Nuclearg-factors of the 328 keV state in194Pt,the 240 keV state in195Pt,and the 356 keV state in196Pt determined by recoil-implantation into iron and cobalt hosts

The iron-implantation-perturbed-angular-correlation technique (IMPACT) has been used to measure the Larmor precessions of the 328, 240, and 356 keV states of¹⁹⁴Pt,¹⁹⁵Pt, and¹⁹⁶Pt nuclei, respectively, in ferromagnetic iron and cobalt hosts. The observed angular precessions in iron, corrected for the transient field effect, wereω τ ₁₉₄(328)=0.103±0.006 rad,ω τ ₁₉₅ (240)=0.142±0.012, andω τ ₁₉₆(356)=0.084±0.010. For cobalt hosts, the observed Larmor precessions were ω τ₁₉₄(328)=0.068±0.006, ω τ₁₉₅(240)=0.096±0.012, andω τ ₁₉₆(356)=0.057±0.013. Agreement between theg-factors obtained from the measurements in iron hosts and the measurements in cobalt hosts is very good, and a weighted average of the two measurements givesg ₁₉₄(328)=0.349±0.031,g ₁₉₅ (240)=0.136±0.013, andg ₁₉₆(356)=0.329±0.039.     

A-entropy for spectrally absolutely continuous observables

In this paper the notion of entropy of a density operator with respect to spectrally absolutely continuous observable is investigated. The concept of such an entropy is introduced and various possibilities of defining it are discussed. These entropies are examined with regard to their usual properties. We show that this kind of entropy increases after measurement of an observable with a continuous spectrum in the sense of von Neumann and assumes its maximum on a Gaussian state.     

Practical synthesis of a potent hepatitis C virus RNA replication inhibitor

A practical, efficient synthesis of 1, a hepatitis C virus RNA replication inhibitor, is described. Starting with the inexpensive diacetone glucose, the 12-step synthesis features a novel stereoselective rearrangement to prepare the key crystalline furanose diol intermediate. This is followed by a highly selective glycosidation to couple the C-2 branched furanose epoxide with deazapurine.     

Practical asymmetric synthesis of aprepitant,a potent human NK-1 receptor antagonist,via a stereoselective Lewis acid-catalyzed trans acetalization reaction

A streamlined and high-yielding synthesis of aprepitant (1), a potent substance P (SP) receptor antagonist, is described. The enantiopure oxazinone 16 starting material was synthesized via a novel crystallization-induced dynamic resolution process. Conversion of 16 to the penultimate intermediate cis-sec-amine 9 features a highly stereoselective Lewis acid-catalyzed trans acetalization of chiral alcohol 3 with trichloroacetimidate 18 followed by inversion of the adjacent chiral center on the morpholine ring. The six-step process for the synthesis of 9 was accomplished in extremely high overall yield (81%) and with only two isolations.     

Sparse optimization in feature selection: application in neuroimaging

Feature selection plays an important role in the successful application of machine learning techniques to large real-world datasets. Avoiding model overfitting, especially when the number of features far exceeds the number of observations, requires selecting informative features and/or eliminating irrelevant ones. Searching for an optimal subset of features can be computationally expensive. Functional magnetic resonance imaging (fMRI) produces datasets with such characteristics creating challenges for applying machine learning techniques to classify cognitive states based on fMRI data. In this study, we present an embedded feature selection framework that integrates sparse optimization for regularization (or sparse regularization) and classification. This optimization approach attempts to maximize training accuracy while simultaneously enforcing sparsity by penalizing the objective function for the coefficients of the features. This process allows many coefficients to become zero, which effectively eliminates their corresponding features from the classification model. To demonstrate the utility of the approach, we apply our framework to three different real-world fMRI datasets. The results show that regularized classifiers yield better classification accuracy, especially when the number of initial features is large. The results further show that sparse regularization is key to achieving scientifically-relevant generalizability and functional localization of classifier features. The approach is thus highly suited for analysis of fMRI data.     

On Turing dynamical systems and the Atiyah problem

Main theorems of the article concern the problem of Atiyah on possible values of \(l^2\) -Betti numbers. It is shown that all non-negative real numbers are \(l^2\) -Betti numbers, and that “many” (for example all non-negative algebraic) real numbers are \(l^2\) -Betti numbers of simply connected manifolds with respect to a free cocompact action. Also an explicit example is constructed which leads to a simply connected manifold with a transcendental \(l^2\) -Betti number with respect to an action of the threefold direct product of the lamplighter group \(\,\mathbb {Z}{/2\mathbb {Z}}\,\wr \mathbb {Z}\) . The main new idea is embedding Turing machines into integral group rings. The main tool developed generalizes known techniques of spectral computations for certain random walk operators to arbitrary operators in groupoid rings of discrete measured groupoids.     

Chemometrics-based approach to enhancing the usefulness of time domain reflectometry in investigating properties of granular materials.

Sets of time domain reflectometry waveforms analyzed with appropriate chemometric methods, instead of typical single waveform analysis, enable one to detect and quantify differences between waveforms, even if they appear at the level of several orders of magnitude below the scale of the measurements. Typical applications of such an approach to samples of healthy and damaged grain showed that differences contributing five orders of magnitude below the scale are still detectable. Under more rigorous experimental conditions, the level of detectable differences can be expected to be even lower.