Electrical and Magnetic behaviour of PrFeAsO0.8F0.2 superconductor

The superconducting and ground state samples of PrFeAsO0.8F0.2 and PrFeAsO have been synthesised via easy and versatile single step solid state reaction route. X-ray & Reitveld refine parameters of the synthesised samples are in good agreement to the earlier reported value of the structure. The ground state of the pristine compound (PrFeAsO) exhibited a metallic like step in resistivity below 150K followed by another step at 12K. The former is associated with the spin density wave (SDW) like ordering of Fe spins and later to the anomalous magnetic ordering for Pr moments. Both the resistivity anomalies are absent in case of superconducting PrFeAsO0.8F0.2 sample. Detailed high field (up to 12Tesla) electrical and magnetization measurements are carried out for superconducting PrFeAsO0.8F0.2 sample. The PrFeAsO0.8F0.2 exhibited superconducting onset (Tconset) at around 47K with Tc({\rho} =0) at 38K. Though the Tconset remains nearly invariant, the Tc({\rho} =0) is decreased with applied field, and the same is around 23K under applied field of 12Tesla. The upper critical field (Hc2) is estimated from the Ginzburg Landau equation (GL) fitting, which is found to be ~ 182Tesla. Critical current density (Jc) being calculated from high field isothermal magnetization (MH) loops with the help of Beans critical state model, is found to be of the order of 103 A/cm2. Summarily, the superconductivity characterization of single step synthesised PrFeAsO0.8F0.2 superconductor is presented.Comment: 15 Pages Text + Fig

Pengaruh Jumlah Stasiun Hujan terhadap Kinerja Metode Storage Function dalam Penentuan Debit Banjir Rancangan

Storage Function Method is a method applied in discharge calculation with consideration on catchments characteristics. This method is commonly used in Indonesia by the Japanese experts. The discharge calculation provided by the method is highly influenced by the catchments rainfall, thus the difference of rainfall station number will effect the accuracy of the calculation result. The objective of this study is to investigate the effect of difference in the number of rainfall stations on the value of model parameters as well as the accuracy of discharge calculation using the storage function method on Kali Madiun Basin. Basically, the concept used in the storage function method is a water balance, which is analyzed using the mathematical model. The data used in this research are the 10 days hourly rainfall during the flood, and the catchment characteristics constant as the model parameters. Using the trial procedure, the catchments characteristics constant as the input for each of the numbers of rainfall station (2;3;4;5;6; and 7 stations) will provide the 10 days hourly discharge, then the result will be calibrated to the observed data. Based on the calibration result, the smallest deviation of each rainfall station will be selected in order to identify the model parameter and to provide deviation of the observed data. The investigated deviation is the different value between the calculated and the observed runoff, includes volume deviation as well as the 10 days hourly discharge deviation, which are located at the control node of AWLR Sekayu and AWLR A. Yani. Based on the calibration results, it is shown that the largest volume deviation at AWLR Sekayu is 31.64% that occurs on 2 rainfall stations, while the smallest occurs on 6 rainfall stations with deviation of 17.43%. It is also shown that the largest discharge is 37.29% and occurs on 2 rainfall stations, while the largest and the smallest discharge deviations respectively are 36.7% that occurs on 2 rainfall stations and 26.39% that occurs on 7 rainfall stations. Based on the results, it is shown that although the largest number of rainfall station is not the most accurate, but in general, as shown in the graphical results, it is indicated that more numbers of rainfall stations tend to provide better accuracy

Prospecting for scarabid specific Bacillus thuringiensis crystal toxin cry8 gene in sugarcane ecosystem of Tamil Nadu, India

In the present study, we report the occurrence of cry8 positive isolates of Bacillus thuringiensis (Bt) in selected white grub, Holotrichia serrata F. (Coleoptera: Scarabaeidae), endemic soils of sugarcane ecosystem and other places in Tamil Nadu. Out of the 66 soil samples collected and screened for white grub specific Bt, 74 isolates of the bacterium, all containing only spherical crystal toxin, were identified. PCR screening of these isolates with cry8 gene universal primer revealed six isolates to be positive. Further, the amplicon of a 370 bp band, amplified with another set of degenerate primer designed based on the conserved sequence of cry8 genes, was sequenced from four isolates. Multiple sequence alignment revealed the gene sequences to be the same for all the isolates. The present report of the availability of cry8 positive Bt isolates opens the avenue for controlling white grubs through transgenic research

The Irreducible String and an Infinity of Additional Constants of Motion in a Deposition-Evaporation Model on a Line

We study a model of stochastic deposition-evaporation with recombination, of three species of dimers on a line. This model is a generalization of the model recently introduced by Barma {\it et. al.} (1993 {\it Phys. Rev. Lett.} {\bf 70} 1033) to $q\ge 3$ states per site. It has an infinite number of constants of motion, in addition to the infinity of conservation laws of the original model which are encoded as the conservation of the irreducible string. We determine the number of dynamically disconnected sectors and their sizes in this model exactly. Using the additional symmetry we construct a class of exact eigenvectors of the stochastic matrix. The autocorrelation function decays with different powers of $t$ in different sectors. We find that the spatial correlation function has an algebraic decay with exponent 3/2, in the sector corresponding to the initial state in which all sites are in the same state. The dynamical exponent is nontrivial in this sector, and we estimate it numerically by exact diagonalization of the stochastic matrix for small sizes. We find that in this case $z=2.39\pm0.05$.Comment: Some minor errors in the first version has been correcte