Improved facial emotion recognition model based on a novel deep convolutional structure.

Facial Emotion Recognition (FER) is a very challenging task due to the varying nature of facial expressions, occlusions, illumination, pose variations, cultural and gender differences, and many other aspects that cause a drastic degradation in quality of facial images. In this paper, an anti-aliased deep convolution network (AA-DCN) model has been developed and proposed to explore how anti-aliasing can increase and improve recognition fidelity of facial emotions. The AA-DCN model detects eight distinct emotions from image data.

In vivo cardioprotective effect of zinc oxide nanoparticles against doxorubicin-induced myocardial infarction by enhancing the antioxidant system and nitric oxide production.

Background: Myocardial infarction (MI) is the result of reduced or stopped blood supply to a section of the myocardium. Regardless of its potential effectiveness in the treatment of several types of cancers, doxorubicin (DOX) capabilities are restricted because of its widespread cardiotoxic impact.

Aim: In this study, the protective effect of zinc oxide nanoparticles against doxorubicin-induced myocardial infarction in rats is examined.

A Novel Multi-Scaled Deep Convolutional Structure for Punctilious Human Gait Authentication.

The need for non-interactive human recognition systems to ensure safe isolation between users and biometric equipment has been exposed by the COVID-19 pandemic. This study introduces a novel Multi-Scaled Deep Convolutional Structure for Punctilious Human Gait Authentication (MSDCS-PHGA). The proposed MSDCS-PHGA involves segmenting, preprocessing, and resizing silhouette images into three scales.

A robust classification of acute lymphocytic leukemia-based microscopic images with supervised Hilbert-Huang transform.

Acute lymphocytic leukemia (ALL) is a malignant condition characterized by the development of blast cells in the bone marrow and their quick dissemination into the bloodstream. It primarily affects children and individuals over the age of 60. Manual blood testing, which has been around for a long time, may be slow.

Model-based and model-free deep features fusion for high performed human gait recognition.

In the last decade, the need for a non-contact biometric model for recognizing candidates has increased, especially after the pandemic of COVID-19 appeared and spread worldwide. This paper presents a novel deep convolutional neural network (CNN) model that guarantees quick, safe, and precise human authentication via their poses and walking style. The concatenated fusion between the proposed CNN and a fully connected model has been formulated, utilized, and tested.

Predictors of Short-Term Mortality Following First Episode of Spontaneous Bacterial Peritonitis in Hospitalized Cirrhotic Patients.

Background and aims Spontaneous bacterial peritonitis (SBP) is an important cause of morbidity and mortality in patients with cirrhosis. This study aimed to identify the factors impacting morbidity and short-term mortality in a cohort of patients with cirrhosis following an index episode of SBP. Methods In a retrospective study of hospitalized cirrhotic cohort, 333 patient records were reviewed.

DObesity: Relationship between vitamin D deficiency, obesity and sclerostin as a novel biomarker of bone metabolism.

Aim: To study the relationship between obesity, insulin resistance, vitamin D deficiency and sclerostin as a bone biomarker.

Materials And Methods: Cross-section study of 75 subjects grouped into 3 groups; obese (n = 31), overweight (n = 23) and normal (n = 21) subjects. Sclerostin, fasting insulin, fasting plasma glucose and 25(OH)D were measured and anthropometric measures were taken.

Centroid tracking and velocity measurement of white blood cell in video.

Automated blood cells tracking system has a vital role as the tracking process reflects the blood cell characteristics and indicates several diseases. Blood cells tracking is challenging due to the non-rigid shapes of the blood cells, and the variability in their videos along with the existence of different moving objects in the blood. To tackle such challenges, we proposed a green star based centroid (GSBC) moving white blood cell (WBC) tracking algorithm to measure its velocity and draw its trajectory.