Safety and immunogenicity of Nanocovax, a SARS-CoV-2 recombinant spike protein vaccine: Interim results of a double-blind, randomised controlled phase 1 and 2 trial.

Background: Nanocovax is a recombinant severe acute respiratory syndrome coronavirus 2 subunit vaccine composed of full-length prefusion stabilized recombinant SARS-CoV-2 spike glycoproteins (S-2P) and aluminium hydroxide adjuvant.

Methods: We conducted a dose-escalation, open label trial (phase 1) and a randomized, double-blind, placebo-controlled trial (phase 2) to evaluate the safety and immunogenicity of the Nanocovax vaccine (in 25 mcg, 50 mcg, and 75 mcg doses, aluminium hydroxide adjuvanted (0·5 mg/dose) in 2-dose regime, 28 days apart (ClinicalTrials.gov number, NCT04683484).

Joint Age Estimation and Gender Classification of Asian Faces Using Wide ResNet.

Two key facial features, age and gender, have been widely explored. Companies and organizations have investigated in related applications in several fields including insurance, retails, marketing, etc. It would bring tremendous benefit, which allow companies to easily identify their customer demographics.

Fully automated MR liver volumetry using watershed segmentation coupled with active contouring.

Purpose: Our purpose is to develop a fully automated scheme for liver volume measurement in abdominal MR images, without requiring any user input or interaction.

Methods: The proposed scheme is fully automatic for liver volumetry from 3D abdominal MR images, and it consists of three main stages: preprocessing, rough liver shape generation, and liver extraction. The preprocessing stage reduced noise and enhanced the liver boundaries in 3D abdominal MR images.

Liver Tumor Segmentation from MR Images Using 3D Fast Marching Algorithm and Single Hidden Layer Feedforward Neural Network.

Objective. Our objective is to develop a computerized scheme for liver tumor segmentation in MR images. Materials and Methods.

Spectral shifts of mammalian ultraviolet-sensitive pigments (short wavelength-sensitive opsin 1) are associated with eye length and photic niche evolution.

Retinal opsin photopigments initiate mammalian vision when stimulated by light. Most mammals possess a short wavelength-sensitive opsin 1 (SWS1) pigment that is primarily sensitive to either ultraviolet or violet light, leading to variation in colour perception across species. Despite knowledge of both ultraviolet- and violet-sensitive SWS1 classes in mammals for 25 years, the adaptive significance of this variation has not been subjected to hypothesis testing, resulting in minimal understanding of the basis for mammalian SWS1 spectral tuning evolution.

Hematocrit estimation using online sequential extreme learning machine.

Hematocrit is a blood test that is defined as the volume percentage of red blood cells in the whole blood. It is one of the important indicators for clinical decision making and the most effective factor in glucose measurement using handheld devices. In this paper, a method for hematocrit estimation that is based upon the transduced current curve and the neural network is presented.

Fully automatic scheme for measuring liver volume in 3D MR images.

In this paper, a fully automatic scheme for measuring liver volume in 3D MR images was developed. The proposed MRI liver volumetry scheme consisted of four main stages. First, the preprocessing stage was applied to T1-weighted MR images of the liver in the portal-venous phase to reduce noise.

Computerized liver volumetry on MRI by using 3D geodesic active contour segmentation.

Objective: Our purpose was to develop an accurate automated 3D liver segmentation scheme for measuring liver volumes on MRI.

Subjects And Methods: Our scheme for MRI liver volumetry consisted of three main stages. First, the preprocessing stage was applied to T1-weighted MRI of the liver in the portal venous phase to reduce noise and produce the boundary-enhanced image.

Computerized segmentation of liver in hepatic CT and MRI by means of level-set geodesic active contouring.

Computerized liver volumetry has been studied, because the current "gold-standard" manual volumetry is subjective and very time-consuming. Liver volumetry is done in either CT or MRI. A number of researchers have developed computerized liver segmentation in CT, but there are fewer studies on ones for MRI.

Performance comparison of SLFN training algorithms for DNA microarray classification.

The classification of biological samples measured by DNA microarrays has been a major topic of interest in the last decade, and several approaches to this topic have been investigated. However, till now, classifying the high-dimensional data of microarrays still presents a challenge to researchers. In this chapter, we focus on evaluating the performance of the training algorithms of the single hidden layer feedforward neural networks (SLFNs) to classify DNA microarrays.

An improvement of extreme learning machine for compact single-hidden-layer feedforward neural networks.

Recently, a novel learning algorithm called extreme learning machine (ELM) was proposed for efficiently training single-hidden-layer feedforward neural networks (SLFNs). It was much faster than the traditional gradient-descent-based learning algorithms due to the analytical determination of output weights with the random choice of input weights and hidden layer biases. However, this algorithm often requires a large number of hidden units and thus slowly responds to new observations.