SOUTHERN JOURNAL OF SCIENCES

Background: in the last decades, colocalization analysis of fluorescently tagged biomolecules has proven to be a powerful approach to studying functional relationships between these biomolecules. However, in many cases, to give this analysis a biological meaning, colocalization coefficients must be tested statistically, comparing them with the colocalization expected by chance. Aim: It addressed the statistical significance of triple colocalization to distinguish real triple colocalization and classify different triple signal scenarios. Methods: we use biological and generated images of triple signal scenarios to contrast seven independent statistical facts with independent statistical tests. Three of these tests correspond to pairwise relationships (double scrambling tests), and the others correspond to triple relationships: single scrambling tests (red, green, and blue scrambling) and the triple scrambling test. The analysis and methodology proposed can be reproduced using the application developed in our laboratory. Results: In the study approach, we found true triple relationships ignored by using traditional methods of computing the statistical significance, while we could reinterpret cases of not significant triple colocalization wrongly considered as significant by traditional methods. Discussion: single scrambling tests can reveal significant triple colocalization for low levels of triple co-occurrence, even when all pairwise relationships were exclusion relationships. Moreover, on the other hand, single scrambling tests can reveal the absence of a significant triple colocalization for high levels of triple co-occurrence, even when all pairwise relationships were significant colocalization. Conclusion: all scrambling tests are useful to classify a specific scenario of a triple relationship. Dynamics like mitosis can be distinguished into their phases by triple signal relationships using these 7 independent statistical tests.

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.

Background: The recovery of any valuable component from dolomite as a double carbonate mineral depends on its dissolution efficiency. Aim: This study aimed to optimize and provide a simplified novel approach to the kinetics of dolomite dissolution in sulphuric acid solution using the Box-Behnken experimental design. Methods: The dolomite sample was dissolved in a sulphuric acid solution at seventeen different experimental conditions. The residue containing impurities was removed via filtration, while precipitation was carried out at the optimum conditions. Results and Discussion: The relationship between the independent and dependent variables best fits into the two-factor interaction model with a coefficient of determination of 0.9492, adjusted R² of 0.9187, and predicted R² of 0.7514. The total residual sum of 3x10^-13 and adequate precision of 18.769 show that the predicted dissolution efficiency is much closer to the experimental values. The analysis of variance revealed that the individual effect of acid concentration, temperature, and dissolution time all positively contribute to the dissolution. The interactive effect of acid concentration with temperature and the interactive effect of temperature with dissolution time also positively influences the dissolution efficiency. Following the dissolution of dolomite in sulphuric acid, a white precipitate was formed at room temperature, which dissolved back at a temperature of 70 oC, agitation speed of 900 revolutions per minute, and within 10 minutes. A predictive approach using a two-factor interactive model was applied to generate the kinetic data. Conclusions: The established model equation is suitable for predicting dolomite dissolution in sulphuric acid. The application of the shrinking core model to the generated data shows that the reaction between dolomite and sulphuric acid is film diffusion control with a first-order reaction (0.6587) and activation energy of 27.5 KJmol-1k-1.