Facile dearomatisation of porphyrins using palladium-catalysed hydrazination: the 5,15-diiminoporphodimethenes and their redox products

The synthesis, electronic absorption and 1H NMR spectra of a suite of novel porphyrinoids derived from meso-bromoporphyrins by palladium-catalysed aminations using ethyl and tert-butylcarbazates are reported. Instead of the expected carbazate-substituted porphyrins, a facile oxidative dearomatisation of the porphyrin ring occurs in high yield, especially for the nickel(II) complexes, resulting in high yields of 5,15-diiminoporphodimethenes (DIPDs). The analogous zinc(II) and free base DIPDs were also characterised, the former by X-ray crystallography. The oxidation and reduction reactions of DIPDs and their precursor carbazate porphyrins were studied. Density Functional Theory (DFT) was used to calculate the optimised geometries and frontier molecular orbitals of DIPD Ni8c and bis(azocarboxylate) 19c, and Time Dependent DFT calculations allowed the prediction of electronic absorption spectra, whose characteristics corresponded well with those of the observed solution spectra. In the latter case, the calculated low-energy absorptions were unlike those of a typical porphyrin, due to the near-degeneracy of the highest filled frontier orbitals, and the wide energy separation between the unfilled orbitals. This feature was present in the observed spectrum.

Assessment of the molecular structure of an intermediate member of the triplite-zwieselite mineral series: A raman and infrared study

The mineral series triplite-zwieselite with theoretical formula (Mn2+)2(PO4)(F)-(Fe2+)2(PO4)(F) from the El Criolo granitic pegmatite, located in the Eastern Pampean Ranges of Córdoba Province, was studied using electron microprobe, thermogravimetry, and Raman and infrared spectroscopy. The analysis of the mineral provided a formula of (Fe1.00, Mn0.85, Ca0.08, Mg0.06)∑2.00(PO4)1.00(F0.80, OH0.20)∑1.00. An intense Raman band at 981 cm−1 with a shoulder at 977 cm−1 is assigned to the ν1 symmetric stretching mode. The observation of two bands for the phosphate symmetric stretching mode offers support for the concept that the phosphate units in the structure of triplite-zwieselite are not equivalent. Low-intensity Raman bands at 1012, 1036, 1071, 1087, and 1127 cm−1 are assigned to the ν3 antisymmetric stretching modes. A set of Raman bands at 572, 604, 639, and 684 cm−1 are attributed to the ν4 out-of-plane bending modes. A single intense Raman band is found at 3508 cm−1 and is assigned to the stretching vibration of hydroxyl units. Infrared bands are observed at 3018, 3125, and 3358 cm−1 and are attributed to water stretching vibrations. Supplemental materials are available for this article. Go to the publisher's online edition of Spectroscopy Letters to view the supplemental file.

Food structure : its formation and relationships with other properties

Food materials are complex in nature as it has heterogeneous, amorphous, hygroscopic and porous properties. During processing, microstructure of food materials changes which significantly affects other properties of food. An appropriate understanding of the microstructure of the raw food material and its evolution during processing is critical in order to understand and accurately describe dehydration processes and quality anticipation. This review critically assesses the factors that influence the modification of microstructure in the course of drying of fruits and vegetables. The effect of simultaneous heat and mass transfer on microstructure in various drying methods is investigated. Effects of changes in microstructure on other functional properties of dried foods are discussed. After an extensive review of the literature, it is found that development of food structure significantly depends on fresh food properties and process parameters. Also, modification of microstructure influences the other properties of final product. An enhanced understanding of the relationships between food microstructure, drying process parameters and final product quality will facilitate the energy efficient optimum design of the food processor in order to achieve high-quality food

Overvoltage and overloading prevention using coordinated PV inverters in distribution network

Overvoltage and overloading due to high utilization of PVs are the main power quality concerns for future distribution power systems. This paper proposes a distributed control coordination strategy to manage multiple PVs within a network to overcome these issues. PVs reactive power is used to deal with over-voltages and PVs active power curtailment are regulated to avoid overloading. The proposed control structure is used to share the required contribution fairly among PVs, in proportion to their ratings. This approach is examined on a practical distribution network with multiple PVs.

Learning the learning rate for prediction with expert advice

Most standard algorithms for prediction with expert advice depend on a parameter called the learning rate. This learning rate needs to be large enough to fit the data well, but small enough to prevent overfitting. For the exponential weights algorithm, a sequence of prior work has established theoretical guarantees for higher and higher data-dependent tunings of the learning rate, which allow for increasingly aggressive learning. But in practice such theoretical tunings often still perform worse (as measured by their regret) than ad hoc tuning with an even higher learning rate. To close the gap between theory and practice we introduce an approach to learn the learning rate. Up to a factor that is at most (poly)logarithmic in the number of experts and the inverse of the learning rate, our method performs as well as if we would know the empirically best learning rate from a large range that includes both conservative small values and values that are much higher than those for which formal guarantees were previously available. Our method employs a grid of learning rates, yet runs in linear time regardless of the size of the grid.

Superpixel-based appearance change prediction for long-term navigation across seasons

Changing environments pose a serious problem to current robotic systems aiming at long term operation under varying seasons or local weather conditions. This paper is built on our previous work where we propose to learn to predict the changes in an environment. Our key insight is that the occurring scene changes are in part systematic, repeatable and therefore predictable. The goal of our work is to support existing approaches to place recognition by learning how the visual appearance of an environment changes over time and by using this learned knowledge to predict its appearance under different environmental conditions. We describe the general idea of appearance change prediction (ACP) and investigate properties of our novel implementation based on vocabularies of superpixels (SP-ACP). Our previous work showed that the proposed approach significantly improves the performance of SeqSLAM and BRIEF-Gist for place recognition on a subset of the Nordland dataset under extremely different environmental conditions in summer and winter. This paper deepens the understanding of the proposed SP-ACP system and evaluates the influence of its parameters. We present the results of a large-scale experiment on the complete 10 h Nordland dataset and appearance change predictions between different combinations of seasons.

Prediction of GMA welding characteristic parameter by artificial neural network system

Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.

The implicit structure of positive characteristics

The implicit structure of positive character traits was examined in two studies of 190 and 100 undergraduates. Participants judged the pairwise covariation or semantic similarity of 42 positive characteristics using a sorting or a rating task. Characteristics were drawn from a new classification of strengths and virtues, the Five-Factor Model, and a taxonomy of values. Participants showed consistent patterns of perceived association among the characteristics across the study conditions. Multidimensional scaling yielded three consistent dimensions underlying these judgments (“warmth vs. self-control,” “vivacity vs. decency,” and “wisdom vs. power”). Cluster analyses yielded six consistent groupings—“self-control,” “love,” “wisdom,” “drive,” “vivacity,” and “collaboration”—that corresponded only moderately to the virtue classification. All three taxonomies were systematically related to this implicit structure, but none captured it satisfactorily on its own. Revisions to positive psychology’s classification of strengths are proposed.

Crystal structure of the magnesium salt of the herbicide 2,4-D: pentaaqua[(2,4-dichlorophenoxy)acetato-kO]magnesium (2,4-dichlorophenoxy)acetate hemihydrate

In the structure of the title magnesium complex with the phenoxy herbicide (2,4-dichlorophenoxy)acetic acid (2,4-D), [Mg(H2O)5(C8H5Cl2O3)]+ C8H5Cl2O3)- . 0.5H2O, the discrete cationic MgO6 complex units comprise a carboxyl O-donor from a monodentate 2,4-D cationic ligand and five water molecules in a slightly distorted octahedral coordination. The 2,4-D anions are linked to the complex units through duplex water O-H...O(carboxyl) hydrogen bonds through the coordinated water molecules. In the crystal inter-unit O-H...O hydrogen-bonding interactions involving coordinated water molecules as well as the hemi-hydrate solvate molecule with carboxyl O-atom acceptors, give a two-dimensional layered structure lying parallel (001), in which pi-pi ligand-cation interactions [minimum ring centroid separation, 3.6405(17)A] and a short O-H...Cl interaction [3.345(2)A] are also found.