An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Enterprise and data center networks consist of a large number of complex networked applications and services that depend upon each other. For this reason, they are difficult to manage and diagnose. In this paper we propose Macroscope, a new approach to extracting the dependencies of networked applications automatically by combining application process information with network level packet traces. We evaluate Macroscope on traces collected at 52 laptops within a large enterprise and show that Macroscope is accurate in finding the dependencies of networked applications. We also show that Macroscope requires less human involvement and is significantly more accurate than state of the art approaches that use only packet traces. Using our rich profiles of the application-service dependencies, we explore and uncover some interesting characteristics about this relationship. Finally, we discuss several usage scenarios that can benefit from Macroscope.
The linear programming network of Tank and Hopfield is shown to obey the same unifying stationary cocontent theorem as the canonical nonlinear programming circuit of Chua and Lin. Application of this theorem highlights an error in the design of Tank and Hopfield and suggests how this can be corrected to guarantee the existence of a bounded solution. The accuracy of the solution is maximized when the circuit of Tank and Hopfield reduces to the simplest special case of the canonical nonlinear programming circuit.
Sequence-dependent materials are a class of materials in which a compositionally aperiodic apportionment of functional groups leads to properties where the whole performs better than the sum of the parts. Here, we discuss what defines a sequence-dependent material, and how the concept can be realized in crystals of extended structures such as metal-organic frameworks.
In this paper, we propose a universal piecewise-linear (PWL) CNN coupling cell, the simplicial cell, which is intended to work with binary as well as gray-level inputs. The construction of the cell is based on the theory of canonical simplicial PWL representations. As a consequence, the coupling function is endowed with important numerical features, namely: the representation of the characteristic cell function is sparse; the family of coupling functions constitutes a Hilbert space; powerful solution algorithms have been developed for the approximation of nonlinear functions, which is particularly useful when the CNN parameters need to be tuned from examples; the parameters can be extracted from a truth table when the CNN is specified analytically.
First-principles investigations of the thermodynamics of binary alloys using a cluster expansion have so far neglected the presence of vacancies. Here, we invoke a local cluster expansion as a perturbation to the standard binary cluster expansion to model the equilibrium vacancy concentration in a binary alloy as a function of temperature and alloy composition. We apply this approach to a first-principles investigation of the fcc ${\mathrm{Al}}_{1\ensuremath{-}x}{\mathrm{Li}}_{x}$ alloy (for $x$ less than 0.3) which at $x=0.25$ exhibits $\mathrm{L}{1}_{2}$ superstructure ordering. The equilibrium vacancy concentration is predicted to be sensitive to the bulk alloy composition $x$ in the ordered $\mathrm{L}{1}_{2}$ phase, varying by more than an order of magnitude in a narrow interval of $x$ at intermediate temperatures. Both in the solid solution and in the ordered $\mathrm{L}{1}_{2}$ phase, the vacancy prefers a nearest neighbor shell rich in aluminum. In the $\mathrm{L}{1}_{2}$ ordered phase, the vacancy predominantly occupies the lithium sublattice. The type of short-range order around a vacancy should affect the mobility of the constituents of the alloy and hence its interdiffusion coefficient.
<p>The iridium-catalyzed silylation of aromatic C–H bonds has become a synthetically valuable reaction because it forms aryl silanes with high sterically derived regioselectivity with silane reagents that are produced and consumed on large scales. Many groups, including our own, have reported iridium complexes of phenanthroline or bipyridine ligands as catalysts for this reaction. Yet, little is known about the mechanism by which the iridium-catalyzed silylation of arenes occurs. Indeed, no iridium-silyl complexes have been prepared that react with C-H bonds to form C-Si bonds in a fashion that is chemically and kinetically competent to be part of the catalytic cycle. </p><p><br></p> <p>In this manuscript, we report the synthesis and reactivity of iridium-silyl compelexes of the 2,9-Me<sub>2</sub>Phen ligand that generates the most active known catalyst for the silylation of aromatic C-H bonds. We show by experiment and computation that the most stable and most reactive silyl complex of this ligand contains two silyl and one hydride ligands and by kinetic analysis of the catalytic reaction determine the rate-limiting step for arenes with varying electronic properties. Computational studies indicate that the steric encumberance of the phenanthroline ligand controls the number of silyl ligands bound to iridium and that the difference in the number of silyl ligands leads to large differences to the rates of the reaction. These studies provide insight into the origins of the high activity of the catalyst containing the 2,9-Me<sub>2</sub>Phen ligand.</p>
