Capsaicin is the primary capsaicinoid compound responsible for the spiciness of chilli peppers. Several known and unknown genes synthesize capsaicin through various metabolic pathways, such as the phenylpropanoid or the L-valine metabolism pathways. We conducted comprehensive comparative genomics and proteomics analyses to identify genes and proteins associated with the capsaicin pathway in Capsicum chinense, Capsicum baccatum and the two C.annuum cultivars, CM334 and ECW. A BLAST search against the NCBI database identified 26 and 58 enzyme genes and proteins, respectively. These enzyme genes

Retinal prostheses are designed to aid individuals with retinal degenerative conditions such as Retinitis Pigmentosa (RP) and Age-related Macular Degeneration (AMD). These prostheses seek to restore vision and improve the perceived scene by stimulating degenerated retinal cells using retinal stimulating electrodes. While these electrodes allow more efficient interaction with the surroundings, they offer limited resolution.This paper presents an innovative approach to revolutionize the visual perception of retinal prosthesis users. The key idea behind the proposed approach is to fuse

Cardiac magnetic resonance perfusion (CMRP) images are used to assess the local function and permeability of the heart muscle. The perfusion analysis requires the segmentation of cardiac inner and outer walls of the left ventricle (LV). However, the available perfusion datasets are limited or have no annotations. A fair dataset was annotated to employ the latest and most effective Deep Learning (DL) methodologies. In this paper, we employ similar cardiac imaging protocols in terms of cardiac geometry by initially training using CINE images and performing domain adaptation to CMRP images using

The Immune Checkpoint Blockade has transformed cancer treatment. Cytotoxic T-Lymphocyte Associated Protein 4 (CTLA4), Programmed death-1 (PD-1) are antibodies that block immune checkpoint proteins that have been FDA approved for treating a variety of cancers including melanoma, renal carcinoma, and non-small cell lung cancer. Immunotherapy tend to stimulate the immune system of patients to detect and kill cancer cells while sparing normal cells by using checkpoints such as CTLA-4 and PD-1, which are molecules on immune cells that are turned on or off to allow the immune response to begin

Recently, sequencing technologies have become readily available, and scientists are more motivated to conduct metagenomic research to unveil the potential of a myriad of ecosystems and biomes. Metagenomics studies the composition and functions of microbial communities and paves the way to multiple applications in medicine, industry, and ecology. Nonetheless, the immense amount of sequencing data of metagenomics research and the few user-friendly analysis tools and pipelines carry a new challenge to the data analysis. Web-based bioinformatics tools are now being developed to facilitate the

This paper aims to enhance emergency medical services by optimizing ambulance routes towards hospitals equipped for spiral CT scans with minimal wait times. It integrates real-time data on hospital availability and traffic conditions, utilizing machine learning and smart routing algorithms to predict traffic jams and determine the fastest routes. Additionally, a machine learning model is used to detect the risk level of patients based on reported symptoms, helping prioritize critical cases. It aims to reduce emergency response times, ensuring quicker patient treatment. Preliminary results show

Fall prediction is a critical process in ensuring the safety and well-being of individuals, particularly the elderly population. This paper focuses on the development of a fall detection and prediction system using wearable sensors and machine learning algorithms. The system issues an alarm upon predicting the occurrence of falling and sends alerts to a monitoring centre for timely assistance. Wearable sensor devices, including Inertial Measurement Units (IMUs) equipped with accelerometers, gyroscopes, and magnetometers are utilized for data collection. UPFALL, a comprehensive online freely

This paper tackles the problem of generating pho-torealstic images of synthetically rendered human avatar faces from computer graphics engines, our approach leverages the high capabilities of generative models as StyleGAN that can generate high quality human faces that are hard to distinguish from real human faces images. We present a framework that effectively bridges the gap between synthetic and real domain through Single shot GAN inversion that maps the synthetic image into the real latent space of StyleGAN. Benchmarks and Quantitative results show that our method demonstrate significant

Omnidirectional mobile robots are considered for many research applications due to their maneuverability in tight spaces and smoothness of motion. This paper presents a novel design of a T-model mecanum wheeled mobile robot (3-MWMR), the derivation of the inverse and forward kinematics model of the proposed robot, the physical body design of the proposed T-model shape, the simulation of the system dynamics and omnidirectional capabilities of the robot on CoppeliaSim V-rep and MATLAB. The experimental results obtained validates the proof of concept of the proposed model for reduced power losses

mobile robots play an enormous role in different fields of daily life applications including military, safety, and logistic multi-tasking capabilities. A new approach is introduced to the market which is the 3 Mecanum wheeled mobile robot (3-MWMR) is being tested and validated. The main goal of the proposed design is to achieve all the desired directions of motion and to improve the performance of the mobile robot in avoiding obstacles using the fuzzy logic controller. © 2022 IEEE.