SOUTHERN JOURNAL OF SCIENCES

Background: This paper presents a straightforward and intuitive method for interactive 3D reconstruction and Direct Linear Transformation (DLT) camera calibration using a single image of a structured scene with known object dimensions. The method relies on manual registration of pairs of points on both the image and the terrain, allowing for precise alignment and calibration. Aim: By utilizing this method, users can easily reconstruct 3D scenes and calibrate cameras without the need for complex algorithms or extensive computational resources. Our approach offers a user-friendly solution for 3D reconstruction and camera calibration, making it accessible to a wider audience and applicable in a range of fields such as computer vision, augmented reality, and virtual reality. Methods: This work primarily focuses on the determination of the projection matrix, which plays a crucial role in mapping 3D points onto a 2D image plane. The projection matrix encapsulates both the intrinsic parameters of the camera (such as focal length and optical center) and the extrinsic parameters (such as camera position and orientation in the world coordinate system). By accurately determining the projection matrix, we can effectively project 3D points onto the 2D image plane, enabling tasks like 3D reconstruction, camera localization, and augmented reality applications. Results: We present experimental results obtained from testing the method on an image of a known object, demonstrating its effectiveness and accuracy in producing realistic 3D reconstructions. Discussion: The method's reliance on manual registration of point pairs allows for precise alignment and calibration without the need for complex algorithms or extensive computational resources. This user-friendly approach makes 3D reconstruction and camera calibration accessible to a wider audience and applicable in various fields. Conclusions: Overall, our approach offers a practical and accessible solution for 3D reconstruction and camera calibration, expanding the potential applications in computer vision, augmented reality, and virtual reality.

This study was designed to prepare vaccines. Cancer vaccines promote the destruction of cancer cells,and the cancer cells contain special antigens on their surface when the vaccine is given, it acts as an antigen to activate the immune system. The IL-2 stimulates the response to a type of cells called T-cell, and outer membrane vesicle (OMV) targeting cancer cells by stimulating the immunity to respond with it two types including innate andadaptive immunity, that lead to stimulating the immune system to reduce mammary adenocarcinoma induction in lab mice using T4-1 cell line breast cancer by taking blood and serum to evaluate the immune system efficacy. The tumor induction success by monitoring mice body weight loss showed the lost weight began in the third week after tumor induction, so 23.2 g at first and second week to 14.35 g at the end of the fourth week, whereas the control animals were weighed 32.37 g. The immunity system efficacy results appear a difference in blood and serum parameters after cancer induction. The result shows an increase in total WBC and monocytes (5900, 0.2 cells/mm respectively) but non significantly decreased in neutrophils and lymphocytes count (2.6, 5.9 cells/mm, respectively). Therefore, the first and second doses of vaccines increased the antibody and complement of the immune system compared with control. While Eliaza data for cytokines profile referred to elevated IL2 (26.5 pg/ml)in the serum of vaccination mice but only significantly decreased in IL6 and IL-22 amount (20.4 and 19.6 pg/ml respectively) comparing with control.

Background: Coronavirus Disease-2019 (COVID-19) appears in individuals asymptomatically and in various symptomatic forms. Symptomatic diversity can result in diagnosis failures, hospitalization, admission to intensive care, multi-organ failure, and death. The causes and risk factors of the severity of disease symptoms are uncertain. This uncertainty can only be resolved by elucidating the effects of host genes and genetic variations on different phenotypes. Aim: This review aimed to emphasize the importance of large-scale genotype-phenotype correlation studies in elucidating the phenotypic diversity in COVID-19 disease. Methods: All publications related to Phenome-Wide Association Study (PheWAS) in the PubMed database were searched. PheWAS studies applied to COVID-19 patients have been identified. In addition, studies applied to the genome-wide association study (GWAS)- Electronic health records (EHRs) data and additionally matched to the gene expression data were systematically reviewed. The latest PheWAS methodology and its importance in Large-scale genotype-phenotype correlations are discussed within the context of published COVID-19 studies. Results: According to our PubMed search data, there are few PheWAS studies on COVID-19 disease. This review explains the use of PheWAS studies applied to health records and GWAS data, and colocalization studies applied to expression quantitative trait locus (eQTL) analysis to understand the phenotypic variability of COVID-19. Discussion; Although there is a very limited number of PheWAS studies on COVID-19 diseases, these studies have obtained important data. At the current stage, there is a need for such studies in COVID-19 research. Conclusions: PheWAS is an ideal method for large-scale genotype-phenotype correlation studies that can reveal genetic diversity and phenotypic diversity in the pathophysiology of the disease.