Crossing point phenomena (T* = 2.7 K) in specific heat curves of superconducting ferromagnets RuSr2Gd1.4Ce0.6Cu2O10-{\delta}

Crossing point phenomena are one of the interesting and still puzzling effects in strongly correlated electron systems. We have synthesized RuSr2Gd1.4Ce0.6Cu2O10-{\delta} (GdRu-1222) magneto-superconductor through standard solid state reaction route and measured its magnetic, transport and thermal properties. We also synthesized RuSr2Eu1.4Ce0.6Cu2O10-{\delta} (EuRu-1222) then measured its heat capacity in zero magnetic fields for reference. The studied compounds crystallized in tetragonal structure with space group I4/mmm. GdRu-1222 is a reported magneto-superconductor with Ru spins magnetic ordering at temperature around 110 K and superconductivity in Cu-O2 planes below around 40 K. To explore the crossing point phenomena, the specific heat [Cp (T)] was investigated in temperature range 1.9-250 K, under magnetic field of up to 70 kOe. Unfortunately though no magnetic and superconducting transitions are observed in specific heat, a Schottky type anomaly is observed at low temperatures below 20 K. This low temperature Schottky type anomaly can be attributed to splitting of the ground state spectroscopic term 8S7/2 of paramagnetic Gd3+ ions by both internal and external magnetic fields. It was also observed that Cp (T) being measured for different values of magnetic field, possesses the same crossing point (T* = 2.7 K), up to the applied magnetic field 70 kOe. A quantitative explanation of this phenomenon, based on its shape and temperature dependence of the associated generalized heat capacity (Cp), is presented. This effect supports the crossing point phenomena, which is supposed to be inherent for strongly correlated systems.Comment: 12 pages Text+Figs ([email protected]

Bioconversion of eugenol into food flavouring agent vanillin

Microorganisms have the ability to chemically modify a wide variety of organic compounds by a process referred to as biological or microbial transformation, or in general, bioconversion. The microbial cells and their catalytic machinery (enzymes) accept a wide array of complex molecules as substrates, yielding products with unparallel chiral (enantio-), positional (region-) and chemical (chemo-) selectivity through various biochemical reactions. The present study was formulated on the objective of the conversion of abundantly available phytomolecules eugenol into vanillin, a compound of industrial importance, using microorganisms Aspergillus flavus, Aspergillus niger and Pseudomonas aeruginosa. These microbes were found to be capable of converting eugenol to industrially important cost-effective products, vanillin (used as flavouring agent). The results were analyzed using thin layer and gas chromatographic techniques. Our results demonstrated that A. flavus, A. niger and P. aerouginosa were able to transform eugenol to vanillin. Our findings may provide a novel approach for the production of cost-effective vanillin using microorganisms

Mutual Information in Frequency and its Application to Measure Cross-Frequency Coupling in Epilepsy

We define a metric, mutual information in frequency (MI-in-frequency), to detect and quantify the statistical dependence between different frequency components in the data, referred to as cross-frequency coupling and apply it to electrophysiological recordings from the brain to infer cross-frequency coupling. The current metrics used to quantify the cross-frequency coupling in neuroscience cannot detect if two frequency components in non-Gaussian brain recordings are statistically independent or not. Our MI-in-frequency metric, based on Shannon's mutual information between the Cramer's representation of stochastic processes, overcomes this shortcoming and can detect statistical dependence in frequency between non-Gaussian signals. We then describe two data-driven estimators of MI-in-frequency: one based on kernel density estimation and the other based on the nearest neighbor algorithm and validate their performance on simulated data. We then use MI-in-frequency to estimate mutual information between two data streams that are dependent across time, without making any parametric model assumptions. Finally, we use the MI-in- frequency metric to investigate the cross-frequency coupling in seizure onset zone from electrocorticographic recordings during seizures. The inferred cross-frequency coupling characteristics are essential to optimize the spatial and spectral parameters of electrical stimulation based treatments of epilepsy.Comment: This paper is accepted for publication in IEEE Transactions on Signal Processing and contains 15 pages, 9 figures and 1 tabl

Mixed Ligand Chelates of Th (IV) with EDT A & CDT A as Primary Ligands & Glycine, dl-a-Alanine & Phenylalanine as Secondary Ligands

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Light Absorption in NO2 Ion in State of Solution (Part III- Effect of Cation)

200mμ band, which is an allowed π-π* transition has been studied in five monovalent nitrates. The blue shift of the band has been found to be proportional to the inverse of the cationic radius