Generation and persistence of S1 IgG and neutralizing antibodies in post-COVID-19 patients.

BACKGROUND: Antibody-mediated immune response plays an important role in protection against reinfection. In the case of SARS-CoV-2 infection, the maximum duration of antibody response is still unknown. In this work, the generation of neutralizing  antibodies (NAbs) and IgG antibodies against the S1 subunit (S1 IgG ) of SARS-CoV-2 and their possible duration were determined through decay models. METHODS: 132 participants with SARS-CoV-2 infection were classified according to the severity of the disease. Seroconversion and persistence of S1 IgG antibodies and NAbs were determined by ELISA, samples were taken at two different times post-infection and duration of those antibodies was estimated using Linear Mixed Models (LMMs). RESULTS: The highest amount of S1 IgGs antibodies was associated with age (41 years or older), greater severity of COVID-19 and male gender. NAbs production was associated with the same variables, except for age. The percentage of NAbs decay is higher in the asymptomatic group (P = 0.033), while in S1 IgG antibodies decay, no statistical difference was found between the 4 severity groups. An exponential decay model was built by using a LMM and similarly, two dispersion regions where constructed. The duration of S1 IgG antibodies was 744 days (668-781) for first region and 744 days (453-1231) for the second. Regarding NAbs, an adaptative LMM was used to model a logistic function, determining a duration of 267 days (215-347). CONCLUSION: Humoral immunity to SARS-CoV-2 infection depends on the severity of the disease, gender and age. This immune response could be long-lasting as for other coronaviruses.

Feature Selection on 2D and 3D Geometric Features to Improve Facial Expression Recognition.

An essential aspect in the interaction between people and computers is the recognition of facial expressions. A key issue in this process is to select relevant features to classify facial expressions accurately. This study examines the selection of optimal geometric features to classify six basic facial expressions: happiness, sadness, surprise, fear, anger, and disgust. Inspired by the Facial Action Coding System (FACS) and the Moving Picture Experts Group 4th standard (MPEG-4), an initial set of 89 features was proposed. These features are normalized distances and angles in 2D and 3D computed from 22 facial landmarks. To select a minimum set of features with the maximum classification accuracy, two selection methods and four classifiers were tested. The first selection method, principal component analysis (PCA), obtained 39 features. The second selection method, a genetic algorithm (GA), obtained 47 features. The experiments ran on the Bosphorus and UIVBFED data sets with 86.62% and 93.92% median accuracy, respectively. Our main finding is that the reduced feature set obtained by the GA is the smallest in comparison with other methods of comparable accuracy. This has implications in reducing the time of recognition.

Interaction Modalities Used on Serious Games for Upper Limb Rehabilitation: A Systematic Review.

This systematic review aims to analyze the state-of-the-art regarding interaction modalities used on serious games for upper limb rehabilitation. A systematic search was performed in IEEE Xplore and Web of Science databases. PRISMA and QualSyst protocols were used to filter and assess the articles. Articles must meet the following inclusion criteria: they must be written in English; be at least four pages in length; use or develop serious games; focus on upper limb rehabilitation; and be published between 2007 and 2017. Of 121 articles initially retrieved, 33 articles met the inclusion criteria. Three interaction modalities were found: vision systems (42.4%), complementary vision systems (30.3%), and no-vision systems (27.2%). Vision systems and no-vision systems obtained a similar mean QualSyst (86%) followed by complementary vision systems (85.7%). Almost half of the studies used vision systems as the interaction modality (42.4%) and used the Kinect sensor to collect the body movements (48.48%). The shoulder was the most treated body part in the studies (19%). A key limitation of vision systems and complementary vision systems is that their device performances might be affected by lighting conditions. A main limitation of the no-vision systems is that the range-of-motion in angles of the body movement might not be measured accurately. Due to a limited number of studies, fruitful areas for further research could be the following: serious games focused on finger rehabilitation and trauma injuries, game difficulty adaptation based on user's muscle strength and posture, and multisensor data fusion on interaction modalities.

Nonlinearities distribution Laplace transform-homotopy perturbation method.

This article proposes non-linearities distribution Laplace transform-homotopy perturbation method (NDLT-HPM) to find approximate solutions for linear and nonlinear differential equations with finite boundary conditions. We will see that the method is particularly relevant in case of equations with nonhomogeneous non-polynomial terms. Comparing figures between approximate and exact solutions we show the effectiveness of the proposed method.

A handy approximate solution for a squeezing flow between two infinite plates by using of Laplace transform-homotopy perturbation method.

This article proposes Laplace Transform Homotopy Perturbation Method (LT-HPM) to find an approximate solution for the problem of an axisymmetric Newtonian fluid squeezed between two large parallel plates. After comparing figures between approximate and exact solutions, we will see that the proposed solutions besides of handy, are highly accurate and therefore LT-HPM is extremely efficient.

Modified Taylor series method for solving nonlinear differential equations with mixed boundary conditions defined on finite intervals.

ABSTRACT: In this article, we propose the application of a modified Taylor series method (MTSM) for the approximation of nonlinear problems described on finite intervals. The issue of Taylor series method with mixed boundary conditions is circumvented using shooting constants and extra derivatives of the problem. In order to show the benefits of this proposal, three different kinds of problems are solved: three-point boundary valued problem (BVP) of third-order with a hyperbolic sine nonlinearity, two-point BVP for a second-order nonlinear differential equation with an exponential nonlinearity, and a two-point BVP for a third-order nonlinear differential equation with a radical nonlinearity. The result shows that the MTSM method is capable to generate easily computable and highly accurate approximations for nonlinear equations. AMS SUBJECT CLASSIFICATION: 34L30.