Laughter and smiling facial expression modelling for the generation of virtual affective behavior

Laughter and smiling are significant facial expressions used in human to human communication. We present a computational model for the generation of facial expressions associated with laughter and smiling in order to facilitate the synthesis of such facial expressions in virtual characters. In addition, a new method to reproduce these types of laughter is proposed and validated using databases of generic and specific facial smile expressions. In particular, a proprietary database of laugh and smile expressions is also presented. This database lists the different types of classified and generated laughs presented in this work. The generated expressions are validated through a user study with 71 subjects, which concluded that the virtual character expressions built using the presented model are perceptually acceptable in quality and facial expression fidelity. Finally, for generalization purposes, an additional analysis shows that the results are independent of the type of virtual character’s appearance. © 2021 Mascaró et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Effect of trace impurities in perchloric acid on blank voltammetry of Pt(111)

Catalysis and Surface Chemistr

Relationship of visceral adipose tissue with surrogate insulin resistance and liver markers in individuals with metabolic syndrome chronic complications

Background: Visceral adipose tissue (VAT) has a hazardous influence on systemic inflammation, insulin resistance and an adverse metabolic profile, which increases the risk of developing non-alcoholic fatty liver disease (NAFLD) and chronic complications of diabetes. In our study we aimed to evaluate the association of VAT and the triglyceride glucose (TyG) as a proxy of insulin resistance surrogated with metabolic and liver risk factors among subjects diagnosed with metabolic syndrome (MetS). Methods: A cross-sectional study was performed including 326 participants with MetS (55-75 years) from the PREDIMED-Plus study. Liver-status markers, VAT and TyG were assessed. Participants were stratified by tertiles according to VAT (n = 254) and TyG (n = 326). A receiver operating characteristic curve was used to analyse the efficiency of TyG for VAT. Results: Subjects with greater visceral fat depots showed worse lipid profile, higher homeostatic model assessment for insulin resistance (HOMA-IR), TyG, alanine transaminase (ALT), fibroblast growth factor-21 (FGF-21), fatty liver index (FLI) and hepatic steatosis index (HSI) compared with participants in the first tertile. The multi-adjusted linear-regression analyses indicated that individuals in the third tertile of TyG (>9.1-10.7) had a positive association with HOMA-IR [beta = 3.07 (95% confidence interval (CI) 2.28-3.86; p trend < 0.001)], ALT [beta = 7.43 (95% CI 2.23-12.63; p trend = 0.005)], gamma glutamyl transferase (GGT) [beta = 14.12 (95% CI 3.64-24.61; p trend = 0.008)], FGF-21 [beta = 190.69 (95% CI 93.13-288.25; p trend < 0.001)], FLI [beta = 18.65 (95% CI 14.97-22.23; p trend < 0.001)] and HSI [beta = 3.46 (95% CI, 2.23-4.68; p trend < 0.001)] versus participants from the first tertile. Interestingly, the TyG showed the largest area under the receiver operating curve (AUC) for women (AUC = 0.713; 95% CI 0.62-0.79) compared with men (AUC = 0.570; 95% CI 0.48-0.66). Conclusions: A disrupted VAT enlargement and impairment of TyG are strongly associated with liver status and cardiometabolic risk factors linked with NAFLD in individuals diagnosed with MetS. Moreover, the TyG could be used as a suitable and reliable marker estimator of VAT

Isotemporal substitution of inactive time with physical activity and time in bed: cross-sectional associations with cardiometabolic health in the PREDIMEDPlus study

Background: This study explored the association between inactive time and measures of adiposity, clinical parameters, obesity, type 2 diabetes and metabolic syndrome components. It further examined the impact of reallocating inactive time to time in bed, light physical activity (LPA) or moderate-to-vigorous physical activity (MVPA) on cardio-metabolic risk factors, including measures of adiposity and body composition, biochemical parameters and blood pressure in older adults. Methods: This is a cross-sectional analysis of baseline data from 2189 Caucasian men and women (age 55-75 years, BMI 27-40 Kg/m2) from the PREDIMED-Plus study (http://www.predimedplus.com/). All participants had ≥3 components of the metabolic syndrome. Inactive time, physical activity and time in bed were objectively determined using triaxial accelerometers GENEActiv during 7 days (ActivInsights Ltd., Kimbolton, United Kingdom). Multiple adjusted linear and logistic regression models were used. Isotemporal substitution regression modelling was performed to assess the relationship of replacing the amount of time spent in one activity for another, on each outcome, including measures of adiposity and body composition, biochemical parameters and blood pressure in older adults. Results: Inactive time was associated with indicators of obesity and the metabolic syndrome. Reallocating 30 min per day of inactive time to 30 min per day of time in bed was associated with lower BMI, waist circumference and glycated hemoglobin (HbA1c) (all p-values < 0.05). Reallocating 30 min per day of inactive time with 30 min per day of LPA or MVPA was associated with lower BMI, waist circumference, total fat, visceral adipose tissue, HbA1c, glucose, triglycerides, and higher body muscle mass and HDL cholesterol (all p-values < 0.05). Conclusions: Inactive time was associated with a poor cardio-metabolic profile. Isotemporal substitution of inactive time with MVPA and LPA or time in bed could have beneficial impact on cardio-metabolic health

Isotemporal substitution of inactive time with physical activity and time in bed: Cross-sectional associations with cardiometabolic health in the PREDIMED-Plus study

© 2019 The Author(s). Background: This study explored the association between inactive time and measures of adiposity, clinical parameters, obesity, type 2 diabetes and metabolic syndrome components. It further examined the impact of reallocating inactive time to time in bed, light physical activity (LPA) or moderate-To-vigorous physical activity (MVPA) on cardio-metabolic risk factors, including measures of adiposity and body composition, biochemical parameters and blood pressure in older adults. Methods: This is a cross-sectional analysis of baseline data from 2189 Caucasian men and women (age 55-75 years, BMI 27-40 Kg/m2) from the PREDIMED-Plus study (http://www.predimedplus.com/). All participants had ≥3 components of the metabolic syndrome. Inactive time, physical activity and time in bed were objectively determined using triaxial accelerometers GENEActiv during 7 days (ActivInsights Ltd., Kimbolton, United Kingdom). Multiple adjusted linear and logistic regression models were used. Isotemporal substitution regression modelling was performed to assess the relationship of replacing the amount of time spent in one activity for another, on each outcome, including measures of adiposity and body composition, biochemical parameters and blood pressure in older adults. Results: Inactive time was associated with indicators of obesity and the metabolic syndrome. Reallocating 30 min per day of inactive time to 30 min per day of time in bed was associated with lower BMI, waist circumference and glycated hemoglobin (HbA1c) (all p-values < 0.05). Reallocating 30 min per day of inactive time with 30 min per day of LPA or MVPA was associated with lower BMI, waist circumference, total fat, visceral adipose tissue, HbA1c, glucose, triglycerides, and higher body muscle mass and HDL cholesterol (all p-values < 0.05). Conclusions: Inactive time was associated with a poor cardio-metabolic profile. Isotemporal substitution of inactive time with MVPA and LPA or time in bed could have beneficial impact on cardio-metabolic health. Trial registration: The trial was registered at the International Standard Randomized Controlled Trial (ISRCTN: http://www.isrctn.com/ISRCTN89898870) with number 89898870 and registration date of 24 July 2014, retrospectively registered