scholarly journals From Affect Theoretical Foundations to Computational Models of Intelligent Affective Agents

2021 ◽  
Vol 11 (22) ◽  
pp. 10874
Author(s):  
Bexy Alfonso ◽  
Joaquin Taverner ◽  
Emilio Vivancos ◽  
Vicente Botti
Keyword(s):  
Computational Model ◽  
Computational Models ◽  
Practical Reasoning ◽  
Theoretical Framework ◽  
Computational Approaches ◽  
Psychological Theories ◽  
Theoretical Foundations

The links between emotions and rationality have been extensively studied and discussed. Several computational approaches have also been proposed to model these links. However, is it possible to build generic computational approaches and languages so that they can be “adapted” when a specific affective phenomenon is being modeled? Would these approaches be sufficiently and properly grounded? In this work, we want to provide the means for the development of these generic approaches and languages by making a horizontal analysis inspired by philosophical and psychological theories of the main affective phenomena that are traditionally studied. Unfortunately, not all the affective theories can be adapted to be used in computational models; therefore, it is necessary to perform an analysis of the most suitable theories. In this analysis, we identify and classify the main processes and concepts which can be used in a generic affective computational model, and we propose a theoretical framework that includes all these processes and concepts that a model of an affective agent with practical reasoning could use. Our generic theoretical framework supports incremental research whereby future proposals can improve previous ones. This framework also supports the evaluation of the coverage of current computational approaches according to the processes that are modeled and according to the integration of practical reasoning and affect-related issues. This framework is being used in the development of the GenIA3 architecture.

scholarly journals What forms the chunks in a subject's performance? Lessons from the CHREST computational model of learning

2001 ◽  
Vol 24 (1) ◽  
pp. 128-129 ◽  
Author(s):  
Peter C.R. Lane ◽  
Fernand Gobet ◽  
Peter C-H. Cheng
Keyword(s):  
Computational Model ◽  
Computational Models ◽  
Short Term Memory ◽  
Memory Capacity ◽  
Theoretical Framework ◽  
Alternative Technique ◽  
Specific Task ◽  
Short Term ◽  
Term Memory ◽  
Visual Short Term Memory

Computational models of learning provide an alternative technique for identifying the number and type of chunks used by a subject in a specific task. Results from applying CHREST to chess expertise support the theoretical framework of Cowan and a limit in visual short-term memory capacity of 3–4 looms. An application to learning from diagrams illustrates different identifiable forms of chunk.

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.

Diagramming discursive intentionality—A cognitive-pragmatic model of intentional verbs

2020 ◽  
Vol 13 (2) ◽  
Author(s):  
Joschka Briese
Keyword(s):  
Practical Reasoning ◽  
Theoretical Framework ◽  
Theory Of Language ◽  
Definition Of

AbstractThis article presents a sign- and usage-based model of intentionality following the works of Robert B. Brandom and T. L. Short. The concept of discursive intentionality is established within Brandom’s theory of language explains discursive and practical reasoning as well as attributive and ascriptive practices. Discursive intentionality is distinguished from other intentionalities of conceptual proximity. Because Brandom’s concept of signs is underdetermined in his works, it will be complemented with T. L. Short’s theory of intentional signs. This dual theoretical framework leads to an innovative analysis of verbs which locates discursive intentionality at the semantic/pragmatic interface. After giving a definition of discursive intentionality, it will be diagrammed by breaking it down into different components (relata, relations, and predicates). Finally, it is tested regarding the plausibility of the diagrammatics of discursive intentionality, using the intentional verb “to promise” to differentiate between the ascription of intentionality and intention.

scholarly journals Experimental and Computational Approaches for Solubility Measurement of Pyridazinone Derivative in Binary (DMSO + Water) Systems

Molecules ◽  
2019 ◽  
Vol 25 (1) ◽  
pp. 171 ◽  
Author(s):  
Faiyaz Shakeel ◽  
Sultan Alshehri ◽  
Mohd Imran ◽  
Nazrul Haq ◽  
Abdullah Alanazi ◽  
...  
Keyword(s):  
Computational Model ◽  
Mole Fraction ◽  
Research Work ◽  
Solvent System ◽  
Binary Solvent ◽  
Thermodynamic Evaluation ◽  
Computational Approaches ◽  
Neat Water ◽  
Poorly Soluble ◽  
Binary Solvent Systems

The current research work was performed to evaluate the solubilization behavior, solution thermodynamics, and solvation behavior of poorly soluble pyridazinone derivative i.e., 6-phenyl-pyridazin-3(2H)-one (PPD) in various binary solvent systems of dimethyl sulfoxide (DMSO) and water using experimental and various computational approaches. The solubility of PPD in various binary solvent system of DMSO and water was investigated within the temperature range T = 298.2 K to 318.2 K at constant air pressure p = 0.1 MPa, by employing an isothermal technique. The generated solubility data of PPD was computationally represented by five different cosolvency models including van’t Hoff, Apelblat, Yalkowsky–Roseman, Jouyban–Acree, and Jouyban–Acree–van’t Hoff models. The performance of each computational model for correlation studies was illustrated using root mean square deviations (RMSD). The overall RMSD value was obtained <2.0% for each computational model. The maximum solubility of PPD in mole fraction was recorded in neat DMSO (4.67 × 10−1 at T = 318.2 K), whereas the lowest one was obtained in neat water (5.82 × 10−6 at T = 298.2 K). The experimental solubility of PPD in mole fraction in neat DMSO was much higher than its ideal solubility, indicating the potential of DMSO for solubility enhancement of PPD. The computed values of activity coefficients showed maximum molecular interaction in PPD-DMSO compared with PPD-water. Thermodynamic evaluation showed an endothermic and entropy-driven dissolution of PPD in all the mixtures of DMSO and water. Additionally, enthalpy–entropy compensation evaluation indicated an enthalpy-driven mechanism as a driven mechanism for the solvation property of PPD.

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.

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.

Role of Genetic Interactions in Lung Diseases Detection using Computational Approaches: A Review

2021 ◽  
Vol 01 ◽  
Author(s):  
S Priya ◽  
R Manavalan
Keyword(s):  
Lung Cancer ◽  
Lung Diseases ◽  
Computational Models ◽  
Association Studies ◽  
Genetic Interactions ◽  
Genome Wide Association Studies ◽  
Computational Approaches ◽  
Genome Wide ◽  
Human Disorders ◽  
Brca1 Brca2

: Genome-wide Association Studies (GWAS) give special insight into genetic differences and environmental influences that are part of different human disorders and provide prognostic help to increase the survival of patients. Lung diseases such as lung cancer, asthma, and tuberculosis are detected by analyzing Single Nucleotide Polymorphism (SNP) genetic variations. The key causes of lung-related diseases are genetic factors, environmental and social behaviors. The epistasis effects act as a blueprint for the researchers to observe the genetic variation associated with lung diseases. The manual examination of the enormous genetic interactions is complicated to detect the lungs syndromes for diagnosis of acute respiratory. Due to its importance, several computational approaches have been modeled to infer epistasis effects. This article includes a comprehensive and multifaceted review of all relevant genetic studies published between 2006 and 2020. In this critical review, various computational approaches are extensively discussed in detecting respondent Epistasis effects for various lung diseases such as Asthma, Tuberculosis, lung cancer, and Nicotine drug dependence. The analysis shows that different computational models identified candidate genes such as CHRNA4, CHRNB2, BDNF, TAS2R16, TAS2R38, BRCA1, BRCA2, RAD21, IL4Ra, IL-13 and IL-1β, have important causes for genetic variants linked to pulmonary disease. These computational approaches' strengths and limitations are described. The issues behind the computational methods while identifying the lung diseases through epistasis effects and the parameters used by various researchers for their evaluation are presented.

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