Heisenberg-type structures of one-dimensional quantum Hamiltonians

We construct a Heisenberg-like algebra for the one dimensional infinite square-well potential in quantum mechanics. The ladder operators are realized in terms of physical operators of the system as in the harmonic oscillator algebra. These physical operators are obtained with the help of variables used in a recently developed non commutative differential calculus. This \textquotedblleft square-well algebra\textquotedblright is an example of an algebra in a large class of generalized Heisenberg algebras recently constructed. This class of algebras also contains $q$-oscillators as a particular case. We also discuss the physical content of this large class of algebras.Comment: 11 pages. The title and abstract were modified and minor corrections were made in the paper's core. Final version to appear in Phys. Rev.

Effect of waste mica on transfer factors of

A greenhouse pot culture experiment was conducted to study the effect of graded levels of waste mica (0, 10, 20 and 40 g kg-1) on reducing the radiocesium uptake by spinach (Spinacia olerecea L) and lettuce (Lactuca sativa L.) grown in 134Cs-contaminated (at 37 k Bq kg-1 soil) Inceptisols, Vertisols and Ultisols. The biomass yield, and potassium content and its uptake by crops have been significantly improved by waste mica application. The crops grown in Vertisols recorded higher biomass yield, and K content and its uptake as compared with Inceptisols and Ultisols. The average 134Cs transfer factor values recorded were : 0.21, 0.17 and 0.26 at the first cutting, 0.15, 0.12 and 0.28 at the second cutting and 0.07, 0.05 and 0.23 at the third cutting from Inceptisols, Vertisols and Ultisols, respectively. Waste mica significantly suppressed radiocesium uptake, the effect being more pronounced at 40 g mica kg-1soil. There exists an inverse relationship between the 134Cs transfer factors with plant potassium content and also the K uptake by the crop

Supporting proces mining by showing events at a glance

Process mining has emerged as a way to analyze processes based on the event logs of the systems that support them. Today's information systems (e.g., ERP systems) log all kinds of events. Moreover, also embedded systems (e.g., medical equipment, copiers, and other high-tech systems) start producing detailed event logs. The presence of event logs is an important enabler for process mining. The primary goal of process mining is to extract knowledge from these logs and use it for a detailed analysis of reality. One of the challenging issues in process mining is process performance analysis. As a method to analyze process performance and to provide new insights, this paper proposes the dotted chart that shows overall process events at a glance. The chart shows process events in a graphical way such that the analyst gets a "helicopter view" of the process and is able to immediately spot opportunities for process improvement. The approach has been implemented in the context of the ProM framework

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