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This book summarizes the current status of theoretical and experimental progress in 2 dimensional graphene-like monolayers and few-layers of transition metal dichalcogenides (TMDCs). Semiconducting monolayer TMDCs, due to the presence of a direct gap, significantly extend the potential of low-dimensional nanomaterials for applications in nanoelectronics and nano-optoelectronics as well as flexible nano-electronics with unprecedented possibilities to control the gap by external stimuli. Strong quantum confinement results in extremely high exciton binding energies which forms an interesting platform for both fundamental studies and device applications. Breaking of spatial inversion symmetry in monolayers results in strong spin-valley coupling potentially leading to their use in valleytronics.Starting with the basic chemistry of transition metals, the reader is introduced to the rich field of transition metal dichalcogenides. After a chapter on three dimensional crystals and a descri

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One of the most notable features of nanometer scale CMOS technology is the increasing magnitude of variability of the key device parameters affecting performance of integrated circuits. The growth of variability can be attributed to multiple factors, including the difficulty of manufacturing control, the emergence of new systematic variation-generating mechanisms, and most importantly, the increase in atomic-scale randomness, where device operation must be described as a stochastic process. In addition to wide-sense stationary stochastic device variability and temperature variation, existence of non-stationary stochastic electrical noise associated with fundamental processes in integrated-circuit devices represents an elementary limit on the performance of electronic circuits.In an attempt to address these issues, Stochastic Process Variation in Deep-Submicron CMOS: Circuits and Algorithms offers unique combination of mathematical treatment of random process variation, electrical noise

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This guide for practicing statisticians and data scientists who use IBM SPSS for statistical analysis of big data in business and finance is the first of a two-part guide to SPSS for Windows, introduc

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