Iodine photodissociation laser system Perun II

A construction and exploitation of a medium size iodine photodissociation laser system Perun II is reported. This laser produced pulses of infrared light (=1.315m) up to 50 J in energy and 300 ps in duration. The diameter of the beam is 82 mm. The beam divergence is about 4×10^–4 rad. The laser beam can be focused in a focal spot of a power density exceeding 10¹⁴ W/cm². The resuls of measurements of basic plasma parameters on an Al foil target are also presented. A recent improvement of the system includes a conversion to the second harmonic by a DKDP crystal.Presented at bilateral international seminar of High Temperature Laser Plasma and High Gain Iodine Lasers held on 4 July 1991 in the Inst. of Physics, Czechosl. Acad. Sci., in Prague (organized by Division of Optics of the Inst. of Physics, Czechosl. Acad. Sci., and Physical Section (Plasma Division) of the Union of Czech Mathematicians and Physicists.     

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.     

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.

     

Novel Method for HPLC Analysis of Triterpenic Acids Using 9-Anthryldiazomethane Derivatization and Fluorescence Detection

Triterpenic acids are a group of secondary plant metabolites which are part of the cuticular waxes covering fruits, leaves, and flowers. To date, quantitative analysis of these compounds has often been conducted using high-performance liquid chromatography coupled with spectrophotometric detection or mass spectrometry; however, these methods have some major drawbacks. This paper reports a new method of analysis implementing derivatization with 9-anthryldiazomethane and fluorescence detection. The method consists of the extraction of analytes from a matrix, purification with anion exchanging SPE columns, and an optional step of the alkaline hydrolysis of triterpenic acid esters. The paper also describes a fast and easy method for the synthesis of the derivatization agent. The detection limits of the method presented are approximately 100-fold lower than in a similar method using ultraviolet spectrophotometry as the mode of detection. The recovery and repeatability of the method are at satisfactory levels.     

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.     

Non-destructive elemental analysis of large meteorite samples by prompt gamma-ray neutron activation analysis with the internal mono-standard method

Prompt gamma-ray neutron activation analysis (PGNAA) using the internal mono-standard method was tested for its applicability to analyzing large solid samples including irregularly shaped meteorite samples. For evaluating the accuracy and precision of the method, large quantities of the Geological Survey of Japan standardized rock powders (JB-1a, JG-1a, and JP-1) were analyzed and 12 elements (B, Na, Mg, Al, Cl, K, Ca, Ti, Mn, Fe, Sm, and Gd) were determined by using Si as an internal standard element. Analytical results were mostly in agreement with literature values within 10 %. The precision of the method was also shown to be within 10 % (1σ) for most of these elements. The analytical procedure was then applied to four stony meteorites (Allende, Kimble County, Leedey, Lake Labyrinth) and four iron meteorites (Canyon Diablo, Toluca (Mexico), Toluca (Xiquipilco), Squaw Creek) consisting of large chunks or single slabs. For stony meteorites, major elements (Mg, Al, Si, S, Ca, and Ni), minor elements (Na and Mn) and trace element (B, Cl, K, Ti, Co, and Sm) were determined with adequate accuracy. For iron meteorites, results for the Co and Ni mass fractions determined are all consistent with corresponding literature values. After the analysis, it was confirmed that the residual radioactivity remaining in the sample after PGNAA was very low and decreased down to the background level. This study shows that PGNAA with the internal mono-standard method is highly practical for determining the elemental composition of large, irregularly shaped solid samples including meteorites.     

Molecular diversity from aromatics. A tandem oxidative dearomatization,cycloaddition and reactivity modulation in excited states: synthesis of tricyclo[5.3.1.0]undecanes and bicyclo[4.2.0]octanes from common precursors

Stereoselective route to tricyclo[5.3.1.0^1,5]undecane and bicyclo[4.2.0]octane ring systems present in the molecular structure of tricycloillicinone, cedrenoids and endiandric acid, elysiapyrones, respectively, is described. A tandem oxidative dearomatization of o-hydroxymethylphenol, π⁴s+π²s cycloaddition, reactivity modulation in excited state and ring-closing metathesis are the key features of our approach.