A novel solid support for the synthesis of 3-aminoalkylated oligonucleotides

A novel improved controlled pore glass (CPG) support based on the 2-(hydroxymethyl)-6-nitrobenzoyl (HMNB) protecting group was developed for the synthesis of 3^′-aminoalkylated oligonucleotides. The release of oligonucleotides with free 3^′-amino groups from the support is complete within 2 h at 55 °C in concentrated ammonia.     

Exact Solution of a(2+1)-Dimensional Anisotropic Star in Finch and Skea Spacetime

We provide a new class of interior solution of a(2+1)-dimensional anisotropic star in Finch and Skea spacetime corresponding to the BTZ black hole. We develop the model by considering the MIT bag model EOS and a particular ansatz for the metric function grrproposed by Finch and Skea [M.R. Finch and J.E.F. Skea, Class. Quantum.Grav. 6(1989) 467]. Our model is free from central singularity and satisfies all the physical requirements for the acceptability of the model.     

Novel Stereoselective Phase Transfer Catalytic Synthesis and Some Applications of ( E )-2-Chlorovinylthioarenes and Hetarenes

A novel two-step method for the preparation of ( E )-2-chlorovinylthioarenes (or hetarenes) from thiols and 1,1,2-trichloroethane in the phase transfer catalytic systems solid K 2 CO 3 /solid KI/18-crown-6/xylene and solid KOH/18-crown-6/toluene has been developed. ( E )-2-chlorovinylthioarenes were isolated in yields up to 98%. Utilization of ( E )-2-chlorovinylthioarenes in the Heck and Stille reactions has been shown.     

Artificial neural network‐based modeling of snow properties using field data and hyperspectral imagery

This study attempts to model snow wetness and snow density of Himalayan snow cover using a combination of Hyperspectral image processing and Artificial Neural Network (ANN). Initially, a total of 300 spectral signature measurements, synchronized with snow wetness and snow density, were collected in the field. The spectral reflectance of snow was then modeled as a function of snow properties using ANN. Four snow wetness and three snow density models were developed. A strong correlation was observed in near‐infrared and shortwave‐infrared region. The correlation analysis of ANN modeled snow density and snow wetness showed a strong linear relationship with field‐based data values ranging from 0.87–0.90 and 0.88–0.91, respectively. Our results indicate that an Artificial Intelligence (AI) approach, using a combination of Hyperspectral image processing and ANN, can be efficiently used to predict snow properties (wetness and density) in the Himalayan region. Recommendations for resource managers

• Snow properties, such as snow wetness and snow density are mainly investigated through field‐based survey but rugged terrains, difficult weather conditions, and logistics management issues establish remote sensing as an efficient alternative to monitor snow properties, especially in the mountain environment.
• Although Hyperspectral remote sensing is a powerful tool to conduct the quantitative analysis of the physical properties of snow, only a few studies have used hyperspectral data for the estimation of snow density and wetness in the Himalayan region. This could be because of the lack of synchronized snow properties data with field‐based spectral acquisitions.
• In combination with Hyperspectral image processing, Artificial Neural Network (ANN) can be a useful tool for effective snow modeling because of its ability to capture and represent complex input‐output relationships.
• Further research into understanding the applicability of neural networks to determine snow properties is required to obtain results from large snow cover areas of the Himalayan region.

     

Hydrosilylation of Pyridinealdehydes and Acetylpyridines Catalyzed by Caesium Fluoride in the Presence of 18-Crown-6

Reactions of isomeric pyridinealdehydes and acetylpyridines with dime thylphenylsi lane proceed readily in dichloromethane in the presence of catalytic amounts of CsF and 18-crown-6 to give silyl ethers of the corresponding pyridyl carbinols in good yields (50–70%).     

Synthesis and Characterization of Novel Biodegradable Di‐ and Tri‐Block Copolymers Based on Ethylene Carbonate Polymer as Hydrophobic Segment

Synthesis of novel amphiphilic biodegradable block copolymers based on ethylene carbonate is reported in this study. Polyethylene glycol monomethyl ether (MeO‐PEO) and polyethylene glycol (PEG) of varying molar masses are used as macro‐initiator for ring‐opening polymerization of ethylene carbonate in the presence of sodium stannate trihydrate as a heterogeneous transesterification catalyst. Earlier elution of block copolymer from macro‐initiator in size exclusion chromatography (SEC) indicated the successful synthesis of the block copolymers. Ratios of both types of blocks are varied systematically. Liquid chromatography at critical conditions is used for the analysis of the non‐critical individual blocks, and if there are any critical segments that are not attached to the non‐critical block. To the best of our knowledge, this is the first report on the synthesis of ethylene carbonate‐based amphiphilic block copolymers. Chromatographic critical conditions of the ethylene carbonate polymer are also reported for the first time. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2017 , 55, 1887–1893     

Chiral Thirring–Wess model with Faddeevian regularization

Replacing vector type of interaction of the Thirring–Wess model by the chiral type a new model is presented which is termed here as chiral Thirring–Wess model. Ambiguity parameters of regularization are so chosen that the model falls into the Faddeevian class. The resulting Faddeevian class of model in general does not possess Lorentz invariance. However we can exploit the arbitrariness admissible in the ambiguity parameters to relate the quantum mechanically generated ambiguity parameters with the classical parameter involved in the masslike term of the gauge field which helps to maintain physical Lorentz invariance instead of the absence of manifestly Lorentz covariance of the model. The phase space structure and the theoretical spectrum of this class of model have been determined through Dirac’s method of quantization of constraint system.     

Synthesis of Isopropyl and Tert-butyl Pyridyl Ketones by Alkylation of Acetylpyridines with Methyl Iodide Using Phase Transfer Catalysis

Isomeric acetylpyridines undergo regiospecific alkylation with methyl iodide under solid/liquid phase transfer conditions (aromatic solvent/KOH/18-crown-6) to give the corresponding isopropyl and/or tert-butyl pyridyl ketones, depending on reaction conditions.