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The present study aims to investigate the relationship between emotions experienced during learning and metacognition in typically developing (TD) children and those with autism spectrum disorder (ASD). This will assist us in using machine learning (ML) to develop a facial emotion recognition (FER) based intelligent tutor system (ITS) to support children’s metacognitive monitoring process in order to enhance their learning outcomes. In this paper, we first report the results of our preliminary research, which utilized an ML-based FER algorithm to detect four spontaneous epistemic emotions (i.e., neutral, confused, frustrated, and boredom) and six spontaneous basic emotions (i.e., anger, disgust, fear, happiness, sadness, and surprise). Subsequently, we adapted an application (‘BrainHood’) to create the ‘Meta-BrainHood’, that embedded our proposed ML-based FER algorithm to examine the relationship between facial emotion expressions and metacognitive monitoring performance in TD children and those with ASD. Finally, we outline the future steps in our research, which adopts the outcomes of the first two steps to construct an ITS to improve children’s metacognitive monitoring performance and learning outcomes.

This paper addresses the aeroacoustic shape optimization of a 3D aero-engine intake by means of gradient-based optimization assisted by continuous adjoint. A hybrid aeroacoustic model based on the (U)RANS equations and the permeable version of the Ffowcs Williams-Hawkings (FW-H) acoustic analogy in the frequency domain is used. The flow and adjoint simulations are for compressible fluid flows realized using the in–house GPU–enabled software PUMA. The continuous adjoint formulation includes the differentiation of the Spalart– Allmaras turbulence model. The implementation and differentiation of the 3D FW–H analogy are verified by comparing the results of the FW–H analogy to both analytical solutions and URANS. In order to save computational cost, periodic boundary conditions are used to reduce the solution domain size together with the use of a moving reference frame which leads to steady flow and adjoint runs. The generatrix of the nacelle lips and the throat area are parameterized using NURBS. The developed tool is used to perform shape optimization to minimize the total energy contained in the spectrum of the sound pressure, at prescribed receiver locations.

This paper presents an adjoint-based shape optimization framework and its demonstration in a Conjugate Heat Transfer problem in a turbine blading. The gradient of the objective function is computed based on the continuous adjoint method which also includes the adjoint to the turbulence model. The developed software was used to optimize both the blade shape of the internally cooled linear C3X turbine blade and the position of cooling channels aiming at (a) minimum total pressure drop of the hot gas flow and (b) minimum highest temperature within the blade. A free-form parameterization tool, based on volumetric NURBS, controls the blade airfoil contour while the cooling channels are free to move inside the blade, being controlled by the coordinates of their centers. Geometric and flow constraints are included in the performed optimizations keeping the cooling channels away from the airfoil sides and retaining the turbine inlet capacity and flow turning., Published in the 14th European Conference on Turbomachinery Fluid dynamics & Thermodynamics (ETC14)

Fanconi-Bickel syndrome (FBS) is a very rare but distinct clinical entity with the combined features of hepatic glycogen storage disease, generalized proximal renal tubular dysfunction with disproportionately severe glucosuria, and impaired galactose tolerance. Here, we report five cases (out of 93 diagnosed in our lab) with pathogenic variants on both GLUT2 (SLC2A2) alleles. They come from 3 families and presented with an exceptionally mild clinical course. This course was correlated to data from old and most recent expression and transport studies in Xenopus oocytes. GLUT2 genotype in patients 1 and 2 was p.[153_4delLI], [P417R] with the first variant exhibiting normal membrane expression and partially retained transport activity (5.8%) for 2-deoxyglucose. In patient 3, the very first GLUT2 variant ever detected (p.V197I) was found, but for the first time it was present in a patient in the homozygous state. This variant had also shown unaffected membrane expression and remarkable residual activity (8%). The genotype in patient 4, p.[153_4delLI], [(E440A)], again included the 2-amino-acid deletion with residual transporter function, and patient 5 is the first found to be homozygous for this variant. Our results provide further evidence for a genotype-phenotype correlation in patients with GLUT2 variants, non-functional variants result in the full picture of FBS while dysfunctional variants may result in milder presentations, even glucosuria only, without other typical signs of FBS.

This paper presents an adjoint-based shape optimization framework and its demon- stration in a Conjugate Heat Transfer problem in a turbine blading. The gradient of the objective function is computed based on the continuous adjoint method which also includes the adjoint to the turbulence model. Differences in the gradient resulting from making the frozen turbulence assumption are discussed. The developed software was used to optimize both the blade shape of the internally cooled linear C3X turbine blade and the position of cooling channels aiming at (a) minimum total pressure drop of the hot gas flow and (b) minimum highest temperature within the blade. A two-step optimization procedure is used. A free-form parameterization tool, based on volumetric NURBS, controls the blade airfoil contour while the cooling channels are free to move following changes in the coordinates of their centers. Geometric and flow constraints are included in the performed optimizations keeping the cooling channels away from the airfoil sides and retaining the turbine inlet capacity and flow turning.

This paper presents the Multi-Disciplinary Optimization (MDO) of a business jet including static aeroelastic effects. Two different CFD tools (AETHER by Dassault Aviation and PUMA by NTUA) are coupled with a CSM model (VPS software by ESI). Single discipline as well as coupled multi-disciplinary sensitivity derivatives (SDs) are computed by means of adjoint methods. Both a purely discrete and a hybrid continuous(fluid)/discrete(structure) adjoint formulations are presented. The computed SDs are verified against finite differences.