,494 hospital admissions of patients discharged between 2008 and 2012 at a tertiary teaching institution that routinely uses an electronic health records system. The standardized number of nursing narratives (i.e., the total number of nursing narratives divided by the length of the hospital stay) was suggested to integrate the frequency and quantity of nursing documentation. The standardized number of nursing narratives was higher for patients aged ≥ 70 years (median = 30.2 narratives/day, interquartile range [IQR] = 24.0-39.4 narratives/day), long (≥ 8 days) hospital stays (median = 34.6 narratives/day, IQR = 27.2-43.5 narratives/day), and hospital deaths (median = 59.1 narratives/day, IQR = 47.0-74.8 narratives/day). The standardized number of narratives was higher in "pregnancy, childbirth, and puerperium" (median = 46.5, IQR = 39.0-54.7) and "diseases of the circulatory system" admissions (median = 35.7, IQR = 29.0-43.4). Diverse hospital admissions can be consistently described with nursing-document-derived metrics for similar hospital admissions and diagnoses. Some areas of hospital admissions may have consistently increasing volumes of nursing documentation across years. Usability of electronic nursing document metrics for evaluating healthcare requires multiple aspects of hospital admissions to be considered.

Integrated narrative assessment exemplification: a leukaemia case history.

PubMed

Artioli, Giovanna; Foà, Chiara; Cosentino, Chiara; Sollami, Alfonso; Taffurelli, Chiara

2017-07-18

In the Integrated Narrative Nursing Assessment (INNA), the Evidence-Based Nursing Model is integrated with the Narrative-Based Nursing Model. The INNA makes use of quantitative instruments, arising from the natural sciences as well as of qualitative ones, arising from the human achieving results of standardization and reproducibility, as well as of customization and uniqueness. Accordingly, the purpose of this work is to exemplify the thinking process of and the method adopted by a nurse adopting an integrated narrative assessment in the evaluation of a patient. The patient suffered from acute myeloid leukaemia, treated with chemotherapy. Her nurse worked in a haematology ward in a North Italy Hospital. The nurse had previous experience in conducting the assessment according to INNA. Based on patient's characteristics, the nurse chose to use the narration (to explore needs from their subjective perception) and the scales (to measure them objectively) among the various assessment instruments provided by the INNA. The resultant integrated outcomes helped the nurse to have a comprehensive overview of the person's health-care needs and their connections. These outcomes derive from the integration of narrative information with those obtained from the scales, which in this paper have shown consistent results. It is very difficult to reach this complexity by considering qualitative and quantitative assessment strategies as mutually foreclosing, given that both emerged as being very useful in identifying, understanding and measuring the needs of the assisted person. Then they both could be used to design a customized intervention, encouraging new connections between disease, illness, sickness and everyday life.

Professional Supervision as Storied Experience: Narrative Analysis Findings for Australian-Based Registered Music Therapists.

PubMed

Kennelly, Jeanette D; Baker, Felicity A; Daveson, Barbara A

2017-03-01

Limited research exists to inform a music therapist's supervision story from their pre-professional training to their practice as a professional. Evidence is needed to understand the complex nature of supervision experiences and their impact on professional practice. This qualitative study explored the supervisory experiences of Australian-based Registered Music Therapists, according to the: 1) themes that characterize their experiences, 2) influences of the supervisor's professional background, 3) outcomes of supervision, and 4) roles of the employer, the professional music therapy association, and the university in supervision standards and practice. Seven professionals were interviewed for this study. Five stages of narrative analysis were used to create their supervision stories: a life course graph, narrative psychological analysis, component story framework and narrative analysis, analysis of narratives, and final integration of the seven narrative summaries. Findings revealed that supervision practice is influenced by a supervisee's personal and professional needs. A range of supervision models or approaches is recommended, including the access of supervisors from different professional backgrounds to support each stage of learning and development. A quality supervisory experience facilitates shifts in awareness and insight, which results in improved or increased skills, confidence, and accountability of practice. Participants' concern about stakeholders included a limited understanding of the role of the supervisor, a lack of clarity about accountability of supervisory practice, and minimal guidelines, which monitor professional competencies. The benefits of supervision in music therapy depend on the quality of the supervision provided, and clarity about the roles of those involved. Research and guidelines are recommended to target these areas. © the American Music Therapy Association 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Comparison of liquid rocket engine base region heat flux computations using three turbulence models

NASA Technical Reports Server (NTRS)

Kumar, Ganesh N.; Griffith, Dwaine O., II; Prendergast, Maurice J.; Seaford, C. M.

1993-01-01

The flow in the base region of launch vehicles is characterized by flow separation, flow reversals, and reattachment. Computation of the convective heat flux in the base region and on the nozzle external surface of Space Shuttle Main Engine and Space Transportation Main Engine (STME) is an important part of defining base region thermal environments. Several turbulence models were incorporated in a CFD code and validated for flow and heat transfer computations in the separated and reattaching regions associated with subsonic and supersonic flows over backward facing steps. Heat flux computations in the base region of a single STME engine and a single S1C engine were performed using three different wall functions as well as a renormalization-group based k-epsilon model. With the very limited data available, the computed values are seen to be of the right order of magnitude. Based on the validation comparisons, it is concluded that all the turbulence models studied have predicted the reattachment location and the velocity profiles at various axial stations downstream of the step very well.

Metrics for Electronic-Nursing-Record-Based Narratives: Cross-sectional Analysis

PubMed Central

Kim, Kidong; Jeong, Suyeon; Lee, Kyogu; Park, Hyeoun-Ae; Min, Yul Ha; Lee, Joo Yun; Kim, Yekyung; Yoo, Sooyoung; Doh, Gippeum

2016-01-01

Summary Objectives We aimed to determine the characteristics of quantitative metrics for nursing narratives documented in electronic nursing records and their association with hospital admission traits and diagnoses in a large data set not limited to specific patient events or hypotheses. Methods We collected 135,406,873 electronic, structured coded nursing narratives from 231,494 hospital admissions of patients discharged between 2008 and 2012 at a tertiary teaching institution that routinely uses an electronic health records system. The standardized number of nursing narratives (i.e., the total number of nursing narratives divided by the length of the hospital stay) was suggested to integrate the frequency and quantity of nursing documentation. Results The standardized number of nursing narratives was higher for patients aged 70 years (median = 30.2 narratives/day, interquartile range [IQR] = 24.0–39.4 narratives/day), long (8 days) hospital stays (median = 34.6 narratives/day, IQR = 27.2–43.5 narratives/day), and hospital deaths (median = 59.1 narratives/day, IQR = 47.0–74.8 narratives/day). The standardized number of narratives was higher in “pregnancy, childbirth, and puerperium” (median = 46.5, IQR = 39.0–54.7) and “diseases of the circulatory system” admissions (median = 35.7, IQR = 29.0–43.4). Conclusions Diverse hospital admissions can be consistently described with nursing-document-derived metrics for similar hospital admissions and diagnoses. Some areas of hospital admissions may have consistently increasing volumes of nursing documentation across years. Usability of electronic nursing document metrics for evaluating healthcare requires multiple aspects of hospital admissions to be considered. PMID:27901174

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.

Construction of Narrative Identity Based on Paintings

ERIC Educational Resources Information Center

Garwolinska, Katarzyna; Oles, Piotr K.; Gricman, Anna

2018-01-01

This article presents a new method for encouraging clients to articulate and explore their narrative identities. The method combines the advantages of perception of art and of construction of narrative identity. It is inspired by McAdams 'Life Story Interview' and Hermans and Hermans-Jansen's Self-Confrontation Method. The material is a set of 100…

Game Design Narrative for Learning: Appropriating Adventure Game Design Narrative Devices and Techniques for the Design of Interactive Learning Environments

ERIC Educational Resources Information Center

Dickey, Michele D.

2006-01-01

The purpose of this conceptual analysis is to investigate how contemporary video and computer games might inform instructional design by looking at how narrative devices and techniques support problem solving within complex, multimodal environments. Specifically, this analysis presents a brief overview of game genres and the role of narrative in…

An industrial educational laboratory at Ducati Foundation: narrative approaches to mechanics based upon continuum physics

NASA Astrophysics Data System (ADS)

Corni, Federico; Fuchs, Hans U.; Savino, Giovanni

2018-02-01

This is a description of the conceptual foundations used for designing a novel learning environment for mechanics implemented as an Industrial Educational Laboratory - called Fisica in Moto (FiM) - at the Ducati Foundation in Bologna. In this paper, we will describe the motivation for and design of the conceptual approach to mechanics used in the lab - as such, the paper is theoretical in nature. The goal of FiM is to provide an approach to the teaching of mechanics based upon imaginative structures found in continuum physics suitable to engineering and science. We show how continuum physics creates models of mechanical phenomena by using momentum and angular momentum as primitive quantities. We analyse this approach in terms of cognitive linguistic concepts such as conceptual metaphor and narrative framing of macroscopic physical phenomena. The model discussed here has been used in the didactical design of the actual lab and raises questions for an investigation of student learning of mechanics in a narrative setting.

A Four-Stage Model for Planning Computer-Based Instruction.

ERIC Educational Resources Information Center

Morrison, Gary R.; Ross, Steven M.

1988-01-01

Describes a flexible planning process for developing computer based instruction (CBI) in which the CBI design is implemented on paper between the lesson design and the program production. A four-stage model is explained, including (1) an initial flowchart, (2) storyboards, (3) a detailed flowchart, and (4) an evaluation. (16 references)…

Effects of narrator empathy in a computer delivered brief intervention for alcohol use.

PubMed

Ellis, Jennifer D; Grekin, Emily R; Beatty, Jessica R; McGoron, Lucy; LaLiberte, Benjamin V; Pop, Damaris E; Kostecki, Anthony P; Ondersma, Steven J

2017-10-01

Computer-delivered, brief interventions (CDBIs) have been an increasingly popular way to treat alcohol use disorders; however, very few studies have examined which characteristics of CDBIs maximize intervention effectiveness. The literature has consistently demonstrated that therapist empathy is associated with reduced substance use in in-person therapy; however, it is unclear whether this principle applies to CDBIs. Therefore, the study aimed to examine whether the presence of an empathic narrator increased intentions to reduce heavy drinking in a CDBI. Results suggest that the presence of empathy increases motivation to reduce drinking, and makes participants feel more supported and less criticized. Copyright © 2017 Elsevier Inc. All rights reserved.

A Narrative-Expectation-Based Approach to Temporal Update in Discourse Comprehension

ERIC Educational Resources Information Center

Dery, Jeruen E.; Koenig, Jean-Pierre

2015-01-01

This study concerns the mechanisms involving temporal update in discourse comprehension, comparing traditional approaches based on "Aktionsart" and Iconicity against an approach based on narrative expectations. Our experiments suggest that readers pay more attention to fine-grained discourse properties (such as salient temporal…

Comparing large-scale computational approaches to epidemic modeling: agent-based versus structured metapopulation models.

PubMed

Ajelli, Marco; Gonçalves, Bruno; Balcan, Duygu; Colizza, Vittoria; Hu, Hao; Ramasco, José J; Merler, Stefano; Vespignani, Alessandro

2010-06-29

In recent years large-scale computational models for the realistic simulation of epidemic outbreaks have been used with increased frequency. Methodologies adapt to the scale of interest and range from very detailed agent-based models to spatially-structured metapopulation models. One major issue thus concerns to what extent the geotemporal spreading pattern found by different modeling approaches may differ and depend on the different approximations and assumptions used. We provide for the first time a side-by-side comparison of the results obtained with a stochastic agent-based model and a structured metapopulation stochastic model for the progression of a baseline pandemic event in Italy, a large and geographically heterogeneous European country. The agent-based model is based on the explicit representation of the Italian population through highly detailed data on the socio-demographic structure. The metapopulation simulations use the GLobal Epidemic and Mobility (GLEaM) model, based on high-resolution census data worldwide, and integrating airline travel flow data with short-range human mobility patterns at the global scale. The model also considers age structure data for Italy. GLEaM and the agent-based models are synchronized in their initial conditions by using the same disease parameterization, and by defining the same importation of infected cases from international travels. The results obtained show that both models provide epidemic patterns that are in very good agreement at the granularity levels accessible by both approaches, with differences in peak timing on the order of a few days. The relative difference of the epidemic size depends on the basic reproductive ratio, R0, and on the fact that the metapopulation model consistently yields a larger incidence than the agent-based model, as expected due to the differences in the structure in the intra-population contact pattern of the approaches. The age breakdown analysis shows that similar attack rates are

Examining narrative transportation to anti-alcohol narratives

PubMed Central

Banerjee, Smita C.; Greene, Kathryn

2016-01-01

This study examined the transportation effects of alcohol consequence narratives varying in source (written by the narrative protagonist vs. protagonist's partner) and type of heath consequence (physical or emotional). Additionally, this study examined the role of narrative transportation and cognitive and discrete affective responses in the persuasion process. In this study, 501 students of a large northern university in the United Kingdom participated and were randomly assigned to one of the four conditions of narratives about alcohol use. Transportation was operationalized as general and self-reflective transportation. Results demonstrated that for narratives written by protagonist, the emotional effect narrative resulted in greater general transportation than the physical effect narrative. However, for narratives written by the protagonist's partner, the physical effect narrative resulted in greater general transportation than the emotional effect narrative. These findings were not substantiated for self-reflective transportation. Finally, results suggest that transportation experienced by anti-alcohol narratives can influence both favourable cognitive response and guilt, which are significant mediators in alcohol-related expectancies. Important theoretical and empirical implications are discussed. PMID:28133436

Learning-based computing techniques in geoid modeling for precise height transformation

NASA Astrophysics Data System (ADS)

Erol, B.; Erol, S.

2013-03-01

Precise determination of local geoid is of particular importance for establishing height control in geodetic GNSS applications, since the classical leveling technique is too laborious. A geoid model can be accurately obtained employing properly distributed benchmarks having GNSS and leveling observations using an appropriate computing algorithm. Besides the classical multivariable polynomial regression equations (MPRE), this study attempts an evaluation of learning based computing algorithms: artificial neural networks (ANNs), adaptive network-based fuzzy inference system (ANFIS) and especially the wavelet neural networks (WNNs) approach in geoid surface approximation. These algorithms were developed parallel to advances in computer technologies and recently have been used for solving complex nonlinear problems of many applications. However, they are rather new in dealing with precise modeling problem of the Earth gravity field. In the scope of the study, these methods were applied to Istanbul GPS Triangulation Network data. The performances of the methods were assessed considering the validation results of the geoid models at the observation points. In conclusion the ANFIS and WNN revealed higher prediction accuracies compared to ANN and MPRE methods. Beside the prediction capabilities, these methods were also compared and discussed from the practical point of view in conclusions.

Local Heroes, Narrative Worlds and the Imagination: The Making of a Moral Curriculum through Experiential Narratives

ERIC Educational Resources Information Center

Conle, Carola; Boone, Michelle

2008-01-01

Concern about the impact of narrative worlds and their heroes offered by the media prompted research on encounters with moral models in experiential, narrative curricula. Researchers tracked the extension of a mandated Language Arts curriculum on "heroes" through the experiential narratives of four local heroes chosen collaboratively by teacher,…

Analysis and Research on Spatial Data Storage Model Based on Cloud Computing Platform

NASA Astrophysics Data System (ADS)

Hu, Yong

2017-12-01

In this paper, the data processing and storage characteristics of cloud computing are analyzed and studied. On this basis, a cloud computing data storage model based on BP neural network is proposed. In this data storage model, it can carry out the choice of server cluster according to the different attributes of the data, so as to complete the spatial data storage model with load balancing function, and have certain feasibility and application advantages.

Impact of implementation choices on quantitative predictions of cell-based computational models

NASA Astrophysics Data System (ADS)

Kursawe, Jochen; Baker, Ruth E.; Fletcher, Alexander G.

2017-09-01

'Cell-based' models provide a powerful computational tool for studying the mechanisms underlying the growth and dynamics of biological tissues in health and disease. An increasing amount of quantitative data with cellular resolution has paved the way for the quantitative parameterisation and validation of such models. However, the numerical implementation of cell-based models remains challenging, and little work has been done to understand to what extent implementation choices may influence model predictions. Here, we consider the numerical implementation of a popular class of cell-based models called vertex models, which are often used to study epithelial tissues. In two-dimensional vertex models, a tissue is approximated as a tessellation of polygons and the vertices of these polygons move due to mechanical forces originating from the cells. Such models have been used extensively to study the mechanical regulation of tissue topology in the literature. Here, we analyse how the model predictions may be affected by numerical parameters, such as the size of the time step, and non-physical model parameters, such as length thresholds for cell rearrangement. We find that vertex positions and summary statistics are sensitive to several of these implementation parameters. For example, the predicted tissue size decreases with decreasing cell cycle durations, and cell rearrangement may be suppressed by large time steps. These findings are counter-intuitive and illustrate that model predictions need to be thoroughly analysed and implementation details carefully considered when applying cell-based computational models in a quantitative setting.

Children's Narrative Development through Computer Game Authoring

ERIC Educational Resources Information Center

Robertson, Judy; Good, Judith

2005-01-01

Playing computer games is an extremely popular leisure activity for children. In fact, the computer games market in the UK is now double that of the video rental market, and substantially larger than cinema box office sales, and under people under the age of 18 make up 38% of these game players. Based on the popularity and strong motivational…

A border-ownership model based on computational electromagnetism.

PubMed

Zainal, Zaem Arif; Satoh, Shunji

2018-03-01

The mathematical relation between a vector electric field and its corresponding scalar potential field is useful to formulate computational problems of lower/middle-order visual processing, specifically related to the assignment of borders to the side of the object: so-called border ownership (BO). BO coding is a key process for extracting the objects from the background, allowing one to organize a cluttered scene. We propose that the problem is solvable simultaneously by application of a theorem of electromagnetism, i.e., "conservative vector fields have zero rotation, or "curl." We hypothesize that (i) the BO signal is definable as a vector electric field with arrowheads pointing to the inner side of perceived objects, and (ii) its corresponding scalar field carries information related to perceived order in depth of occluding/occluded objects. A simple model was developed based on this computational theory. Model results qualitatively agree with object-side selectivity of BO-coding neurons, and with perceptions of object order. The model update rule can be reproduced as a plausible neural network that presents new interpretations of existing physiological results. Results of this study also suggest that T-junction detectors are unnecessary to calculate depth order. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computational models of neuromodulation.

PubMed

Fellous, J M; Linster, C

1998-05-15

Computational modeling of neural substrates provides an excellent theoretical framework for the understanding of the computational roles of neuromodulation. In this review, we illustrate, with a large number of modeling studies, the specific computations performed by neuromodulation in the context of various neural models of invertebrate and vertebrate preparations. We base our characterization of neuromodulations on their computational and functional roles rather than on anatomical or chemical criteria. We review the main framework in which neuromodulation has been studied theoretically (central pattern generation and oscillations, sensory processing, memory and information integration). Finally, we present a detailed mathematical overview of how neuromodulation has been implemented at the single cell and network levels in modeling studies. Overall, neuromodulation is found to increase and control computational complexity.

Narrative theory: II. Self-generated and experimenter-provided negative income shock narratives increase delay discounting.

PubMed

Mellis, Alexandra M; Snider, Sarah E; Bickel, Warren K

2018-04-01

Reading experimenter-provided narratives of negative income shock has been previously demonstrated to increase impulsivity, as measured by discounting of delayed rewards. We hypothesized that writing these narratives would potentiate their effects of negative income shock on decision-making more than simply reading them. In the current study, 193 cigarette-smoking individuals from Amazon Mechanical Turk were assigned to either read an experimenter-provided narrative or self-generate a narrative describing either the negative income shock of job loss or a neutral condition of job transfer. Individuals then completed a task of delay discounting and measures of affective response to narratives, as well as rating various narrative qualities such as personal relevance and vividness. Consistent with past research, narratives of negative income shock increased delay discounting compared to control narratives. No significant differences existed in delay discounting after self-generating compared to reading experimenter-provided narratives. Positive affect was lower and negative affect was higher in response to narratives of job loss, but affect measures did not differ based on whether narratives were experimenter-provided or self-generated. All narratives were rated as equally realistic, but self-generated narratives (whether negative or neutral) were rated as more vivid and relevant than experimenter-provided narratives. These results indicate that the content of negative income shock narratives, regardless of source, consistently drives short-term choices. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

An Effective Model to Increase Student Attitude and Achievement: Narrative Including Analogies

ERIC Educational Resources Information Center

Akkuzu, Nalan; Akcay, Husamettin

2011-01-01

This study describes the analogical models and narratives used to introduce and teach Grade 9 chemical covalent compounds which are relatively abstract and difficult for students. We explained each model's development during the lessons and analyzed understanding students derived from these learning materials. In this context, achievement,…

Models@Home: distributed computing in bioinformatics using a screensaver based approach.

PubMed

Krieger, Elmar; Vriend, Gert

2002-02-01

Due to the steadily growing computational demands in bioinformatics and related scientific disciplines, one is forced to make optimal use of the available resources. A straightforward solution is to build a network of idle computers and let each of them work on a small piece of a scientific challenge, as done by Seti@Home (http://setiathome.berkeley.edu), the world's largest distributed computing project. We developed a generally applicable distributed computing solution that uses a screensaver system similar to Seti@Home. The software exploits the coarse-grained nature of typical bioinformatics projects. Three major considerations for the design were: (1) often, many different programs are needed, while the time is lacking to parallelize them. Models@Home can run any program in parallel without modifications to the source code; (2) in contrast to the Seti project, bioinformatics applications are normally more sensitive to lost jobs. Models@Home therefore includes stringent control over job scheduling; (3) to allow use in heterogeneous environments, Linux and Windows based workstations can be combined with dedicated PCs to build a homogeneous cluster. We present three practical applications of Models@Home, running the modeling programs WHAT IF and YASARA on 30 PCs: force field parameterization, molecular dynamics docking, and database maintenance.

Research on application of intelligent computation based LUCC model in urbanization process

NASA Astrophysics Data System (ADS)

Chen, Zemin

2007-06-01

Global change study is an interdisciplinary and comprehensive research activity with international cooperation, arising in 1980s, with the largest scopes. The interaction between land use and cover change, as a research field with the crossing of natural science and social science, has become one of core subjects of global change study as well as the front edge and hot point of it. It is necessary to develop research on land use and cover change in urbanization process and build an analog model of urbanization to carry out description, simulation and analysis on dynamic behaviors in urban development change as well as to understand basic characteristics and rules of urbanization process. This has positive practical and theoretical significance for formulating urban and regional sustainable development strategy. The effect of urbanization on land use and cover change is mainly embodied in the change of quantity structure and space structure of urban space, and LUCC model in urbanization process has been an important research subject of urban geography and urban planning. In this paper, based upon previous research achievements, the writer systematically analyzes the research on land use/cover change in urbanization process with the theories of complexity science research and intelligent computation; builds a model for simulating and forecasting dynamic evolution of urban land use and cover change, on the basis of cellular automation model of complexity science research method and multi-agent theory; expands Markov model, traditional CA model and Agent model, introduces complexity science research theory and intelligent computation theory into LUCC research model to build intelligent computation-based LUCC model for analog research on land use and cover change in urbanization research, and performs case research. The concrete contents are as follows: 1. Complexity of LUCC research in urbanization process. Analyze urbanization process in combination with the contents

Improving Computational Efficiency of Prediction in Model-Based Prognostics Using the Unscented Transform

NASA Technical Reports Server (NTRS)

Daigle, Matthew John; Goebel, Kai Frank

2010-01-01

Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.

Narrative, Visual Model and Dragon Culture: A Narrative Analysis of Value Presentation in Two Movies Preferred by Chinese Adolescents. Research Bulletin 98.

ERIC Educational Resources Information Center

Jin, He

A narrative study was conducted of the visual models in two movies preferred by Chinese adolescents in two schools (n=152). The two movies studied were "Three Decisive Campaigns" (A Chinese Trilogy) and the American science fiction movie, "Jurassic Park." The modified approach from Bandura's modeling theory and film semiotics…

A spread willingness computing-based information dissemination model.

PubMed

Huang, Haojing; Cui, Zhiming; Zhang, Shukui

2014-01-01

This paper constructs a kind of spread willingness computing based on information dissemination model for social network. The model takes into account the impact of node degree and dissemination mechanism, combined with the complex network theory and dynamics of infectious diseases, and further establishes the dynamical evolution equations. Equations characterize the evolutionary relationship between different types of nodes with time. The spread willingness computing contains three factors which have impact on user's spread behavior: strength of the relationship between the nodes, views identity, and frequency of contact. Simulation results show that different degrees of nodes show the same trend in the network, and even if the degree of node is very small, there is likelihood of a large area of information dissemination. The weaker the relationship between nodes, the higher probability of views selection and the higher the frequency of contact with information so that information spreads rapidly and leads to a wide range of dissemination. As the dissemination probability and immune probability change, the speed of information dissemination is also changing accordingly. The studies meet social networking features and can help to master the behavior of users and understand and analyze characteristics of information dissemination in social network.

Validating the ACE Model for Evaluating Student Performance Using a Teaching-Learning Process Based on Computational Modeling Systems

ERIC Educational Resources Information Center

Louzada, Alexandre Neves; Elia, Marcos da Fonseca; Sampaio, Fábio Ferrentini; Vidal, Andre Luiz Pestana

2014-01-01

The aim of this work is to adapt and test, in a Brazilian public school, the ACE model proposed by Borkulo for evaluating student performance as a teaching-learning process based on computational modeling systems. The ACE model is based on different types of reasoning involving three dimensions. In addition to adapting the model and introducing…

Modeling Teaching with a Computer-Based Concordancer in a TESL Preservice Teacher Education Program.

ERIC Educational Resources Information Center

Gan, Siowck-Lee; And Others

1996-01-01

This study modeled teaching with a computer-based concordancer in a Teaching English-as-a-Second-Language program. Preservice teachers were randomly assigned to work with computer concordancing software or vocabulary exercises to develop word attack skills. Pretesting and posttesting indicated that computer concordancing was more effective in…

Specifying and Refining a Measurement Model for a Computer-Based Interactive Assessment

ERIC Educational Resources Information Center

Levy, Roy; Mislevy, Robert J.

2004-01-01

The challenges of modeling students' performance in computer-based interactive assessments include accounting for multiple aspects of knowledge and skill that arise in different situations and the conditional dependencies among multiple aspects of performance. This article describes a Bayesian approach to modeling and estimating cognitive models…

On Writing and Reading Artistic Computational Ecosystems.

PubMed

Antunes, Rui Filipe; Leymarie, Frederic Fol; Latham, William

2015-01-01

We study the use of the generative systems known as computational ecosystems to convey artistic and narrative aims. These are virtual worlds running on computers, composed of agents that trade units of energy and emulate cycles of life and behaviors adapted from biological life forms. In this article we propose a conceptual framework in order to understand these systems, which are involved in processes of authorship and interpretation that this investigation analyzes in order to identify critical instruments for artistic exploration. We formulate a model of narrative that we call system stories (after Mitchell Whitelaw), characterized by the dynamic network of material and conceptual processes that define these artefacts. They account for narrative constellations with multiple agencies from which meaning and messages emerge. Finally, we present three case studies to explore the potential of this model within an artistic and generative domain, arguing that this understanding expands and enriches the palette of the language of these systems.

Narrative Aversion: Challenges for the Illness Narrative Advocate.

PubMed

Behrendt, Kathy

2017-02-01

Engaging in self-narrative is often touted as a powerful antidote to the bad effects of illness. However, there are various examples of what may broadly be termed "aversion" to illness narrative. I group these into three kinds: aversion to certain types of illness narrative; aversion to illness narrative as a whole; and aversion to illness narrative as an essentially therapeutic endeavor. These aversions can throw into doubt the advantages claimed for the illness narrator, including the key benefits of repair to the damage illness does to identity and life-trajectory. Underlying these alleged benefits are two key presuppositions: that it is the whole of one's life that is narratively unified, and that one's identity is inextricably bound up with narrative. By letting go of these assumptions, illness narrative advocates can respond to the challenges of narrative aversions. © The Author 2016. 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.

Using Case-Based Pedagogy in the Philippines: A Narrative Inquiry

NASA Astrophysics Data System (ADS)

Arellano, Elvira L.; Barcenal, Tessie L.; Bilbao, Purita P.; Castellano, Merilin A.; Nichols, Sharon E.; Tippins, Deborah J.

2001-04-01

This study features use of case-based pedagogy as a context for exploring science teacher education reform. A central premise of the study is that science teacher education reform is a complex process characterised by the individual and collective narrative histories of teachers. The study was conducted at West Visayas State University in the Philippines as a collaborative research endeavour involving two US and four Filipino science teacher educators. The centrepiece of this study was a case experience prompted by reflection on prospective and practicing elementary teachers' written cases. Results of the study are presented here as a layered narrative. An initial layer explores how a case, written by a prospective teacher, was interwoven with her past and future life history. A second layer looks at sociocultural and professional tensions that mediated the participants' case experience. A third layer represents how the case experience provided a community that supported critical reflection among the research team members. Implications from the study emphasise that case-based pedagogy can serve as a basis for critical reflection to inform community-based approaches to science teacher education pedagogical and research reform.

Model of Procedure Usage – Results from a Qualitative Study to Inform Design of Computer-Based Procedures

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

Johanna H Oxstrand; Katya L Le Blanc

The nuclear industry is constantly trying to find ways to decrease the human error rate, especially the human errors associated with procedure use. As a step toward the goal of improving procedure use performance, researchers, together with the nuclear industry, have been looking at replacing the current paper-based procedures with computer-based procedure systems. The concept of computer-based procedures is not new by any means; however most research has focused on procedures used in the main control room. Procedures reviewed in these efforts are mainly emergency operating procedures and normal operating procedures. Based on lessons learned for these previous efforts wemore » are now exploring a more unknown application for computer based procedures - field procedures, i.e. procedures used by nuclear equipment operators and maintenance technicians. The Idaho National Laboratory, the Institute for Energy Technology, and participants from the U.S. commercial nuclear industry are collaborating in an applied research effort with the objective of developing requirements and specifications for a computer-based procedure system to be used by field operators. The goal is to identify the types of human errors that can be mitigated by using computer-based procedures and how to best design the computer-based procedures to do this. The underlying philosophy in the research effort is “Stop – Start – Continue”, i.e. what features from the use of paper-based procedures should we not incorporate (Stop), what should we keep (Continue), and what new features or work processes should be added (Start). One step in identifying the Stop – Start – Continue was to conduct a baseline study where affordances related to the current usage of paper-based procedures were identified. The purpose of the study was to develop a model of paper based procedure use which will help to identify desirable features for computer based procedure prototypes. Affordances such as note taking

Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

ERIC Educational Resources Information Center

Dickes, Amanda Catherine; Sengupta, Pratim

2013-01-01

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these…

Fast computation of derivative based sensitivities of PSHA models via algorithmic differentiation

NASA Astrophysics Data System (ADS)

Leövey, Hernan; Molkenthin, Christian; Scherbaum, Frank; Griewank, Andreas; Kuehn, Nicolas; Stafford, Peter

2015-04-01

Probabilistic seismic hazard analysis (PSHA) is the preferred tool for estimation of potential ground-shaking hazard due to future earthquakes at a site of interest. A modern PSHA represents a complex framework which combines different models with possible many inputs. Sensitivity analysis is a valuable tool for quantifying changes of a model output as inputs are perturbed, identifying critical input parameters and obtaining insight in the model behavior. Differential sensitivity analysis relies on calculating first-order partial derivatives of the model output with respect to its inputs. Moreover, derivative based global sensitivity measures (Sobol' & Kucherenko '09) can be practically used to detect non-essential inputs of the models, thus restricting the focus of attention to a possible much smaller set of inputs. Nevertheless, obtaining first-order partial derivatives of complex models with traditional approaches can be very challenging, and usually increases the computation complexity linearly with the number of inputs appearing in the models. In this study we show how Algorithmic Differentiation (AD) tools can be used in a complex framework such as PSHA to successfully estimate derivative based sensitivities, as is the case in various other domains such as meteorology or aerodynamics, without no significant increase in the computation complexity required for the original computations. First we demonstrate the feasibility of the AD methodology by comparing AD derived sensitivities to analytically derived sensitivities for a basic case of PSHA using a simple ground-motion prediction equation. In a second step, we derive sensitivities via AD for a more complex PSHA study using a ground motion attenuation relation based on a stochastic method to simulate strong motion. The presented approach is general enough to accommodate more advanced PSHA studies of higher complexity.

Rubber airplane: Constraint-based component-modeling for knowledge representation in computer-aided conceptual design

NASA Technical Reports Server (NTRS)

Kolb, Mark A.

1990-01-01

Viewgraphs on Rubber Airplane: Constraint-based Component-Modeling for Knowledge Representation in Computer Aided Conceptual Design are presented. Topics covered include: computer aided design; object oriented programming; airfoil design; surveillance aircraft; commercial aircraft; aircraft design; and launch vehicles.

Agent-Based Computational Modeling of Cell Culture ...

EPA Pesticide Factsheets

Quantitative characterization of cellular dose in vitro is needed for alignment of doses in vitro and in vivo. We used the agent-based software, CompuCell3D (CC3D), to provide a stochastic description of cell growth in culture. The model was configured so that isolated cells assumed a “fried egg shape” but became increasingly cuboidal with increasing confluency. The surface area presented by each cell to the overlying medium varies from cell-to-cell and is a determinant of diffusional flux of toxicant from the medium into the cell. Thus, dose varies among cells for a given concentration of toxicant in the medium. Computer code describing diffusion of H2O2 from medium into each cell and clearance of H2O2 was calibrated against H2O2 time-course data (25, 50, or 75 uM H2O2 for 60 min) obtained with the Amplex Red assay for the medium and the H2O2-sensitive fluorescent reporter, HyPer, for cytosol. Cellular H2O2 concentrations peaked at about 5 min and were near baseline by 10 min. The model predicted a skewed distribution of surface areas, with between cell variation usually 2 fold or less. Predicted variability in cellular dose was in rough agreement with the variation in the HyPer data. These results are preliminary, as the model was not calibrated to the morphology of a specific cell type. Future work will involve morphology model calibration against human bronchial epithelial (BEAS-2B) cells. Our results show, however, the potential of agent-based modeling

Systematic individualized narrative language intervention on the personal narratives of children with autism.

PubMed

Petersen, Douglas B; Brown, Catherine L; Ukrainetz, Teresa A; Wise, Christine; Spencer, Trina D; Zebre, Jennifer

2014-01-01

The purpose of this study was to investigate the effect of an individualized, systematic language intervention on the personal narratives of children with autism. A single-subject, multiple-baseline design across participants and behaviors was used to examine the effect of the intervention on language features of personal narratives. Three 6- to 8-year-old boys with autism participated in 12 individual intervention sessions that targeted 2-3 story grammar elements (e.g., problem, plan) and 3-4 linguistic complexity elements (e.g., causal subordination, adverbs) selected from each participant's baseline performance. Intervention involved repeated retellings of customized model narratives and the generation of personal narratives with a systematic reduction of visual and verbal scaffolding. Independent personal narratives generated at the end of each baseline, intervention, and maintenance session were analyzed for presence and sophistication of targeted features. Graphical and statistical results showed immediate improvement in targeted language features as a function of intervention. There was mixed evidence of maintenance 2 and 7 weeks after intervention. Children with autism can benefit from an individualized, systematic intervention targeting specific narrative language features. Greater intensity of intervention may be needed to gain enduring effects for some language features.

Exploring the Experiences of Living With Stroke Through Narrative

PubMed Central

Nasr, Nasrin; Mawson, Susan; Wright, Peter; Parker, Jack; Mountain, Gail

2016-01-01

Chronic illness models are normally used to explain and predict the experience of living with a long-term condition. The aim of this study was to present the findings of narrative interviews with stroke survivors and their family carers to understand their experiences of stroke. We interviewed five people with stroke and three family carers from the United Kingdom. We used thematic analysis to generate themes from their narrative accounts and then linked them to broader theoretical perspectives while influenced by the concept of reinterpretation of life. The narrative accounts of participants are mainly structured based on how their changed bodies poststroke changed their identities and roles and consequently their relationships with others. In this study, we underline the need for using methods like narrative to explain strategies that people use to make sense of their experiences of living with a long-term condition such as stroke. PMID:28462337

A Spread Willingness Computing-Based Information Dissemination Model

PubMed Central

Cui, Zhiming; Zhang, Shukui

2014-01-01

This paper constructs a kind of spread willingness computing based on information dissemination model for social network. The model takes into account the impact of node degree and dissemination mechanism, combined with the complex network theory and dynamics of infectious diseases, and further establishes the dynamical evolution equations. Equations characterize the evolutionary relationship between different types of nodes with time. The spread willingness computing contains three factors which have impact on user's spread behavior: strength of the relationship between the nodes, views identity, and frequency of contact. Simulation results show that different degrees of nodes show the same trend in the network, and even if the degree of node is very small, there is likelihood of a large area of information dissemination. The weaker the relationship between nodes, the higher probability of views selection and the higher the frequency of contact with information so that information spreads rapidly and leads to a wide range of dissemination. As the dissemination probability and immune probability change, the speed of information dissemination is also changing accordingly. The studies meet social networking features and can help to master the behavior of users and understand and analyze characteristics of information dissemination in social network. PMID:25110738

Computer simulation models of pre-diabetes populations: a systematic review protocol

PubMed Central

Khurshid, Waqar; Pagano, Eva; Feenstra, Talitha

2017-01-01

Introduction Diabetes is a major public health problem and prediabetes (intermediate hyperglycaemia) is associated with a high risk of developing diabetes. With evidence supporting the use of preventive interventions for prediabetes populations and the discovery of novel biomarkers stratifying the risk of progression, there is a need to evaluate their cost-effectiveness across jurisdictions. In diabetes and prediabetes, it is relevant to inform cost-effectiveness analysis using decision models due to their ability to forecast long-term health outcomes and costs beyond the time frame of clinical trials. To support good implementation and reimbursement decisions of interventions in these populations, models should be clinically credible, based on best available evidence, reproducible and validated against clinical data. Our aim is to identify recent studies on computer simulation models and model-based economic evaluations of populations of individuals with prediabetes, qualify them and discuss the knowledge gaps, challenges and opportunities that need to be addressed for future evaluations. Methods and analysis A systematic review will be conducted in MEDLINE, Embase, EconLit and National Health Service Economic Evaluation Database. We will extract peer-reviewed studies published between 2000 and 2016 that describe computer simulation models of the natural history of individuals with prediabetes and/or decision models to evaluate the impact of interventions, risk stratification and/or screening on these populations. Two reviewers will independently assess each study for inclusion. Data will be extracted using a predefined pro forma developed using best practice. Study quality will be assessed using a modelling checklist. A narrative synthesis of all studies will be presented, focussing on model structure, quality of models and input data, and validation status. Ethics and dissemination This systematic review is exempt from ethics approval because the work is carried

Models of home care services for persons with dementia: a narrative review.

PubMed

Low, Lee-Fay; Fletcher, Jennifer

2015-10-01

Worldwide trends of increasing dementia prevalence, have put economic and workforce pressures to shifting care for persons with dementia from residential care to home care. We reviewed the effects of the four dominant models of home care delivery on outcomes for community-dwelling persons with dementia. These models are: case management, integrated care, consumer directed care, and restorative care. This narrative review describes benefits and possible drawbacks for persons with dementia outcomes and elements that comprise successful programs. Case management for persons with dementia may increase use of community-based services and delay nursing home admission. Integrated care is associated with greater client satisfaction, increased use of community based services, and reduced hospital days however the clinical impacts on persons with dementia and their carers are not known. Consumer directed care increases satisfaction with care and service usage, but had little effect on clinical outcomes. Restorative models of home care have been shown to improve function and quality of life however these trials have excluded persons with dementia, with the exception of a pilot study. There has been a little research into models of home care for people with dementia, and no head-to-head comparison of the different models. Research to inform evidence-based policy and service delivery for people with dementia needs to evaluate both the impact of different models on outcomes, and investigate how to best deliver these models to maximize outcomes.

Toward a model-based predictive controller design in brain-computer interfaces.

PubMed

Kamrunnahar, M; Dias, N S; Schiff, S J

2011-05-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain-computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8-23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications.

Toward a Model-Based Predictive Controller Design in Brain–Computer Interfaces

PubMed Central

Kamrunnahar, M.; Dias, N. S.; Schiff, S. J.

2013-01-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain–computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8–23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications. PMID:21267657

Conceptual Models of Social Determinants of Health: A Narrative Review

PubMed Central

HOSSEINI SHOKOUH, Sayyed Morteza; ARAB, Mohammad; EMAMGHOLIPOUR, Sara; RASHIDIAN, Arash; MONTAZERI, Ali; ZABOLI, Rouhollah

2017-01-01

Background: There are several conflicting conceptual models to explain social determinants of health (SDH) as responsible for most health inequalities. This study aimed to present these models in historical perspective and provide main component of SDH models as an SES indicators. Methods: This was a narrative study using international databases to retrieve literature dealing with conceptual models of SDH. All publication in English language until Mar 2015 was included. The CASP and PRISMA were used to summarize the literature. Results: Overall, 248 publications were retrieved and screened. After exclusion of irrelevant and duplicates, 94 citations were found to be relevant and 21 publications included in this review. In general, 21 models of SDH were found: some models presented before year 1995(n=4), some models presented between 1995 and 2005 (n=13) and some models presented after 2005 (n=4). However, we found three categories of indicators that contribute to SDH models and that were classic factors, fixed and demographic factors and proxy factors. Conclusion: Reduction of socioeconomic inequalities in health requires understanding of mechanisms and causal pathways; therefore, every country needs to design the specific model. As the available models are for developed countries, lack of a specific model for developing ones is tangible. As there is no gold standard related to SES indicators, therefore, it is proposed to use the various indicators based on life course approach, which leads to understanding and adopting effective policy interventions. PMID:28540259

Approaches to Classroom-Based Computational Science.

ERIC Educational Resources Information Center

Guzdial, Mark

Computational science includes the use of computer-based modeling and simulation to define and test theories about scientific phenomena. The challenge for educators is to develop techniques for implementing computational science in the classroom. This paper reviews some previous work on the use of simulation alone (without modeling), modeling…

Development of an Interactive Computer-Based Learning Strategy to Assist in Teaching Water Quality Modelling

ERIC Educational Resources Information Center

Zigic, Sasha; Lemckert, Charles J.

2007-01-01

The following paper presents a computer-based learning strategy to assist in introducing and teaching water quality modelling to undergraduate civil engineering students. As part of the learning strategy, an interactive computer-based instructional (CBI) aid was specifically developed to assist students to set up, run and analyse the output from a…

Identity-Based Authentication for Cloud Computing

NASA Astrophysics Data System (ADS)

Li, Hongwei; Dai, Yuanshun; Tian, Ling; Yang, Haomiao

Cloud computing is a recently developed new technology for complex systems with massive-scale services sharing among numerous users. Therefore, authentication of both users and services is a significant issue for the trust and security of the cloud computing. SSL Authentication Protocol (SAP), once applied in cloud computing, will become so complicated that users will undergo a heavily loaded point both in computation and communication. This paper, based on the identity-based hierarchical model for cloud computing (IBHMCC) and its corresponding encryption and signature schemes, presented a new identity-based authentication protocol for cloud computing and services. Through simulation testing, it is shown that the authentication protocol is more lightweight and efficient than SAP, specially the more lightweight user side. Such merit of our model with great scalability is very suited to the massive-scale cloud.

Sensitivity of Narrative Organization Measures Using Narrative Retells Produced by Young School-Age Children

ERIC Educational Resources Information Center

Heilmann, John; Miller, Jon F.; Nockerts, Ann

2010-01-01

Analysis of children's productions of oral narratives provides a rich description of children's oral language skills. However, measures of narrative organization can be directly affected by both developmental and task-based performance constraints which can make a measure insensitive and inappropriate for a particular population and/or sampling…

A Web-based Distributed Voluntary Computing Platform for Large Scale Hydrological Computations

NASA Astrophysics Data System (ADS)

Demir, I.; Agliamzanov, R.

2014-12-01

Distributed volunteer computing can enable researchers and scientist to form large parallel computing environments to utilize the computing power of the millions of computers on the Internet, and use them towards running large scale environmental simulations and models to serve the common good of local communities and the world. Recent developments in web technologies and standards allow client-side scripting languages to run at speeds close to native application, and utilize the power of Graphics Processing Units (GPU). Using a client-side scripting language like JavaScript, we have developed an open distributed computing framework that makes it easy for researchers to write their own hydrologic models, and run them on volunteer computers. Users will easily enable their websites for visitors to volunteer sharing their computer resources to contribute running advanced hydrological models and simulations. Using a web-based system allows users to start volunteering their computational resources within seconds without installing any software. The framework distributes the model simulation to thousands of nodes in small spatial and computational sizes. A relational database system is utilized for managing data connections and queue management for the distributed computing nodes. In this paper, we present a web-based distributed volunteer computing platform to enable large scale hydrological simulations and model runs in an open and integrated environment.

Methodological Pluralism and Narrative Inquiry

ERIC Educational Resources Information Center

Michie, Michael

2013-01-01

This paper considers how the integral theory model of Nancy Davis and Laurie Callihan might be enacted using a different qualitative methodology, in this case the narrative methodology. The focus of narrative research is shown to be on "what meaning is being made" rather than "what is happening here" (quadrant 2 rather than…

On agent-based modeling and computational social science.

PubMed

Conte, Rosaria; Paolucci, Mario

2014-01-01

In the first part of the paper, the field of agent-based modeling (ABM) is discussed focusing on the role of generative theories, aiming at explaining phenomena by growing them. After a brief analysis of the major strengths of the field some crucial weaknesses are analyzed. In particular, the generative power of ABM is found to have been underexploited, as the pressure for simple recipes has prevailed and shadowed the application of rich cognitive models. In the second part of the paper, the renewal of interest for Computational Social Science (CSS) is focused upon, and several of its variants, such as deductive, generative, and complex CSS, are identified and described. In the concluding remarks, an interdisciplinary variant, which takes after ABM, reconciling it with the quantitative one, is proposed as a fundamental requirement for a new program of the CSS.

On agent-based modeling and computational social science

PubMed Central

Conte, Rosaria; Paolucci, Mario

2014-01-01

In the first part of the paper, the field of agent-based modeling (ABM) is discussed focusing on the role of generative theories, aiming at explaining phenomena by growing them. After a brief analysis of the major strengths of the field some crucial weaknesses are analyzed. In particular, the generative power of ABM is found to have been underexploited, as the pressure for simple recipes has prevailed and shadowed the application of rich cognitive models. In the second part of the paper, the renewal of interest for Computational Social Science (CSS) is focused upon, and several of its variants, such as deductive, generative, and complex CSS, are identified and described. In the concluding remarks, an interdisciplinary variant, which takes after ABM, reconciling it with the quantitative one, is proposed as a fundamental requirement for a new program of the CSS. PMID:25071642

A novel computer based expert decision making model for prostate cancer disease management.

PubMed

Richman, Martin B; Forman, Ernest H; Bayazit, Yildirim; Einstein, Douglas B; Resnick, Martin I; Stovsky, Mark D

2005-12-01

We propose a strategic, computer based, prostate cancer decision making model based on the analytic hierarchy process. We developed a model that improves physician-patient joint decision making and enhances the treatment selection process by making this critical decision rational and evidence based. Two groups (patient and physician-expert) completed a clinical study comparing an initial disease management choice with the highest ranked option generated by the computer model. Participants made pairwise comparisons to derive priorities for the objectives and subobjectives related to the disease management decision. The weighted comparisons were then applied to treatment options to yield prioritized rank lists that reflect the likelihood that a given alternative will achieve the participant treatment goal. Aggregate data were evaluated by inconsistency ratio analysis and sensitivity analysis, which assessed the influence of individual objectives and subobjectives on the final rank list of treatment options. Inconsistency ratios less than 0.05 were reliably generated, indicating that judgments made within the model were mathematically rational. The aggregate prioritized list of treatment options was tabulated for the patient and physician groups with similar outcomes for the 2 groups. Analysis of the major defining objectives in the treatment selection decision demonstrated the same rank order for the patient and physician groups with cure, survival and quality of life being more important than controlling cancer, preventing major complications of treatment, preventing blood transfusion complications and limiting treatment cost. Analysis of subobjectives, including quality of life and sexual dysfunction, produced similar priority rankings for the patient and physician groups. Concordance between initial treatment choice and the highest weighted model option differed between the groups with the patient group having 59% concordance and the physician group having only 42

Feasibility of Equivalent Dipole Models for Electroencephalogram-Based Brain Computer Interfaces.

PubMed

Schimpf, Paul H

2017-09-15

This article examines the localization errors of equivalent dipolar sources inverted from the surface electroencephalogram in order to determine the feasibility of using their location as classification parameters for non-invasive brain computer interfaces. Inverse localization errors are examined for two head models: a model represented by four concentric spheres and a realistic model based on medical imagery. It is shown that the spherical model results in localization ambiguity such that a number of dipolar sources, with different azimuths and varying orientations, provide a near match to the electroencephalogram of the best equivalent source. No such ambiguity exists for the elevation of inverted sources, indicating that for spherical head models, only the elevation of inverted sources (and not the azimuth) can be expected to provide meaningful classification parameters for brain-computer interfaces. In a realistic head model, all three parameters of the inverted source location are found to be reliable, providing a more robust set of parameters. In both cases, the residual error hypersurfaces demonstrate local minima, indicating that a search for the best-matching sources should be global. Source localization error vs. signal-to-noise ratio is also demonstrated for both head models.

Use of Cloud-Based Graphic Narrative Software in Medical Ethics Teaching

ERIC Educational Resources Information Center

Weber, Alan S.

2015-01-01

Although used as a common pedagogical tool in K-12 education, online graphic narrative ("comics") software has not generally been incorporated into advanced professional or technical education. This contribution reports preliminary data from a study on the use of cloud-based graphics software Pixton.com to teach basic medical ethics…

Skin lesion computational diagnosis of dermoscopic images: Ensemble models based on input feature manipulation.

PubMed

Oliveira, Roberta B; Pereira, Aledir S; Tavares, João Manuel R S

2017-10-01

The number of deaths worldwide due to melanoma has risen in recent times, in part because melanoma is the most aggressive type of skin cancer. Computational systems have been developed to assist dermatologists in early diagnosis of skin cancer, or even to monitor skin lesions. However, there still remains a challenge to improve classifiers for the diagnosis of such skin lesions. The main objective of this article is to evaluate different ensemble classification models based on input feature manipulation to diagnose skin lesions. Input feature manipulation processes are based on feature subset selections from shape properties, colour variation and texture analysis to generate diversity for the ensemble models. Three subset selection models are presented here: (1) a subset selection model based on specific feature groups, (2) a correlation-based subset selection model, and (3) a subset selection model based on feature selection algorithms. Each ensemble classification model is generated using an optimum-path forest classifier and integrated with a majority voting strategy. The proposed models were applied on a set of 1104 dermoscopic images using a cross-validation procedure. The best results were obtained by the first ensemble classification model that generates a feature subset ensemble based on specific feature groups. The skin lesion diagnosis computational system achieved 94.3% accuracy, 91.8% sensitivity and 96.7% specificity. The input feature manipulation process based on specific feature subsets generated the greatest diversity for the ensemble classification model with very promising results. Copyright © 2017 Elsevier B.V. All rights reserved.

Incidental Becomes Visible: A Comparison of School- and Community-Based Field Experience Narratives

ERIC Educational Resources Information Center

Holder, K. C.; Downey, Jayne A.

2008-01-01

The purpose of this study was to describe and compare student learning documented using written field experience summary narratives and occurring in community-based or school-based locations. Utilizing a hybrid portraiture--instrumental case study design, two researchers selected participants from undergraduate educational psychology courses using…

Computer Modeling and Simulation

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

Pronskikh, V. S.

2014-05-09

Verification and validation of computer codes and models used in simulation are two aspects of the scientific practice of high importance and have recently been discussed by philosophers of science. While verification is predominantly associated with the correctness of the way a model is represented by a computer code or algorithm, validation more often refers to model’s relation to the real world and its intended use. It has been argued that because complex simulations are generally not transparent to a practitioner, the Duhem problem can arise for verification and validation due to their entanglement; such an entanglement makes it impossiblemore » to distinguish whether a coding error or model’s general inadequacy to its target should be blamed in the case of the model failure. I argue that in order to disentangle verification and validation, a clear distinction between computer modeling (construction of mathematical computer models of elementary processes) and simulation (construction of models of composite objects and processes by means of numerical experimenting with them) needs to be made. Holding on to that distinction, I propose to relate verification (based on theoretical strategies such as inferences) to modeling and validation, which shares the common epistemology with experimentation, to simulation. To explain reasons of their intermittent entanglement I propose a weberian ideal-typical model of modeling and simulation as roles in practice. I suggest an approach to alleviate the Duhem problem for verification and validation generally applicable in practice and based on differences in epistemic strategies and scopes« less

Framing Effects in Narrative and Non-Narrative Risk Messages.

PubMed

Steinhardt, Joseph; Shapiro, Michael A

2015-08-01

Narrative messages are increasingly popular in health and risk campaigns, yet gain/loss framing effects have never been tested with such messages. Three experiments examined framing in narrative messages. Experiment 1 found that only the character's decision, not framing, influenced judgments about characters in a narrative derived from a prospect theory context. Experiment 2 found that a framing effect that occurred when presented in a decision format did not occur when the same situation was presented as a narrative. Using a different story/decision context, Experiment 3 found no significant difference in preference for surgery over radiation therapy in a narrative presentation compared to a non-narrative presentation. The results suggest that health and risk campaigns cannot assume that framing effects will be the same in narrative messages and non-narrative messages. Potential reasons for these differences and suggestions for future research are discussed. © 2015 Society for Risk Analysis.

Modeling Students' Problem Solving Performance in the Computer-Based Mathematics Learning Environment

ERIC Educational Resources Information Center

Lee, Young-Jin

2017-01-01

Purpose: The purpose of this paper is to develop a quantitative model of problem solving performance of students in the computer-based mathematics learning environment. Design/methodology/approach: Regularized logistic regression was used to create a quantitative model of problem solving performance of students that predicts whether students can…

Maternal Autonomy Support and Dyadic Verbal Synchrony during Narrative Coconstruction: Links with Child Attachment Representations and Independent Narrative Competence

ERIC Educational Resources Information Center

Kelly, Kimberly Reynolds

2018-01-01

This study investigated the empirical bases for 2 dimensions of narrative coconstruction (autonomy support and verbal synchrony) with 65 mother-child dyads. Links between the 2 narrative dimensions and child narrative competence were tested, and differences in autonomy support and verbal synchrony across attachment groups (child story-stem…

Narratives of health and illness: Arts-based research capturing the lived experience of dementia.

PubMed

Moss, Hilary; O'Neill, Desmond

2017-01-01

Introduction This paper presents three artists' residencies in a geriatric medicine unit in a teaching hospital. The aim of the residencies was creation of new work of high artistic quality reflecting the lived experience of the person with dementia and greater understanding of service user experience of living with dementia. This paper also explores arts-based research methodologies in a medical setting. Method Arts-based research and narrative enquiry were the method used in this study. Artists had extensive access to service users with dementia, family carers and clinical team. Projects were created through collaboration between clinical staff, arts and health director, artist, patients and family carers. Each performance was accompanied by a public seminar discussing dementia. Evaluations were undertaken following each residency. The process of creating artistic responses to dementia is outlined, presented and discussed. Results The artworks were well received with repeat performances and exhibitions requested. Evaluations of each residency indicated increased understanding of dementia. The narratives within the artworks aided learning about dementia. The results are a new chamber music composition, a series of visual artworks created collaboratively between visual artist and patients and family carers and a dance film inspired by a dancer's residency, all created through narrative enquiry. These projects support the role of arts-based research as creative process and qualitative research method which contributes to illuminating and exploring the lived experience of dementia. The arts act as a reflective tool for learning and understanding a complex health condition, as well as creating opportunities for increased understanding and public awareness of dementia. Issues arising in arts-based research in medical settings are highlighted, including ethical issues, the importance of service user narrative and multidisciplinary collaboration in arts and health

Some Useful Cost-Benefit Criteria for Evaluating Computer-Based Test Delivery Models and Systems

ERIC Educational Resources Information Center

Luecht, Richard M.

2005-01-01

Computer-based testing (CBT) is typically implemented using one of three general test delivery models: (1) multiple fixed testing (MFT); (2) computer-adaptive testing (CAT); or (3) multistage testing (MSTs). This article reviews some of the real cost drivers associated with CBT implementation--focusing on item production costs, the costs…

Optical Computing Based on Neuronal Models

DTIC Science & Technology

1988-05-01

walking, and cognition are far too complex for existing sequential digital computers. Therefore new architectures, hardware, and algorithms modeled...collective behavior, and iterative processing into optical processing and artificial neurodynamical systems. Another intriguing promise of neural nets is...with architectures, implementations, and programming; and material research s -7- called for. Our future research in neurodynamics will continue to

Epistemic Gameplay and Discovery in Computational Model-Based Inquiry Activities

ERIC Educational Resources Information Center

Wilkerson, Michelle Hoda; Shareff, Rebecca; Laina, Vasiliki; Gravel, Brian

2018-01-01

In computational modeling activities, learners are expected to discover the inner workings of scientific and mathematical systems: First elaborating their understandings of a given system through constructing a computer model, then "debugging" that knowledge by testing and refining the model. While such activities have been shown to…

An agent-based computational model of the spread of tuberculosis

NASA Astrophysics Data System (ADS)

de Espíndola, Aquino L.; Bauch, Chris T.; Troca Cabella, Brenno C.; Souto Martinez, Alexandre

2011-05-01

In this work we propose an alternative model of the spread of tuberculosis (TB) and the emergence of drug resistance due to the treatment with antibiotics. We implement the simulations by an agent-based model computational approach where the spatial structure is taken into account. The spread of tuberculosis occurs according to probabilities defined by the interactions among individuals. The model was validated by reproducing results already known from the literature in which different treatment regimes yield the emergence of drug resistance. The different patterns of TB spread can be visualized at any time of the system evolution. The implementation details as well as some results of this alternative approach are discussed.

The Index of Narrative Microstructure: A Clinical Tool for Analyzing School-Age Children's Narrative Performances

ERIC Educational Resources Information Center

Justice, Laura M.; Bowles, Ryan P.; Kaderavek, Joan N.; Ukrainetz, Teresa A.; Eisenberg, Sarita L.; Gillam, Ronald B.

2006-01-01

Purpose: This research was conducted to develop a clinical tool--the Index of Narrative Microstructure (INMIS)--that would parsimoniously account for important microstructural aspects of narrative production for school-age children. The study provides field test age- and grade-based INMIS values to aid clinicians in making normative judgments…

Narrativity and enaction: the social nature of literary narrative understanding

PubMed Central

Popova, Yanna B.

2014-01-01

This paper proposes an understanding of literary narrative as a form of social cognition and situates the study of such narratives in relation to the new comprehensive approach to human cognition, enaction. The particular form of enactive cognition that narrative understanding is proposed to depend on is that of participatory sense-making, as developed in the work of Di Paolo and De Jaegher. Currently there is no consensus as to what makes a good literary narrative, how it is understood, and why it plays such an irreplaceable role in human experience. The proposal thus identifies a gap in the existing research on narrative by describing narrative as a form of intersubjective process of sense-making between two agents, a teller and a reader. It argues that making sense of narrative literature is an interactional process of co-constructing a story-world with a narrator. Such an understanding of narrative makes a decisive break with both text-centered approaches that have dominated both structuralist and early cognitivist study of narrative, as well as pragmatic communicative ones that view narrative as a form of linguistic implicature. The interactive experience that narrative affords and necessitates at the same time, I argue, serves to highlight the active yet cooperative and communal nature of human sociality, expressed in the many forms than human beings interact in, including literary ones. PMID:25202286

Narrativity and enaction: the social nature of literary narrative understanding.

PubMed

Popova, Yanna B

2014-01-01

This paper proposes an understanding of literary narrative as a form of social cognition and situates the study of such narratives in relation to the new comprehensive approach to human cognition, enaction. The particular form of enactive cognition that narrative understanding is proposed to depend on is that of participatory sense-making, as developed in the work of Di Paolo and De Jaegher. Currently there is no consensus as to what makes a good literary narrative, how it is understood, and why it plays such an irreplaceable role in human experience. The proposal thus identifies a gap in the existing research on narrative by describing narrative as a form of intersubjective process of sense-making between two agents, a teller and a reader. It argues that making sense of narrative literature is an interactional process of co-constructing a story-world with a narrator. Such an understanding of narrative makes a decisive break with both text-centered approaches that have dominated both structuralist and early cognitivist study of narrative, as well as pragmatic communicative ones that view narrative as a form of linguistic implicature. The interactive experience that narrative affords and necessitates at the same time, I argue, serves to highlight the active yet cooperative and communal nature of human sociality, expressed in the many forms than human beings interact in, including literary ones.

Examining effects of medical cannabis narratives on beliefs, attitudes, and intentions related to recreational cannabis: A web-based randomized experiment.

PubMed

Sznitman, Sharon R; Lewis, Nehama

2018-04-01

This experimental study tests effects of exposure to video narratives about successful symptom relief with Medical Cannabis (MC) on attitudes, beliefs, and intentions related to recreational cannabis use. Patient video testimonials were modeled after those found in extant media coverage. Israeli participants (N = 396) recruited through an online survey company were randomly assigned to view a narrative or a non-narrative video containing equivalent information about MC. Video content was further manipulated based on whether the protagonist had a stigmatized disease or not, and whether attribution of responsibility for his disease was internal or external. Exposure to patient testimonials indirectly increased positive attitudes, beliefs and intentions related to recreational cannabis use through changing attitudes, beliefs and intentions related to MC. Furthermore, exposure to narratives in which the patient was presented as not to blame for contracting his illness (external attribution) was associated with more positive attitudes, beliefs and intentions toward MC, a factor that was significantly associated with more positive attitudes, beliefs and intentions related to recreational cannabis use. These results suggest that narrative news media coverage of MC may influence public attitudes toward recreational cannabis. Because such media stories continue to be commonplace, it is important to examine potential spillover effects of this coverage on public perceptions of recreational cannabis. Cannabis prevention programs should address the role of media coverage in shaping public opinion and address the distinction between medical and recreational cannabis use. Copyright © 2018 Elsevier B.V. All rights reserved.

Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses

PubMed Central

Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

2016-01-01

Background Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. Objective The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Methods Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Results Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however

Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses.

PubMed

Syrowatka, Ania; Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

2016-01-26

Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than

A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory.

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

Johnson, J. D.; Oberkampf, William Louis; Helton, Jon Craig

2006-10-01

Evidence theory provides an alternative to probability theory for the representation of epistemic uncertainty in model predictions that derives from epistemic uncertainty in model inputs, where the descriptor epistemic is used to indicate uncertainty that derives from a lack of knowledge with respect to the appropriate values to use for various inputs to the model. The potential benefit, and hence appeal, of evidence theory is that it allows a less restrictive specification of uncertainty than is possible within the axiomatic structure on which probability theory is based. Unfortunately, the propagation of an evidence theory representation for uncertainty through a modelmore » is more computationally demanding than the propagation of a probabilistic representation for uncertainty, with this difficulty constituting a serious obstacle to the use of evidence theory in the representation of uncertainty in predictions obtained from computationally intensive models. This presentation describes and illustrates a sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory. Preliminary trials indicate that the presented strategy can be used to propagate uncertainty representations based on evidence theory in analysis situations where naive sampling-based (i.e., unsophisticated Monte Carlo) procedures are impracticable due to computational cost.« less

Fast and accurate computation of system matrix for area integral model-based algebraic reconstruction technique

NASA Astrophysics Data System (ADS)

Zhang, Shunli; Zhang, Dinghua; Gong, Hao; Ghasemalizadeh, Omid; Wang, Ge; Cao, Guohua

2014-11-01

Iterative algorithms, such as the algebraic reconstruction technique (ART), are popular for image reconstruction. For iterative reconstruction, the area integral model (AIM) is more accurate for better reconstruction quality than the line integral model (LIM). However, the computation of the system matrix for AIM is more complex and time-consuming than that for LIM. Here, we propose a fast and accurate method to compute the system matrix for AIM. First, we calculate the intersection of each boundary line of a narrow fan-beam with pixels in a recursive and efficient manner. Then, by grouping the beam-pixel intersection area into six types according to the slopes of the two boundary lines, we analytically compute the intersection area of the narrow fan-beam with the pixels in a simple algebraic fashion. Overall, experimental results show that our method is about three times faster than the Siddon algorithm and about two times faster than the distance-driven model (DDM) in computation of the system matrix. The reconstruction speed of our AIM-based ART is also faster than the LIM-based ART that uses the Siddon algorithm and DDM-based ART, for one iteration. The fast reconstruction speed of our method was accomplished without compromising the image quality.

Theorizing Foreshadowed Death Narratives: Examining the Impact of Character Death on Narrative Processing and Skin Self-Exam Intentions

PubMed Central

JENSEN, JAKOB D.; YALE, ROBERT N.; KRAKOW, MELINDA; JOHN, KEVIN K.; KING, ANDY J.

2017-01-01

Narratives are common in health campaigns and interventions, with many depicting individuals battling a particular illness or disease. Past research has focused primarily on the form and effects of survivor stories, but considerably less attention has been devoted to stories in which 1 or more of the central characters passes away. The goal of the current study was to compare the relative persuasive impact of survivor and death narratives in influencing skin prevention behaviors and to test narrative mediators that might explicate underlying mechanisms of effect. To that end, adults (N = 635, M age = 32.43 [SD = 11.23]) were randomly assigned to 1 of 6 narrative intervention conditions in an online message experiment. Participants read 1 of 2 stories about a person with melanoma (Rusty or Diane) that was manipulated as a narrative depicting the survival, death, or foreshadowed death of the main character. Foreshadowed death narratives increased intentions to perform a skin self-exam (SSE), a relationship that was mediated by narrative transportation and perceived SSE benefits. The results support the central postulate of narrative transportation theory and the utility of using foreshadowed death narratives in communication-based interventions designed to increase SSE frequency. PMID:28060585

The Cinematic Narrator: The Logic and Pragmatics of Impersonal Narration.

ERIC Educational Resources Information Center

Burgoyne, Robert

1990-01-01

Describes "impersonal narration," an approach that defends the concept of the cinematic narrator as a logical and pragmatic necessity. Compares this approach with existing theories of the cinematic narrator, addressing disagreements in the field of film narrative theory. (MM)

Using Narrative to Understand the Convergence of Distance and Campus-Based Learning during the Time of SARS in Hong Kong

ERIC Educational Resources Information Center

McNaught, Carmel

2004-01-01

This paper is a narrative about the use of narrative as a means to understand how the use of technology assisted the educational community of Hong Kong during the SARS crisis of 2003. It is not a carefully planned conventional research study. It is based on seven narratives written by staff at The Chinese University of Hong Kong about their…

The emotional impact of loss narratives: event severity and narrative perspectives.

PubMed

Habermas, Tilmann; Diel, Verena

2010-06-01

Out of the complex influences of event, narrative and listener characteristics on narrative emotions, this paper focuses on event severity, narrative perspectives, mood, and dispositions for emotion regulation and empathy. Event severity and perspective representation were systematically varied in sad autobiographical narratives to study their influence on quantity and quality of readers' emotional response. Each of three stories were manipulated to contain elaborated perspectives, only the past protagonists' perspective (dramatic narration), and very little perspectives at all (impersonal narration). We predicted that event severity influences the quantity of emotional response, while degree of perspective representation influences plausibility and whether emotional responses are sympathetic or interactional, that is, directed against the narrator. Hypotheses were confirmed except for plausibility, and perspective representation had an effect only on anger against and dislike of the narrator. In a second study, impersonal narration evoked anger at and negative evaluations of the narrator which were related to blaming the narrator for showing too little emotional involvement. The generalizability of findings across emotions and implications for sharing of emotions in everyday and clinical settings are discussed.

From Stories to Scientific Models and Back: Narrative Framing in Modern Macroscopic Physics

ERIC Educational Resources Information Center

Fuchs, Hans U.

2015-01-01

Narrative in science learning has become an important field of inquiry. Most applications of narrative are extrinsic to science--such as when they are used for creating affect and context. Where they are intrinsic, they are often limited to special cases and uses. To extend the reach of narrative in science, a hypothesis of narrative framing of…

Using Rasch Measurement to Develop a Computer Modeling-Based Instrument to Assess Students' Conceptual Understanding of Matter

ERIC Educational Resources Information Center

Wei, Silin; Liu, Xiufeng; Wang, Zuhao; Wang, Xingqiao

2012-01-01

Research suggests that difficulty in making connections among three levels of chemical representations--macroscopic, submicroscopic, and symbolic--is a primary reason for student alternative conceptions of chemistry concepts, and computer modeling is promising to help students make the connections. However, no computer modeling-based assessment…

Reliability models for dataflow computer systems

NASA Technical Reports Server (NTRS)

Kavi, K. M.; Buckles, B. P.

1985-01-01

The demands for concurrent operation within a computer system and the representation of parallelism in programming languages have yielded a new form of program representation known as data flow (DENN 74, DENN 75, TREL 82a). A new model based on data flow principles for parallel computations and parallel computer systems is presented. Necessary conditions for liveness and deadlock freeness in data flow graphs are derived. The data flow graph is used as a model to represent asynchronous concurrent computer architectures including data flow computers.

The Effect of Patient Narratives on Information Search in a Web-Based Breast Cancer Decision Aid: An Eye-Tracking Study

PubMed Central

Owens, Justin; Zikmund-Fisher, Brian J

2013-01-01

Background Previous research has examined the impact of patient narratives on treatment choices, but to our knowledge, no study has examined the effect of narratives on information search. Further, no research has considered the relative impact of their format (text vs video) on health care decisions in a single study. Objective Our goal was to examine the impact of video and text-based narratives on information search in a Web-based patient decision aid for early stage breast cancer. Methods Fifty-six women were asked to imagine that they had been diagnosed with early stage breast cancer and needed to choose between two surgical treatments (lumpectomy with radiation or mastectomy). Participants were randomly assigned to view one of four versions of a Web decision aid. Two versions of the decision aid included videos of interviews with patients and physicians or videos of interviews with physicians only. To distinguish between the effect of narratives and the effect of videos, we created two text versions of the Web decision aid by replacing the patient and physician interviews with text transcripts of the videos. Participants could freely browse the Web decision aid until they developed a treatment preference. We recorded participants’ eye movements using the Tobii 1750 eye-tracking system equipped with Tobii Studio software. A priori, we defined 24 areas of interest (AOIs) in the Web decision aid. These AOIs were either separate pages of the Web decision aid or sections within a single page covering different content. Results We used multilevel modeling to examine the effect of narrative presence, narrative format, and their interaction on information search. There was a significant main effect of condition, P=.02; participants viewing decision aids with patient narratives spent more time searching for information than participants viewing the decision aids without narratives. The main effect of format was not significant, P=.10. However, there was a

The effect of patient narratives on information search in a web-based breast cancer decision aid: an eye-tracking study.

PubMed

Shaffer, Victoria A; Owens, Justin; Zikmund-Fisher, Brian J

2013-12-17

Previous research has examined the impact of patient narratives on treatment choices, but to our knowledge, no study has examined the effect of narratives on information search. Further, no research has considered the relative impact of their format (text vs video) on health care decisions in a single study. Our goal was to examine the impact of video and text-based narratives on information search in a Web-based patient decision aid for early stage breast cancer. Fifty-six women were asked to imagine that they had been diagnosed with early stage breast cancer and needed to choose between two surgical treatments (lumpectomy with radiation or mastectomy). Participants were randomly assigned to view one of four versions of a Web decision aid. Two versions of the decision aid included videos of interviews with patients and physicians or videos of interviews with physicians only. To distinguish between the effect of narratives and the effect of videos, we created two text versions of the Web decision aid by replacing the patient and physician interviews with text transcripts of the videos. Participants could freely browse the Web decision aid until they developed a treatment preference. We recorded participants' eye movements using the Tobii 1750 eye-tracking system equipped with Tobii Studio software. A priori, we defined 24 areas of interest (AOIs) in the Web decision aid. These AOIs were either separate pages of the Web decision aid or sections within a single page covering different content. We used multilevel modeling to examine the effect of narrative presence, narrative format, and their interaction on information search. There was a significant main effect of condition, P=.02; participants viewing decision aids with patient narratives spent more time searching for information than participants viewing the decision aids without narratives. The main effect of format was not significant, P=.10. However, there was a significant condition by format interaction on

Computer Models of Personality: Implications for Measurement

ERIC Educational Resources Information Center

Cranton, P. A.

1976-01-01

Current research on computer models of personality is reviewed and categorized under five headings: (1) models of belief systems; (2) models of interpersonal behavior; (3) models of decision-making processes; (4) prediction models; and (5) theory-based simulations of specific processes. The use of computer models in personality measurement is…

Process-Based Development of Competence Models to Computer Science Education

ERIC Educational Resources Information Center

Zendler, Andreas; Seitz, Cornelia; Klaudt, Dieter

2016-01-01

A process model ("cpm.4.CSE") is introduced that allows the development of competence models in computer science education related to curricular requirements. It includes eight subprocesses: (a) determine competence concept, (b) determine competence areas, (c) identify computer science concepts, (d) assign competence dimensions to…

Scientific Playworlds: a Model of Teaching Science in Play-Based Settings

NASA Astrophysics Data System (ADS)

Fleer, Marilyn

2017-09-01

Eminent scientists, like Einstein, worked with theoretical contradiction, thought experiments, mental models and visualisation—all characteristics of children's play. Supporting children's play is a strength of early childhood teachers. Promising research shows a link between imagination in science and imagination in play. A case study of 3 preschool teachers and 26 children (3.6-5.9 years; mean age of 4.6 years) over 6 weeks was undertaken, generating 59.6 h of digital observations and 788 photographs of play practices. The research sought to understand (1) how imaginative play promotes scientific learning and (2) examined how teachers engaged children in scientific play. Although play pedagogy is a strength of early childhood teachers, it was found that transforming imaginary situations into scientific narratives requires different pedagogical characteristics. The study found that the building of collective scientific narratives alongside of discourses of wondering were key determinants of science learning in play-based settings. Specifically, the pedagogical principles of using a cultural device that mirrors the science experiences, creating imaginary scientific situations, collectively building scientific problem situations, and imagining the relations between observable contexts and non-observable concepts, changed everyday practices into a scientific narrative and engagement. It is argued that these unique pedagogical characteristics promote scientific narratives in play-based settings. An approach, named as Scientific Playworlds, is presented as a possible model for teaching science in play-based settings.

DualTrust: A Trust Management Model for Swarm-Based Autonomic Computing Systems

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

Maiden, Wendy M.

Trust management techniques must be adapted to the unique needs of the application architectures and problem domains to which they are applied. For autonomic computing systems that utilize mobile agents and ant colony algorithms for their sensor layer, certain characteristics of the mobile agent ant swarm -- their lightweight, ephemeral nature and indirect communication -- make this adaptation especially challenging. This thesis looks at the trust issues and opportunities in swarm-based autonomic computing systems and finds that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust management problem becomes much more scalable and stillmore » serves to protect the swarm. After analyzing the applicability of trust management research as it has been applied to architectures with similar characteristics, this thesis specifies the required characteristics for trust management mechanisms used to monitor the trustworthiness of entities in a swarm-based autonomic computing system and describes a trust model that meets these requirements.« less

Computationally modeling interpersonal trust.

PubMed

Lee, Jin Joo; Knox, W Bradley; Wormwood, Jolie B; Breazeal, Cynthia; Desteno, David

2013-01-01

We present a computational model capable of predicting-above human accuracy-the degree of trust a person has toward their novel partner by observing the trust-related nonverbal cues expressed in their social interaction. We summarize our prior work, in which we identify nonverbal cues that signal untrustworthy behavior and also demonstrate the human mind's readiness to interpret those cues to assess the trustworthiness of a social robot. We demonstrate that domain knowledge gained from our prior work using human-subjects experiments, when incorporated into the feature engineering process, permits a computational model to outperform both human predictions and a baseline model built in naiveté of this domain knowledge. We then present the construction of hidden Markov models to investigate temporal relationships among the trust-related nonverbal cues. By interpreting the resulting learned structure, we observe that models built to emulate different levels of trust exhibit different sequences of nonverbal cues. From this observation, we derived sequence-based temporal features that further improve the accuracy of our computational model. Our multi-step research process presented in this paper combines the strength of experimental manipulation and machine learning to not only design a computational trust model but also to further our understanding of the dynamics of interpersonal trust.

Trust models in ubiquitous computing.

PubMed

Krukow, Karl; Nielsen, Mogens; Sassone, Vladimiro

2008-10-28

We recapture some of the arguments for trust-based technologies in ubiquitous computing, followed by a brief survey of some of the models of trust that have been introduced in this respect. Based on this, we argue for the need of more formal and foundational trust models.

Factors Affecting Utilization of Information Output of Computer-Based Modeling Procedures in Local Government Organizations.

ERIC Educational Resources Information Center

Komsky, Susan

Fiscal Impact Budgeting Systems (FIBS) are sophisticated computer based modeling procedures used in local government organizations, whose results, however, are often overlooked or ignored by decision makers. A study attempted to discover the reasons for this situation by focusing on four factors: potential usefulness, faith in computers,…

Getting off the Straight and Narrow: Exploiting Non-Linear, Interactive Narrative Structures in Digital Stories for Language Teaching

ERIC Educational Resources Information Center

Prosser, Andrew

2014-01-01

Digital storytelling is already used extensively in language education. Web documentaries, particularly in terms of design and narrative structure, provide an extension of the digital storytelling concept, specifically in terms of increased interactivity. Using a model of interactive, non-linear storytelling, originally derived from computer game…

Computational Modeling of Cobalt-Based Water Oxidation: Current Status and Future Challenges

PubMed Central

Schilling, Mauro; Luber, Sandra

2018-01-01

A lot of effort is nowadays put into the development of novel water oxidation catalysts. In this context, mechanistic studies are crucial in order to elucidate the reaction mechanisms governing this complex process, new design paradigms and strategies how to improve the stability and efficiency of those catalysts. This review is focused on recent theoretical mechanistic studies in the field of homogeneous cobalt-based water oxidation catalysts. In the first part, computational methodologies and protocols are summarized and evaluated on the basis of their applicability toward real catalytic or smaller model systems, whereby special emphasis is laid on the choice of an appropriate model system. In the second part, an overview of mechanistic studies is presented, from which conceptual guidelines are drawn on how to approach novel studies of catalysts and how to further develop the field of computational modeling of water oxidation reactions. PMID:29721491

Computational Modeling of Cobalt-based Water Oxidation: Current Status and Future Challenges

NASA Astrophysics Data System (ADS)

Schilling, Mauro; Luber, Sandra

2018-04-01

A lot of effort is nowadays put into the development of novel water oxidation catalysts. In this context mechanistic studies are crucial in order to elucidate the reaction mechanisms governing this complex process, new design paradigms and strategies how to improve the stability and efficiency of those catalysis. This review is focused on recent theoretical mechanistic studies in the field of homogeneous cobalt-based water oxidation catalysts. In the first part, computational methodologies and protocols are summarized and evaluated on the basis of their applicability towards real catalytic or smaller model systems, whereby special emphasis is laid on the choice of an appropriate model system. In the second part, an overview of mechanistic studies is presented, from which conceptual guidelines are drawn on how to approach novel studies of catalysts and how to further develop the field of computational modeling of water oxidation reactions.

Narrative Constructions for the Organization of Self Experience: Proof of Concept via Embodied Robotics.

PubMed

Mealier, Anne-Laure; Pointeau, Gregoire; Mirliaz, Solène; Ogawa, Kenji; Finlayson, Mark; Dominey, Peter F

2017-01-01

It has been proposed that starting from meaning that the child derives directly from shared experience with others, adult narrative enriches this meaning and its structure, providing causal links between unseen intentional states and actions. This would require a means for representing meaning from experience-a situation model-and a mechanism that allows information to be extracted from sentences and mapped onto the situation model that has been derived from experience, thus enriching that representation. We present a hypothesis and theory concerning how the language processing infrastructure for grammatical constructions can naturally be extended to narrative constructions to provide a mechanism for using language to enrich meaning derived from physical experience. Toward this aim, the grammatical construction models are augmented with additional structures for representing relations between events across sentences. Simulation results demonstrate proof of concept for how the narrative construction model supports multiple successive levels of meaning creation which allows the system to learn about the intentionality of mental states, and argument substitution which allows extensions to metaphorical language and analogical problem solving. Cross-linguistic validity of the system is demonstrated in Japanese. The narrative construction model is then integrated into the cognitive system of a humanoid robot that provides the memory systems and world-interaction required for representing meaning in a situation model. In this context proof of concept is demonstrated for how the system enriches meaning in the situation model that has been directly derived from experience. In terms of links to empirical data, the model predicts strong usage based effects: that is, that the narrative constructions used by children will be highly correlated with those that they experience. It also relies on the notion of narrative or discourse function words. Both of these are validated in

Novel schemes for measurement-based quantum computation.

PubMed

Gross, D; Eisert, J

2007-06-01

We establish a framework which allows one to construct novel schemes for measurement-based quantum computation. The technique develops tools from many-body physics-based on finitely correlated or projected entangled pair states-to go beyond the cluster-state based one-way computer. We identify resource states radically different from the cluster state, in that they exhibit nonvanishing correlations, can be prepared using nonmaximally entangling gates, or have very different local entanglement properties. In the computational models, randomness is compensated in a different manner. It is shown that there exist resource states which are locally arbitrarily close to a pure state. We comment on the possibility of tailoring computational models to specific physical systems.

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach

PubMed Central

2016-01-01

Background Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. Purpose It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. Method We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. Results The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach. PMID:26812235

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

PubMed

Laghari, Samreen; Niazi, Muaz A

2016-01-01

Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

Theorizing Foreshadowed Death Narratives: Examining the Impact of Character Death on Narrative Processing and Skin Self-Exam Intentions.

PubMed

Jensen, Jakob D; Yale, Robert N; Krakow, Melinda; John, Kevin K; King, Andy J

2017-01-01

Narratives are common in health campaigns and interventions, with many depicting individuals battling a particular illness or disease. Past research has focused primarily on the form and effects of survivor stories, but considerably less attention has been devoted to stories in which 1 or more of the central characters passes away. The goal of the current study was to compare the relative persuasive impact of survivor and death narratives in influencing skin prevention behaviors and to test narrative mediators that might explicate underlying mechanisms of effect. To that end, adults (N = 635, M age = 32.43 [SD = 11.23]) were randomly assigned to 1 of 6 narrative intervention conditions in an online message experiment. Participants read 1 of 2 stories about a person with melanoma (Rusty or Diane) that was manipulated as a narrative depicting the survival, death, or foreshadowed death of the main character. Foreshadowed death narratives increased intentions to perform a skin self-exam (SSE), a relationship that was mediated by narrative transportation and perceived SSE benefits. The results support the central postulate of narrative transportation theory and the utility of using foreshadowed death narratives in communication-based interventions designed to increase SSE frequency.

Narrative methods in quality improvement research

PubMed Central

Greenhalgh, T; Russell, J; Swinglehurst, D

2005-01-01



 This paper reviews and critiques the different approaches to the use of narrative in quality improvement research. The defining characteristics of narrative are chronology (unfolding over time); emplotment (the literary juxtaposing of actions and events in an implicitly causal sequence); trouble (that is, harm or the risk of harm); and embeddedness (the personal story nests within a particular social, historical and organisational context). Stories are about purposeful action unfolding in the face of trouble and, as such, have much to offer quality improvement researchers. But the quality improvement report (a story about efforts to implement change), which is common, must be distinguished carefully from narrative based quality improvement research (focused systematic enquiry that uses narrative methods to generate new knowledge), which is currently none. We distinguish four approaches to the use of narrative in quality improvement research—narrative interview; naturalistic story gathering; organisational case study; and collective sense-making—and offer a rationale, describe how data can be collected and analysed, and discuss the strengths and limitations of each using examples from the quality improvement literature. Narrative research raises epistemological questions about the nature of narrative truth (characterised by sense-making and emotional impact rather than scientific objectivity), which has implications for how rigour should be defined (and how it might be achieved) in this type of research. We offer some provisional guidance for distinguishing high quality narrative research in a quality improvement setting from other forms of narrative account such as report, anecdote, and journalism. PMID:16326792

A computational visual saliency model based on statistics and machine learning.

PubMed

Lin, Ru-Je; Lin, Wei-Song

2014-08-01

Identifying the type of stimuli that attracts human visual attention has been an appealing topic for scientists for many years. In particular, marking the salient regions in images is useful for both psychologists and many computer vision applications. In this paper, we propose a computational approach for producing saliency maps using statistics and machine learning methods. Based on four assumptions, three properties (Feature-Prior, Position-Prior, and Feature-Distribution) can be derived and combined by a simple intersection operation to obtain a saliency map. These properties are implemented by a similarity computation, support vector regression (SVR) technique, statistical analysis of training samples, and information theory using low-level features. This technique is able to learn the preferences of human visual behavior while simultaneously considering feature uniqueness. Experimental results show that our approach performs better in predicting human visual attention regions than 12 other models in two test databases. © 2014 ARVO.

Narrative Constructions for the Organization of Self Experience: Proof of Concept via Embodied Robotics

PubMed Central

Mealier, Anne-Laure; Pointeau, Gregoire; Mirliaz, Solène; Ogawa, Kenji; Finlayson, Mark; Dominey, Peter F.

2017-01-01

It has been proposed that starting from meaning that the child derives directly from shared experience with others, adult narrative enriches this meaning and its structure, providing causal links between unseen intentional states and actions. This would require a means for representing meaning from experience—a situation model—and a mechanism that allows information to be extracted from sentences and mapped onto the situation model that has been derived from experience, thus enriching that representation. We present a hypothesis and theory concerning how the language processing infrastructure for grammatical constructions can naturally be extended to narrative constructions to provide a mechanism for using language to enrich meaning derived from physical experience. Toward this aim, the grammatical construction models are augmented with additional structures for representing relations between events across sentences. Simulation results demonstrate proof of concept for how the narrative construction model supports multiple successive levels of meaning creation which allows the system to learn about the intentionality of mental states, and argument substitution which allows extensions to metaphorical language and analogical problem solving. Cross-linguistic validity of the system is demonstrated in Japanese. The narrative construction model is then integrated into the cognitive system of a humanoid robot that provides the memory systems and world-interaction required for representing meaning in a situation model. In this context proof of concept is demonstrated for how the system enriches meaning in the situation model that has been directly derived from experience. In terms of links to empirical data, the model predicts strong usage based effects: that is, that the narrative constructions used by children will be highly correlated with those that they experience. It also relies on the notion of narrative or discourse function words. Both of these are validated

Computational Model of Population Dynamics Based on the Cell Cycle and Local Interactions

NASA Astrophysics Data System (ADS)

Oprisan, Sorinel Adrian; Oprisan, Ana

2005-03-01

Our study bridges cellular (mesoscopic) level interactions and global population (macroscopic) dynamics of carcinoma. The morphological differences and transitions between well and smooth defined benign tumors and tentacular malignat tumors suggest a theoretical analysis of tumor invasion based on the development of mathematical models exhibiting bifurcations of spatial patterns in the density of tumor cells. Our computational model views the most representative and clinically relevant features of oncogenesis as a fight between two distinct sub-systems: the immune system of the host and the neoplastic system. We implemented the neoplastic sub-system using a three-stage cell cycle: active, dormant, and necrosis. The second considered sub-system consists of cytotoxic active (effector) cells — EC, with a very broad phenotype ranging from NK cells to CTL cells, macrophages, etc. Based on extensive numerical simulations, we correlated the fractal dimensions for carcinoma, which could be obtained from tumor imaging, with the malignat stage. Our computational model was able to also simulate the effects of surgical, chemotherapeutical, and radiotherapeutical treatments.

Using narrative as a bridge: linking language processing models with real-life communication.

PubMed

Whitworth, Anne

2010-02-01

In chronic aphasia, maximizing generalization of improved language abilities from clinical tasks to everyday communication can require the same systematic planning process as the early stages of therapy, often drawing on additional areas of knowledge and successes from other clinical populations. The use of narrative structure is shown here to be a useful framework for building on the developments within sentence processing impairments in aphasia and creating a bridge to more real-life language tasks. An intervention based on narrative structure is described with two people with different language profiles and at different stages of the chronic aphasia spectrum. The insights gained in assessing language ability, underpinning intervention, and capturing therapeutic changes are demonstrated. Thieme Medical Publishers.

From Numerical Problem Solving to Model-Based Experimentation Incorporating Computer-Based Tools of Various Scales into the ChE Curriculum

ERIC Educational Resources Information Center

Shacham, Mordechai; Cutlip, Michael B.; Brauner, Neima

2009-01-01

A continuing challenge to the undergraduate chemical engineering curriculum is the time-effective incorporation and use of computer-based tools throughout the educational program. Computing skills in academia and industry require some proficiency in programming and effective use of software packages for solving 1) single-model, single-algorithm…

Evaluating Computer-Based Assessment in a Risk-Based Model

ERIC Educational Resources Information Center

Zakrzewski, Stan; Steven, Christine; Ricketts, Chris

2009-01-01

There are three purposes for evaluation: evaluation for action to aid the decision making process, evaluation for understanding to further enhance enlightenment and evaluation for control to ensure compliance to standards. This article argues that the primary function of evaluation in the "Catherine Wheel" computer-based assessment (CBA)…

A Novel Cost Based Model for Energy Consumption in Cloud Computing

PubMed Central

Horri, A.; Dastghaibyfard, Gh.

2015-01-01

Cloud data centers consume enormous amounts of electrical energy. To support green cloud computing, providers also need to minimize cloud infrastructure energy consumption while conducting the QoS. In this study, for cloud environments an energy consumption model is proposed for time-shared policy in virtualization layer. The cost and energy usage of time-shared policy were modeled in the CloudSim simulator based upon the results obtained from the real system and then proposed model was evaluated by different scenarios. In the proposed model, the cache interference costs were considered. These costs were based upon the size of data. The proposed model was implemented in the CloudSim simulator and the related simulation results indicate that the energy consumption may be considerable and that it can vary with different parameters such as the quantum parameter, data size, and the number of VMs on a host. Measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment. Also, measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment. PMID:25705716

A novel cost based model for energy consumption in cloud computing.

PubMed

Horri, A; Dastghaibyfard, Gh

2015-01-01

Cloud data centers consume enormous amounts of electrical energy. To support green cloud computing, providers also need to minimize cloud infrastructure energy consumption while conducting the QoS. In this study, for cloud environments an energy consumption model is proposed for time-shared policy in virtualization layer. The cost and energy usage of time-shared policy were modeled in the CloudSim simulator based upon the results obtained from the real system and then proposed model was evaluated by different scenarios. In the proposed model, the cache interference costs were considered. These costs were based upon the size of data. The proposed model was implemented in the CloudSim simulator and the related simulation results indicate that the energy consumption may be considerable and that it can vary with different parameters such as the quantum parameter, data size, and the number of VMs on a host. Measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment. Also, measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment.

Personal Narratives in Life History Research

ERIC Educational Resources Information Center

Germeten, Sidsel

2013-01-01

In this article I discuss how to create personal narratives in life history research methodology. People tell stories of their lives, and the researchers make these stories into life histories. Based on theoretical perspectives on "discourse" inspired by Michel Foucault, narratives are seen as ways of positioning oneself as a…

The Use of the Clinical Ethnographic Narrative Interview to Understand and Support Help Seeking After Gender-Based Violence

PubMed Central

Saint Arnault, Denise M.

2017-01-01

Gender-based violence (GBV), characterized by the abduction or rape of women and girls to humiliate, intimidate, and traumatize them and their communities, is a profoundly disturbing tactic in international conflict. Long after armed conflict has ended, survivors continue to experience physical injuries, psychological trauma, and social and cultural stigma. Guilt, shame, and continued interpersonal violence can become a normalized part of daily life, significantly challenging the road to healing and recovery. Research about self-disclosure and narrative after GBV has shown that help seeking rates are shockingly low, with estimates ranging from 4-27%. From a feminist and a humanistic perspective, studying trauma history and related help seeking is delicate work that must use interview processes that ensure the survivor can tell her story without revictimization, while also aiming to restore personal mastery, empowerment, and self-understanding. Based on theories about benefits and challenges of the narrative after GBV and trauma, we propose that the Clinical Ethnographic Narrative Interview (CENI) allows researchers and practitioners a safe container to examine the complex interplay between suffering, culture, and help seeking. Using this interview, the interviewer and the participant work as partners to define, compare, and contrast the socio-cultural barriers and facilitators of help seeking. This paper explains the narrative theory and the challenges and benefits of the narrative approach after trauma. Then we provide support for the use of the CENI for an understanding of the help seeking process and facilitating a health-promoting narrative interview for survivors. We then address implications for research, practice, and policy. PMID:29098071

The Use of the Clinical Ethnographic Narrative Interview to Understand and Support Help Seeking After Gender-Based Violence.

PubMed

Saint Arnault, Denise M

2017-09-01

Gender-based violence (GBV), characterized by the abduction or rape of women and girls to humiliate, intimidate, and traumatize them and their communities, is a profoundly disturbing tactic in international conflict. Long after armed conflict has ended, survivors continue to experience physical injuries, psychological trauma, and social and cultural stigma. Guilt, shame, and continued interpersonal violence can become a normalized part of daily life, significantly challenging the road to healing and recovery. Research about self-disclosure and narrative after GBV has shown that help seeking rates are shockingly low, with estimates ranging from 4-27%. From a feminist and a humanistic perspective, studying trauma history and related help seeking is delicate work that must use interview processes that ensure the survivor can tell her story without revictimization, while also aiming to restore personal mastery, empowerment, and self-understanding. Based on theories about benefits and challenges of the narrative after GBV and trauma, we propose that the Clinical Ethnographic Narrative Interview (CENI) allows researchers and practitioners a safe container to examine the complex interplay between suffering, culture, and help seeking. Using this interview, the interviewer and the participant work as partners to define, compare, and contrast the socio-cultural barriers and facilitators of help seeking. This paper explains the narrative theory and the challenges and benefits of the narrative approach after trauma. Then we provide support for the use of the CENI for an understanding of the help seeking process and facilitating a health-promoting narrative interview for survivors. We then address implications for research, practice, and policy.

Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives.

PubMed

Gehrmann, Sebastian; Dernoncourt, Franck; Li, Yeran; Carlson, Eric T; Wu, Joy T; Welt, Jonathan; Foote, John; Moseley, Edward T; Grant, David W; Tyler, Patrick D; Celi, Leo A

2018-01-01

In secondary analysis of electronic health records, a crucial task consists in correctly identifying the patient cohort under investigation. In many cases, the most valuable and relevant information for an accurate classification of medical conditions exist only in clinical narratives. Therefore, it is necessary to use natural language processing (NLP) techniques to extract and evaluate these narratives. The most commonly used approach to this problem relies on extracting a number of clinician-defined medical concepts from text and using machine learning techniques to identify whether a particular patient has a certain condition. However, recent advances in deep learning and NLP enable models to learn a rich representation of (medical) language. Convolutional neural networks (CNN) for text classification can augment the existing techniques by leveraging the representation of language to learn which phrases in a text are relevant for a given medical condition. In this work, we compare concept extraction based methods with CNNs and other commonly used models in NLP in ten phenotyping tasks using 1,610 discharge summaries from the MIMIC-III database. We show that CNNs outperform concept extraction based methods in almost all of the tasks, with an improvement in F1-score of up to 26 and up to 7 percentage points in area under the ROC curve (AUC). We additionally assess the interpretability of both approaches by presenting and evaluating methods that calculate and extract the most salient phrases for a prediction. The results indicate that CNNs are a valid alternative to existing approaches in patient phenotyping and cohort identification, and should be further investigated. Moreover, the deep learning approach presented in this paper can be used to assist clinicians during chart review or support the extraction of billing codes from text by identifying and highlighting relevant phrases for various medical conditions.

Exploratory analysis regarding the domain definitions for computer based analytical models

NASA Astrophysics Data System (ADS)

Raicu, A.; Oanta, E.; Barhalescu, M.

2017-08-01

Our previous computer based studies dedicated to structural problems using analytical methods defined the composite cross section of a beam as a result of Boolean operations with so-called ‘simple’ shapes. Using generalisations, in the class of the ‘simple’ shapes were included areas bounded by curves approximated using spline functions and areas approximated as polygons. However, particular definitions lead to particular solutions. In order to ascend above the actual limitations, we conceived a general definition of the cross sections that are considered now calculus domains consisting of several subdomains. The according set of input data use complex parameterizations. This new vision allows us to naturally assign a general number of attributes to the subdomains. In this way there may be modelled new phenomena that use map-wise information, such as the metal alloys equilibrium diagrams. The hierarchy of the input data text files that use the comma-separated-value format and their structure are also presented and discussed in the paper. This new approach allows us to reuse the concepts and part of the data processing software instruments already developed. The according software to be subsequently developed will be modularised and generalised in order to be used in the upcoming projects that require rapid development of computer based models.

Narrative competence in Spanish-speaking adults with Williams syndrome.

PubMed

Diez-Itza, Eliseo; Martínez, Verónica; Antón, Aránzazu

2016-08-01

Williams syndrome (WS) is a genetic disorder associated with intellectual disability and characterised by displaying an atypical neuropsychological profile, with peaks and valleys, where language skills seem better preserved than non-verbal intelligence. This study researches the narrative competence of nine Spanish-speaking adults with WS. Oral narratives were elicited from a silent film, and narrative coherence was analysed as a function of sequential order of the events narrated at three structure levels, while narrative cohesion was assessed through the frequency of use and type of discourse markers. WS subjects were able to remember a significant proportion of the events from the film, but coherence of narratives, i.e., sequential order of events, was more impaired. Consistently with their linguistic abilities, cohesion of narratives was better preserved, as they used discourse markers to introduce a high proportion of events. Construction of mental models of the narratives may be constrained in WS by non-verbal cognitive abilities, but narrative competence is also determined by textual pragmatic abilities to organize discourse, which should be addressed by specific intervention in narrative competence.

Subgraph augmented non-negative tensor factorization (SANTF) for modeling clinical narrative text

PubMed Central

Xin, Yu; Hochberg, Ephraim; Joshi, Rohit; Uzuner, Ozlem; Szolovits, Peter

2015-01-01

Objective Extracting medical knowledge from electronic medical records requires automated approaches to combat scalability limitations and selection biases. However, existing machine learning approaches are often regarded by clinicians as black boxes. Moreover, training data for these automated approaches at often sparsely annotated at best. The authors target unsupervised learning for modeling clinical narrative text, aiming at improving both accuracy and interpretability. Methods The authors introduce a novel framework named subgraph augmented non-negative tensor factorization (SANTF). In addition to relying on atomic features (e.g., words in clinical narrative text), SANTF automatically mines higher-order features (e.g., relations of lymphoid cells expressing antigens) from clinical narrative text by converting sentences into a graph representation and identifying important subgraphs. The authors compose a tensor using patients, higher-order features, and atomic features as its respective modes. We then apply non-negative tensor factorization to cluster patients, and simultaneously identify latent groups of higher-order features that link to patient clusters, as in clinical guidelines where a panel of immunophenotypic features and laboratory results are used to specify diagnostic criteria. Results and Conclusion SANTF demonstrated over 10% improvement in averaged F-measure on patient clustering compared to widely used non-negative matrix factorization (NMF) and k-means clustering methods. Multiple baselines were established by modeling patient data using patient-by-features matrices with different feature configurations and then performing NMF or k-means to cluster patients. Feature analysis identified latent groups of higher-order features that lead to medical insights. We also found that the latent groups of atomic features help to better correlate the latent groups of higher-order features. PMID:25862765

A computational model of in vitro angiogenesis based on extracellular matrix fibre orientation.

PubMed

Edgar, Lowell T; Sibole, Scott C; Underwood, Clayton J; Guilkey, James E; Weiss, Jeffrey A

2013-01-01

Recent interest in the process of vascularisation within the biomedical community has motivated numerous new research efforts focusing on the process of angiogenesis. Although the role of chemical factors during angiogenesis has been well documented, the role of mechanical factors, such as the interaction between angiogenic vessels and the extracellular matrix, remains poorly understood. In vitro methods for studying angiogenesis exist; however, measurements available using such techniques often suffer from limited spatial and temporal resolutions. For this reason, computational models have been extensively employed to investigate various aspects of angiogenesis. This paper outlines the formulation and validation of a simple and robust computational model developed to accurately simulate angiogenesis based on length, branching and orientation morphometrics collected from vascularised tissue constructs. Microvessels were represented as a series of connected line segments. The morphology of the vessels was determined by a linear combination of the collagen fibre orientation, the vessel density gradient and a random walk component. Excellent agreement was observed between computational and experimental morphometric data over time. Computational predictions of microvessel orientation within an anisotropic matrix correlated well with experimental data. The accuracy of this modelling approach makes it a valuable platform for investigating the role of mechanical interactions during angiogenesis.

Parallel computing in enterprise modeling.

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

Goldsby, Michael E.; Armstrong, Robert C.; Shneider, Max S.

2008-08-01

This report presents the results of our efforts to apply high-performance computing to entity-based simulations with a multi-use plugin for parallel computing. We use the term 'Entity-based simulation' to describe a class of simulation which includes both discrete event simulation and agent based simulation. What simulations of this class share, and what differs from more traditional models, is that the result sought is emergent from a large number of contributing entities. Logistic, economic and social simulations are members of this class where things or people are organized or self-organize to produce a solution. Entity-based problems never have an a priorimore » ergodic principle that will greatly simplify calculations. Because the results of entity-based simulations can only be realized at scale, scalable computing is de rigueur for large problems. Having said that, the absence of a spatial organizing principal makes the decomposition of the problem onto processors problematic. In addition, practitioners in this domain commonly use the Java programming language which presents its own problems in a high-performance setting. The plugin we have developed, called the Parallel Particle Data Model, overcomes both of these obstacles and is now being used by two Sandia frameworks: the Decision Analysis Center, and the Seldon social simulation facility. While the ability to engage U.S.-sized problems is now available to the Decision Analysis Center, this plugin is central to the success of Seldon. Because Seldon relies on computationally intensive cognitive sub-models, this work is necessary to achieve the scale necessary for realistic results. With the recent upheavals in the financial markets, and the inscrutability of terrorist activity, this simulation domain will likely need a capability with ever greater fidelity. High-performance computing will play an important part in enabling that greater fidelity.« less

Visual narrative structure.

PubMed

Cohn, Neil

2013-04-01

Narratives are an integral part of human expression. In the graphic form, they range from cave paintings to Egyptian hieroglyphics, from the Bayeux Tapestry to modern day comic books (Kunzle, 1973; McCloud, 1993). Yet not much research has addressed the structure and comprehension of narrative images, for example, how do people create meaning out of sequential images? This piece helps fill the gap by presenting a theory of Narrative Grammar. We describe the basic narrative categories and their relationship to a canonical narrative arc, followed by a discussion of complex structures that extend beyond the canonical schema. This demands that the canonical arc be reconsidered as a generative schema whereby any narrative category can be expanded into a node in a tree structure. Narrative "pacing" is interpreted as a reflection of various patterns of this embedding: conjunction, left-branching trees, center-embedded constituencies, and others. Following this, diagnostic methods are proposed for testing narrative categories and constituency. Finally, we outline the applicability of this theory beyond sequential images, such as to film and verbal discourse, and compare this theory with previous approaches to narrative and discourse. Copyright © 2012 Cognitive Science Society, Inc.

Functional Competency Development Model for Academic Personnel Based on International Professional Qualification Standards in Computing Field

ERIC Educational Resources Information Center

Tumthong, Suwut; Piriyasurawong, Pullop; Jeerangsuwan, Namon

2016-01-01

This research proposes a functional competency development model for academic personnel based on international professional qualification standards in computing field and examines the appropriateness of the model. Specifically, the model consists of three key components which are: 1) functional competency development model, 2) blended training…

MIRO Computational Model

NASA Technical Reports Server (NTRS)

Broderick, Daniel

2010-01-01

A computational model calculates the excitation of water rotational levels and emission-line spectra in a cometary coma with applications for the Micro-wave Instrument for Rosetta Orbiter (MIRO). MIRO is a millimeter-submillimeter spectrometer that will be used to study the nature of cometary nuclei, the physical processes of outgassing, and the formation of the head region of a comet (coma). The computational model is a means to interpret the data measured by MIRO. The model is based on the accelerated Monte Carlo method, which performs a random angular, spatial, and frequency sampling of the radiation field to calculate the local average intensity of the field. With the model, the water rotational level populations in the cometary coma and the line profiles for the emission from the water molecules as a function of cometary parameters (such as outgassing rate, gas temperature, and gas and electron density) and observation parameters (such as distance to the comet and beam width) are calculated.

"Response to Comments": Finding the Narrative in Narrative Research

ERIC Educational Resources Information Center

Coulter, Cathy A.

2009-01-01

The author responds to comments by Barone (2009), Clandinin and Murphy (2009), and M. W. Smith (2009) on "The Construction Zone: Literary Elements in Narrative Research" (Coulter & M. L. Smith, 2009). She clarifies issues regarding point of view, authorial surplus, narrative coherence, and the relational qualities of narrative research. She…

Discovery and Change: How Children Redraft Their Narrative Writing.

ERIC Educational Resources Information Center

Booley, Heather A.

1984-01-01

Fourteen year olds were introduced to a process model for writing and revising fictional narratives. Drafts were analyzed for evidence that they actively worked on cognitive, stylistic, and affective aspects of their narratives. Eighteen of 32 pupils made extensive or significant changes influenced by the process model. (SK)

The Effect of Modality and Narration Style on Recall of Online Health Information: Results From a Web-Based Experiment

PubMed Central

van Weert, Julia CM; de Haes, Hanneke CJM; Loos, Eugene F; Smets, Ellen MA

2015-01-01

Background Older adults are increasingly using the Internet for health information; however, they are often not able to correctly recall Web-based information (eHealth information). Recall of information is crucial for optimal health outcomes, such as adequate disease management and adherence to medical regimes. Combining effective message strategies may help to improve recall of eHealth information among older adults. Presenting information in an audiovisual format using conversational narration style is expected to optimize recall of information compared to other combinations of modality and narration style. Objective The aim of this paper is to investigate the effect of modality and narration style on recall of health information, and whether there are differences between younger and older adults. Methods We conducted a Web-based experiment using a 2 (modality: written vs audiovisual information) by 2 (narration style: formal vs conversational style) between-subjects design (N=440). Age was assessed in the questionnaire and included as a factor: younger (<65 years) versus older (≥65 years) age. Participants were randomly assigned to one of four experimental webpages where information about lung cancer treatment was presented. A Web-based questionnaire assessed recall of eHealth information. Results Audiovisual modality (vs written modality) was found to increase recall of information in both younger and older adults (P=.04). Although conversational narration style (vs formal narration style) did not increase recall of information (P=.17), a synergistic effect between modality and narration style was revealed: combining audiovisual information with conversational style outperformed combining written information with formal style (P=.01), as well as written information with conversational style (P=.045). This finding suggests that conversational style especially increases recall of information when presented audiovisually. This combination of modality and

The effect of modality and narration style on recall of online health information: results from a Web-based experiment.

PubMed

Bol, Nadine; van Weert, Julia C M; de Haes, Hanneke C J M; Loos, Eugene F; Smets, Ellen M A

2015-04-24

Older adults are increasingly using the Internet for health information; however, they are often not able to correctly recall Web-based information (eHealth information). Recall of information is crucial for optimal health outcomes, such as adequate disease management and adherence to medical regimes. Combining effective message strategies may help to improve recall of eHealth information among older adults. Presenting information in an audiovisual format using conversational narration style is expected to optimize recall of information compared to other combinations of modality and narration style. The aim of this paper is to investigate the effect of modality and narration style on recall of health information, and whether there are differences between younger and older adults. We conducted a Web-based experiment using a 2 (modality: written vs audiovisual information) by 2 (narration style: formal vs conversational style) between-subjects design (N=440). Age was assessed in the questionnaire and included as a factor: younger (<65 years) versus older (≥65 years) age. Participants were randomly assigned to one of four experimental webpages where information about lung cancer treatment was presented. A Web-based questionnaire assessed recall of eHealth information. Audiovisual modality (vs written modality) was found to increase recall of information in both younger and older adults (P=.04). Although conversational narration style (vs formal narration style) did not increase recall of information (P=.17), a synergistic effect between modality and narration style was revealed: combining audiovisual information with conversational style outperformed combining written information with formal style (P=.01), as well as written information with conversational style (P=.045). This finding suggests that conversational style especially increases recall of information when presented audiovisually. This combination of modality and narration style improved recall of

Exploring the Experiences of Living With Stroke Through Narrative: Stroke Survivors' Perspectives.

PubMed

Nasr, Nasrin; Mawson, Susan; Wright, Peter; Parker, Jack; Mountain, Gail

2016-01-01

Chronic illness models are normally used to explain and predict the experience of living with a long-term condition. The aim of this study was to present the findings of narrative interviews with stroke survivors and their family carers to understand their experiences of stroke. We interviewed five people with stroke and three family carers from the United Kingdom. We used thematic analysis to generate themes from their narrative accounts and then linked them to broader theoretical perspectives while influenced by the concept of reinterpretation of life. The narrative accounts of participants are mainly structured based on how their changed bodies poststroke changed their identities and roles and consequently their relationships with others. In this study, we underline the need for using methods like narrative to explain strategies that people use to make sense of their experiences of living with a long-term condition such as stroke.

GRAVTool, a Package to Compute Geoid Model by Remove-Compute-Restore Technique

NASA Astrophysics Data System (ADS)

Marotta, G. S.; Blitzkow, D.; Vidotti, R. M.

2015-12-01

Currently, there are several methods to determine geoid models. They can be based on terrestrial gravity data, geopotential coefficients, astro-geodetic data or a combination of them. Among the techniques to compute a precise geoid model, the Remove-Compute-Restore (RCR) has been widely applied. It considers short, medium and long wavelengths derived from altitude data provided by Digital Terrain Models (DTM), terrestrial gravity data and global geopotential coefficients, respectively. In order to apply this technique, it is necessary to create procedures that compute gravity anomalies and geoid models, by the integration of different wavelengths, and that adjust these models to one local vertical datum. This research presents a developed package called GRAVTool based on MATLAB software to compute local geoid models by RCR technique and its application in a study area. The studied area comprehends the federal district of Brazil, with ~6000 km², wavy relief, heights varying from 600 m to 1340 m, located between the coordinates 48.25ºW, 15.45ºS and 47.33ºW, 16.06ºS. The results of the numerical example on the studied area show the local geoid model computed by the GRAVTool package (Figure), using 1377 terrestrial gravity data, SRTM data with 3 arc second of resolution, and geopotential coefficients of the EIGEN-6C4 model to degree 360. The accuracy of the computed model (σ = ± 0.071 m, RMS = 0.069 m, maximum = 0.178 m and minimum = -0.123 m) matches the uncertainty (σ =± 0.073) of 21 points randomly spaced where the geoid was computed by geometrical leveling technique supported by positioning GNSS. The results were also better than those achieved by Brazilian official regional geoid model (σ = ± 0.099 m, RMS = 0.208 m, maximum = 0.419 m and minimum = -0.040 m).

The Accuracy of Adult Narrative Reports of Developmental Trajectories

ERIC Educational Resources Information Center

Cohen, Patricia; Kasen, Stephanie; Bifulco, Antonia; Andrews, Howard; Gordon, Kathy

2005-01-01

This methodological investigation examines the accuracy of narrative-based scaled ratings covering several post high school years. Guided narratives by young adults described developmentally relevant behaviour and context for each month between ages 17 and the mid-20s. "Prospective" narratives covered shorter time periods in three interviews…

Narrative meaning making and integration: Toward a better understanding of the way falling ill influences quality of life.

PubMed

Hartog, Iris; Scherer-Rath, Michael; Kruizinga, Renske; Netjes, Justine; Henriques, José; Nieuwkerk, Pythia; Sprangers, Mirjam; van Laarhoven, Hanneke

2017-09-01

Falling seriously ill is often experienced as a life event that causes conflict with people's personal goals and expectations in life and evokes existential questions. This article presents a new humanities approach to the way people make meaning of such events and how this influences their quality of life. Incorporating theories on contingency, narrative identity, and quality of life, we developed a theoretical model entailing the concepts life event, worldview, ultimate life goals, experience of contingency, narrative meaning making, narrative integration, and quality of life. We formulate testable hypotheses and describe the self-report questionnaire that was developed based on the model.

Narrative means to manage responsibility in life narratives across adolescence.

PubMed

De Silveira, Cybèle; Habermas, Tilmann

2011-01-01

Adolescence is a passage from dependence to adult responsibility. Alongside identity development, social-cognitive development, and the ability to construct a life story, adolescents become increasingly aware of both their potential responsibility in an expanded sphere of life and of complex, contextual influences on their lives. This was partially tested in a cross-sectional study, both in terms of linguistic means and content expressed in life narratives. Indicators were defined for narrative agency, grading of responsibility, serendipity, and turning points, and tested for age differences in relative frequencies in 102 life narratives from age groups of 8, 12, 16, and 20 years, balanced for gender. Narrative grading of responsibility, serendipity, and turning points increased throughout adolescence. The relative frequency of narrative agency, in contrast, remained constant across age groups. Results are interpreted in the context of adolescent development of narrative identity.

"These Are Just Stories, Mulder": Exposure to Conspiracist Fiction Does Not Produce Narrative Persuasion.

PubMed

Nera, Kenzo; Pantazi, Myrto; Klein, Olivier

2018-01-01

Narrative persuasion, i.e., the impact of narratives on beliefs, behaviors and attitudes, and the mechanisms underpinning endorsement of conspiracy theories have both drawn substantial attention from social scientists. Yet, to date, these two fields have evolved separately, and to our knowledge no study has empirically examined the impact of conspiracy narratives on real-world conspiracy beliefs. In a first study, we exposed a group of participants ( n = 37) to an X-Files episode before asking them to fill in a questionnaire related to their narrative experience and conspiracy beliefs. A control group ( n = 41) had to answer the conspiracy beliefs items before watching the episode. Based on past findings of both the aforementioned fields of research, we hypothesized that the experimental group would show greater endorsement of conspiracy beliefs, an effect expected to be mediated by identification to the episodes' characters. We furthermore hypothesized that identification would be associated with cognitive elaboration of the topics developed in the narrative. The first two hypotheses were disproved since no narrative persuasion effect was observed. In a second study, we sought to replicate these results in a larger sample ( n = 166). No persuasive effect was found in the new data and a Bayesian meta-analysis of the two studies strongly supports the absence of a positive effect of exposure to narrative material on endorsement of conspiracy theories. In both studies, a significant relation between conspiracy mentality and enjoyment was observed. In the second study, this relation was fully mediated by two dimensions of perceived realism, i.e., plausibility and narrative consistency. We discuss our results, based on theoretical models of narrative persuasion and compare our studies with previous narrative persuasion studies. Implications of these results for future research are also discussed.

Teaching Life Narratives in the Classroom: Strategies Based on Indigenous Traditions

ERIC Educational Resources Information Center

Lavoie, Constance; Blanchet, Patricia-Anne

2018-01-01

The life narrative is an oral genre grounded in Indigenous tradition and teaching practice. In Canadian Indigenous communities, the expertise and content transmitted by life narratives are a part of their oral heritage. Drawing from their personal and professional experiences in Indigenous school environments, as well as the results from…

Data driven model generation based on computational intelligence

NASA Astrophysics Data System (ADS)

Gemmar, Peter; Gronz, Oliver; Faust, Christophe; Casper, Markus

2010-05-01

The simulation of discharges at a local gauge or the modeling of large scale river catchments are effectively involved in estimation and decision tasks of hydrological research and practical applications like flood prediction or water resource management. However, modeling such processes using analytical or conceptual approaches is made difficult by both complexity of process relations and heterogeneity of processes. It was shown manifold that unknown or assumed process relations can principally be described by computational methods, and that system models can automatically be derived from observed behavior or measured process data. This study describes the development of hydrological process models using computational methods including Fuzzy logic and artificial neural networks (ANN) in a comprehensive and automated manner. Methods We consider a closed concept for data driven development of hydrological models based on measured (experimental) data. The concept is centered on a Fuzzy system using rules of Takagi-Sugeno-Kang type which formulate the input-output relation in a generic structure like Ri : IFq(t) = lowAND...THENq(t+Δt) = ai0 +ai1q(t)+ai2p(t-Δti1)+ai3p(t+Δti2)+.... The rule's premise part (IF) describes process states involving available process information, e.g. actual outlet q(t) is low where low is one of several Fuzzy sets defined over variable q(t). The rule's conclusion (THEN) estimates expected outlet q(t + Δt) by a linear function over selected system variables, e.g. actual outlet q(t), previous and/or forecasted precipitation p(t ?Δtik). In case of river catchment modeling we use head gauges, tributary and upriver gauges in the conclusion part as well. In addition, we consider temperature and temporal (season) information in the premise part. By creating a set of rules R = {Ri|(i = 1,...,N)} the space of process states can be covered as concise as necessary. Model adaptation is achieved by finding on optimal set A = (aij) of conclusion

Using a narrative to spark safer sex communication.

PubMed

Donné, Lennie; Hoeks, John; Jansen, Carel

2017-10-01

College students are a group at risk for contracting sexually transmitted infections (STIs). While they are generally well informed about STIs, they do not consistently use condoms. An important element in preventing STIs is safer sex communication, especially with a sexual partner. This may be difficult, however, because of a lack of experience in talking about safer sex or because of the absence of suitable role models. In this study, a narrative intervention was tested that was developed to provide receivers with a social script for safer sex communication. An experiment was conducted among college students ( N  = 225) who were exposed to either a narrative intervention or a non-narrative (brochure) intervention, followed by a post-test questionnaire. In the narrative condition, part of the participants completed a pre-test questionnaire before being exposed to the intervention. Compared to pre-test scores, the narrative positively influenced safer sex communication intentions. The results show no significant differences between post-test scores of the narrative and the non-narrative condition. Mediation analyses showed that narrative processes (identification and transportation) were positively related to safer sex communication. In this study, we investigated both the effects of a narrative intervention on safer sex communication intentions, and the mechanisms of narrative processing underlying these effects. The narrative turned out to be as effective as a brochure version with the same information. Our mediation analyses suggest that narratives can be made more persuasive by increasing the reader's involvement with the story as a whole, and with one of the characters in particular.

Evidence-Based Practice for Children with Speech Sound Disorders: Part 1 Narrative Review

ERIC Educational Resources Information Center

Baker, Elise; McLeod, Sharynne

2011-01-01

Purpose: This article provides a comprehensive narrative review of intervention studies for children with speech sound disorders (SSD). Its companion paper (Baker & McLeod, 2011) provides a tutorial and clinical example of how speech-language pathologists (SLPs) can engage in evidence-based practice (EBP) for this clinical population. Method:…

Overview of Threats and Failure Models for Safety-Relevant Computer-Based Systems

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2015-01-01

This document presents a high-level overview of the threats to safety-relevant computer-based systems, including (1) a description of the introduction and activation of physical and logical faults; (2) the propagation of their effects; and (3) function-level and component-level error and failure mode models. These models can be used in the definition of fault hypotheses (i.e., assumptions) for threat-risk mitigation strategies. This document is a contribution to a guide currently under development that is intended to provide a general technical foundation for designers and evaluators of safety-relevant systems.

A computer graphics based model for scattering from objects of arbitrary shapes in the optical region

NASA Technical Reports Server (NTRS)

Goel, Narendra S.; Rozehnal, Ivan; Thompson, Richard L.

1991-01-01

A computer-graphics-based model, named DIANA, is presented for generation of objects of arbitrary shape and for calculating bidirectional reflectances and scattering from them, in the visible and infrared region. The computer generation is based on a modified Lindenmayer system approach which makes it possible to generate objects of arbitrary shapes and to simulate their growth, dynamics, and movement. Rendering techniques are used to display an object on a computer screen with appropriate shading and shadowing and to calculate the scattering and reflectance from the object. The technique is illustrated with scattering from canopies of simulated corn plants.

Category-theoretic models of algebraic computer systems

NASA Astrophysics Data System (ADS)

Kovalyov, S. P.

2016-01-01

A computer system is said to be algebraic if it contains nodes that implement unconventional computation paradigms based on universal algebra. A category-based approach to modeling such systems that provides a theoretical basis for mapping tasks to these systems' architecture is proposed. The construction of algebraic models of general-purpose computations involving conditional statements and overflow control is formally described by a reflector in an appropriate category of algebras. It is proved that this reflector takes the modulo ring whose operations are implemented in the conventional arithmetic processors to the Łukasiewicz logic matrix. Enrichments of the set of ring operations that form bases in the Łukasiewicz logic matrix are found.

Measurement of negativity bias in personal narratives using corpus-based emotion dictionaries.

PubMed

Cohen, Shuki J

2011-04-01

This study presents a novel methodology for the measurement of negativity bias using positive and negative dictionaries of emotion words applied to autobiographical narratives. At odds with the cognitive theory of mood dysregulation, previous text-analytical studies have failed to find significant correlation between emotion dictionaries and negative affectivity or dysphoria. In the present study, an a priori list dictionary of emotion words was refined based on the actual use of these words in personal narratives collected from close to 500 college students. Half of the corpus was used to construct, via concordance analysis, the grammatical structures associated with the words in their emotional sense. The second half of the corpus served as a validation corpus. The resulting dictionary ignores words that are not used in their intended emotional sense, including negated emotions, homophones, frozen idioms etc. Correlations of the resulting corpus-based negative and positive emotion dictionaries with self-report measures of negative affectivity were in the expected direction, and were statistically significant, with medium effect size. The potential use of these dictionaries as implicit measures of negativity bias and in the analysis of psychotherapy transcripts is discussed.

Quantum vertex model for reversible classical computing.

PubMed

Chamon, C; Mucciolo, E R; Ruckenstein, A E; Yang, Z-C

2017-05-12

Mappings of classical computation onto statistical mechanics models have led to remarkable successes in addressing some complex computational problems. However, such mappings display thermodynamic phase transitions that may prevent reaching solution even for easy problems known to be solvable in polynomial time. Here we map universal reversible classical computations onto a planar vertex model that exhibits no bulk classical thermodynamic phase transition, independent of the computational circuit. Within our approach the solution of the computation is encoded in the ground state of the vertex model and its complexity is reflected in the dynamics of the relaxation of the system to its ground state. We use thermal annealing with and without 'learning' to explore typical computational problems. We also construct a mapping of the vertex model into the Chimera architecture of the D-Wave machine, initiating an approach to reversible classical computation based on state-of-the-art implementations of quantum annealing.

Quantum vertex model for reversible classical computing

NASA Astrophysics Data System (ADS)

Chamon, C.; Mucciolo, E. R.; Ruckenstein, A. E.; Yang, Z.-C.

2017-05-01

Mappings of classical computation onto statistical mechanics models have led to remarkable successes in addressing some complex computational problems. However, such mappings display thermodynamic phase transitions that may prevent reaching solution even for easy problems known to be solvable in polynomial time. Here we map universal reversible classical computations onto a planar vertex model that exhibits no bulk classical thermodynamic phase transition, independent of the computational circuit. Within our approach the solution of the computation is encoded in the ground state of the vertex model and its complexity is reflected in the dynamics of the relaxation of the system to its ground state. We use thermal annealing with and without `learning' to explore typical computational problems. We also construct a mapping of the vertex model into the Chimera architecture of the D-Wave machine, initiating an approach to reversible classical computation based on state-of-the-art implementations of quantum annealing.

Computational aeroelasticity using a pressure-based solver

NASA Astrophysics Data System (ADS)

Kamakoti, Ramji

A computational methodology for performing fluid-structure interaction computations for three-dimensional elastic wing geometries is presented. The flow solver used is based on an unsteady Reynolds-Averaged Navier-Stokes (RANS) model. A well validated k-ε turbulence model with wall function treatment for near wall region was used to perform turbulent flow calculations. Relative merits of alternative flow solvers were investigated. The predictor-corrector-based Pressure Implicit Splitting of Operators (PISO) algorithm was found to be computationally economic for unsteady flow computations. Wing structure was modeled using Bernoulli-Euler beam theory. A fully implicit time-marching scheme (using the Newmark integration method) was used to integrate the equations of motion for structure. Bilinear interpolation and linear extrapolation techniques were used to transfer necessary information between fluid and structure solvers. Geometry deformation was accounted for by using a moving boundary module. The moving grid capability was based on a master/slave concept and transfinite interpolation techniques. Since computations were performed on a moving mesh system, the geometric conservation law must be preserved. This is achieved by appropriately evaluating the Jacobian values associated with each cell. Accurate computation of contravariant velocities for unsteady flows using the momentum interpolation method on collocated, curvilinear grids was also addressed. Flutter computations were performed for the AGARD 445.6 wing at subsonic, transonic and supersonic Mach numbers. Unsteady computations were performed at various dynamic pressures to predict the flutter boundary. Results showed favorable agreement of experiment and previous numerical results. The computational methodology exhibited capabilities to predict both qualitative and quantitative features of aeroelasticity.

Paper-Based and Computer-Based Concept Mappings: The Effects on Computer Achievement, Computer Anxiety and Computer Attitude

ERIC Educational Resources Information Center

Erdogan, Yavuz

2009-01-01

The purpose of this paper is to compare the effects of paper-based and computer-based concept mappings on computer hardware achievement, computer anxiety and computer attitude of the eight grade secondary school students. The students were randomly allocated to three groups and were given instruction on computer hardware. The teaching methods used…

Models of neuromodulation for computational psychiatry.

PubMed

Iglesias, Sandra; Tomiello, Sara; Schneebeli, Maya; Stephan, Klaas E

2017-05-01

Psychiatry faces fundamental challenges: based on a syndrome-based nosology, it presently lacks clinical tests to infer on disease processes that cause symptoms of individual patients and must resort to trial-and-error treatment strategies. These challenges have fueled the recent emergence of a novel field-computational psychiatry-that strives for mathematical models of disease processes at physiological and computational (information processing) levels. This review is motivated by one particular goal of computational psychiatry: the development of 'computational assays' that can be applied to behavioral or neuroimaging data from individual patients and support differential diagnosis and guiding patient-specific treatment. Because the majority of available pharmacotherapeutic approaches in psychiatry target neuromodulatory transmitters, models that infer (patho)physiological and (patho)computational actions of different neuromodulatory transmitters are of central interest for computational psychiatry. This article reviews the (many) outstanding questions on the computational roles of neuromodulators (dopamine, acetylcholine, serotonin, and noradrenaline), outlines available evidence, and discusses promises and pitfalls in translating these findings to clinical applications. WIREs Cogn Sci 2017, 8:e1420. doi: 10.1002/wcs.1420 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

A narrative method for consciousness research

PubMed Central

Díaz, José-Luis

2013-01-01

Some types of first-person narrations of mental processes that constitute phenomenological accounts and texts, such as internal monolog statements, epitomize the best expressions and representations of human consciousness available and therefore may be used to model phenomenological streams of consciousness. The type of autonomous monolog in which an author or narrator declares actual mental processes in a think aloud manner seems particularly suitable for modeling streams of consciousness. A narrative method to extract and depict conscious processes, operations, contents, and states from an acceptable phenomenological text would require three subsequent steps: operational criteria for producing and/or selecting a phenomenological text, a system for detecting text items that are indicative of conscious contents and processes, and a procedure for representing such items in formal dynamic system devices such as Petri nets. The requirements and restrictions of each of these steps are presented, analyzed, and applied to phenomenological texts in the following manner: (1) the relevance of introspective language and narrative analyses to consciousness research and the idea that specific narratives are of paramount interest for such investigation is justified; (2) some of the obstacles and constraints to attain plausible consciousness inferences from narrative texts and the methodological requirements to extract and depict items relevant to consciousness contents and operations from a suitable phenomenological text are examined; (3) a preliminary exercise of the proposed method is used to analyze and chart a classical interior monolog excerpted from James Joyce’s Ulysses, a masterpiece of the stream-of-consciousness literary technique and, finally, (4) an inter-subjective evaluation for inter-observer agreement of mental attributions of another phenomenological text (an excerpt from the Intimate Journal of Miguel de Unamuno) is presented using some mathematical tools

A narrative method for consciousness research.

PubMed

Díaz, José-Luis

2013-01-01

Some types of first-person narrations of mental processes that constitute phenomenological accounts and texts, such as internal monolog statements, epitomize the best expressions and representations of human consciousness available and therefore may be used to model phenomenological streams of consciousness. The type of autonomous monolog in which an author or narrator declares actual mental processes in a think aloud manner seems particularly suitable for modeling streams of consciousness. A narrative method to extract and depict conscious processes, operations, contents, and states from an acceptable phenomenological text would require three subsequent steps: operational criteria for producing and/or selecting a phenomenological text, a system for detecting text items that are indicative of conscious contents and processes, and a procedure for representing such items in formal dynamic system devices such as Petri nets. The requirements and restrictions of each of these steps are presented, analyzed, and applied to phenomenological texts in the following manner: (1) the relevance of introspective language and narrative analyses to consciousness research and the idea that specific narratives are of paramount interest for such investigation is justified; (2) some of the obstacles and constraints to attain plausible consciousness inferences from narrative texts and the methodological requirements to extract and depict items relevant to consciousness contents and operations from a suitable phenomenological text are examined; (3) a preliminary exercise of the proposed method is used to analyze and chart a classical interior monolog excerpted from James Joyce's Ulysses, a masterpiece of the stream-of-consciousness literary technique and, finally, (4) an inter-subjective evaluation for inter-observer agreement of mental attributions of another phenomenological text (an excerpt from the Intimate Journal of Miguel de Unamuno) is presented using some mathematical tools.

A cortical edge-integration model of object-based lightness computation that explains effects of spatial context and individual differences

PubMed Central

Rudd, Michael E.

2014-01-01

Previous work has demonstrated that perceived surface reflectance (lightness) can be modeled in simple contexts in a quantitatively exact way by assuming that the visual system first extracts information about local, directed steps in log luminance, then spatially integrates these steps along paths through the image to compute lightness (Rudd and Zemach, 2004, 2005, 2007). This method of computing lightness is called edge integration. Recent evidence (Rudd, 2013) suggests that human vision employs a default strategy to integrate luminance steps only along paths from a common background region to the targets whose lightness is computed. This implies a role for gestalt grouping in edge-based lightness computation. Rudd (2010) further showed the perceptual weights applied to edges in lightness computation can be influenced by the observer's interpretation of luminance steps as resulting from either spatial variation in surface reflectance or illumination. This implies a role for top-down factors in any edge-based model of lightness (Rudd and Zemach, 2005). Here, I show how the separate influences of grouping and attention on lightness can be modeled in tandem by a cortical mechanism that first employs top-down signals to spatially select regions of interest for lightness computation. An object-based network computation, involving neurons that code for border-ownership, then automatically sets the neural gains applied to edge signals surviving the earlier spatial selection stage. Only the borders that survive both processing stages are spatially integrated to compute lightness. The model assumptions are consistent with those of the cortical lightness model presented earlier by Rudd (2010, 2013), and with neurophysiological data indicating extraction of local edge information in V1, network computations to establish figure-ground relations and border ownership in V2, and edge integration to encode lightness and darkness signals in V4. PMID:25202253

A cortical edge-integration model of object-based lightness computation that explains effects of spatial context and individual differences.

PubMed

Rudd, Michael E

2014-01-01

Previous work has demonstrated that perceived surface reflectance (lightness) can be modeled in simple contexts in a quantitatively exact way by assuming that the visual system first extracts information about local, directed steps in log luminance, then spatially integrates these steps along paths through the image to compute lightness (Rudd and Zemach, 2004, 2005, 2007). This method of computing lightness is called edge integration. Recent evidence (Rudd, 2013) suggests that human vision employs a default strategy to integrate luminance steps only along paths from a common background region to the targets whose lightness is computed. This implies a role for gestalt grouping in edge-based lightness computation. Rudd (2010) further showed the perceptual weights applied to edges in lightness computation can be influenced by the observer's interpretation of luminance steps as resulting from either spatial variation in surface reflectance or illumination. This implies a role for top-down factors in any edge-based model of lightness (Rudd and Zemach, 2005). Here, I show how the separate influences of grouping and attention on lightness can be modeled in tandem by a cortical mechanism that first employs top-down signals to spatially select regions of interest for lightness computation. An object-based network computation, involving neurons that code for border-ownership, then automatically sets the neural gains applied to edge signals surviving the earlier spatial selection stage. Only the borders that survive both processing stages are spatially integrated to compute lightness. The model assumptions are consistent with those of the cortical lightness model presented earlier by Rudd (2010, 2013), and with neurophysiological data indicating extraction of local edge information in V1, network computations to establish figure-ground relations and border ownership in V2, and edge integration to encode lightness and darkness signals in V4.

Using a narrative to spark safer sex communication

PubMed Central

Donné, Lennie; Hoeks, John; Jansen, Carel

2017-01-01

Objective: College students are a group at risk for contracting sexually transmitted infections (STIs). While they are generally well informed about STIs, they do not consistently use condoms. An important element in preventing STIs is safer sex communication, especially with a sexual partner. This may be difficult, however, because of a lack of experience in talking about safer sex or because of the absence of suitable role models. In this study, a narrative intervention was tested that was developed to provide receivers with a social script for safer sex communication. Design: An experiment was conducted among college students (N = 225) who were exposed to either a narrative intervention or a non-narrative (brochure) intervention, followed by a post-test questionnaire. In the narrative condition, part of the participants completed a pre-test questionnaire before being exposed to the intervention. Results: Compared to pre-test scores, the narrative positively influenced safer sex communication intentions. The results show no significant differences between post-test scores of the narrative and the non-narrative condition. Mediation analyses showed that narrative processes (identification and transportation) were positively related to safer sex communication. Conclusion: In this study, we investigated both the effects of a narrative intervention on safer sex communication intentions, and the mechanisms of narrative processing underlying these effects. The narrative turned out to be as effective as a brochure version with the same information. Our mediation analyses suggest that narratives can be made more persuasive by increasing the reader’s involvement with the story as a whole, and with one of the characters in particular. PMID:28919639

Clarifying the Narrative Paradigm.

ERIC Educational Resources Information Center

Fisher, Walter R.

1989-01-01

Replies to Rowland's article (same issue) on Fisher's views of the narrative paradigm. Clarifies the narrative paradigm by discussing three senses in which "narration" can be understood, and by indicating what the narrative paradigm is not. (SR)

Computational study on cortical spreading depression based on a generalized cellular automaton model

NASA Astrophysics Data System (ADS)

Chen, Shangbin; Hu, Lele; Li, Bing; Xu, Changcheng; Liu, Qian

2009-02-01

Cortical spreading depression (CSD) is an important neurophysiological phenomenon correlating with some neural disorders, such as migraine, cerebral ischemia and epilepsy. By now, we are still not clear about the mechanisms of CSD's initiation and propagation, also the relevance between CSD and those neural diseases. Nevertheless, characterization of CSD, especially the spatiotemporal evolution, will promote the understanding of the CSD's nature and mechanisms. Besides the previous experimental work on charactering the spatiotemporal evolution of CSD in rats by optical intrinsic signal imaging, a computational study based on a generalized cellular automaton (CA) model was proposed here. In the model, we exploited a generalized neighborhood connection rule: a central CA cell is related with a group of surrounding CA cells with different weight coefficients. By selecting special parameters, the generalized CA model could be transformed to the traditional CA models with von Neumann, Moore and hexagon neighborhood connection means. Hence, the new model covered several properties of CSD simulated in traditional CA models: 1) expanding from the origin site like a circular wave; 2) annihilation of two waves traveling in opposite directions after colliding; 3) wavefront of CSD breaking and recovering when and after encountering an obstacle. By setting different refractory period in the different CA lattice field, different connection coefficient in different direction within the defined neighborhood, inhomogeneous propagation of CSD was simulated with high fidelity. The computational results were analogous to the reported time-varying CSD waves by optical imaging. So, the generalized CA model would be useful to study CSD because of its intuitive appeal and computational efficiency.

Computer 3D site model generation based on aerial images

NASA Astrophysics Data System (ADS)

Zheltov, Sergey Y.; Blokhinov, Yuri B.; Stepanov, Alexander A.; Skryabin, Sergei V.; Sibiriakov, Alexandre V.

1997-07-01

The technology for 3D model design of real world scenes and its photorealistic rendering are current topics of investigation. Development of such technology is very attractive to implement in vast varieties of applications: military mission planning, crew training, civil engineering, architecture, virtual reality entertainments--just a few were mentioned. 3D photorealistic models of urban areas are often discussed now as upgrade from existing 2D geographic information systems. Possibility of site model generation with small details depends on two main factors: available source dataset and computer power resources. In this paper PC based technology is presented, so the scenes of middle resolution (scale of 1:1000) be constructed. Types of datasets are the gray level aerial stereo pairs of photographs (scale of 1:14000) and true color on ground photographs of buildings (scale ca.1:1000). True color terrestrial photographs are also necessary for photorealistic rendering, that in high extent improves human perception of the scene.

Impact of computational structure-based methods on drug discovery.

PubMed

Reynolds, Charles H

2014-01-01

Structure-based drug design has become an indispensible tool in drug discovery. The emergence of structure-based design is due to gains in structural biology that have provided exponential growth in the number of protein crystal structures, new computational algorithms and approaches for modeling protein-ligand interactions, and the tremendous growth of raw computer power in the last 30 years. Computer modeling and simulation have made major contributions to the discovery of many groundbreaking drugs in recent years. Examples are presented that highlight the evolution of computational structure-based design methodology, and the impact of that methodology on drug discovery.

Narrative, Poststructuralism, and Social Justice: Current Practices in Narrative Therapy

ERIC Educational Resources Information Center

Combs, Gene; Freedman, Jill

2012-01-01

This paper is a review of current practice in narrative therapy with a focus on how it is attractive and useful for therapists who wish to work for social justice. The authors describe narrative therapy's roots in poststructuralist philosophy and social science. They illustrate its major theoretical constructs, including the "narrative metaphor,"…

Autism as Metaphor: Narrative and Counter-Narrative

ERIC Educational Resources Information Center

Broderick, Alicia A.; Ne'eman, Ari

2008-01-01

In this paper we explore the significance of metaphor and dominant cultural narratives in current autism discourse. We briefly explore the history of metaphor in autism discourse, and outline the contemporary struggle between the culturally dominant metaphor of autism as disease and the emergent counter-narrative of autism within neurodiversity.…

“These Are Just Stories, Mulder”: Exposure to Conspiracist Fiction Does Not Produce Narrative Persuasion

PubMed Central

Nera, Kenzo; Pantazi, Myrto; Klein, Olivier

2018-01-01

Narrative persuasion, i.e., the impact of narratives on beliefs, behaviors and attitudes, and the mechanisms underpinning endorsement of conspiracy theories have both drawn substantial attention from social scientists. Yet, to date, these two fields have evolved separately, and to our knowledge no study has empirically examined the impact of conspiracy narratives on real-world conspiracy beliefs. In a first study, we exposed a group of participants (n = 37) to an X-Files episode before asking them to fill in a questionnaire related to their narrative experience and conspiracy beliefs. A control group (n = 41) had to answer the conspiracy beliefs items before watching the episode. Based on past findings of both the aforementioned fields of research, we hypothesized that the experimental group would show greater endorsement of conspiracy beliefs, an effect expected to be mediated by identification to the episodes' characters. We furthermore hypothesized that identification would be associated with cognitive elaboration of the topics developed in the narrative. The first two hypotheses were disproved since no narrative persuasion effect was observed. In a second study, we sought to replicate these results in a larger sample (n = 166). No persuasive effect was found in the new data and a Bayesian meta-analysis of the two studies strongly supports the absence of a positive effect of exposure to narrative material on endorsement of conspiracy theories. In both studies, a significant relation between conspiracy mentality and enjoyment was observed. In the second study, this relation was fully mediated by two dimensions of perceived realism, i.e., plausibility and narrative consistency. We discuss our results, based on theoretical models of narrative persuasion and compare our studies with previous narrative persuasion studies. Implications of these results for future research are also discussed. PMID:29875710

The use of narrative in Jewish medical ethics.

PubMed

Jotkowitz, Alan

2013-09-01

Anne Jones has pointed out that over the last three decades, stories have been important to medical ethics in at least three ways: (1). Stories as cases for teaching principle-based medical ethics (2). Narratives for moral guides on what is considered living a good life (3). Stories as testimonials written by both patients and physicians. A pioneer in this effort, particularly in regard to using narratives as moral guides, has been the ethicist and philosopher Stanley Hauerwas. Heavily influenced by virtue ethics, Hauerwas believes that it is a person's particular narrative tradition that provides one with convictions that form the basis of one's morality. Befitting a Protestant theologian, he is particularly concerned with the Christian narrative. From a Jewish perspective, there has been much less written on the use of narrative in medical ethics. However, it is a mistake to think that narrative has little, if any, role in Rabbinic ethical decision making. The purpose of this article is to demonstrate the centrality of narrative in the thought of Orthodox Jewish decisors and the problems inherent in this methodology.

The narrative approach to personalisation

NASA Astrophysics Data System (ADS)

Conlan, Owen; Staikopoulos, Athanasios; Hampson, Cormac; Lawless, Séamus; O'keeffe, Ian

2013-06-01

This article describes the narrative approach to personalisation. This novel approach to the generation of personalised adaptive hypermedia experiences employs runtime reconciliation between a personalisation strategy and a number of contextual models (e.g. user and domain). The approach also advocates the late binding of suitable content and services to the generated personalised pathway resulting in an interactive composition that comprises services as well as content. This article provides a detailed definition of the narrative approach to personalisation and showcases the approach through the examination of two use-cases: the personalised digital educational games developed by the ELEKTRA and 80Days projects; and the personalised learning activities realised as part of the AMAS project. These use-cases highlight the general applicability of the narrative approach and how it has been applied to create a diverse range of real-world systems.

A System Computational Model of Implicit Emotional Learning

PubMed Central

Puviani, Luca; Rama, Sidita

2016-01-01

Nowadays, the experimental study of emotional learning is commonly based on classical conditioning paradigms and models, which have been thoroughly investigated in the last century. Unluckily, models based on classical conditioning are unable to explain or predict important psychophysiological phenomena, such as the failure of the extinction of emotional responses in certain circumstances (for instance, those observed in evaluative conditioning, in post-traumatic stress disorders and in panic attacks). In this manuscript, starting from the experimental results available from the literature, a computational model of implicit emotional learning based both on prediction errors computation and on statistical inference is developed. The model quantitatively predicts (a) the occurrence of evaluative conditioning, (b) the dynamics and the resistance-to-extinction of the traumatic emotional responses, (c) the mathematical relation between classical conditioning and unconditioned stimulus revaluation. Moreover, we discuss how the derived computational model can lead to the development of new animal models for resistant-to-extinction emotional reactions and novel methodologies of emotions modulation. PMID:27378898

A System Computational Model of Implicit Emotional Learning.

PubMed

Puviani, Luca; Rama, Sidita

2016-01-01

Nowadays, the experimental study of emotional learning is commonly based on classical conditioning paradigms and models, which have been thoroughly investigated in the last century. Unluckily, models based on classical conditioning are unable to explain or predict important psychophysiological phenomena, such as the failure of the extinction of emotional responses in certain circumstances (for instance, those observed in evaluative conditioning, in post-traumatic stress disorders and in panic attacks). In this manuscript, starting from the experimental results available from the literature, a computational model of implicit emotional learning based both on prediction errors computation and on statistical inference is developed. The model quantitatively predicts (a) the occurrence of evaluative conditioning, (b) the dynamics and the resistance-to-extinction of the traumatic emotional responses, (c) the mathematical relation between classical conditioning and unconditioned stimulus revaluation. Moreover, we discuss how the derived computational model can lead to the development of new animal models for resistant-to-extinction emotional reactions and novel methodologies of emotions modulation.

Hybrid architecture for encoded measurement-based quantum computation

PubMed Central

Zwerger, M.; Briegel, H. J.; Dür, W.

2014-01-01

We present a hybrid scheme for quantum computation that combines the modular structure of elementary building blocks used in the circuit model with the advantages of a measurement-based approach to quantum computation. We show how to construct optimal resource states of minimal size to implement elementary building blocks for encoded quantum computation in a measurement-based way, including states for error correction and encoded gates. The performance of the scheme is determined by the quality of the resource states, where within the considered error model a threshold of the order of 10% local noise per particle for fault-tolerant quantum computation and quantum communication. PMID:24946906

The Secret between Storytelling and Retelling: Tea, School, & Narrative

ERIC Educational Resources Information Center

Yu, Jie

2014-01-01

In this paper, I will tell two of my personal stories to try to explore the secret or opaque space between the original telling and retelling of stories in narrative inquiry. Based upon my difficult struggles with the two stories of tea, school, and narrative, I suggest that narrative inquiry has to be a complex loop of relationship, reflexivity,…

Some Computer-Based Developments in Sociology.

ERIC Educational Resources Information Center

Heise, David R.; Simmons, Roberta G.

1985-01-01

Discusses several ways in which computers are being used in sociology and how they continue to change this discipline. Areas considered include data collection, data analysis, simulations of social processes based on mathematical models, and problem areas (including standardization concerns, training, and the financing of computing facilities).…

A Systematic Review of Narrative-Based Language Intervention with Children Who Have Language Impairment

ERIC Educational Resources Information Center

Petersen, Douglas B.

2011-01-01

This systematic review focuses on research articles published since 1980 that assess outcomes of narrative-based language intervention for preschool and school-age children with language impairment. The author conducted a comprehensive search of electronic databases and hand searches of other sources for studies using all research designs except…

Listeners as co-narrators.

PubMed

Bavelas, J B; Coates, L; Johnson, T

2000-12-01

A collaborative theory of narrative story-telling was tested in two experiments that examined what listeners do and their effect on the narrator. In 63 unacquainted dyads (81 women and 45 men), a narrator told his or her own close-call story. The listeners made 2 different kinds of listener responses: Generic responses included nodding and vocalizations such as "mhm." Specific responses, such as wincing or exclaiming, were tightly connected to (and served to illustrate) what the narrator was saying at the moment. In experimental conditions that distracted listeners from the narrative content, listeners made fewer responses, especially specific ones, and the narrators also told their stories significantly less well, particularly at what should have been the dramatic ending. Thus, listeners were co-narrators both through their own specific responses, which helped illustrate the story, and in their apparent effect on the narrator's performance. The results demonstrate the importance of moment-by-moment collaboration in face-to-face dialogue.

Narratives of Experiential Learning: Students' Engagement in a Physical Activity-Based Service-Learning Course

ERIC Educational Resources Information Center

Whitley, Meredith A.; Walsh, David; Hayden, Laura; Gould, Daniel

2017-01-01

Purpose: Three undergraduate students' experiences in a physical activity-based service learning course are chronicled using narrative inquiry. Method: Data collection included demographics questionnaires, pre- and postservice interviews, reflection journals, postservice written reflections, and participant observations. The data were analyzed…

Narrative as Inquiry

ERIC Educational Resources Information Center

Hendry, Petra Munro

2010-01-01

The author suggests that all research is narrative. Resituating all research as narrative, as opposed to characterizing narrative as one particular form of inquiry, provides a critical space for rethinking "research" beyond current dualisms and bifurcations that create boundaries that limit the capacity for dialogue across diverse epistemologies.…

Slave Narratives as Polemic.

ERIC Educational Resources Information Center

Heglar, Charles J.

Although slave narratives have enjoyed critical attention as literature and autobiography, when presenting them to undergraduates, there is some confusion--usually centering on the dissimilarities between the narratives and traditional autobiography. The narratives are not as linear, not as focused on personal development; the narrators are not as…

Action starring narratives and events: Structure and inference in visual narrative comprehension.

PubMed

Cohn, Neil; Wittenberg, Eva

Studies of discourse have long placed focus on the inference generated by information that is not overtly expressed, and theories of visual narrative comprehension similarly focused on the inference generated between juxtaposed panels. Within the visual language of comics, star-shaped "flashes" commonly signify impacts, but can be enlarged to the size of a whole panel that can omit all other representational information. These "action star" panels depict a narrative culmination (a "Peak"), but have content which readers must infer, thereby posing a challenge to theories of inference generation in visual narratives that focus only on the semantic changes between juxtaposed images. This paper shows that action stars demand more inference than depicted events, and that they are more coherent in narrative sequences than scrambled sequences (Experiment 1). In addition, action stars play a felicitous narrative role in the sequence (Experiment 2). Together, these results suggest that visual narratives use conventionalized depictions that demand the generation of inferences while retaining narrative coherence of a visual sequence.

Characterizing the Pain Narratives of Parents of Youth With Chronic Pain.

PubMed

Noel, Melanie; Beals-Erickson, Sarah E; Law, Emily F; Alberts, Nicole M; Palermo, Tonya M

2016-10-01

Questionnaire-based research has shown that parents exert a powerful influence on and are profoundly influenced by living with a child with chronic pain. Examination of parents' pain narratives through an observational lens offers an alternative approach to understanding the complexity of pediatric chronic pain; however, the narratives of parents of youth with chronic pain have been largely overlooked. The present study aimed to characterize the vulnerability-based and resilience-based aspects of the pain narratives of parents of youth with chronic pain. Pain narratives of 46 parents were recorded during the baseline session as part of 2 clinical trials evaluating a behavioral intervention for parents of youth with chronic pain. The narratives were coded for aspects of pain-related vulnerability and resilience. Using exploratory cluster analysis, 2 styles of parents' pain narratives were identified. Distress narratives were characterized by more negative affect and an exclusively unresolved orientation toward the child's diagnosis of chronic pain, whereas resilience narratives were characterized by positive affect and a predominantly resolved orientation toward the child's diagnosis. Preliminary support for the validity of these clusters was provided through our finding of differences between clusters in parental pain catastrophizing about child pain (helplessness). Findings highlight the multidimensional nature of parents' experience of their child's pain problem. Clinical implications in terms of assessment and treatment are discussed.

A micro-computer based system to compute magnetic variation

NASA Technical Reports Server (NTRS)

Kaul, R.

1984-01-01

A mathematical model of magnetic variation in the continental United States (COT48) was implemented in the Ohio University LORAN C receiver. The model is based on a least squares fit of a polynomial function. The implementation on the microprocessor based LORAN C receiver is possible with the help of a math chip, Am9511 which performs 32 bit floating point mathematical operations. A Peripheral Interface Adapter (M6520) is used to communicate between the 6502 based micro-computer and the 9511 math chip. The implementation provides magnetic variation data to the pilot as a function of latitude and longitude. The model and the real time implementation in the receiver are described.

A pattern-based analysis of clinical computer-interpretable guideline modeling languages.

PubMed

Mulyar, Nataliya; van der Aalst, Wil M P; Peleg, Mor

2007-01-01

Languages used to specify computer-interpretable guidelines (CIGs) differ in their approaches to addressing particular modeling challenges. The main goals of this article are: (1) to examine the expressive power of CIG modeling languages, and (2) to define the differences, from the control-flow perspective, between process languages in workflow management systems and modeling languages used to design clinical guidelines. The pattern-based analysis was applied to guideline modeling languages Asbru, EON, GLIF, and PROforma. We focused on control-flow and left other perspectives out of consideration. We evaluated the selected CIG modeling languages and identified their degree of support of 43 control-flow patterns. We used a set of explicitly defined evaluation criteria to determine whether each pattern is supported directly, indirectly, or not at all. PROforma offers direct support for 22 of 43 patterns, Asbru 20, GLIF 17, and EON 11. All four directly support basic control-flow patterns, cancellation patterns, and some advance branching and synchronization patterns. None support multiple instances patterns. They offer varying levels of support for synchronizing merge patterns and state-based patterns. Some support a few scenarios not covered by the 43 control-flow patterns. CIG modeling languages are remarkably close to traditional workflow languages from the control-flow perspective, but cover many fewer workflow patterns. CIG languages offer some flexibility that supports modeling of complex decisions and provide ways for modeling some decisions not covered by workflow management systems. Workflow management systems may be suitable for clinical guideline applications.

Computational Modeling of Inflammation and Wound Healing

PubMed Central

Ziraldo, Cordelia; Mi, Qi; An, Gary; Vodovotz, Yoram

2013-01-01

Objective Inflammation is both central to proper wound healing and a key driver of chronic tissue injury via a positive-feedback loop incited by incidental cell damage. We seek to derive actionable insights into the role of inflammation in wound healing in order to improve outcomes for individual patients. Approach To date, dynamic computational models have been used to study the time evolution of inflammation in wound healing. Emerging clinical data on histo-pathological and macroscopic images of evolving wounds, as well as noninvasive measures of blood flow, suggested the need for tissue-realistic, agent-based, and hybrid mechanistic computational simulations of inflammation and wound healing. Innovation We developed a computational modeling system, Simple Platform for Agent-based Representation of Knowledge, to facilitate the construction of tissue-realistic models. Results A hybrid equation–agent-based model (ABM) of pressure ulcer formation in both spinal cord-injured and -uninjured patients was used to identify control points that reduce stress caused by tissue ischemia/reperfusion. An ABM of arterial restenosis revealed new dynamics of cell migration during neointimal hyperplasia that match histological features, but contradict the currently prevailing mechanistic hypothesis. ABMs of vocal fold inflammation were used to predict inflammatory trajectories in individuals, possibly allowing for personalized treatment. Conclusions The intertwined inflammatory and wound healing responses can be modeled computationally to make predictions in individuals, simulate therapies, and gain mechanistic insights. PMID:24527362

Context-Model-Based Instruction in Teaching EFL Writing: A Narrative Inquiry

ERIC Educational Resources Information Center

Lin, Zheng

2016-01-01

This study aims to re-story the provision of the context-model-based instruction in teaching EFL writing, focusing especially on students' development of the context model and learning to guide EFL writing with the context model. The research data have been collected from the audio recordings of the classroom instruction, the teacher-researcher's…

Computer-based creativity enhanced conceptual design model for non-routine design of mechanical systems

NASA Astrophysics Data System (ADS)

Li, Yutong; Wang, Yuxin; Duffy, Alex H. B.

2014-11-01

Computer-based conceptual design for routine design has made great strides, yet non-routine design has not been given due attention, and it is still poorly automated. Considering that the function-behavior-structure(FBS) model is widely used for modeling the conceptual design process, a computer-based creativity enhanced conceptual design model(CECD) for non-routine design of mechanical systems is presented. In the model, the leaf functions in the FBS model are decomposed into and represented with fine-grain basic operation actions(BOA), and the corresponding BOA set in the function domain is then constructed. Choosing building blocks from the database, and expressing their multiple functions with BOAs, the BOA set in the structure domain is formed. Through rule-based dynamic partition of the BOA set in the function domain, many variants of regenerated functional schemes are generated. For enhancing the capability to introduce new design variables into the conceptual design process, and dig out more innovative physical structure schemes, the indirect function-structure matching strategy based on reconstructing the combined structure schemes is adopted. By adjusting the tightness of the partition rules and the granularity of the divided BOA subsets, and making full use of the main function and secondary functions of each basic structure in the process of reconstructing of the physical structures, new design variables and variants are introduced into the physical structure scheme reconstructing process, and a great number of simpler physical structure schemes to accomplish the overall function organically are figured out. The creativity enhanced conceptual design model presented has a dominant capability in introducing new deign variables in function domain and digging out simpler physical structures to accomplish the overall function, therefore it can be utilized to solve non-routine conceptual design problem.

A pilot test of the acceptability and efficacy of narrative and non-narrative health education materials in a low health literacy population

PubMed Central

Moran, Meghan Bridgid; Frank, Lauren B.; Chatterjee, Joyee S.; Murphy, Sheila T.; Baezconde-Garbanati, Lourdes

2016-01-01

Although entertainment-education narratives are increasingly being used to communicate health information to a diversity of populations, there is limited evidence examining the use of narrative health education videos in low compared with adequate health literacy populations. There are also very few studies directly comparing narrative materials to more traditional, non-narrative materials. Because individuals with low health literacy are less likely than those with adequate health literacy to benefit from health communication interventions, it is especially important to develop an evidence base supporting the use of narrative health education materials in low literacy populations. This study extends knowledge on the use of narrative health education materials in populations with low health literacy by conducting a randomized trial comparing the acceptability and efficacy (knowledge gain) of two fact-equivalent films, one in a narrative and one in a non-narrative format, on individuals with adequate and low health literacy. This study finds that while both films were well-accepted and produced knowledge gains, the narrative film was more effective in this regard. This effect occurred regardless of health literacy level, indicating that narrative health communication materials are appropriate for individuals with low health literacy and do not exacerbate existing health disparities. These findings add to a small but growing body of evidence testing narrative health education materials in individuals with low health literacy, and provide new evidence supporting narrative, entertainment-education style video as a health communication tool to help reduce health literacy-related health disparities. PMID:27872657

Efficient calibration for imperfect computer models

DOE PAGES

Tuo, Rui; Wu, C. F. Jeff

2015-12-01

Many computer models contain unknown parameters which need to be estimated using physical observations. Furthermore, the calibration method based on Gaussian process models may lead to unreasonable estimate for imperfect computer models. In this work, we extend their study to calibration problems with stochastic physical data. We propose a novel method, called the L 2 calibration, and show its semiparametric efficiency. The conventional method of the ordinary least squares is also studied. Theoretical analysis shows that it is consistent but not efficient. Here, numerical examples show that the proposed method outperforms the existing ones.

Death narratives and cervical cancer: Impact of character death on narrative processing and HPV vaccination.

PubMed

Krakow, Melinda; Yale, Robert N; Perez Torres, Debora; Christy, Katheryn; Jensen, Jakob D

2017-12-01

Narratives hold promise as an effective public health message strategy for health behavior change, yet research on what types of narratives are most persuasive is still in the formative stage. Narrative persuasion research has identified 2 promising features of such messages that could influence behavior: whether characters live or die, and whether characters encounter key barriers. This study investigated the effects of these 2 narrative message features on young women's HPV vaccination intentions and examined mediating psychological processes of narrative persuasion in the context of cervical cancer messages. We manipulated these 2 features in a narrative HPV vaccine intervention targeted to a national sample of U.S. women 18-26 who had not initiated the vaccine (N = 247). Participants were randomized in a 2 × 2 between-subjects experiment. Compared to death narratives, survival narratives increased narrative believability and self-efficacy while lowering perceived barriers to vaccination. As features interacted, survival narratives featuring social barriers led to greater narrative transportation (absorption into the story) than other combinations. Moderated mediation analysis tested 10 theoretically derived mediators; transportation and risk severity mediated the narrative-intention relationship. Findings provide evidence for key psychological postulates of narrative persuasion theory. Results inform practical application for the construction of effective narrative message content in cervical cancer prevention campaigns for young women. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Enabling narrative pedagogy: inviting, waiting, and letting be.

PubMed

Ironside, Pamela M

2014-01-01

This article describes how teachers enable Narrative Pedagogy in their courses by explicating the Concernful Practice Inviting: Waiting and Letting Be. Narrative Pedagogy, a research-based, phenomenological approach to teaching and learning, extends conventional pedagogies and offers nursing faculty an alternative way of transforming their schools and courses. Using hermeneutic phenomenology, interview data collected over a 10-year period were analyzed by coding practical examples of teachers' efforts to enact Narrative Pedagogy. When Narrative Pedagogy is enacted, teachers and students focus on thinking and learning together about nursing phenomena and seek new understandings about how they may provide care in the myriad situations they encounter. Although the Concernful Practices co-occur, explicating inviting experiences can assist new teachers, and those seeking to extend their pedagogical literacy, by providing new understandings of how Narrative Pedagogy can be enacted.

Performing Narrative Medicine

ERIC Educational Resources Information Center

Langellier, Kristin M.

2009-01-01

In this article, the author weaves narrative medicine and performance together to consider what might it mean to call narrative medicine a performance. To name narrative medicine as performance is to recognize the texts and bodies, the stories and selves, that participate in its practice--patients' and physicians' embodied stories as well as the…

A numerical study of different projection-based model reduction techniques applied to computational homogenisation

NASA Astrophysics Data System (ADS)

Soldner, Dominic; Brands, Benjamin; Zabihyan, Reza; Steinmann, Paul; Mergheim, Julia

2017-10-01

Computing the macroscopic material response of a continuum body commonly involves the formulation of a phenomenological constitutive model. However, the response is mainly influenced by the heterogeneous microstructure. Computational homogenisation can be used to determine the constitutive behaviour on the macro-scale by solving a boundary value problem at the micro-scale for every so-called macroscopic material point within a nested solution scheme. Hence, this procedure requires the repeated solution of similar microscopic boundary value problems. To reduce the computational cost, model order reduction techniques can be applied. An important aspect thereby is the robustness of the obtained reduced model. Within this study reduced-order modelling (ROM) for the geometrically nonlinear case using hyperelastic materials is applied for the boundary value problem on the micro-scale. This involves the Proper Orthogonal Decomposition (POD) for the primary unknown and hyper-reduction methods for the arising nonlinearity. Therein three methods for hyper-reduction, differing in how the nonlinearity is approximated and the subsequent projection, are compared in terms of accuracy and robustness. Introducing interpolation or Gappy-POD based approximations may not preserve the symmetry of the system tangent, rendering the widely used Galerkin projection sub-optimal. Hence, a different projection related to a Gauss-Newton scheme (Gauss-Newton with Approximated Tensors- GNAT) is favoured to obtain an optimal projection and a robust reduced model.

Modeling of Tool-Tissue Interactions for Computer-Based Surgical Simulation: A Literature Review

PubMed Central

Misra, Sarthak; Ramesh, K. T.; Okamura, Allison M.

2009-01-01

Surgical simulators present a safe and potentially effective method for surgical training, and can also be used in robot-assisted surgery for pre- and intra-operative planning. Accurate modeling of the interaction between surgical instruments and organs has been recognized as a key requirement in the development of high-fidelity surgical simulators. Researchers have attempted to model tool-tissue interactions in a wide variety of ways, which can be broadly classified as (1) linear elasticity-based, (2) nonlinear (hyperelastic) elasticity-based finite element (FE) methods, and (3) other techniques that not based on FE methods or continuum mechanics. Realistic modeling of organ deformation requires populating the model with real tissue data (which are difficult to acquire in vivo) and simulating organ response in real time (which is computationally expensive). Further, it is challenging to account for connective tissue supporting the organ, friction, and topological changes resulting from tool-tissue interactions during invasive surgical procedures. Overcoming such obstacles will not only help us to model tool-tissue interactions in real time, but also enable realistic force feedback to the user during surgical simulation. This review paper classifies the existing research on tool-tissue interactions for surgical simulators specifically based on the modeling techniques employed and the kind of surgical operation being simulated, in order to inform and motivate future research on improved tool-tissue interaction models. PMID:20119508

Action starring narratives and events: Structure and inference in visual narrative comprehension

PubMed Central

Cohn, Neil; Wittenberg, Eva

2015-01-01

Studies of discourse have long placed focus on the inference generated by information that is not overtly expressed, and theories of visual narrative comprehension similarly focused on the inference generated between juxtaposed panels. Within the visual language of comics, star-shaped “flashes” commonly signify impacts, but can be enlarged to the size of a whole panel that can omit all other representational information. These “action star” panels depict a narrative culmination (a “Peak”), but have content which readers must infer, thereby posing a challenge to theories of inference generation in visual narratives that focus only on the semantic changes between juxtaposed images. This paper shows that action stars demand more inference than depicted events, and that they are more coherent in narrative sequences than scrambled sequences (Experiment 1). In addition, action stars play a felicitous narrative role in the sequence (Experiment 2). Together, these results suggest that visual narratives use conventionalized depictions that demand the generation of inferences while retaining narrative coherence of a visual sequence. PMID:26709362

Computer-Based Resource Accounting Model for Automobile Technology Impact Assessment

DOT National Transportation Integrated Search

1976-10-01

A computer-implemented resource accounting model has been developed for assessing resource impacts of future automobile technology options. The resources tracked are materials, energy, capital, and labor. The model has been used in support of the Int...

The role of conviction and narrative in decision-making under radical uncertainty.

PubMed

Tuckett, David; Nikolic, Milena

2017-08-01

We propose conviction narrative theory (CNT) to broaden decision-making theory in order to better understand and analyse how subjectively means-end rational actors cope in contexts in which the traditional assumptions in decision-making models fail to hold. Conviction narratives enable actors to draw on their beliefs, causal models, and rules of thumb to identify opportunities worth acting on, to simulate the future outcome of their actions, and to feel sufficiently convinced to act. The framework focuses on how narrative and emotion combine to allow actors to deliberate and to select actions that they think will produce the outcomes they desire. It specifies connections between particular emotions and deliberative thought, hypothesising that approach and avoidance emotions evoked during narrative simulation play a crucial role. Two mental states, Divided and Integrated, in which narratives can be formed or updated, are introduced and used to explain some familiar problems that traditional models cannot.

The role of conviction and narrative in decision-making under radical uncertainty

PubMed Central

Tuckett, David; Nikolic, Milena

2017-01-01

We propose conviction narrative theory (CNT) to broaden decision-making theory in order to better understand and analyse how subjectively means–end rational actors cope in contexts in which the traditional assumptions in decision-making models fail to hold. Conviction narratives enable actors to draw on their beliefs, causal models, and rules of thumb to identify opportunities worth acting on, to simulate the future outcome of their actions, and to feel sufficiently convinced to act. The framework focuses on how narrative and emotion combine to allow actors to deliberate and to select actions that they think will produce the outcomes they desire. It specifies connections between particular emotions and deliberative thought, hypothesising that approach and avoidance emotions evoked during narrative simulation play a crucial role. Two mental states, Divided and Integrated, in which narratives can be formed or updated, are introduced and used to explain some familiar problems that traditional models cannot. PMID:28804217

A Computational Model of Reasoning from the Clinical Literature

PubMed Central

Rennels, Glenn D.

1986-01-01

This paper explores the premise that a formalized representation of empirical studies can play a central role in computer-based decision support. The specific motivations underlying this research include the following propositions: 1. Reasoning from experimental evidence contained in the clinical literature is central to the decisions physicians make in patient care. 2. A computational model, based upon a declarative representation for published reports of clinical studies, can drive a computer program that selectively tailors knowledge of the clinical literature as it is applied to a particular case. 3. The development of such a computational model is an important first step toward filling a void in computer-based decision support systems. Furthermore, the model may help us better understand the general principles of reasoning from experimental evidence both in medicine and other domains. Roundsman is a developmental computer system which draws upon structured representations of the clinical literature in order to critique plans for the management of primary breast cancer. Roundsman is able to produce patient-specific analyses of breast cancer management options based on the 24 clinical studies currently encoded in its knowledge base. The Roundsman system is a first step in exploring how the computer can help to bring a critical analysis of the relevant literature to the physician, structured around a particular patient and treatment decision.

The Use of Podcasts to Enhance Narrative Writing Skills

ERIC Educational Resources Information Center

Qaddour, Kinana

2017-01-01

This activity uses podcasts to model narrative writing techniques. The challenges students face when exercising narrative writing skills are unique when compared to those of persuasive and expository writing; my students have repeatedly expressed their qualms with articulating experiences that engage their audience. Although students have…

Role of Narrative Perspective and Modality in the Persuasiveness of Public Service Advertisements Promoting HPV Vaccination.

PubMed

Nan, Xiaoli; Futerfas, Michelle; Ma, Zexin

2017-03-01

In the context of public service advertisements promoting human papillomavirus (HPV) vaccination, the current research examines 1) the relative persuasiveness of narrative vs. non-narrative messages and 2) the influence of narrative perspective (first- vs. third-person) and modality (text-based vs. audio-based) on message effectiveness. Results of a controlled experiment (N = 121) suggested that both a non-narrative message and a first-person narrative message led to greater perceived risk of getting HPV than a third-person narrative message. There was no difference in risk perception between the non-narrative and first-person narrative conditions. These findings were confined to the text-based condition, however. When the messages were audio-based, no differential message effects were detected. The analysis also provided partial evidence for an indirect effect of narrative perspective on intentions to vaccinate against HPV through HPV risk perception. Theoretical and practical implications of the findings are discussed.

Toward a Computational Model of Tutoring.

ERIC Educational Resources Information Center

Woolf, Beverly Park

1992-01-01

Discusses the integration of instructional science and computer science. Topics addressed include motivation for building knowledge-based systems; instructional design issues, including cognitive models, representing student intentions, and student models and error diagnosis; representing tutoring knowledge; building a tutoring system, including…

From Lévy to Brownian: a computational model based on biological fluctuation.

PubMed

Nurzaman, Surya G; Matsumoto, Yoshio; Nakamura, Yutaka; Shirai, Kazumichi; Koizumi, Satoshi; Ishiguro, Hiroshi

2011-02-03

Theoretical studies predict that Lévy walks maximizes the chance of encountering randomly distributed targets with a low density, but Brownian walks is favorable inside a patch of targets with high density. Recently, experimental data reports that some animals indeed show a Lévy and Brownian walk movement patterns when forage for foods in areas with low and high density. This paper presents a simple, Gaussian-noise utilizing computational model that can realize such behavior. We extend Lévy walks model of one of the simplest creature, Escherichia coli, based on biological fluctuation framework. We build a simulation of a simple, generic animal to observe whether Lévy or Brownian walks will be performed properly depends on the target density, and investigate the emergent behavior in a commonly faced patchy environment where the density alternates. Based on the model, animal behavior of choosing Lévy or Brownian walk movement patterns based on the target density is able to be generated, without changing the essence of the stochastic property in Escherichia coli physiological mechanism as explained by related researches. The emergent behavior and its benefits in a patchy environment are also discussed. The model provides a framework for further investigation on the role of internal noise in realizing adaptive and efficient foraging behavior.

A narrative review of undergraduate peer-based healthcare ethics teaching.

PubMed

Hindmarch, Thomas; Allikmets, Silvia; Knights, Felicity

2015-12-12

This study explores the literature in establishing the value of undergraduate peer-based healthcare ethics teaching as an educational methodology. A narrative review of the literature concerning peer-based ethics teaching was conducted. MEDLINE, EMBASE, CINAHL, SCOPUS databases, and the Cochrane Library, were systematically searched for studies of peer-based ethics or professionalism teaching. Selected studies related peer-based teaching to ethics education outcomes. Ten publications were identified. Selected studies were varied in their chosen intervention methodology and analysis. Collectively, the identified studies suggest peer-based ethics education is an effective and valued educational methodology in training healthcare professionals. One paper suggests peer-based ethics teaching has advantages over traditional didactic methods. Peer-based ethics teaching also receives positive feedback from student participants. However, the limited literature base demonstrates a clear need for more evaluation of this pedagogy. The current literature base suggests that undergraduate peer based healthcare ethics teaching is valuable in terms of efficacy and student satisfaction. We conclude that the medical community should invest in further study in order to capitalise upon the potential of peer-based ethics teaching in undergraduate healthcare education.

A narrative review of undergraduate peer-based healthcare ethics teaching

PubMed Central

Allikmets, Silvia; Knights, Felicity

2015-01-01

Objectives This study explores the literature in establishing the value of undergraduate peer-based healthcare ethics teaching as an educational methodology. Methods A narrative review of the literature concerning peer-based ethics teaching was conducted. MEDLINE, EMBASE, CINAHL, SCOPUS databases, and the Cochrane Library, were systematically searched for studies of peer-based ethics or professionalism teaching. Selected studies related peer-based teaching to ethics education outcomes. Results Ten publications were identified. Selected studies were varied in their chosen intervention methodology and analysis. Collectively, the identified studies suggest peer-based ethics education is an effective and valued educational methodology in training healthcare professionals. One paper suggests peer-based ethics teaching has advantages over traditional didactic methods. Peer-based ethics teaching also receives positive feedback from student participants. However, the limited literature base demonstrates a clear need for more evaluation of this pedagogy. Conclusions The current literature base suggests that undergraduate peer based healthcare ethics teaching is valuable in terms of efficacy and student satisfaction. We conclude that the medical community should invest in further study in order to capitalise upon the potential of peer-based ethics teaching in undergraduate healthcare education. PMID:26668050

Agent-based computational models to explore diffusion of medical innovations among cardiologists.

PubMed

Borracci, Raul A; Giorgi, Mariano A

2018-04-01

Diffusion of medical innovations among physicians rests on a set of theoretical assumptions, including learning and decision-making under uncertainty, social-normative pressures, medical expert knowledge, competitive concerns, network performance effects, professional autonomy or individualism and scientific evidence. The aim of this study was to develop and test four real data-based, agent-based computational models (ABM) to qualitatively and quantitatively explore the factors associated with diffusion and application of innovations among cardiologists. Four ABM were developed to study diffusion and application of medical innovations among cardiologists, considering physicians' network connections, leaders' opinions, "adopters' categories", physicians' autonomy, scientific evidence, patients' pressure, affordability for the end-user population, and promotion from companies. Simulations demonstrated that social imitation among local cardiologists was sufficient for innovation diffusion, as long as opinion leaders did not act as detractors of the innovation. Even in the absence of full scientific evidence to support innovation, up to one-fifth of cardiologists could accept it when local leaders acted as promoters. Patients' pressure showed a large effect size (Cohen's d > 1.2) on the proportion of cardiologists applying an innovation. Two qualitative patterns (speckled and granular) appeared associated to traditional Gompertz and sigmoid cumulative distributions. These computational models provided a semiquantitative insight on the emergent collective behavior of a physician population facing the acceptance or refusal of medical innovations. Inclusion in the models of factors related to patients' pressure and accesibility to medical coverage revealed the contrast between accepting and effectively adopting a new product or technology for population health care. Copyright © 2018 Elsevier B.V. All rights reserved.

Model implementation for dynamic computation of system cost

NASA Astrophysics Data System (ADS)

Levri, J.; Vaccari, D.

The Advanced Life Support (ALS) Program metric is the ratio of the equivalent system mass (ESM) of a mission based on International Space Station (ISS) technology to the ESM of that same mission based on ALS technology. ESM is a mission cost analog that converts the volume, power, cooling and crewtime requirements of a mission into mass units to compute an estimate of the life support system emplacement cost. Traditionally, ESM has been computed statically, using nominal values for system sizing. However, computation of ESM with static, nominal sizing estimates cannot capture the peak sizing requirements driven by system dynamics. In this paper, a dynamic model for a near-term Mars mission is described. The model is implemented in Matlab/Simulink' for the purpose of dynamically computing ESM. This paper provides a general overview of the crew, food, biomass, waste, water and air blocks in the Simulink' model. Dynamic simulations of the life support system track mass flow, volume and crewtime needs, as well as power and cooling requirement profiles. The mission's ESM is computed, based upon simulation responses. Ultimately, computed ESM values for various system architectures will feed into an optimization search (non-derivative) algorithm to predict parameter combinations that result in reduced objective function values.

Reciprocity in computer-human interaction: source-based, norm-based, and affect-based explanations.

PubMed

Lee, Seungcheol Austin; Liang, Yuhua Jake

2015-04-01

Individuals often apply social rules when they interact with computers, and this is known as the Computers Are Social Actors (CASA) effect. Following previous work, one approach to understand the mechanism responsible for CASA is to utilize computer agents and have the agents attempt to gain human compliance (e.g., completing a pattern recognition task). The current study focuses on three key factors frequently cited to influence traditional notions of compliance: evaluations toward the source (competence and warmth), normative influence (reciprocity), and affective influence (mood). Structural equation modeling assessed the effects of these factors on human compliance with computer request. The final model shows that norm-based influence (reciprocity) increased the likelihood of compliance, while evaluations toward the computer agent did not significantly influence compliance.

Computational Model-Based Prediction of Human Episodic Memory Performance Based on Eye Movements

NASA Astrophysics Data System (ADS)

Sato, Naoyuki; Yamaguchi, Yoko

Subjects' episodic memory performance is not simply reflected by eye movements. We use a ‘theta phase coding’ model of the hippocampus to predict subjects' memory performance from their eye movements. Results demonstrate the ability of the model to predict subjects' memory performance. These studies provide a novel approach to computational modeling in the human-machine interface.

Systemic therapy and attachment narratives: Attachment Narrative Therapy.

PubMed

Dallos, Rudi; Vetere, Arlene

2014-10-01

This article outlines an integration of attachment theory with narrative theory and systemic theory and practice: Attachment Narrative Therapy (ANT). This integration offers a more powerful explanatory formulation of the development and maintenance of human distress in relationships, families and communities, and gives direction to psychotherapeutic intervention. © The Author(s) 2014.

Linking Serious Game Narratives with Pedagogical Theories and Pedagogical Design Strategies

ERIC Educational Resources Information Center

De Troyer, Olga; Van Broeckhoven, Frederik; Vlieghe, Joachim

2017-01-01

Narrative-based serious games present pedagogical content and interventions through an interactive narrative. To ensure effective learning in such kind of serious games, designers are not only faced with the challenge of creating a compelling narrative, but also with the additional challenge of incorporating suitable pedagogical strategies.…

Cellular automata-based modelling and simulation of biofilm structure on multi-core computers.

PubMed

Skoneczny, Szymon

2015-01-01

The article presents a mathematical model of biofilm growth for aerobic biodegradation of a toxic carbonaceous substrate. Modelling of biofilm growth has fundamental significance in numerous processes of biotechnology and mathematical modelling of bioreactors. The process following double-substrate kinetics with substrate inhibition proceeding in a biofilm has not been modelled so far by means of cellular automata. Each process in the model proposed, i.e. diffusion of substrates, uptake of substrates, growth and decay of microorganisms and biofilm detachment, is simulated in a discrete manner. It was shown that for flat biofilm of constant thickness, the results of the presented model agree with those of a continuous model. The primary outcome of the study was to propose a mathematical model of biofilm growth; however a considerable amount of focus was also placed on the development of efficient algorithms for its solution. Two parallel algorithms were created, differing in the way computations are distributed. Computer programs were created using OpenMP Application Programming Interface for C++ programming language. Simulations of biofilm growth were performed on three high-performance computers. Speed-up coefficients of computer programs were compared. Both algorithms enabled a significant reduction of computation time. It is important, inter alia, in modelling and simulation of bioreactor dynamics.

IVUS-Based Computational Modeling and Planar Biaxial Artery Material Properties for Human Coronary Plaque Vulnerability Assessment

PubMed Central

Liu, Haofei; Cai, Mingchao; Yang, Chun; Zheng, Jie; Bach, Richard; Kural, Mehmet H.; Billiar, Kristen L.; Muccigrosso, David; Lu, Dongsi; Tang, Dalin

2012-01-01

Image-based computational modeling has been introduced for vulnerable atherosclerotic plaques to identify critical mechanical conditions which may be used for better plaque assessment and rupture predictions. In vivo patient-specific coronary plaque models are lagging due to limitations on non-invasive image resolution, flow data, and vessel material properties. A framework is proposed to combine intravascular ultrasound (IVUS) imaging, biaxial mechanical testing and computational modeling with fluid-structure interactions and anisotropic material properties to acquire better and more complete plaque data and make more accurate plaque vulnerability assessment and predictions. Impact of pre-shrink-stretch process, vessel curvature and high blood pressure on stress, strain, flow velocity and flow maximum principal shear stress was investigated. PMID:22428362

What are narratives good for?

PubMed

Beatty, John

2016-08-01

Narratives may be easy to come by, but not everything is worth narrating. What merits a narrative? Here, I follow the lead of narratologists and literary theorists, and focus on one particular proposal concerning the elements of a story that make it narrative-worthy. These elements correspond to features of the natural world addressed by the historical sciences, where narratives figure so prominently. What matters is contingency. Narratives are especially good for representing contingency and accounting for contingent outcomes. This will be squared with a common view that narratives leave no room for chance. On the contrary, I will argue, tracing one path through a maze of alternative possibilities, and alluding to those possibilities along the way, is what a narrative does particularly well. Copyright © 2016 Elsevier Ltd. All rights reserved.

Manipulating the Geometric Computer-aided Design of the Operational Requirements-based Casualty Assessment Model within BRL-CAD

DTIC Science & Technology

2018-03-30

ARL-TR-8336 ● MAR 2018 US Army Research Laboratory Manipulating the Geometric Computer-aided Design of the Operational...so designated by other authorized documents. Citation of manufacturer’s or trade names does not constitute an official endorsement or approval of...Army Research Laboratory Manipulating the Geometric Computer-aided Design of the Operational Requirements-based Casualty Assessment Model within

"mysterium Cosmographicum", for Orchestra, Narrator/actor, and Computer Music on Tape. (with Original Composition)

NASA Astrophysics Data System (ADS)

Keefe, Robert Michael

Mysterium Cosmographicum is a musical chronicle of an astronomy treatise by the German astronomer Johannes Kepler (1571-1630). Kepler's Mysterium Cosmographicum (Tubingen, 1596), or "Secret of the Universe," was a means by which he justified the existence of the six planets discovered during his lifetime. Kepler, through flawless a priori reasoning, goes to great lengths to explain that the reason there are six and only six planets (Mercury, Venus, Earth, Mars, Jupiter, and Saturn) is because God had placed one of the five regular solids (tetrahedron, cube, octa-, dodeca-, and icosahedron) around each orbiting body. Needless to say, the publication was not very successful, nor did it gain much comment from Kepler's peers, Galileo Galilei (1564-1642) and Tycho Brahe (1546-1601). But hidden within the Mysterium Cosmographicum, almost like a new planet waiting to be discovered, is one of Kepler's three laws of planetary motion, a law that held true for planets discovered long after Kepler's lifetime. Mysterium Cosmographicum is a monologue with music in three parts for orchestra, narrator/actor, and computer music on tape. All musical data structures are generated via an interactive Pascal computer program that computes latitudinal and longitudinal coordinates for each of the nine planets as seen from a fixed point on Earth for any given time frame. These coordinates are then mapped onto selected musical parameters as determined by the composer. Whenever Kepler reads from his treatise or from a lecture or correspondence, the monologue is supported by orchestral planetary data generated from the exact place, date, and time of the treatise, lecture, or correspondence. To the best of my knowledge, Mysterium Cosmographicum is the first composition ever written that employs planetary data as a supporting chronology to action and monologue.

Storytelling/narrative theory to address health communication with minority populations.

PubMed

Lee, Haeok; Fawcett, Jacqueline; DeMarco, Rosanna

2016-05-01

To explain the development and application of storytelling/narrative theory in health disparities intervention research as a way to promote health communication and behavior change among racial, ethnic, and minority populations. The proposed storytelling theory helps explain that storytelling affects changes in attitude and health behavior of the viewer through realism, identification, and transportation. The proposed storytelling/narrative theory can be a guide to develop culturally grounded narrative interventions that have the ability to connect with hard-to-reach populations. Narrative communication is context-dependent because it derives meaning from the surrounding situation and provides situation-based stories that are a pathway to processing story content. Although storytelling is grounded in nursing practice and education, it is underutilized in nursing interventional research. Future efforts are needed to extend theory-based narrative intervention studies designed to change attitude and behaviors that will reduce health disparities among minorities. Copyright © 2015 Elsevier Inc. All rights reserved.

The Importance Of Integrating Narrative Into Health Care Decision Making.

PubMed

Dohan, Daniel; Garrett, Sarah B; Rendle, Katharine A; Halley, Meghan; Abramson, Corey

2016-04-01

When making health care decisions, patients and consumers use data but also gather stories from family and friends. When advising patients, clinicians consult the medical evidence but also use professional judgment. These stories and judgments, as well as other forms of narrative, shape decision making but remain poorly understood. Furthermore, qualitative research methods to examine narrative are rarely included in health science research. We illustrate how narratives shape decision making and explain why it is difficult but necessary to integrate qualitative research on narrative into the health sciences. We draw on social-scientific insights on rigorous qualitative research and our ongoing studies of decision making by patients with cancer, and we describe new tools and approaches that link qualitative research findings with the predominantly quantitative health science scholarship. Finally, we highlight the benefits of more fully integrating qualitative research and narrative analysis into the medical evidence base and into evidence-based medical practice. Project HOPE—The People-to-People Health Foundation, Inc.

Reduced-Order Modeling: New Approaches for Computational Physics

NASA Technical Reports Server (NTRS)

Beran, Philip S.; Silva, Walter A.

2001-01-01

In this paper, we review the development of new reduced-order modeling techniques and discuss their applicability to various problems in computational physics. Emphasis is given to methods ba'sed on Volterra series representations and the proper orthogonal decomposition. Results are reported for different nonlinear systems to provide clear examples of the construction and use of reduced-order models, particularly in the multi-disciplinary field of computational aeroelasticity. Unsteady aerodynamic and aeroelastic behaviors of two- dimensional and three-dimensional geometries are described. Large increases in computational efficiency are obtained through the use of reduced-order models, thereby justifying the initial computational expense of constructing these models and inotivatim,- their use for multi-disciplinary design analysis.

BCM: toolkit for Bayesian analysis of Computational Models using samplers.

PubMed

Thijssen, Bram; Dijkstra, Tjeerd M H; Heskes, Tom; Wessels, Lodewyk F A

2016-10-21

Computational models in biology are characterized by a large degree of uncertainty. This uncertainty can be analyzed with Bayesian statistics, however, the sampling algorithms that are frequently used for calculating Bayesian statistical estimates are computationally demanding, and each algorithm has unique advantages and disadvantages. It is typically unclear, before starting an analysis, which algorithm will perform well on a given computational model. We present BCM, a toolkit for the Bayesian analysis of Computational Models using samplers. It provides efficient, multithreaded implementations of eleven algorithms for sampling from posterior probability distributions and for calculating marginal likelihoods. BCM includes tools to simplify the process of model specification and scripts for visualizing the results. The flexible architecture allows it to be used on diverse types of biological computational models. In an example inference task using a model of the cell cycle based on ordinary differential equations, BCM is significantly more efficient than existing software packages, allowing more challenging inference problems to be solved. BCM represents an efficient one-stop-shop for computational modelers wishing to use sampler-based Bayesian statistics.

Quantum Vertex Model for Reversible Classical Computing

NASA Astrophysics Data System (ADS)

Chamon, Claudio; Mucciolo, Eduardo; Ruckenstein, Andrei; Yang, Zhicheng

We present a planar vertex model that encodes the result of a universal reversible classical computation in its ground state. The approach involves Boolean variables (spins) placed on links of a two-dimensional lattice, with vertices representing logic gates. Large short-ranged interactions between at most two spins implement the operation of each gate. The lattice is anisotropic with one direction corresponding to computational time, and with transverse boundaries storing the computation's input and output. The model displays no finite temperature phase transitions, including no glass transitions, independent of circuit. The computational complexity is encoded in the scaling of the relaxation rate into the ground state with the system size. We use thermal annealing and a novel and more efficient heuristic \\x9Dannealing with learning to study various computational problems. To explore faster relaxation routes, we construct an explicit mapping of the vertex model into the Chimera architecture of the D-Wave machine, initiating a novel approach to reversible classical computation based on quantum annealing.

Physics Model-Based Scatter Correction in Multi-Source Interior Computed Tomography.

PubMed

Gong, Hao; Li, Bin; Jia, Xun; Cao, Guohua

2018-02-01

Multi-source interior computed tomography (CT) has a great potential to provide ultra-fast and organ-oriented imaging at low radiation dose. However, X-ray cross scattering from multiple simultaneously activated X-ray imaging chains compromises imaging quality. Previously, we published two hardware-based scatter correction methods for multi-source interior CT. Here, we propose a software-based scatter correction method, with the benefit of no need for hardware modifications. The new method is based on a physics model and an iterative framework. The physics model was derived analytically, and was used to calculate X-ray scattering signals in both forward direction and cross directions in multi-source interior CT. The physics model was integrated to an iterative scatter correction framework to reduce scatter artifacts. The method was applied to phantom data from both Monte Carlo simulations and physical experimentation that were designed to emulate the image acquisition in a multi-source interior CT architecture recently proposed by our team. The proposed scatter correction method reduced scatter artifacts significantly, even with only one iteration. Within a few iterations, the reconstructed images fast converged toward the "scatter-free" reference images. After applying the scatter correction method, the maximum CT number error at the region-of-interests (ROIs) was reduced to 46 HU in numerical phantom dataset and 48 HU in physical phantom dataset respectively, and the contrast-noise-ratio at those ROIs increased by up to 44.3% and up to 19.7%, respectively. The proposed physics model-based iterative scatter correction method could be useful for scatter correction in dual-source or multi-source CT.

Becoming Theatrical: Performing Narrative Research, Staging Visual Representation

ERIC Educational Resources Information Center

Valle, Jan W.; Connor, David J.

2012-01-01

This article describes a collaborative project among the author of a book about mothers and special education (based on a collection of oral narratives of mothers who represent diverse generations, races, and social classes), a playwright, and an artist. Together, they created a theatrical and visual staging of the author's narrative research. The…

Narrative performance of gifted African American school-aged children from low-income backgrounds.

PubMed

Mills, Monique T

2015-02-01

This study investigated classroom differences in the narrative performance of school-age African American English (AAE)-speaking children in gifted and general education classrooms. Forty-three children, Grades 2-5, each generated fictional narratives in response to the book Frog, Where Are You? (Mayer, 1969). Differences in performance on traditional narrative measures (total number of communication units [C-units], number of different words, and mean length of utterance in words) and on AAE production (dialect density measure) between children in gifted and general education classrooms were examined. There were no classroom-based differences in total number of C-units, number of different words, and mean length of utterance in words. Children in gifted education classrooms produced narratives with lower dialect density than did children in general educated classrooms. Direct logistic regression assessed whether narrative dialect density measure scores offered additional information about giftedness beyond scores on the Peabody Picture Vocabulary Test-Fourth Edition (Dunn & Dunn, 2007), a standard measure of language ability. Results indicated that a model with only Peabody Picture Vocabulary Test-Fourth Edition scores best discriminated children in the 2 classrooms. African American children across gifted and general education classrooms produce fictional narratives of similar length, lexical diversity, and syntax complexity. However, African American children in gifted education classrooms may produce lower rates of AAE and perform better on standard measures of vocabulary than those in general education classrooms.

Maintaining connections in children's grief narratives in popular film.

PubMed

Sedney, Mary Anne

2002-04-01

Children's grief narratives in popular films were examined for their portrayal of connection-maintaining strategies with the deceased. Comparisons were made between strategies found in actual parentally bereaved children and in child characters in films. Implications of these filmed grief narratives for models of grieving and for practice are discussed.

Parallelization of fine-scale computation in Agile Multiscale Modelling Methodology

NASA Astrophysics Data System (ADS)

Macioł, Piotr; Michalik, Kazimierz

2016-10-01

Nowadays, multiscale modelling of material behavior is an extensively developed area. An important obstacle against its wide application is high computational demands. Among others, the parallelization of multiscale computations is a promising solution. Heterogeneous multiscale models are good candidates for parallelization, since communication between sub-models is limited. In this paper, the possibility of parallelization of multiscale models based on Agile Multiscale Methodology framework is discussed. A sequential, FEM based macroscopic model has been combined with concurrently computed fine-scale models, employing a MatCalc thermodynamic simulator. The main issues, being investigated in this work are: (i) the speed-up of multiscale models with special focus on fine-scale computations and (ii) on decreasing the quality of computations enforced by parallel execution. Speed-up has been evaluated on the basis of Amdahl's law equations. The problem of `delay error', rising from the parallel execution of fine scale sub-models, controlled by the sequential macroscopic sub-model is discussed. Some technical aspects of combining third-party commercial modelling software with an in-house multiscale framework and a MPI library are also discussed.

Narrative in Exergames: Thoughts on Procedure, Mechanism, and Others

PubMed Central

2015-01-01

Abstract Narratives are stories with a beginning, middle, and end that provide information about the characters and plot. Exergames are videogames that require players to move or exercise. Narratives and exergames have seldom been examined together. Based on my review of the literature, there are five potential opportunities narratives could bring to exergames: Enhanced engagement with characters and with the plot, increased motivation, repeated play sessions, and better behavioral consequence. However, the rewards offered by these possibilities may be offset by the challenges they pose. These challenges include the difficulty in fully integrating narratives into the gameplay, the players' limited information processing capacity, difficulty in measurement, the lack of full understanding of the player–character identification process, and the narrative saturation effects. Innovative research is needed to bridge the two potentially important domains. PMID:26181676

Narrating positive versus negative memories of illness: does narrating influence the emotional tone of memories?

PubMed

Fioretti, C; Smorti, A

2017-05-01

Psychoncological studies have recognised a reduced autobiographical memory in cancer patients, furthermore cognitive studies have found that narrative is an effective instrument to re-elaborate memories. However, it is still unclear whether narrating positive versus negative events can have a different impact on autobiographical memory. The present study aims to explore the emotional experience of autobiographical memory before and after having narrated negative or positive events related to the illness. Of 63 oncological patients, 35 were selected for the present study. Participants completed a Memory Fluency Task twice, before and after having selected and narrated a positive (PN group) or a negative (NN group) memory of illness. They also had to attribute one or more emotions to each memory and to the narrative. The number of emotions and the percentage of emotional tones in both narrated and non-narrated memories were assessed. Narrated memories were more emotionally re-elaborated than non-narrated ones. Negative group participants, more than positive group ones, decreased negative emotions and increased complex ones. Authors discuss these results claiming that narrating works as a rehearsal of autobiographical memories in oncological patients and narrating negative memories eases the emotional re-elaboration of illness. © 2016 John Wiley & Sons Ltd.

Verifiable fault tolerance in measurement-based quantum computation

NASA Astrophysics Data System (ADS)

Fujii, Keisuke; Hayashi, Masahito

2017-09-01

Quantum systems, in general, cannot be simulated efficiently by a classical computer, and hence are useful for solving certain mathematical problems and simulating quantum many-body systems. This also implies, unfortunately, that verification of the output of the quantum systems is not so trivial, since predicting the output is exponentially hard. As another problem, the quantum system is very delicate for noise and thus needs an error correction. Here, we propose a framework for verification of the output of fault-tolerant quantum computation in a measurement-based model. In contrast to existing analyses on fault tolerance, we do not assume any noise model on the resource state, but an arbitrary resource state is tested by using only single-qubit measurements to verify whether or not the output of measurement-based quantum computation on it is correct. Verifiability is equipped by a constant time repetition of the original measurement-based quantum computation in appropriate measurement bases. Since full characterization of quantum noise is exponentially hard for large-scale quantum computing systems, our framework provides an efficient way to practically verify the experimental quantum error correction.

Narratives About Mental Illnesses in China: The Voices of Generation Y.

PubMed

Tang, Lu; Bie, Bijie

2016-01-01

This study explores the cultured understanding of mental health and mental illnesses among members of Generation Y in China through a narrative approach. Five prominent narratives are identified through the analysis of stories about mental illnesses collected through semistructured interviews with college students. These five narratives feature the tragic genius, the psychotic criminal, the fragile victim, the antisocial recluse, and the homosexual. These narratives are gendered, in that women are the primary protagonists in the narrative about the fragile victim, while men are featured prominently in the narratives about the tragic genius, the psychotic criminal, and the antisocial recluse. Our study demonstrates that these narratives are based on, and will further reinforce, highly cultural-specific stereotypes and biases about mental illnesses in China. Theoretical and practical implications of this study are discussed.

Discourse on Narrative Research: The Construction Zone--Literary Elements in Narrative Research

ERIC Educational Resources Information Center

Coulter, Cathy A.; Smith, Mary Lee

2009-01-01

Narrative research has become part of the landscape of education inquiry, yet its theory and practice are still debated and evolving. This article addresses the construction of narratives using literary elements common to nonfiction and fiction writings. The authors discuss these elements and use four narratives to illustrate them. They address…

Narrative and emotion process in psychotherapy: an empirical test of the Narrative-Emotion Process Coding System (NEPCS).

PubMed

Boritz, Tali Z; Bryntwick, Emily; Angus, Lynne; Greenberg, Leslie S; Constantino, Michael J

2014-01-01

While the individual contributions of narrative and emotion processes to psychotherapy outcome have been the focus of recent interest in psychotherapy research literature, the empirical analysis of narrative and emotion integration has rarely been addressed. The Narrative-Emotion Processes Coding System (NEPCS) was developed to provide researchers with a systematic method for identifying specific narrative and emotion process markers, for application to therapy session videos. The present study examined the relationship between NEPCS-derived problem markers (same old storytelling, empty storytelling, unstoried emotion, abstract storytelling) and change markers (competing plotlines storytelling, inchoate storytelling, unexpected outcome storytelling, and discovery storytelling), and treatment outcome (recovered versus unchanged at therapy termination) and stage of therapy (early, middle, late) in brief emotion-focused (EFT), client-centred (CCT), and cognitive (CT) therapies for depression. Hierarchical linear modelling analyses demonstrated a significant Outcome effect for inchoate storytelling (p = .037) and discovery storytelling (p = .002), a Stage × Outcome effect for abstract storytelling (p = .05), and a Stage × Outcome × Treatment effect for competing plotlines storytelling (p = .001). There was also a significant Stage × Outcome effect for NEPCS problem markers (p = .007) and change markers (p = .03). The results provide preliminary support for the importance of assessing the contribution of narrative-emotion processes to efficacious treatment outcomes in EFT, CCT, and CT treatments of depression.

Documentary Evidence and the Construction of Narratives in Legal and Historical Contexts.

PubMed

Jones, Gwynneth C D

2015-02-01

Based on her experiences as an expert witness in Canadian litigation related to Aboriginal peoples, the author shares some personal reflections on the use of the written record as "evidence" in a legal context. As end users in a litigation context will be constructing their own narratives, a historian can add value in the courtroom by sharing skills in analyzing and providing context for written materials as well as providing a narrative based on their content. This process of simultaneously constructing and deconstructing a narrative can support the legitimacy of multiple narratives and provide space for evidence of other types, particularly oral evidence.

On the usage of ultrasound computational models for decision making under ambiguity

NASA Astrophysics Data System (ADS)

Dib, Gerges; Sexton, Samuel; Prowant, Matthew; Crawford, Susan; Diaz, Aaron

2018-04-01

Computer modeling and simulation is becoming pervasive within the non-destructive evaluation (NDE) industry as a convenient tool for designing and assessing inspection techniques. This raises a pressing need for developing quantitative techniques for demonstrating the validity and applicability of the computational models. Computational models provide deterministic results based on deterministic and well-defined input, or stochastic results based on inputs defined by probability distributions. However, computational models cannot account for the effects of personnel, procedures, and equipment, resulting in ambiguity about the efficacy of inspections based on guidance from computational models only. In addition, ambiguity arises when model inputs, such as the representation of realistic cracks, cannot be defined deterministically, probabilistically, or by intervals. In this work, Pacific Northwest National Laboratory demonstrates the ability of computational models to represent field measurements under known variabilities, and quantify the differences using maximum amplitude and power spectrum density metrics. Sensitivity studies are also conducted to quantify the effects of different input parameters on the simulation results.

Scaling predictive modeling in drug development with cloud computing.

PubMed

Moghadam, Behrooz Torabi; Alvarsson, Jonathan; Holm, Marcus; Eklund, Martin; Carlsson, Lars; Spjuth, Ola

2015-01-26

Growing data sets with increased time for analysis is hampering predictive modeling in drug discovery. Model building can be carried out on high-performance computer clusters, but these can be expensive to purchase and maintain. We have evaluated ligand-based modeling on cloud computing resources where computations are parallelized and run on the Amazon Elastic Cloud. We trained models on open data sets of varying sizes for the end points logP and Ames mutagenicity and compare with model building parallelized on a traditional high-performance computing cluster. We show that while high-performance computing results in faster model building, the use of cloud computing resources is feasible for large data sets and scales well within cloud instances. An additional advantage of cloud computing is that the costs of predictive models can be easily quantified, and a choice can be made between speed and economy. The easy access to computational resources with no up-front investments makes cloud computing an attractive alternative for scientists, especially for those without access to a supercomputer, and our study shows that it enables cost-efficient modeling of large data sets on demand within reasonable time.

From Lévy to Brownian: A Computational Model Based on Biological Fluctuation

PubMed Central

Nurzaman, Surya G.; Matsumoto, Yoshio; Nakamura, Yutaka; Shirai, Kazumichi; Koizumi, Satoshi; Ishiguro, Hiroshi

2011-01-01

Background Theoretical studies predict that Lévy walks maximizes the chance of encountering randomly distributed targets with a low density, but Brownian walks is favorable inside a patch of targets with high density. Recently, experimental data reports that some animals indeed show a Lévy and Brownian walk movement patterns when forage for foods in areas with low and high density. This paper presents a simple, Gaussian-noise utilizing computational model that can realize such behavior. Methodology/Principal Findings We extend Lévy walks model of one of the simplest creature, Escherichia coli, based on biological fluctuation framework. We build a simulation of a simple, generic animal to observe whether Lévy or Brownian walks will be performed properly depends on the target density, and investigate the emergent behavior in a commonly faced patchy environment where the density alternates. Conclusions/Significance Based on the model, animal behavior of choosing Lévy or Brownian walk movement patterns based on the target density is able to be generated, without changing the essence of the stochastic property in Escherichia coli physiological mechanism as explained by related researches. The emergent behavior and its benefits in a patchy environment are also discussed. The model provides a framework for further investigation on the role of internal noise in realizing adaptive and efficient foraging behavior. PMID:21304911

A Contrast-Based Computational Model of Surprise and Its Applications.

PubMed

Macedo, Luis; Cardoso, Amílcar

2017-11-19

We review our work on a contrast-based computational model of surprise and its applications. The review is contextualized within related research from psychology, philosophy, and particularly artificial intelligence. Influenced by psychological theories of surprise, the model assumes that surprise-eliciting events initiate a series of cognitive processes that begin with the appraisal of the event as unexpected, continue with the interruption of ongoing activity and the focusing of attention on the unexpected event, and culminate in the analysis and evaluation of the event and the revision of beliefs. It is assumed that the intensity of surprise elicited by an event is a nonlinear function of the difference or contrast between the subjective probability of the event and that of the most probable alternative event (which is usually the expected event); and that the agent's behavior is partly controlled by actual and anticipated surprise. We describe applications of artificial agents that incorporate the proposed surprise model in three domains: the exploration of unknown environments, creativity, and intelligent transportation systems. These applications demonstrate the importance of surprise for decision making, active learning, creative reasoning, and selective attention. Copyright © 2017 Cognitive Science Society, Inc.

Transforming narratives into educational tools: the collaborative development of a transformative learning tool based on Nicaraguan adolescents' creative writing about intimate partner violence.

PubMed

Singleton, Robyn; Picado Araúz, María de la Paz; Trocin, Kathleen; Winskell, Kate

2017-01-01

The use of narrative has become increasingly popular in the public health, community development, and education fields. Via emotionally engaging plotlines with authentic, captivating characters, stories provide an opportunity for participants to be carried away imaginatively into the characters' world while connecting the story with their own lived experiences. Stories have been highlighted as valuable tools in transformative learning. However, little published literature exists demonstrating applications of stories in group-based transformative learning curricula. This paper describes the creation of a narrative-based transformative learning tool based on an analysis of Nicaraguan adolescents' meaning-making around intimate partner violence (IPV) in their creative narratives. In collaboration with a Nicaraguan organization, US researchers analyzed a sample of narratives ( n = 55; 16 male-authored, 39 female-authored) on IPV submitted to a 2014 scriptwriting competition by adolescents aged 15-19. The data were particularly timely in that they responded to a new law protecting victims of gender-based violence, Law 779, and contradicted social-conservative claims that the Law 779 destroys family unity. We incorporated results from this analysis into the creation of the transformative learning tool, separated into thematic sections. The tool's sections (which comprise one story and three corresponding activities) aim to facilitate critical reflection, interpersonal dialogue, and self- and collective efficacy for social action around the following themes derived from the analysis: IPV and social support; IPV and romantic love; masculinity; warning signs of IPV; and sexual abuse. As a collaboration between a public health research team based at a US university and a Nicaraguan community-based organization, it demonstrates the potential in the age of increasingly smooth electronic communication for novel community-university partnerships to facilitate the development of

Electrophysiological Correlates of Semantic Dissimilarity Reflect the Comprehension of Natural, Narrative Speech.

PubMed

Broderick, Michael P; Anderson, Andrew J; Di Liberto, Giovanni M; Crosse, Michael J; Lalor, Edmund C

2018-03-05

People routinely hear and understand speech at rates of 120-200 words per minute [1, 2]. Thus, speech comprehension must involve rapid, online neural mechanisms that process words' meanings in an approximately time-locked fashion. However, electrophysiological evidence for such time-locked processing has been lacking for continuous speech. Although valuable insights into semantic processing have been provided by the "N400 component" of the event-related potential [3-6], this literature has been dominated by paradigms using incongruous words within specially constructed sentences, with less emphasis on natural, narrative speech comprehension. Building on the discovery that cortical activity "tracks" the dynamics of running speech [7-9] and psycholinguistic work demonstrating [10-12] and modeling [13-15] how context impacts on word processing, we describe a new approach for deriving an electrophysiological correlate of natural speech comprehension. We used a computational model [16] to quantify the meaning carried by words based on how semantically dissimilar they were to their preceding context and then regressed this measure against electroencephalographic (EEG) data recorded from subjects as they listened to narrative speech. This produced a prominent negativity at a time lag of 200-600 ms on centro-parietal EEG channels, characteristics common to the N400. Applying this approach to EEG datasets involving time-reversed speech, cocktail party attention, and audiovisual speech-in-noise demonstrated that this response was very sensitive to whether or not subjects understood the speech they heard. These findings demonstrate that, when successfully comprehending natural speech, the human brain responds to the contextual semantic content of each word in a relatively time-locked fashion. Copyright © 2018 Elsevier Ltd. All rights reserved.

Inventing Memories: Returnees' Retrospective Narratives of Street Experience

ERIC Educational Resources Information Center

Choi, Jung-ah

2005-01-01

In this paper I focus on the narratives of youths who attended an alternative school after engaging in the street culture. Based on retrospective narrative stories I examine the ways in which returnees? returning decision stimulates reflections on their past experiences, both in mainstream schools as well as in the street, and the way in which the…

Characterizing the Pain Narratives of Parents of Youth with Chronic Pain

PubMed Central

Noel, Melanie; Beals-Erickson, Sarah E.; Law, Emily F.; Alberts, Nicole; Palermo, Tonya M.

2015-01-01

Objectives Questionnaire-based research has shown that parents exert a powerful influence on and are profoundly influenced by living with a child with chronic pain. Examination of parents' pain narratives through an observational lens offers an alternative approach to understanding the complexity of pediatric chronic pain; however, the narratives of parents of youth with chronic pain have been largely overlooked. The present study aimed to characterize the vulnerability- and resilience-based aspects of the pain narratives of parents of youth with chronic pain. Methods Pain narratives of 46 parents were recorded during the baseline session as part of two clinical trials evaluating a behavioral intervention for parents of youth with chronic pain. The narratives were coded for aspects of pain-related vulnerability and resilience. Results Using exploratory cluster analysis, two styles of parents’ pain narratives were identified. Distress narratives were characterized by more negative affect and an exclusively unresolved orientation towards the child’s diagnosis of chronic pain whereas resilience narratives were characterized by positive affect and a predominantly resolved orientation towards the child’s diagnosis. Preliminary support for the validity of these clusters was provided through our finding of differences between clusters in parental pain catastrophizing about child pain (helplessness). Discussion Findings highlight the multidimensional nature of parents’ experience of their child’s pain problem. Clinical implications in terms of assessment and treatment are discussed. PMID:26736026

Exploring outcomes and evaluation in narrative pedagogy: An integrative review.

PubMed

Brady, Destiny R; Asselin, Marilyn E

2016-10-01

To identify narrative pedagogy learning outcomes and evaluation methods used for pre-licensure nursing students. Recommend areas for expanding narrative pedagogy research. An integrative review using a modified version of Cooper's 1998 framework, as described by Whittemore and Knafl (2005). A computer-assisted search of the literature from 1995 to 2015 was performed using the search terms narrative pedagogy and nursing. Databases included the Cumulative Index to Nursing and Allied Health Literature, Academic Search Premier, Educational Resources Information Center, Educational Research Complete, Medline, PsychArticles, PsychINFO, and the Teacher Reference Center. Ancestry searches led to the inclusion of additional articles. Twenty-six texts met the criteria for full review and were evaluated for methodological rigor and relevance to the review aims. Nine articles achieved an acceptable quality score and were used for thematic analysis. Learning outcomes associated with narrative pedagogy were grouped into five themes: thinking, empowerment, interconnectedness, learning as a process of making meaning, and ethical/moral judgment. Multiple methods of evaluation are necessary to evaluate these learning outcomes. Narrative pedagogy may be a beneficial philosophical approach to teaching. However, at this time, there is insufficient evidence to recommend its universal adoption. It is too broad in its approach to reliably measure its effectiveness. Future research should examine the effectiveness of specific teaching strategies to promote desired learning outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computational Modeling of Tissue Self-Assembly

NASA Astrophysics Data System (ADS)

Neagu, Adrian; Kosztin, Ioan; Jakab, Karoly; Barz, Bogdan; Neagu, Monica; Jamison, Richard; Forgacs, Gabor

As a theoretical framework for understanding the self-assembly of living cells into tissues, Steinberg proposed the differential adhesion hypothesis (DAH) according to which a specific cell type possesses a specific adhesion apparatus that combined with cell motility leads to cell assemblies of various cell types in the lowest adhesive energy state. Experimental and theoretical efforts of four decades turned the DAH into a fundamental principle of developmental biology that has been validated both in vitro and in vivo. Based on computational models of cell sorting, we have developed a DAH-based lattice model for tissues in interaction with their environment and simulated biological self-assembly using the Monte Carlo method. The present brief review highlights results on specific morphogenetic processes with relevance to tissue engineering applications. Our own work is presented on the background of several decades of theoretical efforts aimed to model morphogenesis in living tissues. Simulations of systems involving about 105 cells have been performed on high-end personal computers with CPU times of the order of days. Studied processes include cell sorting, cell sheet formation, and the development of endothelialized tubes from rings made of spheroids of two randomly intermixed cell types, when the medium in the interior of the tube was different from the external one. We conclude by noting that computer simulations based on mathematical models of living tissues yield useful guidelines for laboratory work and can catalyze the emergence of innovative technologies in tissue engineering.

A Comparison of Computational Cognitive Models: Agent-Based Systems Versus Rule-Based Architectures

DTIC Science & Technology

2003-03-01

Java™ How To Program , Prentice Hall, 1999. Friedman-Hill, E., Jess, The Expert System Shell for the Java Platform, Sandia National Laboratories, 2001...transition from the descriptive NDM theory to a computational model raises several questions: Who is an experienced decision maker? How do you model the...progression from being a novice to an experienced decision maker? How does the model account for previous experiences? Are there situations where

Harnessing the Persuasive Power of Narrative: Science, Storytelling, and Movie Censorship, 1930-1968.

PubMed

Kirby, David A

2018-03-01

Argument As the deficit model's failure leaves scientists searching for more effective communicative approaches, science communication scholars have begun promoting narrative as a potent persuasive tool. Narratives can help the public make choices by setting out a scientific issue's contexts, establishing the stakes involved, and offering potential solutions. However, employing narrative for persuasion risks embracing the same top-down communication approach underlying deficit model thinking. This essay explores the parallels between movie censorship and the current use of narrative to influence public opinion by examining how the Hays Office and the Catholic Legion of Decency responded to science in movies. I argue that deploying narratives solely as public relations exercises demonstrates the same mistrust of audiences that provided the foundation of movie censorship. But the history of movie censorship reveals the dangers of using narrative to remove the public's agency and to coerce them towards a preferred position rather than fostering their ability to come to their own conclusions.

Understanding Emergency Care Delivery Through Computer Simulation Modeling.

PubMed

Laker, Lauren F; Torabi, Elham; France, Daniel J; Froehle, Craig M; Goldlust, Eric J; Hoot, Nathan R; Kasaie, Parastu; Lyons, Michael S; Barg-Walkow, Laura H; Ward, Michael J; Wears, Robert L

2018-02-01

In 2017, Academic Emergency Medicine convened a consensus conference entitled, "Catalyzing System Change through Health Care Simulation: Systems, Competency, and Outcomes." This article, a product of the breakout session on "understanding complex interactions through systems modeling," explores the role that computer simulation modeling can and should play in research and development of emergency care delivery systems. This article discusses areas central to the use of computer simulation modeling in emergency care research. The four central approaches to computer simulation modeling are described (Monte Carlo simulation, system dynamics modeling, discrete-event simulation, and agent-based simulation), along with problems amenable to their use and relevant examples to emergency care. Also discussed is an introduction to available software modeling platforms and how to explore their use for research, along with a research agenda for computer simulation modeling. Through this article, our goal is to enhance adoption of computer simulation, a set of methods that hold great promise in addressing emergency care organization and design challenges. © 2017 by the Society for Academic Emergency Medicine.

Discovering Event Structure in Continuous Narrative Perception and Memory.

PubMed

Baldassano, Christopher; Chen, Janice; Zadbood, Asieh; Pillow, Jonathan W; Hasson, Uri; Norman, Kenneth A

2017-08-02

During realistic, continuous perception, humans automatically segment experiences into discrete events. Using a novel model of cortical event dynamics, we investigate how cortical structures generate event representations during narrative perception and how these events are stored to and retrieved from memory. Our data-driven approach allows us to detect event boundaries as shifts between stable patterns of brain activity without relying on stimulus annotations and reveals a nested hierarchy from short events in sensory regions to long events in high-order areas (including angular gyrus and posterior medial cortex), which represent abstract, multimodal situation models. High-order event boundaries are coupled to increases in hippocampal activity, which predict pattern reinstatement during later free recall. These areas also show evidence of anticipatory reinstatement as subjects listen to a familiar narrative. Based on these results, we propose that brain activity is naturally structured into nested events, which form the basis of long-term memory representations. Copyright © 2017 Elsevier Inc. All rights reserved.

QPSO-Based Adaptive DNA Computing Algorithm

PubMed Central

Karakose, Mehmet; Cigdem, Ugur

2013-01-01

DNA (deoxyribonucleic acid) computing that is a new computation model based on DNA molecules for information storage has been increasingly used for optimization and data analysis in recent years. However, DNA computing algorithm has some limitations in terms of convergence speed, adaptability, and effectiveness. In this paper, a new approach for improvement of DNA computing is proposed. This new approach aims to perform DNA computing algorithm with adaptive parameters towards the desired goal using quantum-behaved particle swarm optimization (QPSO). Some contributions provided by the proposed QPSO based on adaptive DNA computing algorithm are as follows: (1) parameters of population size, crossover rate, maximum number of operations, enzyme and virus mutation rate, and fitness function of DNA computing algorithm are simultaneously tuned for adaptive process, (2) adaptive algorithm is performed using QPSO algorithm for goal-driven progress, faster operation, and flexibility in data, and (3) numerical realization of DNA computing algorithm with proposed approach is implemented in system identification. Two experiments with different systems were carried out to evaluate the performance of the proposed approach with comparative results. Experimental results obtained with Matlab and FPGA demonstrate ability to provide effective optimization, considerable convergence speed, and high accuracy according to DNA computing algorithm. PMID:23935409

Self-guaranteed measurement-based quantum computation

NASA Astrophysics Data System (ADS)

Hayashi, Masahito; Hajdušek, Michal

2018-05-01

In order to guarantee the output of a quantum computation, we usually assume that the component devices are trusted. However, when the total computation process is large, it is not easy to guarantee the whole system when we have scaling effects, unexpected noise, or unaccounted for correlations between several subsystems. If we do not trust the measurement basis or the prepared entangled state, we do need to be worried about such uncertainties. To this end, we propose a self-guaranteed protocol for verification of quantum computation under the scheme of measurement-based quantum computation where no prior-trusted devices (measurement basis or entangled state) are needed. The approach we present enables the implementation of verifiable quantum computation using the measurement-based model in the context of a particular instance of delegated quantum computation where the server prepares the initial computational resource and sends it to the client, who drives the computation by single-qubit measurements. Applying self-testing procedures, we are able to verify the initial resource as well as the operation of the quantum devices and hence the computation itself. The overhead of our protocol scales with the size of the initial resource state to the power of 4 times the natural logarithm of the initial state's size.

Computational neuroanatomy: ontology-based representation of neural components and connectivity

PubMed Central

Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

2009-01-01

Background A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. Results We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Conclusion Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future. PMID:19208191

Computational neuroanatomy: ontology-based representation of neural components and connectivity.

PubMed

Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

2009-02-05

A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future.

Narrative versus Non-narrative: The Role of Identification, Transportation and Emotion in Reducing Health Disparities

PubMed Central

Murphy, Sheila T.; Frank, Lauren B.; Chatterjee, Joyee S.; Baezconde-Garbanati, Lourdes

2013-01-01

This research empirically tests whether using a fictional narrative produces a greater impact on health-related knowledge, attitudes, and behavioral intention than presenting the identical information in a more traditional, nonfiction, non-narrative format. European American, Mexican American, and African American women (N = 758) were surveyed before and after viewing either a narrative or non-narrative cervical cancer-related film. The narrative was more effective in increasing cervical cancer-related knowledge and attitudes. Moreover, in response to the narrative featuring Latinas, Mexican Americans were most transported, identified most with the characters, and experienced the strongest emotions. Regressions revealed that transportation, identification with specific characters, and emotion each contributed to shifts in knowledge, attitudes, and behavioral intentions. Thus, narrative formats may provide a valuable tool in reducing health disparities. PMID:24347679

Archetype-Based Modeling of Persona for Comprehensive Personality Computing from Personal Big Data.

PubMed

Guo, Ao; Ma, Jianhua

2018-02-25

A model describing the wide variety of human behaviours called personality, is becoming increasingly popular among researchers due to the widespread availability of personal big data generated from the use of prevalent digital devices, e.g., smartphones and wearables. Such an approach can be used to model an individual and even digitally clone a person, e.g., a Cyber-I (cyber individual). This work is aimed at establishing a unique and comprehensive description for an individual to mesh with various personalized services and applications. An extensive research literature on or related to psychological modelling exists, i.e., into automatic personality computing. However, the integrity and accuracy of the results from current automatic personality computing is insufficient for the elaborate modeling in Cyber-I due to an insufficient number of data sources. To reach a comprehensive psychological description of a person, it is critical to bring in heterogeneous data sources that could provide plenty of personal data, i.e., the physiological data, and the Internet data. In addition, instead of calculating personality traits from personal data directly, an approach to a personality model derived from the theories of Carl Gustav Jung is used to measure a human subject's persona. Therefore, this research is focused on designing an archetype-based modeling of persona covering an individual's facets in different situations to approach a comprehensive personality model. Using personal big data to measure a specific persona in a certain scenario, our research is designed to ensure the accuracy and integrity of the generated personality model.

Archetype-Based Modeling of Persona for Comprehensive Personality Computing from Personal Big Data

PubMed Central

Ma, Jianhua

2018-01-01

A model describing the wide variety of human behaviours called personality, is becoming increasingly popular among researchers due to the widespread availability of personal big data generated from the use of prevalent digital devices, e.g., smartphones and wearables. Such an approach can be used to model an individual and even digitally clone a person, e.g., a Cyber-I (cyber individual). This work is aimed at establishing a unique and comprehensive description for an individual to mesh with various personalized services and applications. An extensive research literature on or related to psychological modelling exists, i.e., into automatic personality computing. However, the integrity and accuracy of the results from current automatic personality computing is insufficient for the elaborate modeling in Cyber-I due to an insufficient number of data sources. To reach a comprehensive psychological description of a person, it is critical to bring in heterogeneous data sources that could provide plenty of personal data, i.e., the physiological data, and the Internet data. In addition, instead of calculating personality traits from personal data directly, an approach to a personality model derived from the theories of Carl Gustav Jung is used to measure a human subject’s persona. Therefore, this research is focused on designing an archetype-based modeling of persona covering an individual’s facets in different situations to approach a comprehensive personality model. Using personal big data to measure a specific persona in a certain scenario, our research is designed to ensure the accuracy and integrity of the generated personality model. PMID:29495343

Project Narrative

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

Driscoll, Mary C.

2012-07-12

The Project Narrative describes how the funds from the DOE grant were used to purchase equipment for the biology, chemistry, physics and mathematics departments. The Narrative also describes how the equipment is being used. There is also a list of the positive outcomes as a result of having the equipment that was purchased with the DOE grant.

Asian and Pacific Islander women scientists and engineers: A narrative exploration of model minority, gender, and racial stereotypes

NASA Astrophysics Data System (ADS)

Chinn, Pauline W. U.

2002-04-01

This qualitative study uses narrative methodology to understand what becoming a scientist or engineer entails for women stereotyped as model minorities. Interviews with four Chinese and Japanese women focused on the social contexts in which science is encountered in classrooms, families, and community. Interpretation was guided by theories that individuals construct personal narratives mediated by cultural symbolic systems to make meaning of experiences. Narratives revealed that Confucian cultural scripts shaped gender expectations even in families several generations in America. Regardless of parents' level of education, country of birth, and number of children, educational expectations, and resources were lower for daughters. Parents expected daughters to be compliant, feminine, and educated enough to be marriageable. Findings suggest K-12 gender equity science practices encouraged development of the women's interests and abilities but did not affect parental beliefs. The author's 1999 study of Hawaiians/Pacific Islander and Filipina female engineers is included in implications for teacher education programs sensitive to gender, culture, ethnicity, and language.

Biocellion: accelerating computer simulation of multicellular biological system models

PubMed Central

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-01-01

Motivation: Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. Results: We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Availability and implementation: Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. Contact: seunghwa.kang@pnnl.gov PMID:25064572

Computational modelling of the impact of AIDS on business.

PubMed

Matthews, Alan P

2007-07-01

An overview of computational modelling of the impact of AIDS on business in South Africa, with a detailed description of the AIDS Projection Model (APM) for companies, developed by the author, and suggestions for further work. Computational modelling of the impact of AIDS on business in South Africa requires modelling of the epidemic as a whole, and of its impact on a company. This paper gives an overview of epidemiological modelling, with an introduction to the Actuarial Society of South Africa (ASSA) model, the most widely used such model for South Africa. The APM produces projections of HIV prevalence, new infections, and AIDS mortality on a company, based on the anonymous HIV testing of company employees, and projections from the ASSA model. A smoothed statistical model of the prevalence test data is computed, and then the ASSA model projection for each category of employees is adjusted so that it matches the measured prevalence in the year of testing. FURTHER WORK: Further techniques that could be developed are microsimulation (representing individuals in the computer), scenario planning for testing strategies, and models for the business environment, such as models of entire sectors, and mapping of HIV prevalence in time and space, based on workplace and community data.

Do Live versus Audio-Recorded Narrative Stimuli Influence Young Children's Narrative Comprehension and Retell Quality?

ERIC Educational Resources Information Center

Kim, Young-Suk Grace

2016-01-01

Purpose: The primary aim of the present study was to examine whether different ways of presenting narrative stimuli (i.e., live narrative stimuli versus audio-recorded narrative stimuli) influence children's performances on narrative comprehension and oral-retell quality. Method: Children in kindergarten (n = 54), second grade (n = 74), and fourth…

Politics of love: narrative structures, intertextuality and social agency in the narratives of parents with disabled children.

PubMed

Hanisch, Halvor

2013-11-01

Recent research has highlighted how parental narratives can be important in the resistance against disabling processes. This article contains analyses of enabling language in narratives published by Scandinavian disability rights organizations. First, drawing on the work of Fisher and Goodley, I point out that the material constitute a threefold: normality narratives, resistance narratives, and narratives that demonstrate an appreciation of the present and the child's individual alterity. Second, I demonstrate that the last narrative draws on Romanticism rather than linguistic resources from disability culture. Third, I show that these narratives are hyperboles - texts that strengthen and emphasise the valuation to the point where the narrative structure transcends narrative consistency. Fourth, drawing on the work of Kristeva, I argue that this form of narration constitutes an intimate politics of love. © 2013 The Author. Sociology of Health & Illness © 2013 Foundation for the Sociology of Health & Illness/John Wiley & Sons Ltd.

Computer Security Models

DTIC Science & Technology

1984-09-01

Verification Technique for a Class of Security Kernels," International Symposium on Programming , Lecture Notes in Computer Science 137, Springer-Verlag, New York...September 1984 MTR9S31 " J. K. Millen Computer Security C. M. Cerniglia Models * 0 Ne c - ¢- C. S• ~CONTRACT SPONSOR OUSDRE/C31 & ESO/ALEE...ABSTRACT The purpose of this report is to provide a basis for evaluating security models in the context of secure computer system development

Narrative Performance of Gifted African American School-Aged Children From Low-Income Backgrounds

PubMed Central

2015-01-01

Purpose This study investigated classroom differences in the narrative performance of school-age African American English (AAE)-speaking children in gifted and general education classrooms. Method Forty-three children, Grades 2–5, each generated fictional narratives in response to the book Frog, Where Are You? (Mayer, 1969). Differences in performance on traditional narrative measures (total number of communication units [C-units], number of different words, and mean length of utterance in words) and on AAE production (dialect density measure) between children in gifted and general education classrooms were examined. Results There were no classroom-based differences in total number of C-units, number of different words, and mean length of utterance in words. Children in gifted education classrooms produced narratives with lower dialect density than did children in general educated classrooms. Direct logistic regression assessed whether narrative dialect density measure scores offered additional information about giftedness beyond scores on the Peabody Picture Vocabulary Test–Fourth Edition (Dunn & Dunn, 2007), a standard measure of language ability. Results indicated that a model with only Peabody Picture Vocabulary Test–Fourth Edition scores best discriminated children in the 2 classrooms. Conclusion African American children across gifted and general education classrooms produce fictional narratives of similar length, lexical diversity, and syntax complexity. However, African American children in gifted education classrooms may produce lower rates of AAE and perform better on standard measures of vocabulary than those in general education classrooms. PMID:25409770

Narrative, Preaching, and Formation

ERIC Educational Resources Information Center

Finney, Mark David

2017-01-01

This dissertation focuses on the place of narrative in the transformational encounter that can take place between hearers of sermons and God. Chapter 1 surveys the history and development of contemporary scholarship related to narrative preaching. It argues that most homileticians consider narrative either as a way of structuring sermons, or as a…

Narrative Inquiry: Theory and Practice

ERIC Educational Resources Information Center

Savin-Baden, Maggi; Van Niekerk, Lana

2007-01-01

This article offers an overview of the method of narrative inquiry and explores competing trends in the use of the approach. It not only examines the theories relating to the method but also offers practical guidance on using narrative inquiry, including an exploration of what might count as a narrative and ways of analysing narrative data. The…

The narrative labyrinth of violent dying.

PubMed

Rynearson, E K

2005-05-01

This essay outlines the dynamics of retelling the violent death of a loved one and the narrative "dilemma" of vulnerable family members fixated on retelling. To counter this fixation, the author presents a mythic retelling of violent death (the Myth of Theseus) as narrative basis for developing a restorative retelling. The essay begins by exploring the deformed and deforming structure of the violent dying story, then details the dynamics of its retelling and concludes by presenting a restorative retelling model for family members who cannot release themselves from the story for months or years after the violent dying.

Narratives Boost Entrepreneurial Attitudes: Making an Entrepreneurial Career Attractive?

ERIC Educational Resources Information Center

Fellnhofer, Katharina

2018-01-01

This article analyses the impact of narratives on entrepreneurial attitudes and intentions. To this end, a quasi-experiment was conducted to evaluate web-based entrepreneurial narratives. The paired-sample tests and regression analysis use a sample of 466 people from Austria, Finland, and Greece and indicate that individuals' perceptions of the…

Forensic historiography: narratives and science.

PubMed

Drukteinis, Albert M

2014-01-01

Psychiatrists function, in part, as historians who rely on patient narratives to help them understand presenting mental disorders and explain their causes. Forensic psychiatrists have been skeptical of using narratives, raising concerns about their lack of objectivity and potential for bias. They also have criticized narratives as being more performative than scientific. Recent authors, however, have pointed out that narratives may be helpful in forming forensic opinions and supporting oral testimony, while stressing that their use must be consistent with the ethics espoused by forensic psychiatry. This article reviews the role of narratives in understanding human events and the ubiquitous presence of narratives in the judicial process. It delves into the inescapability of using explicit or implicit narratives in the course of forensic practice, as well as how they may be meaningfully incorporated into evaluations and find expression alongside scientific principles. © 2014 American Academy of Psychiatry and the Law.

Image analysis and modeling in medical image computing. Recent developments and advances.

PubMed

Handels, H; Deserno, T M; Meinzer, H-P; Tolxdorff, T

2012-01-01

Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body

The Rise of the Life Narrative

ERIC Educational Resources Information Center

Goodson, Ivor

2006-01-01

In this article, the author discusses how narratives, which are part of the common currency of the day, have dramatically changed over the years. Grand narratives, which grew exponentially in the mid-nineteenth century, have now been replaced by two different narratives: life narratives and small-scale narratives. He also discusses how small…

Testimony in Narrative Educational Research: A Qualitative Interview, Narrative Analysis and Epistemological Evaluation

ERIC Educational Resources Information Center

Christopher, Justin

2017-01-01

The purpose of this study is to assess issues that arise in the context of epistemological claims in narrative educational research by means of narrative analysis and epistemological evaluation. The research questions which guided the study were: 1) To what extent is epistemology considered by narrative educational researchers?; 2) What issues do…

What's the Story? A Computational Analysis of Narrative Competence in Autism

ERIC Educational Resources Information Center

Lee, Michelle; Martin, Gary E.; Hogan, Abigail; Hano, Deanna; Gordon, Peter C.; Losh, Molly

2018-01-01

Individuals with autism spectrum disorder demonstrate narrative (i.e. storytelling) difficulties which can significantly impact their ability to form and maintain social relationships. However, existing research has not comprehensively documented these impairments in more open-ended, emotionally evocative situations common to daily interactions.…

Computational assessment of model-based wave separation using a database of virtual subjects.

PubMed

Hametner, Bernhard; Schneider, Magdalena; Parragh, Stephanie; Wassertheurer, Siegfried

2017-11-07

The quantification of arterial wave reflection is an important area of interest in arterial pulse wave analysis. It can be achieved by wave separation analysis (WSA) if both the aortic pressure waveform and the aortic flow waveform are known. For better applicability, several mathematical models have been established to estimate aortic flow solely based on pressure waveforms. The aim of this study is to investigate and verify the model-based wave separation of the ARCSolver method on virtual pulse wave measurements. The study is based on an open access virtual database generated via simulations. Seven cardiac and arterial parameters were varied within physiological healthy ranges, leading to a total of 3325 virtual healthy subjects. For assessing the model-based ARCSolver method computationally, this method was used to perform WSA based on the aortic root pressure waveforms of the virtual patients. Asa reference, the values of WSA using both the pressure and flow waveforms provided by the virtual database were taken. The investigated parameters showed a good overall agreement between the model-based method and the reference. Mean differences and standard deviations were -0.05±0.02AU for characteristic impedance, -3.93±1.79mmHg for forward pressure amplitude, 1.37±1.56mmHg for backward pressure amplitude and 12.42±4.88% for reflection magnitude. The results indicate that the mathematical blood flow model of the ARCSolver method is a feasible surrogate for a measured flow waveform and provides a reasonable way to assess arterial wave reflection non-invasively in healthy subjects. Copyright © 2017 Elsevier Ltd. All rights reserved.

Narrative research in psychotherapy: a critical review.

PubMed

Avdi, Evrinomy; Georgaca, Eugenie

2007-09-01

This paper is a review of studies which utilise the notion of narrative to analyse psychotherapy. Its purpose is to systematically present this diverse field of research, to highlight common themes and divergences between different strands and to further the development and integration of narrative research in psychotherapy. The paper reviews studies which employ an applied textual analysis of narratives produced in the context of psychotherapy. Criteria for inclusion of studies are, firstly, the analysis of therapeutic and therapy-related texts and, secondly, the adoption of a narrative psychological perspective. The studies were examined on the basis of the notion of narrative they employ and the aspects of client narratives they focus on, and were grouped accordingly in the review. The majority of the studies reviewed assume a constructivist approach to narrative, adopt a representational view of language, focus primarily on client micro-narratives and relate to cognitive-constructivist and process-experiential psychotherapeutic approaches. A smaller group of studies assume a social constructionist approach to narrative and a functional view of language, focus on micro-narratives, highlight the interactional and wider social aspects of narrative and relate to postmodern trends in psychotherapy. The range of conceptualisations of narrative in the studies reviewed, from a representational psychological view to a constructionist social view, reflects tensions within narrative psychology itself. Moreover, two trends can be discerned in the field reviewed, narrative analysis of therapy, which draws from narrative theory and utilises the analytic approaches of narrative research to study psychotherapy, and analyses of narrative in therapy, which study client narratives using non-narrative qualitative methods. Finally, the paper highlights the need for integration of this diverse field of research and urges for the development of narrative studies of psychotherapy

A Research Roadmap for Computation-Based Human Reliability Analysis

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

Boring, Ronald; Mandelli, Diego; Joe, Jeffrey

2015-08-01

The United States (U.S.) Department of Energy (DOE) is sponsoring research through the Light Water Reactor Sustainability (LWRS) program to extend the life of the currently operating fleet of commercial nuclear power plants. The Risk Informed Safety Margin Characterization (RISMC) research pathway within LWRS looks at ways to maintain and improve the safety margins of these plants. The RISMC pathway includes significant developments in the area of thermalhydraulics code modeling and the development of tools to facilitate dynamic probabilistic risk assessment (PRA). PRA is primarily concerned with the risk of hardware systems at the plant; yet, hardware reliability is oftenmore » secondary in overall risk significance to human errors that can trigger or compound undesirable events at the plant. This report highlights ongoing efforts to develop a computation-based approach to human reliability analysis (HRA). This computation-based approach differs from existing static and dynamic HRA approaches in that it: (i) interfaces with a dynamic computation engine that includes a full scope plant model, and (ii) interfaces with a PRA software toolset. The computation-based HRA approach presented in this report is called the Human Unimodels for Nuclear Technology to Enhance Reliability (HUNTER) and incorporates in a hybrid fashion elements of existing HRA methods to interface with new computational tools developed under the RISMC pathway. The goal of this research effort is to model human performance more accurately than existing approaches, thereby minimizing modeling uncertainty found in current plant risk models.« less

They Call Me Agnes: A Crow Narrative Based on the Life of Agnes Yellowtail Deernose.

ERIC Educational Resources Information Center

Voget, Fred W.; Mee, Mary K.

This book is about life on the Crow Indian Reservation from around 1910 to the present and is based on the personal experiences of Donnie and Agnes Deernose. Following Donnie's death, Agnes became the principal narrator of the book. The Crow Indian Reservation is situated between Billings, Montana, and Sheridan, Wyoming. More so than any other…

Spaces and Physical Education Pre-Service Teachers' Narrative Identities

ERIC Educational Resources Information Center

Wrench, Alison

2017-01-01

Stories or narratives are integral to meaning making in relation to selves, others and the choices we make in living. It follows that pre-service teachers' narratives can provide a means for understanding experiences and processes of becoming teachers of physical education (PE). This paper reports on an interview-based inquiry from which…

Understanding the Person through Narrative

PubMed Central

Hall, Joanne M.; Powell, Jill

2011-01-01

Mental health nurses need to know their clients at depth, and to comprehend their social contexts in order to provide holistic care. Knowing persons through their stories, narratives they tell, provides contextual detail and person-revealing characteristics that make them individuals. Narratives are an everyday means of communicating experience, and there is a place for storytelling in nearly all cultures. Thus narrative is a culturally congruent way to ascertain and understand experiences. This means the nurse should ask questions such as “How did that come about?” versus why questions. A narrative approach stands in contrast to a yes/no algorithmic process in conversing with clients. Eliciting stories illustrates the social context of events, and implicitly provides answers to questions of feeling and meaning. Here we include background on narrative, insights from narrative research, and clinical wisdom in explaining how narratively understanding the person can improve mental health nursing services. Implications for theory, practice, and research are discussed. PMID:21994820

Predicting Motivation: Computational Models of PFC Can Explain Neural Coding of Motivation and Effort-based Decision-making in Health and Disease.

PubMed

Vassena, Eliana; Deraeve, James; Alexander, William H

2017-10-01

Human behavior is strongly driven by the pursuit of rewards. In daily life, however, benefits mostly come at a cost, often requiring that effort be exerted to obtain potential benefits. Medial PFC (MPFC) and dorsolateral PFC (DLPFC) are frequently implicated in the expectation of effortful control, showing increased activity as a function of predicted task difficulty. Such activity partially overlaps with expectation of reward and has been observed both during decision-making and during task preparation. Recently, novel computational frameworks have been developed to explain activity in these regions during cognitive control, based on the principle of prediction and prediction error (predicted response-outcome [PRO] model [Alexander, W. H., & Brown, J. W. Medial prefrontal cortex as an action-outcome predictor. Nature Neuroscience, 14, 1338-1344, 2011], hierarchical error representation [HER] model [Alexander, W. H., & Brown, J. W. Hierarchical error representation: A computational model of anterior cingulate and dorsolateral prefrontal cortex. Neural Computation, 27, 2354-2410, 2015]). Despite the broad explanatory power of these models, it is not clear whether they can also accommodate effects related to the expectation of effort observed in MPFC and DLPFC. Here, we propose a translation of these computational frameworks to the domain of effort-based behavior. First, we discuss how the PRO model, based on prediction error, can explain effort-related activity in MPFC, by reframing effort-based behavior in a predictive context. We propose that MPFC activity reflects monitoring of motivationally relevant variables (such as effort and reward), by coding expectations and discrepancies from such expectations. Moreover, we derive behavioral and neural model-based predictions for healthy controls and clinical populations with impairments of motivation. Second, we illustrate the possible translation to effort-based behavior of the HER model, an extended version of PRO

Computational modelling of cellular level metabolism

NASA Astrophysics Data System (ADS)

Calvetti, D.; Heino, J.; Somersalo, E.

2008-07-01

The steady and stationary state inverse problems consist of estimating the reaction and transport fluxes, blood concentrations and possibly the rates of change of some of the concentrations based on data which are often scarce noisy and sampled over a population. The Bayesian framework provides a natural setting for the solution of this inverse problem, because a priori knowledge about the system itself and the unknown reaction fluxes and transport rates can compensate for the insufficiency of measured data, provided that the computational costs do not become prohibitive. This article identifies the computational challenges which have to be met when analyzing the steady and stationary states of multicompartment model for cellular metabolism and suggest stable and efficient ways to handle the computations. The outline of a computational tool based on the Bayesian paradigm for the simulation and analysis of complex cellular metabolic systems is also presented.

Biocellion: accelerating computer simulation of multicellular biological system models.

PubMed

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-11-01

Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Management Approaches to Stomal and Peristomal Complications: A Narrative Descriptive Study.

PubMed

Beitz, Janice M; Colwell, Janice C

2016-01-01

The purpose of this study was to identify optimal interventions for selected complications based on WOC nurse experts' judgment/expertise. A cross-sectional quantitative descriptive design with qualitative, narrative-type components was used for this study. Following validation rating of appropriateness of interventions and quantitative rankings of first-, second-, and third-line approaches, participants provided substantive handwritten narrative comments about listed interventions. Comments were organized and prioritized using frequency count. Narrative comments reflected the quantitative rankings of efficacy of approaches. Clinicians offered further specific suggestions regarding product use and progression of care for selected complications. Narrative analysis using descriptive quantitative frequency count supported the rankings of most preferred treatments of selected stomal and peristomal complications. Findings add to the previous research on prioritized approaches and evidence-based practice in ostomy care.

Modeling and Computing of Stock Index Forecasting Based on Neural Network and Markov Chain

PubMed Central

Dai, Yonghui; Han, Dongmei; Dai, Weihui

2014-01-01

The stock index reflects the fluctuation of the stock market. For a long time, there have been a lot of researches on the forecast of stock index. However, the traditional method is limited to achieving an ideal precision in the dynamic market due to the influences of many factors such as the economic situation, policy changes, and emergency events. Therefore, the approach based on adaptive modeling and conditional probability transfer causes the new attention of researchers. This paper presents a new forecast method by the combination of improved back-propagation (BP) neural network and Markov chain, as well as its modeling and computing technology. This method includes initial forecasting by improved BP neural network, division of Markov state region, computing of the state transition probability matrix, and the prediction adjustment. Results of the empirical study show that this method can achieve high accuracy in the stock index prediction, and it could provide a good reference for the investment in stock market. PMID:24782659

Base Flow Model Validation

NASA Technical Reports Server (NTRS)

Sinha, Neeraj; Brinckman, Kevin; Jansen, Bernard; Seiner, John

2011-01-01

A method was developed of obtaining propulsive base flow data in both hot and cold jet environments, at Mach numbers and altitude of relevance to NASA launcher designs. The base flow data was used to perform computational fluid dynamics (CFD) turbulence model assessments of base flow predictive capabilities in order to provide increased confidence in base thermal and pressure load predictions obtained from computational modeling efforts. Predictive CFD analyses were used in the design of the experiments, available propulsive models were used to reduce program costs and increase success, and a wind tunnel facility was used. The data obtained allowed assessment of CFD/turbulence models in a complex flow environment, working within a building-block procedure to validation, where cold, non-reacting test data was first used for validation, followed by more complex reacting base flow validation.

Diagnosis of pulmonary hypertension from magnetic resonance imaging-based computational models and decision tree analysis.

PubMed

Lungu, Angela; Swift, Andrew J; Capener, David; Kiely, David; Hose, Rod; Wild, Jim M

2016-06-01

Accurately identifying patients with pulmonary hypertension (PH) using noninvasive methods is challenging, and right heart catheterization (RHC) is the gold standard. Magnetic resonance imaging (MRI) has been proposed as an alternative to echocardiography and RHC in the assessment of cardiac function and pulmonary hemodynamics in patients with suspected PH. The aim of this study was to assess whether machine learning using computational modeling techniques and image-based metrics of PH can improve the diagnostic accuracy of MRI in PH. Seventy-two patients with suspected PH attending a referral center underwent RHC and MRI within 48 hours. Fifty-seven patients were diagnosed with PH, and 15 had no PH. A number of functional and structural cardiac and cardiovascular markers derived from 2 mathematical models and also solely from MRI of the main pulmonary artery and heart were integrated into a classification algorithm to investigate the diagnostic utility of the combination of the individual markers. A physiological marker based on the quantification of wave reflection in the pulmonary artery was shown to perform best individually, but optimal diagnostic performance was found by the combination of several image-based markers. Classifier results, validated using leave-one-out cross validation, demonstrated that combining computation-derived metrics reflecting hemodynamic changes in the pulmonary vasculature with measurement of right ventricular morphology and function, in a decision support algorithm, provides a method to noninvasively diagnose PH with high accuracy (92%). The high diagnostic accuracy of these MRI-based model parameters may reduce the need for RHC in patients with suspected PH.

Computational neurorehabilitation: modeling plasticity and learning to predict recovery.

PubMed

Reinkensmeyer, David J; Burdet, Etienne; Casadio, Maura; Krakauer, John W; Kwakkel, Gert; Lang, Catherine E; Swinnen, Stephan P; Ward, Nick S; Schweighofer, Nicolas

2016-04-30

Despite progress in using computational approaches to inform medicine and neuroscience in the last 30 years, there have been few attempts to model the mechanisms underlying sensorimotor rehabilitation. We argue that a fundamental understanding of neurologic recovery, and as a result accurate predictions at the individual level, will be facilitated by developing computational models of the salient neural processes, including plasticity and learning systems of the brain, and integrating them into a context specific to rehabilitation. Here, we therefore discuss Computational Neurorehabilitation, a newly emerging field aimed at modeling plasticity and motor learning to understand and improve movement recovery of individuals with neurologic impairment. We first explain how the emergence of robotics and wearable sensors for rehabilitation is providing data that make development and testing of such models increasingly feasible. We then review key aspects of plasticity and motor learning that such models will incorporate. We proceed by discussing how computational neurorehabilitation models relate to the current benchmark in rehabilitation modeling - regression-based, prognostic modeling. We then critically discuss the first computational neurorehabilitation models, which have primarily focused on modeling rehabilitation of the upper extremity after stroke, and show how even simple models have produced novel ideas for future investigation. Finally, we conclude with key directions for future research, anticipating that soon we will see the emergence of mechanistic models of motor recovery that are informed by clinical imaging results and driven by the actual movement content of rehabilitation therapy as well as wearable sensor-based records of daily activity.

Computational modeling in melanoma for novel drug discovery.

PubMed

Pennisi, Marzio; Russo, Giulia; Di Salvatore, Valentina; Candido, Saverio; Libra, Massimo; Pappalardo, Francesco

2016-06-01

There is a growing body of evidence highlighting the applications of computational modeling in the field of biomedicine. It has recently been applied to the in silico analysis of cancer dynamics. In the era of precision medicine, this analysis may allow the discovery of new molecular targets useful for the design of novel therapies and for overcoming resistance to anticancer drugs. According to its molecular behavior, melanoma represents an interesting tumor model in which computational modeling can be applied. Melanoma is an aggressive tumor of the skin with a poor prognosis for patients with advanced disease as it is resistant to current therapeutic approaches. This review discusses the basics of computational modeling in melanoma drug discovery and development. Discussion includes the in silico discovery of novel molecular drug targets, the optimization of immunotherapies and personalized medicine trials. Mathematical and computational models are gradually being used to help understand biomedical data produced by high-throughput analysis. The use of advanced computer models allowing the simulation of complex biological processes provides hypotheses and supports experimental design. The research in fighting aggressive cancers, such as melanoma, is making great strides. Computational models represent the key component to complement these efforts. Due to the combinatorial complexity of new drug discovery, a systematic approach based only on experimentation is not possible. Computational and mathematical models are necessary for bringing cancer drug discovery into the era of omics, big data and personalized medicine.

A new parallel DNA algorithm to solve the task scheduling problem based on inspired computational model.

PubMed

Wang, Zhaocai; Ji, Zuwen; Wang, Xiaoming; Wu, Tunhua; Huang, Wei

2017-12-01

As a promising approach to solve the computationally intractable problem, the method based on DNA computing is an emerging research area including mathematics, computer science and molecular biology. The task scheduling problem, as a well-known NP-complete problem, arranges n jobs to m individuals and finds the minimum execution time of last finished individual. In this paper, we use a biologically inspired computational model and describe a new parallel algorithm to solve the task scheduling problem by basic DNA molecular operations. In turn, we skillfully design flexible length DNA strands to represent elements of the allocation matrix, take appropriate biological experiment operations and get solutions of the task scheduling problem in proper length range with less than O(n 2 ) time complexity. Copyright © 2017. Published by Elsevier B.V.

More STELLA Narratives.

ERIC Educational Resources Information Center

Doecke, Brenton

2001-01-01

Presents six brief (about one page) narratives by primary and secondary teachers arising from STELLA (Standards for Teachers of English Language and Literacy in Australia) workshops and interpretive discussions. Notes that each narrative describes a moment of "good" English/literacy teaching. (SG)

Natural history's hypothetical moments: narratives of contingency in Victorian culture.

PubMed

Choi, Tina Young

2009-01-01

This essay focuses on the ways in which works by Robert Chambers, Charles Darwin, and George Eliot encouraged readers to imagine the future as contingent. But where Chambers alludes to Charles Babbage's computational engine and the period's life insurance industry to hint at the role of contingency in natural history, Darwin insists on the importance of contingently determined outcomes to speciation. The "Origin" consistently exercises the reader's speculative energies by generating conditional statements, causal hypotheses, adn diverging alternatives. "Adam Bede" constitutes its characters' interior lives around the proliferation of such contingent narratives. To reflect on the future or on the past, these works suggest, demands a temporal, moral, and narrative complexity in one's thinking.

Flow-based model of computer hackers' motivation.

PubMed

Voiskounsky, Alexander E; Smyslova, Olga V

2003-04-01

Hackers' psychology, widely discussed in the media, is almost entirely unexplored by psychologists. In this study, hackers' motivation is investigated, using the flow paradigm. Flow is likely to motivate hackers, according to views expressed by researchers and by hackers themselves. Taken as granted that hackers experience flow, it was hypothesized that flow increases with the increase of hackers' competence in IT use. Self-selected subjects were recruited on specialized web sources; 457 hackers filled out a web questionnaire. Competence in IT use, specific flow experience, and demographic data were questioned. An on-line research was administered within the Russian-speaking community (though one third of Ss are non-residents of Russian Federation); since hacking seems to be international, the belief is expressed that the results are universal. The hypothesis is not confirmed: flow motivation characterizes the least and the most competent hackers, and the members of an intermediate group, that is, averagely competent Ss report the "flow crisis"-no (or less) flow experience. Two differing strategies of task choice were self-reported by Ss: a step-by-step increase of the difficulty of choices leads to a match of challenges and skills (and to preserving the flow experience); putting choices irrespective of the likelihood of solution leads to a "flow crisis." The findings give productive hints on processes of hackers' motivational development. The flow-based model of computer hackers' motivation was developed. It combines both empirically confirmed and theoretically possible ways of hackers' "professional" growth.

A computer simulation model to compute the radiation transfer of mountainous regions

NASA Astrophysics Data System (ADS)

Li, Yuguang; Zhao, Feng; Song, Rui

2011-11-01

In mountainous regions, the radiometric signal recorded at the sensor depends on a number of factors such as sun angle, atmospheric conditions, surface cover type, and topography. In this paper, a computer simulation model of radiation transfer is designed and evaluated. This model implements the Monte Carlo ray-tracing techniques and is specifically dedicated to the study of light propagation in mountainous regions. The radiative processes between sun light and the objects within the mountainous region are realized by using forward Monte Carlo ray-tracing methods. The performance of the model is evaluated through detailed comparisons with the well-established 3D computer simulation model: RGM (Radiosity-Graphics combined Model) based on the same scenes and identical spectral parameters, which shows good agreements between these two models' results. By using the newly developed computer model, series of typical mountainous scenes are generated to analyze the physical mechanism of mountainous radiation transfer. The results show that the effects of the adjacent slopes are important for deep valleys and they particularly affect shadowed pixels, and the topographic effect needs to be considered in mountainous terrain before accurate inferences from remotely sensed data can be made.

Narratives and Accounts: "Post-Crisis" Narration in Annual Company Reports

ERIC Educational Resources Information Center

Winchester, Jules; Williams, Simon

2014-01-01

This paper aims to provide Business English and EAP practitioners with a rationale for including the analysis of narrative elements in business addresses in their language teaching in order to encourage critical thinking in learners. By studying these elements, and the rhetorical function of the narrative in particular, students can become more…

From affliction to affirmation: narrative transformation and the therapeutics of Candomblé mediumship.

PubMed

Seligman, Rebecca

2005-06-01

Through the presentation and analysis of a prototypical mediumship narrative, this article shows how individuals initiated into the Candomblé religion of north-eastern Brazil come to alter their own self-narratives by learning and internalizing the cultural model for an established social/religious role: that of the medium. As individuals come to identify with this 'role model,' they are able to reinterpret their own life histories in terms of the model's structure and its symbolic content. This article also demonstrates how the social articulation and cognitive internalization of this new self-narrative act therapeutically, to foster a positive transformation in self-understanding that facilitates positive behavior.

COSP - A computer model of cyclic oxidation

NASA Technical Reports Server (NTRS)

Lowell, Carl E.; Barrett, Charles A.; Palmer, Raymond W.; Auping, Judith V.; Probst, Hubert B.

1991-01-01

A computer model useful in predicting the cyclic oxidation behavior of alloys is presented. The model considers the oxygen uptake due to scale formation during the heating cycle and the loss of oxide due to spalling during the cooling cycle. The balance between scale formation and scale loss is modeled and used to predict weight change and metal loss kinetics. A simple uniform spalling model is compared to a more complex random spall site model. In nearly all cases, the simpler uniform spall model gave predictions as accurate as the more complex model. The model has been applied to several nickel-base alloys which, depending upon composition, form Al2O3 or Cr2O3 during oxidation. The model has been validated by several experimental approaches. Versions of the model that run on a personal computer are available.

Using narrative pedagogy: learning and practising interpretive thinking.

PubMed

Ironside, Pamela M

2006-08-01

This paper reports a hermeneutic study undertaken to explicate students' experiences in educational courses in which teachers enact Narrative Pedagogy. International interest in developing and implementing discipline-specific pedagogies is becoming commonplace as teachers respond to the challenges of preparing students for contemporary practice. Lifeworld Pedagogy, developed in Scandinavia, and Narrative Pedagogy, developed in the United States of America, Canada and New Zealand, are two approaches developed from nursing research for nursing education that provide teachers with research-based alternatives to conventional pedagogy. Further research is needed, however, that addresses how new pedagogies are experienced in schools of nursing. Teachers and students from 22 schools of nursing in the United States of America were interviewed over a 4-year period between 2002 and 2005. Using interpretive phenomenology as the philosophical background and Heideggerian hermeneutics as the method, accounts from 52 participants were analysed by a research team. The theme Learning and Practising Interpretive Thinking reveals how reform is occurring in schools of nursing that use Narrative Pedagogy. It documents how Narrative Pedagogy helps students challenge their assumptions and think through and interpret situations they encounter from multiple perspectives. Findings suggest that by focusing teachers' and students' attention on thinking and interpreting as communal experiences, interpretive pedagogies such as Narrative Pedagogy engage teachers and students in pooling their wisdom, challenging their preconceptions, envisioning new possibilities for providing care and engaging with others to ensure patient-centred care and safety. By documenting students' experiences in courses in which Narrative Pedagogy is used, this study provides teachers with research-based evidence to guide their pedagogical decisions. It extends international efforts to develop discipline

Narrative Family Therapy.

ERIC Educational Resources Information Center

Walsh, William M.; Keenan, Robert

1997-01-01

States that narrative family therapy is informed by social constructionism and postmodern worldviews, and is a relatively significant departure from mainstream psychotherapy. Discusses the use of narrative family therapy. Uses the story of Adam and Eve in the Garden of Eden as an example. (MKA)

Post-traumatic stress disorder and opioid use disorder: A narrative review of conceptual models.

PubMed

Danovitch, Itai

2016-01-01

Post-traumatic stress disorder is highly prevalent among individuals who suffer from opioid use disorder. Compared to individuals with opioid use disorder alone, those with post-traumatic stress disorder have a worse course of illness, occupational functioning, and physical health. The neurobiological pathways underlying each disorder overlap substantially, and there are multiple pathways through which these disorders may interact. This narrative review explores evidence underpinning 3 explanatory perspectives on comorbid post-traumatic stress disorder and opioid use disorder: The opioid susceptibility model (a.k.a.: the Self-Medication Hypothesis), the post-traumatic stress disorder susceptibility model, and the common factors model. Diagnostic implications, treatment implications, and directions for future research are discussed.

Narratives boost entrepreneurial attitudes: Making an entrepreneurial career attractive?

PubMed

Fellnhofer, Katharina

2018-06-01

This article analyses the impact of narratives on entrepreneurial attitudes and intentions. To this end, a quasi-experiment was conducted to evaluate web-based entrepreneurial narratives. The paired-sample tests and regression analysis use a sample of 466 people from Austria, Finland, and Greece and indicate that individuals' perceptions of the desirability of entrepreneurship and entrepreneurial intention are significantly different before and after exposure to entrepreneurial narratives. Furthermore, the findings indicate that perceptions of the feasibility of entrepreneurship are more strongly affected by videos than by cases. From a policy perspective, this study raises awareness that entrepreneurship is an attractive career path.

The neuroscience of vision-based grasping: a functional review for computational modeling and bio-inspired robotics.

PubMed

Chinellato, Eris; Del Pobil, Angel P

2009-06-01

The topic of vision-based grasping is being widely studied in humans and in other primates using various techniques and with different goals. The fundamental related findings are reviewed in this paper, with the aim of providing researchers from different fields, including intelligent robotics and neural computation, a comprehensive but accessible view on the subject. A detailed description of the principal sensorimotor processes and the brain areas involved is provided following a functional perspective, in order to make this survey especially useful for computational modeling and bio-inspired robotic applications.

Discourse Markers in Chinese Conversational Narrative

ERIC Educational Resources Information Center

Xiao, Yang

2010-01-01

This study examines the indexicality of discourse markers (DMs) in Chinese conversational narrative. Drawing upon theoretical and methodological principles related to narrative dimensions (Ochs & Capps, 2001), narrative desires (Ochs, 1997, 2004), and narrative positioning (Bamberg, 1997), this work proposes an integrated analytical framework for…

Sentence-Based Attentional Mechanisms in Word Learning: Evidence from a Computational Model

PubMed Central

Alishahi, Afra; Fazly, Afsaneh; Koehne, Judith; Crocker, Matthew W.

2012-01-01

When looking for the referents of novel nouns, adults and young children are sensitive to cross-situational statistics (Yu and Smith, 2007; Smith and Yu, 2008). In addition, the linguistic context that a word appears in has been shown to act as a powerful attention mechanism for guiding sentence processing and word learning (Landau and Gleitman, 1985; Altmann and Kamide, 1999; Kako and Trueswell, 2000). Koehne and Crocker (2010, 2011) investigate the interaction between cross-situational evidence and guidance from the sentential context in an adult language learning scenario. Their studies reveal that these learning mechanisms interact in a complex manner: they can be used in a complementary way when context helps reduce referential uncertainty; they influence word learning about equally strongly when cross-situational and contextual evidence are in conflict; and contextual cues block aspects of cross-situational learning when both mechanisms are independently applicable. To address this complex pattern of findings, we present a probabilistic computational model of word learning which extends a previous cross-situational model (Fazly et al., 2010) with an attention mechanism based on sentential cues. Our model uses a framework that seamlessly combines the two sources of evidence in order to study their emerging pattern of interaction during the process of word learning. Simulations of the experiments of (Koehne and Crocker, 2010, 2011) reveal an overall pattern of results that are in line with their findings. Importantly, we demonstrate that our model does not need to explicitly assign priority to either source of evidence in order to produce these results: learning patterns emerge as a result of a probabilistic interaction between the two clue types. Moreover, using a computational model allows us to examine the developmental trajectory of the differential roles of cross-situational and sentential cues in word learning. PMID:22783211

Teaching about Narrative.

ERIC Educational Resources Information Center

Davies, Gill

1978-01-01

Raises issues involved in the study and teaching of narrative, with reference to both literature and film. Considers the function of realism in narrative fiction and the teaching of theory and practice of those writers and filmmakers who have challenged the realist text by alternative strategies. (JMF)

The Narrative-Emotion Process Coding System 2.0: A multi-methodological approach to identifying and assessing narrative-emotion process markers in psychotherapy.

PubMed

Angus, Lynne E; Boritz, Tali; Bryntwick, Emily; Carpenter, Naomi; Macaulay, Christianne; Khattra, Jasmine

2017-05-01

Recent studies suggest that it is not simply the expression of emotion or emotional arousal in session that is important, but rather it is the reflective processing of emergent, adaptive emotions, arising in the context of personal storytelling and/or Emotion-Focused Therapy (EFT) interventions, that is associated with change. To enhance narrative-emotion integration specifically in EFT, Angus and Greenberg originally identified a set of eight clinically derived narrative-emotion integration markers were originally identified for the implementation of process-guiding therapeutic responses. Further evaluation and testing by the Angus Narrative-Emotion Marker Lab resulted in the identification of 10 empirically validated Narrative-Emotion Process (N-EP) markers that are included in the Narrative-Emotion Process Coding System Version 2.0 (NEPCS 2.0). Based on empirical research findings, individual markers are clustered into Problem (e.g., stuckness in repetitive story patterns, over-controlled or dysregulated emotion, lack of reflectivity), Transition (e.g., reflective, access to adaptive emotions and new emotional plotlines, heightened narrative and emotion integration), and Change (e.g., new story outcomes and self-narrative discovery, and co-construction and re-conceptualization) subgroups. To date, research using the NEPCS 2.0 has investigated the proportion and pattern of narrative-emotion markers in Emotion-Focused, Client-Centered, and Cognitive Therapy for Major Depression, Motivational Interviewing plus Cognitive Behavioral Therapy for Generalized Anxiety Disorder, and EFT for Complex Trauma. Results have consistently identified significantly higher proportions of N-EP Transition and Change markers, and productive shifts, in mid- and late phase sessions, for clients who achieved recovery by treatment termination. Recovery is consistently associated with client storytelling that is emotionally engaged, reflective, and evidencing new story outcomes and self-narrative