Tracking excited state dynamics with coherent control: automated limiting of population transfer in LDS750

Closed loop automated pulse shaping experiments are conducted to investigate population transfer in solutions of the laser dye LDS750 in acetonitrile and ethanol. Guided by a genetic algorithm, the optical phases of broadband noncollinear parametric amplifier pulses are modulated by a micromachined deformable mirror to minimize sample fluorescence. The objectives were to test if nonlinearly chirped pulses could reduce population transfer below levels attained by their linearly chirped analogues, and if so, whether the resulting pulse shapes could be rationalized in terms of the photoinduced molecular dynamics. We further aimed to discover how the optimal solutions depend on the pulse fluence, and on the nature of the solvent. Using frequency resolved optical gating, the optimal field is shown to consist of a transform limited blue portion, which promotes population to the excited state, and a negatively chirped red tail, which follows the Stokes shifting of the excited density and dumps it back down to the ground state through stimulated emission. This is verified by comparing the optimal group delay dispersion with multichannel transient absorption data collected in acetonitrile. The optimal pulse shape was not significantly affected by variation of pulse fluence or by the change of solvent for the two polar liquids investigated. These results are discussed in terms of accumulated insights concerning the photophysics of LDS750 and the capabilities of our learning feedback scheme for quantum control.     

A comparative analysis of machine learning techniques and fuzzy analytic hierarchy process to determine the tacit knowledge criteria

Knowledge management is widely considered as a strategic tool to increase firm performance by enabling the reuse of organizational knowledge. Although many have studied knowledge management in a variety of business settings, the concept of tacit knowledge, especially the individual one, has not been explored in due detail. The objective of this study is to identify and prioritize individual tacit knowledge criteria and to explain their effects on firm performance. In the proposed methodology, first, the most prevalent individual tacit knowledge variables are identified by means of knowledge elicitation and feature selection methods. Then, the extracted variables were prioritized using machine learning methods and fuzzy Analytic Hierarchy Process (AHP). Support vector machine (SVM), logistic regression, and artificial neural networks are used as the first approach, followed by fuzzy AHP as the second approach. Based on the comparative analysis results, SVM (as the best-performed machine-learning technique) and fuzzy AHP methods were identified for the subsequent analysis. The results showed that both SVM and fuzzy AHP determined time efficiency of employees, communication between employees and supervisors, and innovative capability of employees as the most important tacit knowledge criteria. These findings are mostly supported by the extant literature, and collectively shows the synergistic nature of the utilized analytics approaches in determining individual tacit knowledge criteria.

     

Enantioselective synthesis of 2-amino-4-(nitromethyl)-4H-chromene-3-carbonitriles from 2-iminochromenes

A series of medicinally important 2-amino-4-(nitromethyl)-4H-chromene-3-carbonitriles were synthesized using enantioselective conjugate addition of nitromethane to 2-iminochromenes. The reactions were performed using L8-Cu (II) catalytic system and moderate to good enantioselectivities (62–88%) and yields (66–96%) were obtained.     

Scenery reconstruction on finite abelian groups

We consider the question of when a random walk on a finite abelian group with a given step distribution can be used to reconstruct a binary labeling of the elements of the group, up to a shift. Matzinger and Lember (2006) give a sufficient condition for reconstructability on cycles. While, as we show, this condition is not in general necessary, our main result is that it is necessary when the length of the cycle is prime and larger than 5, and the step distribution has only rational probabilities. We extend this result to other abelian groups.     

Risk analysis under progressive type II censoring with binomial claim numbers

This paper presents a model of actuarial loss events that follow a progressive censoring scheme. Loss events are modelled according to this scheme regarding the claim number and size. Claim events at random time points are assumed to happen progressively in a given period due to each of an m number of claims that occur due to hazardous events, while a fixed number of n claims are anticipated to take place in total. Distribution of the resulting total loss amount is derived, and according to its properties, some risk management issues about reserves and solvency are discussed.     

Reactionen zum Nachweis von Naphtol, Chloroform und Jodoform

Ohne Zusammenfassung