National Defence University, Pakistan

About: National Defence University, Pakistan is a education organization based out in Islamabad, Pakistan. It is known for research contribution in the topics: Decision support system & Population. The organization has 802 authors who have published 816 publications receiving 3701 citations. The organization is also known as: National Defence University of Pakistan & National Defence University Islamabad.

Correlation between tongue body colour, as quantified by machine learning, and clinical indices

Abstract: Objectives Evaluation of tongue colour is an important approach for assessment of human health in traditional East Asian medicine, which originated in ancient China. However, tongue colour analyses are unreliable due to poor quantification and reproducibility. Given these limitations, the utility of this technique as a clinical index has not been demonstrated. Here, we assessed whether tongue colour evaluations, as performed in Kampo (traditional Japanese) medicine, via an automated image acquisition system were associated with particular indices of patient health. Methods We obtained high colour reproduction tongue images from 816 Japanese subjects and applied a machine-learning analysis approach to the quantification of tongue body colour in them. Data on sex, age, systolic blood pressure, diastolic blood pressure, pulse rate (PR), body temperature, body mass index (BMI), past medical history (PMH), and blood examination results (haemoglobin, Hb; creatinine) were also collected. Results Tongue body colour was influenced by multiple clinical indices, per simple correlation analyses. In particular, sex, age, BMI, PR, and Hb were correlated with tongue body colour. No significant correlation with PMH was found. Conclusions Tongue body colour, as quantified with a machine learning approach, was found to be a clinical predictor of changes in several clinical indices, particularly those related to obesity and haemoglobin concentrations.

Challenges in predicting risks of premature coronary artery disease (PCAD)

Abstract: Coronary artery disease (CAD) predominantly manifests in older population above the age of 60 years old. The incidence of CAD in younger individuals has been reported and is called premature CAD (pCAD). The prevalence for pCAD in individuals below 45 years old is about 3-10% worldwide. Advances in risk prediction are of great importance as absolute values of risk factors sometimes correlate poorly with individuals. The measurement of traditional risk factors such as cholesterol level and blood pressure might be inadequate to predict risk for pCAD and therefore new biomarkers are required. The introduction of omics technology offers insight into the mechanism and interactions involved during disease progression and open the possibilities of discovering new biomarkers. Currently, new potential biomarkers for pCAD have been explored such as homocysteine, apolipoproteins, microRNAs and single nucleotide polymorphisms. In this review, we discussed the associated risk factors for pCAD, several reported and newly proposed biomarkers and their potential to be used clinically.

Adaptive order of block backward differentiation formulas for stiff ODEs

Abstract: In this paper, Adapative Order of Block Backward Differentiation Formulas (ABBDFs) are formulated using uniform step size for the numerical solution of stiff ordinary differential equations (ODEs). These ABBDF methods are of order four, five and six. The benefit of the ABBDF methods is the computation time in the computation of solutions. Numerical results are presented to demonstrate the advantage of implementing adaptive order selection in a single code.

Analysis and Modeling the Energy System of a Chemical Tanker by LEAP

Abstract: Maritime transportation has been a cost-effective option among other transport modes. Meanwhile, this demand has been increasing day by day because of the expanding global economy. The ships are one of the most important transport and trade vehicles in the world; 90% of the world trade is carried out by maritime transport, and this sector plays a crucial role in climate change and global warming because it is one of the key sectors leading to emissions of carbon dioxide, the main greenhouse gas (GHG). In other sectors that lead to CO2 emissions, i.e., energy production, manufacturing industry, and heating in residences, energy efficiency has been improved and emissions have been reduced significantly. However, there has been no net reduction in the transport sector; total CO2 emissions have also increased because of the continuous increase in freight and passenger traffic, although efficiency has increased. Increasing the energy efficiency of a ship allows for fuel consumption reduction and GHG emissions. In this study, the energy system of a chemical tanker ship was analyzed and then modeled by using the long-range energy alternatives planning system, a widely used platform for energy policy analysis and climate change mitigation assessment, including a comprehensive energy flow diagram, namely, reference energy system. A base scenario was developed, and the ship’s energy system was convenient to be analyzed and evaluated in terms of technical, economic, and environmental aspects, including low-emission development strategies, to comply with marine engine regulations of the International Maritime Organization.