Shape variation in epitaxial microstructures of gold silicide grown on Br-passivated Si(1 1 1) surfaces

Kinetic Monte Carlo simulations for growth on substrates of three-fold symmetry predict the growth of islands of various shapes depending on the growth temperature [Phys. Rev. Lett. 71 (1993) 2967]. On Br-Si(1 1 1) substrates growth of epitaxial gold silicide islands of equilateral triangular and trapezoidal shapes have earlier been observed by annealing at the Au-Si eutectic temperature, 363 °C [Phys. Rev. B 51 (1995) 14330]. We carried out annealing with temperature variation within a small window--(363 ± 30) °C. This has led to island growth of additional shapes like regular hexagon, elongated hexagon, walled hexagon and dendrite. Some of the observed island shapes have not been predicted.     

Two optimized synthetic pathways toward a chiral precursor of Mivacurium chloride and other skeletal muscle relaxants

A chiral precursor of Mivacurium chloride, (R)-5′-methoxylaudanosine, was prepared using two different methods. The chiral resolution of racemic 5′-methoxylaudanosine, typically used in industry, was carried out in parallel with a procedure consisting of asymmetric transfer hydrogenation (ATH) and reductive methylation. A novel one-pot synthetic step was developed for the synthesis of racemic 5′-methoxylaudanosine. In both routes, the enantioselectivity was high but further purification was necessary to reach the level of a pharmaceutical standard. The individual synthetic steps reported herein can also be used for the synthesis of analogous bistetrahydroisoquinoline-based skeletal muscle relaxants.     

A cross-validation method for data with ties in kernel density estimation

Limitation of the cross-validation method of bandwidth selection is well known when applied to data with ties. A method which resolves this problem and which is easy to understand and implement is proposed. We show that the proposed approach is viable in theory, by proving its asymptotic equivalence to the standard cross-validation method. The practical usefulness is shown in simulations and an application to a real data example.     

Fit-for-Purpose Assessment of QuEChERS LC-MS/MS Methods for Environmental Monitoring of Organotin Compounds in the Bottom Sediments of the Odra River Estuary

Organotin compounds (OTCs) are among the most hazardous substances found in the marine environment and can be determined by either the ISO 23161 method based on extraction with non-polar organic solvents and gas chromatography analysis or by the recently developed QuEChERS method coupled to liquid chromatography-mass spectrometry (LC-MS/MS). To date, the QuEChERS LC/MS and ISO 23161 methods have not been compared in terms of their fit-for-purpose and reliability in the determination of OTCs in bottom sediments. In the case of ISO 23161, due to a large number of interferences gas chromatography-mass spectrometry was not suitable for the determination of OTCs contrary to more selective determination by gas chromatography with an atomic emission detector. Moreover, it has been found that the derivatization of OTCs to volatile compounds, which required prior gas chromatography determination, was strongly affected by the sediments’ matrices. As a result, a large amount of reagent was needed for the complete derivatization of the compounds. Contrary to ISO 23161, the QuEChERS LC-MS/MS method did not require the derivatization of OTC and is less prone to interferences. Highly volatile and toxic solvents were not used in the QuEChERS LC-MS/MS method. This makes the method more environmentally friendly according to the principles of green analytical chemistry. QuEChERS LC-MS/MS is suitable for fast and reliable environmental monitoring of OTCs in bottom sediments from the Odra River estuary. However, determination of di- and monobutyltin by the QuEChERS LC-MS/MS method was not possible due to the constraints of the chromatographic system. Hence, further development of this method is needed for monitoring di- and monobutyltin in bottom sediments.     

Application of a Multilayer Perceptron Artificial Neural Network for the Prediction and Optimization of the Andrographolide Content in Andrographis paniculata

Andrographolide, the principal secondary metabolite of Andrographis paniculata, displays a wide spectrum of medicinal activities. The content of andrographolide varies significantly in the species collected from different geographical regions. Therefore, this study aims at investigating the role of different abiotic factors and selecting suitable sites for the cultivation of A. paniculata with high andrographolide content using a multilayer perceptron artificial neural network (MLP-ANN) approach. A total of 150 accessions of A. paniculata collected from different regions of Odisha and West Bengal in eastern India showed a variation in andrographolide content in the range of 0.28–5.45% on a dry weight basis. The MLP-ANN was trained using climatic factors and soil nutrients as the input layer and the andrographolide content as the output layer. The best topological ANN architecture, consisting of 14 input neurons, 12 hidden neurons, and 1 output neuron, could predict the andrographolide content with 90% accuracy. The developed ANN model showed good predictive performance with a correlation coefficient (R²) of 0.9716 and a root-mean-square error (RMSE) of 0.18. The global sensitivity analysis revealed nitrogen followed by phosphorus and potassium as the predominant input variables influencing the andrographolide content. The andrographolide content could be increased from 3.38% to 4.90% by optimizing these sensitive factors. The result showed that the ANN approach is reliable for the prediction of suitable sites for the optimum andrographolide yield in A. paniculata.