scholarly journals Learning to Read and Dyslexia: From Theory to Intervention Through Personalized Computational Models

2020 ◽  
Vol 29 (3) ◽  
pp. 293-300
Author(s):  
Johannes C. Ziegler ◽  
Conrad Perry ◽  
Marco Zorzi
Keyword(s):  
Computational Model ◽  
Learning Outcomes ◽  
Computational Models ◽  
Reading Development ◽  
Reading Performance ◽  
Computational Approach ◽  
Learning Trajectories ◽  
Learning To Read ◽  
Component Skills ◽  
Practical Implications

How do children learn to read? How do deficits in various components of the reading network affect learning outcomes? How does remediating one or several components change reading performance? In this article, we summarize what is known about learning to read and how this can be formalized in a developmentally plausible computational model of reading acquisition. The model is used to understand normal and impaired reading development (dyslexia). In particular, we show that it is possible to simulate individual learning trajectories and intervention outcomes on the basis of three component skills: orthography, phonology, and vocabulary. We therefore advocate a multifactorial computational approach to understanding reading that has practical implications for dyslexia and intervention.

scholarly journals Understanding Dyslexia Through Personalized Large-Scale Computational Models

2019 ◽  
Vol 30 (3) ◽  
pp. 386-395 ◽  
Author(s):  
Conrad Perry ◽  
Marco Zorzi ◽  
Johannes C. Ziegler
Keyword(s):  
Computational Model ◽  
Learning Outcomes ◽  
Large Scale ◽  
Computational Models ◽  
Individual Learning ◽  
Reading Scores ◽  
Learning Trajectories ◽  
Learning To Read ◽  
The Core ◽  
Component Skills

Learning to read is foundational for literacy development, yet many children in primary school fail to become efficient readers despite normal intelligence and schooling. This condition, referred to as developmental dyslexia, has been hypothesized to occur because of deficits in vision, attention, auditory and temporal processes, and phonology and language. Here, we used a developmentally plausible computational model of reading acquisition to investigate how the core deficits of dyslexia determined individual learning outcomes for 622 children (388 with dyslexia). We found that individual learning trajectories could be simulated on the basis of three component skills related to orthography, phonology, and vocabulary. In contrast, single-deficit models captured the means but not the distribution of reading scores, and a model with noise added to all representations could not even capture the means. These results show that heterogeneity and individual differences in dyslexia profiles can be simulated only with a personalized computational model that allows for multiple deficits.

CSBPI_Site：Multi-Information Sources of Features to RNA Binding Sites Prediction

2021 ◽  
Vol 15 ◽  
Author(s):  
Lichao Zhang ◽  
Zihong Huang ◽  
Liang Kong
Keyword(s):  
Computational Model ◽  
Binding Sites ◽  
Noncoding Rna ◽  
Computational Models ◽  
Information Sources ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Gradient Boosting ◽  
Position Information ◽  
Rna Binding Sites

Background: RNA-binding proteins establish posttranscriptional gene regulation by coordinating the maturation, editing, transport, stability, and translation of cellular RNAs. The immunoprecipitation experiments could identify interaction between RNA and proteins, but they are limited due to the experimental environment and material. Therefore, it is essential to construct computational models to identify the function sites. Objective: Although some computational methods have been proposed to predict RNA binding sites, the accuracy could be further improved. Moreover, it is necessary to construct a dataset with more samples to design a reliable model. Here we present a computational model based on multi-information sources to identify RNA binding sites. Method: We construct an accurate computational model named CSBPI_Site, based on xtreme gradient boosting. The specifically designed 15-dimensional feature vector captures four types of information (chemical shift, chemical bond, chemical properties and position information). Results: The satisfied accuracy of 0.86 and AUC of 0.89 were obtained by leave-one-out cross validation. Meanwhile, the accuracies were slightly different (range from 0.83 to 0.85) among three classifiers algorithm, which showed the novel features are stable and fit to multiple classifiers. These results showed that the proposed method is effective and robust for noncoding RNA binding sites identification. Conclusion: Our method based on multi-information sources is effective to represent the binding sites information among ncRNAs. The satisfied prediction results of Diels-Alder riboz-yme based on CSBPI_Site indicates that our model is valuable to identify the function site.

scholarly journals Numerical and Experimental Investigations on Vocal Fold Approximation in Healthy and Simulated Unilateral Vocal Fold Paralysis

2021 ◽  
Vol 11 (4) ◽  
pp. 1817
Author(s):  
Zheng Li ◽  
Azure Wilson ◽  
Lea Sayce ◽  
Amit Avhad ◽  
Bernard Rousseau ◽  
...  
Keyword(s):  
Computational Model ◽  
Vocal Fold ◽  
High Speed ◽  
Computational Models ◽  
Ex Vivo ◽  
Vocal Fold Paralysis ◽  
Future Application ◽  
Experimental Investigations ◽  
Type I ◽  
Mri Scans

We have developed a novel surgical/computational model for the investigation of unilat-eral vocal fold paralysis (UVFP) which will be used to inform future in silico approaches to improve surgical outcomes in type I thyroplasty. Healthy phonation (HP) was achieved using cricothyroid suture approximation on both sides of the larynx to generate symmetrical vocal fold closure. Following high-speed videoendoscopy (HSV) capture, sutures on the right side of the larynx were removed, partially releasing tension unilaterally and generating asymmetric vocal fold closure characteristic of UVFP (sUVFP condition). HSV revealed symmetric vibration in HP, while in sUVFP the sutured side demonstrated a higher frequency (10–11%). For the computational model, ex vivo magnetic resonance imaging (MRI) scans were captured at three configurations: non-approximated (NA), HP, and sUVFP. A finite-element method (FEM) model was built, in which cartilage displacements from the MRI images were used to prescribe the adduction, and the vocal fold deformation was simulated before the eigenmode calculation. The results showed that the frequency comparison between the two sides was consistent with observations from HSV. This alignment between the surgical and computational models supports the future application of these methods for the investigation of treatment for UVFP.

scholarly journals The Exponential-Weight Mean-Variance Model: A novel computational model for the Balloon Analogue Risk Task

2019 ◽  
Author(s):  
Harhim Park ◽  
Jaeyeong Yang ◽  
Jasmin Vassileva ◽  
Woo-Young Ahn
Keyword(s):  
Computational Model ◽  
Computational Models ◽  
Model Comparison ◽  
Exponential Weight ◽  
Multiple Model ◽  
Variance Model ◽  
Balloon Analogue Risk Task ◽  
Parameter Recovery ◽  
Post Hoc ◽  
Mean Variance

The Balloon Analogue Risk Task (BART) is a popular task used to measure risk-taking behavior. To identify cognitive processes associated with choice behavior on the BART, a few computational models have been proposed. However, the extant models are either too simplistic or fail to show good parameter recovery performance. Here, we propose a novel computational model, the exponential-weight mean-variance (EWMV) model, which addresses the limitations of existing models. By using multiple model comparison methods, including post hoc model fits criterion and parameter recovery, we showed that the EWMV model outperforms the existing models. In addition, we applied the EWMV model to BART data from healthy controls and substance-using populations (patients with past opiate and stimulant dependence). The results suggest that (1) the EWMV model addresses the limitations of existing models and (2) heroin-dependent individuals show reduced risk preference than other groups in the BART.

scholarly journals Logical word learning: The case of kinship

2021 ◽  
Author(s):  
Francis Mollica ◽  
Steven T. Piantadosi
Keyword(s):  
Learning Environment ◽  
Computational Model ◽  
Learning Environments ◽  
Conceptual Development ◽  
Learning Model ◽  
Learning Trajectories ◽  
Model Framework ◽  
Model Simulations ◽  
Linguistic Data ◽  
Kinship Term

AbstractWe examine the conceptual development of kinship through the lens of program induction. We present a computational model for the acquisition of kinship term concepts, resulting in the first computational model of kinship learning that is closely tied to developmental phenomena. We demonstrate that our model can learn several kinship systems of varying complexity using cross-linguistic data from English, Pukapuka, Turkish, and Yanomamö. More importantly, the behavioral patterns observed in children learning kinship terms, under-extension and over-generalization, fall out naturally from our learning model. We then conducted interviews to simulate realistic learning environments and demonstrate that the characteristic-to-defining shift is a consequence of our learning model in naturalistic contexts containing abstract and concrete features. We use model simulations to understand the influence of logical simplicity and children’s learning environment on the order of acquisition of kinship terms, providing novel predictions for the learning trajectories of these words. We conclude with a discussion of how this model framework generalizes beyond kinship terms, as well as a discussion of its limitations.

Information literacy assessment by portfolio: a case study

2007 ◽  
Vol 35 (1) ◽  
pp. 41-70 ◽  
Author(s):  
Valerie Sonley ◽  
Denise Turner ◽  
Sue Myer ◽  
Yvonne Cotton
Keyword(s):  
Learning Outcomes ◽  
Information Literacy ◽  
Assessment Method ◽  
Literacy Assessment ◽  
Content Type ◽  
Small Cohort ◽  
The University ◽  
Practical Implications ◽  
Selection Of

PurposeThe purpose of this paper is to report the results of a case study evaluating the revision of the assessment methods of an information literacy module. The revised assessment method took the form of a portfolio.Design/methodology/approachDuring 2004, all six credit modules at the University of Teesside had to be reviewed and restructured into ten credit modules. Following Biggs' principles of constructive alignment, the tutors looked at the existing module aims and learning outcomes. A review of the literature and previous experience informed the selection of the new assessment method by portfolio. An evaluation of the assessment method was undertaken after the module had run.FindingsThe paper finds that the assessment method had real strengths especially in terms of validity. It was also economical and efficient. Students knew what they were expected to do and where they needed to put in effort.Research limitations/implicationsThe assessment by a portfolio method has been carried out once with a relatively small cohort of students, so the findings can only be regarded as interim.Practical implicationsThe tutors believe that they have created a very useful module with an aligned assessment method which would be of benefit to a much greater number of studentsOriginality/valueThere is a shortage of publications that report the results of the use of portfolios for the assessment of information literacy.

A Mechanistic Motor-Clutch Model That Explains Cell Shape Dynamics to Cyclic Stretch

2022 ◽  
Author(s):  
Benjamin W. Scandling ◽  
Jia Gou ◽  
Jessica Thomas ◽  
Jacqueline Xuan ◽  
Chuan Xue ◽  
...  
Keyword(s):  
Computational Model ◽  
Computational Models ◽  
The Body ◽  
Cyclic Stretch ◽  
Substrate Stiffness ◽  
Cell Alignment ◽  
Cellular Mechanisms ◽  
Actin Bundles ◽  
The Impact

Many cells in the body experience cyclic mechanical loading, which can impact cellular processes and morphology. In vitro studies often report that cells reorient in response to cyclic stretch of their substrate. To explore cellular mechanisms involved in this reorientation, a computational model was developed by utilizing the previous computational models of the actin-myosin-integrin motor-clutch system developed by others. The computational model predicts that under most conditions, actin bundles align perpendicular to the direction of applied cyclic stretch, but under specific conditions, such as low substrate stiffness, actin bundles align parallel to the direction of stretch. The model also predicts that stretch frequency impacts the rate of reorientation, and that proper myosin function is critical in the reorientation response. These computational predictions are consistent with reports from the literature and new experimental results presented here. The model suggests that the impact of different stretching conditions (stretch type, amplitude, frequency, substrate stiffness, etc.) on the direction of cell alignment can largely be understood by considering their impact on cell-substrate detachment events, specifically whether detachment occurs during stretching or relaxing of the substrate.

2. How to learn to read (or not)

2019 ◽  
pp. 12-33
Author(s):  
Margaret J. Snowling
Keyword(s):  
Phonological Awareness ◽  
Reading Development ◽  
Spoken Language ◽  
Rapid Naming ◽  
Phoneme Awareness ◽  
Alphabetic Principle ◽  
Learning To Read

‘How to learn to read (or not)’ looks at the stages through which a child must progress on the journey to literacy and the demands of learning to read. It argues that literacy builds on a foundation of spoken language and emphasizes the importance of the skills a child brings to reading. It also discusses the alphabetic principle, phoneme awareness, learning to spell, reading for meaning, and learning to read in different languages. In summary, a ‘triple foundation’ of symbol knowledge, phonological awareness, and rapid naming ability appears to underpin reading development universally. However, there are also additional predictors that are language-specific.

scholarly journals Computational simulation of fracture behaviour in auxetic cellular structure by multiaxial loading

2019 ◽  
Vol 300 ◽  
pp. 03001
Author(s):  
Branko Nečemer ◽  
Janez Kramberger ◽  
Nejc Novak ◽  
Srečko Glodež
Keyword(s):  
Computational Model ◽  
Cellular Structure ◽  
Computational Models ◽  
Fracture Behaviour ◽  
Computational Simulation ◽  
Tangential Direction ◽  
Multiaxial Loading ◽  
Loading Conditions ◽  
Normal Contact ◽  
Auxetic Structure

A computational simulation of fracture behaviour in auxetic cellular structure, subjected to multiaxial loading is presented in this paper. A fracture behaviour of the 3D (three-dimensional) chiral auxetic structure under multiaxial loading conditions was studied. The computational models were used to study the geometry effect of the unit cell on the Poisson’s ratio and fracture behaviour of the analysed chiral auxetic structure. A 3D computational model was built using FEM-code LS DYNA. The discrete computational model of chiral auxetic structure was built using beam finite elements. The lattice model of the analysed auxetic structure was positioned between rigid plates and assembled in a way to simulate a hydro-compression loading conditions. Between the contacting surfaces interactions in normal (contact) and tangential direction (friction) with the node-to-surface approach were simulated. A developed computational model offers insight in the fracture behaviour of considered auxetic cellular structure and helps to better understanding their crushing behaviour under impact multiaxial loading.

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