An 8-bit Scientific Calculator based Intel 8086 Virtual Machine Emulator

AbstractMicroprocessors and their applications course is considered as a significant core course for electrical engineering students due to its potential impact into several real life applications such as complex calculations, interfacing, control and automation technology. In this paper, we propose an eight bit scientific calculator based Intel 8086 assembly language programming. The calculator were designed over the virtual machine for Intel 8086 microprocessor using EMU8086 emulator software. Several arithmetic and logic operations as well as trigonometric functions were implemented in this paper. Also, a plot function and integration of function tools are to be implemented and added as a separate modules for this design. This work was very beneficial in enhancing the student’ skills in mathematics, engineering and computer programming which can be employed in designing a useful applications for users as well as the ability to apply numerical techniques and programming algorithms to design a small microprocessor-based system

Leukotoxin Confers Beta-Hemolytic Activity to Actinobacillus actinomycetemcomitans

Actinobacillus actinomycetemcomitans is the etiologic agent of localized aggressive periodontitis, a rapidly progressing oral disease that occurs in adolescents. A. actinomycetemcomitans can also cause systemic disease, including infective endocarditis. In early work on A. actinomycetemcomitans workers concluded that this bacterium is not beta-hemolytic. More recent reports have suggested that A. actinomycetemcomitans does have the potential to be beta-hemolytic. While growing A. actinomycetemcomitans on several types of growth media, we noticed a beta-hemolytic reaction on media from one manufacturer. Beta-hemolysis occurred on Columbia agar from Accumedia with either sheep or horse blood, but not on similar media from other manufacturers. A surprising result was that mutants of A. actinomycetemcomitans defective for production of leukotoxin, a toxin that is reportedly highly specific for only human and primate white blood cells, are not beta-hemolytic. Purified leukotoxin was able to lyse sheep and human erythrocytes in vitro. This work showed that in contrast to the accepted view, A. actinomycetemcomitans leukotoxin can indeed destroy erythrocytes and that the production of this toxin results in beta-hemolytic colonies on solid medium. In light of these results, the diagnostic criteria for clinical identification of A. actinomycetemcomitans and potentially related bacteria should be reevaluated. Furthermore, in studies on A. actinomycetemcomitans leukotoxin workers should now consider this toxin's ability to destroy red blood cells

RDET stacking classifier: a novel machine learning based approach for stroke prediction using imbalance data

The main cause of stroke is the unexpected blockage of blood flow to the brain. The brain cells die if blood is not supplied to them, resulting in body disability. The timely identification of medical conditions ensures patients receive the necessary treatments and assistance. This early diagnosis plays a crucial role in managing symptoms effectively and enhancing the overall quality of life for individuals affected by the stroke. The research proposed an ensemble machine learning (ML) model that predicts brain stroke while reducing parameters and computational complexity. The dataset was obtained from an open-source website Kaggle and the total number of participants is 3,254. However, this dataset needs a significant class imbalance problem. To address this issue, we utilized Synthetic Minority Over-sampling Technique (SMOTE) and Adaptive Synthetic Sampling (ADAYSN), a technique for oversampling issues. The primary focus of this study centers around developing a stacking and voting approach that exhibits exceptional performance. We propose a stacking ensemble classifier that is more accurate and effective in predicting stroke disease in order to improve the classifier’s performance and minimize overfitting problems. To create a final stronger classifier, the study used three tree-based ML classifiers. Hyperparameters are used to train and fine-tune the random forest (RF), decision tree (DT), and extra tree classifier (ETC), after which they were combined using a stacking classifier and a k-fold cross-validation technique. The effectiveness of this method is verified through the utilization of metrics such as accuracy, precision, recall, and F1-score. In addition, we utilized nine ML classifiers with Hyper-parameter tuning to predict the stroke and compare the effectiveness of Proposed approach with these classifiers. The experimental outcomes demonstrated the superior performance of the stacking classification method compared to other approaches. The stacking method achieved a remarkable accuracy of 100% as well as exceptional F1-score, precision, and recall score. The proposed approach demonstrates a higher rate of accurate predictions compared to previous techniques

Strain estimation in aortic roots from 4D echocardiographic images using medial modeling and deformable registration

Even though the central role of mechanics in the cardiovascular system is widely recognized, estimating mechanical deformation and strains in-vivo remains an ongoing practical challenge. Herein, we present a semi-automated framework to estimate strains from four-dimensional (4D) echocardiographic images and apply it to the aortic roots of patients with normal trileaflet aortic valves (TAV) and congenital bicuspid aortic valves (BAV). The method is based on fully nonlinear shell-based kinematics, which divides the strains into in-plane (shear and dilatational) and out-of-plane components. The results indicate that, even for size-matched non-aneurysmal aortic roots, BAV patients experience larger regional shear strains in their aortic roots. This elevated strains might be a contributing factor to the higher risk of aneurysm development in BAV patients. The proposed framework is openly available and applicable to any tubular structures