Ionization phase-match gating for wavelength-tunable isolated attosecond pulse generation

High-order harmonic emission can be confined to the leading edge of an 800 nm driver laser pulse under moderately intense focusing conditions (7×10¹⁴ W/cm²) (Pfeifer et al. in Opt. Express 15:17120, 2007). Here, the experimentally observed curtailment of harmonic production on the leading edge of the driver pulse is shown to be controlled by an ionization-induced phase-matching condition. The transient plasma density inherent to the process of high-harmonic generation terminates the harmonic emission by an ultrafast loss of phase matching on the leading edge of the laser pulse. The analysis is supported by a reconstruction of the in situ intensity envelope of the driver pulse with attosecond temporal resolution, performed by measurements of the carrier-envelope phase dependence of individual half-cycle harmonic cutoffs. The method opens the way to wavelength-tunable isolated attosecond pulse generation.     

An Unusual Fullerene–Carbene Adduct: Thermal Motion,Disorder, or Both?**

A single-crystal X-ray study of a fullerene-imidazole adduct at nine temperatures (80 K≤T≤480 K), accompanied by energy calculations, strongly suggested thermal motion of the C₆₀ moiety with respect to the imidazolium heterocycle. Analysis of the anisotropic displacement parameters, calculations of frequencies, and the refinement of disorder models for the crystal at four temperatures (230 K≤T≤380 K) lead to the conclusion that the rotator is moving at all temperatures. The rotation barrier is low, with one preferred crystallographic site and several other energy minima.     

Assessment of maximum likelihood PCA missing data imputation

Maximum likelihood principal component analysis (MLPCA) was originally proposed to incorporate measurement error variance information in principal component analysis (PCA) models. MLPCA can be used to fit PCA models in the presence of missing data, simply by assigning very large variances to the non‐measured values. An assessment of maximum likelihood missing data imputation is performed in this paper, analysing the algorithm of MLPCA and adapting several methods for PCA model building with missing data to its maximum likelihood version. In this way, known data regression (KDR), KDR with principal component regression (PCR), KDR with partial least squares regression (PLS) and trimmed scores regression (TSR) methods are implemented within the MLPCA method to work as different imputation steps. Six data sets are analysed using several percentages of missing data, comparing the performance of the original algorithm, and its adapted regression‐based methods, with other state‐of‐the‐art methods. Copyright © 2016 John Wiley & Sons, Ltd.