Azulenesulfonium Salts: Accessible,Stable, and Versatile Reagents for Cross‐Coupling

Azulenesulfonium salts may be readily prepared from the corresponding azulenes by an S_EAr reaction. These azulene sulfonium salts are bench‐stable species that may be employed as pseudohalides for cross‐coupling. Specifically, their application in Suzuki–Miyaura reactions has been demonstrated with a diverse selection of coupling partners. These azulenesulfonium salts possess significant advantages in comparison with the corresponding azulenyl halides, which are known to be unstable and difficult to prepare in pure form.     

Lasing without inversion: A useful concept?

The historical development that led to the modern concept of amplification and losing without inversion is reviewed. The two basic mechanisms for amplification without inversion and their theoretical formulation are discussed. Finally, the three experiments that confirm the occurrence of these effects are described.     

Selective Reductions of 1-(Carbonyl)Substituted 2-Nitro-Imidazoles with Alkali Metal Borohydrides and with Borane. Tetrahydrofuran

Sodium borohydride, lithium borohydride and borane. THF reduce carbonyl groups (esters, amide) in 1-substituted 2-nitroimidazoIes in high yield without reduction of the nitroheterocycle.     

Comparison of Multivariate Matching Methods: Structures,Distances, and Algorithms

Abstract

A comparison and evaluation is made of recent proposals for multivariate matched sampling in observational studies, where the following three questions are answered: (1) Algorithms: In current statistical practice, matched samples are formed using “nearest available” matching, a greedy algorithm. Greedy matching does not minimize the total distance within matched pairs, though good algorithms exist for optimal matching that do minimize the total distance. How much better is optimal matching than greedy matching? We find that optimal matching is sometimes noticeably better than greedy matching in the sense of producing closely matched pairs, sometimes only marginally better, but it is no better than greedy matching in the sense of producing balanced matched samples. (2) Structures: In common practice, treated units are matched to one control, called pair matching or 1–1 matching, or treated units are matched to two controls, called 1–2 matching, and so on. It is known, however, that the optimal structure is a full matching in which a treated unit may have one or more controls or a control may have one or more treated units. Optimal 1 — k matching is compared to optimal full matching, finding that optimal full matching is often much better. (3) Distances: Matching involves defining a distance between covariate vectors, and several such distances exist. Three recent proposals are compared. Practical advice is summarized in a final section.