Catalytic Hydroetherification of Unactivated Alkenes Enabled by Proton-Coupled Electron Transfer

We report a catalytic, light-driven method for the intramolecular hydroetherification of unactivated alkenols to furnish cyclic ether products. These reactions occur under visible-light irradiation in the presence of an Ir^III-based photoredox catalyst, a Brønsted base catalyst, and a hydrogen-atom transfer (HAT) co-catalyst. Reactive alkoxy radicals are proposed as key intermediates, generated by direct homolytic activation of alcohol O−H bonds through a proton-coupled electron-transfer mechanism. This method exhibits a broad substrate scope and high functional-group tolerance, and it accommodates a diverse range of alkene substitution patterns. Results demonstrating the extension of this catalytic system to carboetherification reactions are also presented.     

Exciton Interactions,Excimer Formation,and [2π+2π] Photodimerization in Nonconjugated Curcuminoid-BF2 Dimers

We describe the synthesis of a series of covalently linked dimers of quadrupolar curcuminoid-BF₂ dyes and the detailed investigation of their solvent-dependent spectroscopic and photophysical properties. In solvents of low polarity, intramolecular folding induces the formation of aggregated chromophores, the UV/Vis absorption spectra of which display the optical signature characteristic of weakly-coupled H-aggregates. The extent of folding and, in turn, of ground-state aggregation is strongly dependent on the nature of the flexible linker. Steady-state and time-resolved fluorescence emission spectroscopies show that the Frenkel exciton relaxes into a fluorescent symmetrical excimer state with a long lifetime. Furthermore, our in-depth studies show that a weakly emitting excimer lies on the pathway toward a photocyclomer. Two-dimensional ¹H NMR spectroscopy and density functional theory (DFT) allowed the structure of the photoproduct to be established. To our knowledge, this represents the first example of a [2π+2π] photodimerization of the curcuminoid chromophore.     

Recent advances in the asymmetric catalytic synthesis of chiral 3-hydroxy and 3-aminooxindoles and derivatives: Medicinally relevant compounds

Several oxindole derivatives, of natural or synthetic origin, have been identified as medicinally appealing compounds, with a plethora of bioactivities reported. Chiral 3-hydroxy and 3-aminooxindole scaffolds have captured the attention of several research groups, due to their importance in drug discovery. In this review, we systematically address the wide variety of asymmetric catalytic methodologies employed in the preparation of these relevant chiral scaffolds, present in many biologically active compounds and/or natural products. Special focus will be given to the nature of the catalyst used.     

Monte Carlo approximation through Gibbs output in generalized linear mixed models

Geyer (J. Roy. Statist. Soc. 56 (1994) 291) proposed Monte Carlo method to approximate the whole likelihood function. His method is limited to choosing a proper reference point. We attempt to improve the method by assigning some prior information to the parameters and using the Gibbs output to evaluate the marginal likelihood and its derivatives through a Monte Carlo approximation. Vague priors are assigned to the parameters as well as the random effects within the Bayesian framework to represent a non-informative setting. Then the maximum likelihood estimates are obtained through the Newton Raphson method. Thus, out method serves as a bridge between Bayesian and classical approaches. The method is illustrated by analyzing the famous salamander mating data by generalized linear mixed models.     

A directed topic model applied to call center improvement

We propose subject matter expert refined topic (SMERT) allocation, a generative probabilistic model applicable to clustering freestyle text. SMERT models are three‐level hierarchical Bayesian models in which each item is modeled as a finite mixture over a set of topics. In addition to discrete data inputs, we introduce binomial inputs. These ‘high‐level’ data inputs permit the ‘boosting’ or affirming of terms in the topic definitions and the ‘zapping’ of other terms. We also present a collapsed Gibbs sampler for efficient estimation. The methods are illustrated using real world data from a call center. Also, we compare SMERT with three alternative approaches and two criteria. Copyright © 2015 John Wiley & Sons, Ltd.     

Universality properties of Gelfand–Tsetlin patterns

A standard Gelfand–Tsetlin pattern of depth n is a configuration of particles in ${\{1,\ldots,n\} \times \mathbb{R}}$ . For each ${r \in \{1, \ldots, n\}, \{r\} \times \mathbb{R}}$ is referred to as the rth level of the pattern. A standard Gelfand–Tsetlin pattern has exactly r particles on each level r, and particles on adjacent levels satisfy an interlacing constraint. Probability distributions on the set of Gelfand–Tsetlin patterns of depth n arise naturally as distributions of eigenvalue minor processes of random Hermitian matrices of size n. We consider such probability spaces when the distribution of the matrix is unitarily invariant, prove a determinantal structure for a broad subclass, and calculate the correlation kernel. In particular we consider the case where the eigenvalues of the random matrix are fixed. This corresponds to choosing uniformly from the set of Gelfand–Tsetlin patterns whose nth level is fixed at the eigenvalues of the matrix. Fixing ${q_n \in \{1,\ldots,n\}}$ , and letting n → ∞ under the assumption that ${\frac{q_n}n \to \alpha \in (0, 1)}$ and the empirical distribution of the particles on the nth level converges weakly, the asymptotic behaviour of particles on level q _n is relevant to free probability theory. Saddle point analysis is used to identify the set in which these particles behave asymptotically like a determinantal random point field with the Sine kernel.     

Superefficient drift estimation on the Wiener space

In the framework of a nonparametric functional estimation for the drift of a Brownian motion $X_t$ we construct Stein type estimators of the form $X_t+D_t\log F$ which are superefficient when $\sqrt{F}$ is a superharmonic functional on the Wiener space for the Malliavin derivative D. To cite this article: N. Privault, A. Réveillac, C. R. Acad. Sci. Paris, Ser. I 343 (2006).