The addition of tert-butyl hydro­peroxide (tBuOOH) to two MnII complexes, differing by a small synthetic alteration from an ethyl to a propyl linker in the ligand scaffold, results in the formation of the high-valent bis-oxo complexes, {[MnIV{N4(6-Me-DPEN)}]2(μ-O)2}2+ (1) and {[MnIV{N4(6-Me-DPPN)}]2(μ-O)2}2+ (2).

This article aims to encourage practitioners, young and seasoned, by enhancing their structure-determination toolboxes with a selection of tips and tricks on recognizing and handling aspects of data collection, structure modelling and refinement, and the interpretation of results.

The new copper(II) complex [CuLCl2]2, where L is a product of Schiff base condensation between methyl­amine and 2-pyridine­carbaldehyde, is built of discrete centrosymmetric dimers.

The title complex, Cu(L)2 or [Cu(C15HF10O2)2], comprising one copper ion and two fully fluorinated ligands (L−), was crystallized with 3,4-ethyl­ene­dioxy­thio­phene (EDOT, C6H6O2S) as a guest mol­ecule to give in a di­chloro­methane solution a unique co-crystal, Cu(L)2·3C6H6O2S.

The report of the Executive Committee for 2017 is presented.

The development of antiviral strategies requires a clear understanding of the principles that control the protein arrangements in viral shells. Considered here are those capsids that violate the paradigmatic Caspar and Klug (CK) model, and it is shown that the important structural features of such anomalous shells from the Picobirnaviridae, Flaviviridae and Leviviridae families can be revealed by models in the form of spherical icosahedral packings of equivalent rhombic structural units (SUs). These SUs are composed of protein dimers forming the investigated capsids which, as shown here, are based on the rhombic triacontahedron (RT) geometry. How to modify the original CK approach in order to make it compatible with the considered rhombic tessellations of a sphere is also discussed. Analogies between capsids self-assembled from dimers and trimers are demonstrated. This analysis reveals the principles controlling the localization of receptor proteins (which recognize the host cell) on the capsid surface.

An elementary method is described for finding the coordination sequences for a tiling, based on coloring the underlying graph. The first application is to the two kinds of vertices (tetravalent and trivalent) in the Cairo (or dual-32.4.3.4) tiling. The coordination sequence for a tetravalent vertex turns out, surprisingly, to be 1, 4, 8, 12, 16, …, the same as for a vertex in the familiar square (or 44) tiling. The authors thought that such a simple fact should have a simple proof, and this article is the result. The method is also used to obtain coordination sequences for the 32.4.3.4, 3.4.6.4, 4.82, 3.122 and 34.6 uniform tilings, and the snub-632 tiling. In several cases the results provide proofs for previously conjectured formulas.

In this article, a framework is presented that allows the systematic derivation of planar edge-to-edge k-isocoronal tilings from tile-s-transitive tilings, s ≤ k. A tiling {cal T} is k-isocoronal if its vertex coronae form k orbits or k transitivity classes under the action of its symmetry group. The vertex corona of a vertex x of {cal T} is used to refer to the tiles that are incident to x. The k-isocoronal tilings include the vertex-k-transitive tilings (k-isogonal) and k-uniform tilings. In a vertex-k-transitive tiling, the vertices form k transitivity classes under its symmetry group. If this tiling consists of regular polygons then it is k-uniform. This article also presents the classification of isocoronal tilings in the Euclidean plane.

It is shown how to reconstruct the stacking sequence from the pairwise correlation functions between layers in close-packed structures. First, of theoretical interest, the analytical formulation and solution of the problem are presented when the exact pairwise correlation counts are known. In the second part, the practical problem is approached. A simulated annealing procedure is developed to solve the problem using as initial guess approximate solutions from previous treatments. The robustness of the procedure is tested with synthetic data, followed by an experimental example. The developed approach performs robustly over different synthetic and experimental data, comparing favorably with the reported methods.

Attempting to display the contents of an HDF5 file containing fixed-length UTF-8 encoded strings results in an unexpected error in MATLAB.

For example, the following code

  h5disp('myHDF5FileWithFixedLenUTF8Strings.h5')

returns this error:

Error using h5infoc
UTF-8 encoding is only supported for variable length strings.

Error in h5info (line 108)
hinfo = h5infoc(filename,location, useUtf8);

Error in h5disp>display_hdf5 (line 121)
hinfo = h5info(options.Filename,options.Location);

Error in h5disp (line 99)
display_hdf5(options);

When creating a System Composer architecture model, if the following functions are called with an invalid or missing stereotype, it can cause the model to get corrupted and might lead to a MATLAB crash:

• addComponent
• addPort
• connect

Simulink might produce an incorrect sorted order for a model that meets all of the following conditions:

• The model contains blocks from the SoC Blockset
• The Signal logging option is selected in the model configuration set
• Signals using asynchronous sample time are configured for logging

If you try to open a text file with UTF-16 or UTF-32 encoding, the Import Tool displays a warning message stating that the encoding is not supported.  If you continue to load the file anyways, it is opened with UTF-8 encoding, and the file may not be displayed or imported as expected.This bug exists in the following release(s):
R2020a

This bug has a workaround

Interested in Upgrading?

When the Signal Editor is saving data, the indicator that the save is occurring does not appear.  You might notice a delay when saving large data files.This bug exists in the following release(s):
R2020a

Interested in Upgrading?

In certain scenarios, a Subsystem Reference block changes its position. It can happen during: 

1. Loading of top model which contains the Subsystem Reference block 
2. Synchronization of Subsystem Reference block's contents
3. Converting a subsystem to Subsystem Reference block 

This free report highlights the main facts, numbers and trends of the Russian ecommerce and e-payments markets in an international perspective.

The new Cross-Border Payments and Commerce Report 2019 – 2020 depicts the major trends driving growth in cross-border payments, cross-border commerce, and marketplaces.

Who’s Who in Payments – Complete Overview of Key Payment Providers encompasses key trends in the payments industry.

The new copper(II) complex, namely, di-μ-chlorido-bis{chlorido[methyl(pyridin-2-ylmethylidene)amine-κ2N,N']copper(II)}, [Cu2Cl4(C7H8N2)2], (I), with the ligand 2-pyridylmethyl-N-methylimine (L, a product of Schiff base condensation between methylamine and 2-pyridinecarbaldehyde) is built of discrete centrosymmetric dimers. The coordination about the CuII ion can be described as distorted square pyramidal. The base of the pyramid consists of two nitrogen atoms from the bidentate chelate L [Cu—N = 2.0241 (9), 2.0374 (8) Å] and two chlorine atoms [Cu—Cl = 2.2500 (3), 2.2835 (3) Å]. The apical position is occupied by another Cl atom with the apical bond being significantly elongated at 2.6112 (3) Å. The trans angles of the base are 155.16 (3) and 173.79 (2)°. The Cu...Cu separation in the dimer is 3.4346 (3) Å. In the crystal structure, the loosely packed dimers are arranged in stacks propagating along the a axis. The X-band polycrystalline 77 K EPR spectrum of (I) demonstrates a typical axial pattern characteristic of mononuclear CuII complexes. Compound (I) is redox active and shows a cyclic voltammetric response with E1/2 = −0.037 V versus silver–silver chloride electrode (SSCE) assignable to the reduction peak of CuII/CuI in methanol as solvent.

In small-molecule single-crystal structure determination, we now have at our disposal an inspiring range of fantastic diffractometers with better, brighter sources, and faster, more sensitive detectors. Faster and more powerful computers provide integrated tools and software with impressive graphical user interfaces. Yet these tools can lead to the temptation not to check the work thoroughly and one can too easily overlook tell-tale signs that something might be amiss in a structure determination; validation with checkCIF is not always revealing. This article aims to encourage practitioners, young and seasoned, by enhancing their structure-determination toolboxes with a selection tips and tricks on recognizing and handling aspects that one should constantly be aware of. Topics include a pitfall when setting up data collections, the usefulness of reciprocal lattice layer images, processing twinned data, tips for disorder modelling and the use of restraints, ensuring hydrogen atoms are added to a model correctly, validation beyond checkCIF, and the derivation and interpretation of the final results.