This paper aims to focus on research work related to metamaterial-based sensors for material characterization that have been developed for past ten years. A decade of research on metamaterial for sensing application has led to the advancement of compact and improved sensors.
In this study, relevant research papers on metamaterial sensors for material characterization published in reputed journals during the period 2007-2018 were reviewed, particularly focusing on shape, size and nature of materials characterized. Each sensor with its design and performance parameters have been summarized and discussed here.
As metamaterial structures are excited by electromagnetic wave interaction, sensing application throughout electromagnetic spectrum is possible. Recent advancement in fabrication techniques and improvement in metamaterial structures have led to the development of compact, label free and reversible sensors with high sensitivity.
The paper provides useful information on the development of metamaterial sensors for material characterization.
Popular understandings of the financial crisis tend to focus on the rents extracted by elite personnel in the financial sector. Professional discussions, however, have…
Popular understandings of the financial crisis tend to focus on the rents extracted by elite personnel in the financial sector. Professional discussions, however, have addressed the faulty assumptions underlying theory and practice – in particular, the assumption that returns to financial assets follow the Gaussian distribution, in the face of much empirical evidence that these have power law distributions with far higher kurtosis. It turns out that the power law tails of returns to financial assets are also a feature of the distribution of company rates of profit, a discovery that stems from proposals to ‘dissolve’ the traditional transformation problem by abandoning the condition of a uniform rate of profit and instead considering its distribution.Marx himself was aware of the importance of considering the distributional properties of economic variables, based on his reading of Quetelet. In fact, heavy-tailed distributions characterise a wide range of variables in capitalist economies, the best-known probably being the Paretian tail component in distributions of income and wealth. Nor is this simply an empirical fact – such distributions emerge readily from a range of agent-based simulations.Capitalist economies are, in a particular technical sense, complex self-organising systems perpetually on the brink of crisis. This modern understanding is prefigured in Marx’s discussion of how the compulsive character of social relations emerges from the atomistic exercise of human free will in commercial society. The developing literature of probabilistic Marxism successfully applies these insights to the wider fields of econophysics and complexity, demonstrating the continuing relevance of Marx’s thought.