No abstract

In this paper, an analytical model is proposed to predict magnetic flux leakage (MFL) signals from the surface defects in ferromagnetic tubes. The analytical expression consists of elliptic integrals of first kind based on the magnetic dipole model. The radial (B z ) component of leakage fields is computed from the cylindrical holes in ferromagnetic tubes. The effectiveness of the model has been studied by analyzing MFL signals as a function of the defect parameters and lift-off. The model predicted results are verified with experimental results and a good agreement is observed between the analytical and the experimental results. This analytical expression could be used for quick prediction of MFL signals and also input data for defect reconstructions in inverse MFL problem.

The corona virus outbreak, which originated in China, has infected lakhs of people. Its spread has left businesses around the world counting costs. The corona virus is going global, and it could bring the world economy to a standstill. COVID-2019 that began in the depths of China’s Hubei province is spreading rapidly, persuading the World Health Organization to declare it as a pandemic. There are now significant outbreaks from South Korea to Italy and Iran, from America to Britain. The ongoing spread of the new corona virus has become one of the biggest threats to the global economy and financial markets. The economic impact of the COVID-2019 pandemic has introduced extraordinary volatility in global financial markets, as participants are obliged to reassess their valuations of all investments and associated derivatives as the situation develops. In an environment where uncertainty makes it unusually hard to price assets and for market-makers to operate, exchanges are providing the only way to establish consensus on these valuations in real time. Volatility has reached levels comparable with the Global Financial Crisis of 2008, with one-day losses not seen since 1987. The situation is made more challenging by high levels of indebtedness and already low interest rates. The financial markets are all integrated into one as global markets in the current era of globalization. It is important that financial markets remain able to perform their role — providing investors with liquidity, facilitating price discovery, and allowing for risk transfer and the transmission of monetary policy. This study aims at examining the performance of the selected Asian stock markets amidst the times of COVID-2019. This study intends to examine the interlinkages of Asian stock markets selected and to observe the impact of COVID-2019 on these markets. The period of study is from 1st December, 2019 to 31st March, 2020. The tools adopted for the study are correlation, regression, ANOVA and paired sample [Formula: see text] test.

Dipole model based analytical expression is proposed to estimate the length and depth of the rectangular defect on ferromagnetic pipe. Among the three leakage profiles of Magnetic Flux Leakage (MFL), radial and axial leakage profiles are considered in this work. Permeability variation of the specimen is ignored by considering the flux density as close to saturation level of the inspected specimen. Comparing the profile of both the components, radial leakage profile furnishes the better estimation of defect parameter. This is evident from the results of error percentage of length and depth of the defect. Normalized pattern of the proposed analytical model radial leakage profile is good agreement with the experimentally obtained profile support the performance of proposed expression.

The Global Competitiveness Index (GCI) developed by Xavier Salai-Martín, in collaboration with the World Economic Forum, has been measuring the factors that drive the growth and prosperity since 2005. This paper focuses on grouping the European nations according to global competitiveness. It uses the hierarchical and K-means cluster with a particular focus to examine the grouping of countries from 2008 to 2017 and to reduce the complexity in examining the relationship between European countries. The drivers of competitiveness are grouped into 12 critical pillars, namely, institutions, macroeconomic environment, infrastructure, higher education and training, health and primary education, goods market efficiency, financial market development, labor market efficiency, technological readiness, market size, business sophistication, and innovation respectively. The mean score of Europe during the study period was 4.7 and 40% of the European countries were found to be above the average and have been consistently performing well ahead of the average on competitiveness. This study can be generalized to other nations as well as compared with other indexes for exhaustive research that can be useful for policymakers.