A Report on implementation of operational Global and Indian Ocean HYCOM at INCOIS

A state of the art operational forecasting system with data assimilation (DA) is established at INCOIS, which is the first of it's kind in the country. The Indian Ocean model is the highest resolution operational system with DA available for the basin compared to any operational agency in the world. The core of the system is a 1/16th eddy resolving Indian ocean Hybrid Coordinate Model (HYCOM), nested to a 1/4th Global HYCOM which provides lateral boundary conditions to the high-resolution model. The system uses data assimilation scheme based on Tentral Statistical Interpolation (T-SIS) scheme. A five-year hindcast for the period 2012 to 2016 has been carried out using both setups. This report presents a detailed evaluation of both global and Indian ocean models in comparison with observations and two other established systems, NRL HYCOM and GODAS from INCOIS. The five-year hindcast results show that both Indian Ocean and global model simulated SST, SSS, SLA, currents and vertical structure of the ocean favourably when compared with observations and other models. Bias, RMSD, correlation and skill score compared to observations from each of the four models for selected parameters are evaluated as part of this exercise. Sea-level and currents, show a notable better performance for the new setups at INCOIS over NRL-HYCOM and INCOIS-GODA

A VALIDATED RP-HPLC METHOD FOR IMPURITY PROFILING OF SODIUM NITROPRUSSIDE IN INJECTION DOSAGE FORM

Objective: The main objective of this research work is to develop and validate a single reverse-phase high-performance liquid chromatography (RP-HPLC) method. This method should becapable of quantifying all the known, as well as other possible degradation impurities of sodium nitroprusside (SNP) in its injection formulation. Methods: Of allmethod development trails, we have observed better separations between known and degradation impuritiesin Inert sustain C18, (250 x 4.6) mm, 5 µm column at 30 °C temperature. Isocratic elution was carried out by using pH 8.6 phosphate buffer and acetonitrile in the ratio of 65:35 %v/v with a flow rate of 0.8 ml/min. The detection was carried out at 220 nm, with an injection volume of 10 µl. Results: In the proposed method, SNP was eluted at 22.5 min. Nitrite, nitrate, and ferrocyanide were linear from 0.25 to 37 μg/ml, ferricyanide was linear from 1.0 to 37 μg/ml, and SNP was linear from 0.75 to 37 μg/ml. The % RSD for six spiked samples (precision)was found to be less than 0.5 %. Accuracy was performed for known impurities from LOQ to 150 % for a 0.5 % specification level. The resultswere found to be in the acceptance range of 90-110 %. The LOQ concentration of nitrite, nitrate, and ferrocyanide was 0.25 μg/ml each,LOQ offerricyanide and SNP was found to be 1.0 μg/ml and 0.75 μg/ml, respectively. The SNP injection samples were exposed to different degradation conditions, and the results were found specific in the proposed methodology. Conclusion: The proposed RP-HPLC method is specific, precise, accurate, linear, stable, and robust for quantification of known and other possible degradation impurities in SNP injection formulation

Rural Education and Employment Skill Improvement Model Using Artificial Intelligence

This groundbreaking initiative introduces an advanced AI-powered model designed to revolutionize education and employment prospects in rural communities. The Rural Education and Employment Skill Improvement Model is an all-encompassing solution that adapts learning paths using sophisticated AI algorithms, ensuring a personalized approach tailored to the unique challenges faced by rural learners. This model collaborates closely with local educators, leveraging technology to augment traditional teaching methods and bridge the digital divide. At its core, a cutting-edge Learning Management System (LMS) powered by AI integrates various features, including interactive video tutorials, real-time assessments, and a dynamic grading system. The system goes beyond conventional evaluations by employing AI to monitor and prevent cheating during exams, ensuring a fair and secure evaluation process. The multifaceted LMS also includes a job portal, facilitating a seamless transition from academia to the professional arena. Live meeting classes create an interactive virtual environment for real-time engagement, complemented by community discussion chat for collaborative learning. Notably, the project introduces a unique article-creation feature, allowing both instructors and students to contribute valuable content to the educational community. The success metrics of this ambitious project include improved educational outcomes, increased employment rates, and an overall enhancement in community well-being. Serving as a scalable and adaptable solution, this AI-driven model offers a transformative blueprint for leveraging technology to empower individuals in rural areas, paving the way for a more prosperous economic future

Analysis of Oil Content in Jatropha by Nuclear Magnetic Resonance Spectrometry

Thirty two diverse Jatropha curcas L. cultivars were analyzed for their oil content by the standard Soxhlet extraction method using hexane as solvent. The results were then compared with those obtained by nuclear magnetic resonance (NMR) spectrometer. The cultivars had a wide range in oil content, which ranged from 4.8 to 38.8% by the Soxhlet method, and from 6.0 to 38.9% by the NMR method. The values of oil content determined by the NMR method were highly significantly correlated (R2 = 0.9929, P<0.0001, n = 32) with those obtained using the Soxhlet method. The NMR method is simple, non-destructive, rapid, and accurate for the routine analysis of oil content in Jatropha

Comparative Evaluation of Inductively Coupled Plasma-Optical Emission Spectrometry and Colorimetry for Determining Phosphorus in Grain Samples

The inductively coupled plasma (ICP)-based method provides the opportunity to determine phosphorus (P) along with other major, secondary, micro and trace elements in plant materials. This study was conducted to compare and evaluate the relative efficacy of the inductively coupled plasma-optical emission spectrometry (ICP-OES) method with that of the colorimetric method using Skalar autoanalyzer, for determining P in 428 grain samples of eight diverse crops. The results on grain P analysis by the two methods, for individual as well as for all crop samples combined, showed that they were highly positively correlated (r varied from 0.84 to 0.98, p < 0.0001 for the eight crops, and R2 for all crop grain samples was 0.9201, p < 0.0001). Moreover, the precision by the ICP method was similar to that determined by the Skalar method. Our results demonstrate that the ICP-OES method can be conveniently used for determining P along with other plant nutrient elements in grain samples of diverse crops

Non-resonant microwave absorption studies of superconducting MgB_2

Non-resonant microwave absorption(NRMA) studies of superconducting MgB_2 at a frequency of 9.43 GHz in the field range -50 Gauss to 5000 Gauss are reported. The NRMA results indicate near absence of intergranular weak links. A linear temperature dependence of the lower critical field H_c1 is observed indicating a non s-wave superconductivity. However, the phase reversal of the NRMA signal which could suggest d-wave symmetry is also not observed.Comment: 8 pages, 2 figure

Comparative evaluation of protein content in groundnut samples by near infrared reflectance spectroscopy and Skalar colorimetric methods

A lot of research has been done in developing groundnut cultivars with high-quality oil. As a result, methods for routinely determining oil content and quality have been developed and utilized1. However, groundnut is also a source of protein, and obviously, there is a need to develop a rapid, accurate and economic method that can be routinely used for screening a large number of groundnut cultivars for protein content. At the ICRISAT analytical service laboratory, protein (total N) in various crops is routinely determined by colorimetric method using Skalar auto analyser. However, near infrared reflectance spectroscopy (NIRS) also provides an opportunity to determine protein content in groundnut samples; and the method seems attractive as it is low cost, simple and rapid. The NIRS based method provides an automated measurement and has the potential to become a valuable tool for providing analytical support for agricultural research2,3. The objectives of this study were to estimate and compare the relative efficacy of the NIRS method, with that of a conventional colorimetric method, following digestion of ground samples, using Skalar autoanalyser for determining protein in groundnut samples..

Stability and aromaticity of nH2@B12N12 (n=1–12) clusters

Standard ab initio and density functional calculations are carried out to determine the structure, stability, and reactivity of B12N12 clusters with hydrogen doping. To lend additional support, conceptual DFT-based reactivity descriptors and the associated electronic structure principles are also used. Related cage aromaticity of this B12N12 and nH2@B12N12 are analyzed through the nucleus independent chemical shift values

Enhanced Microwave Absorption Properties of Intrinsically Core/shell Structured La0.6Sr0.4MnO3Nanoparticles

The intrinsically core/shell structured La0.6Sr0.4MnO3nanoparticles with amorphous shells and ferromagnetic cores have been prepared. The magnetic, dielectric and microwave absorption properties are investigated in the frequency range from 1 to 12 GHz. An optimal reflection loss of −41.1 dB is reached at 8.2 GHz with a matching thickness of 2.2 mm, the bandwidth with a reflection loss less than −10 dB is obtained in the 5.5–11.3 GHz range for absorber thicknesses of 1.5–2.5 mm. The excellent microwave absorption properties are a consequence of the better electromagnetic matching due to the existence of the protective amorphous shells, the ferromagnetic cores, as well as the particular core/shell microstructure. As a result, the La0.6Sr0.4MnO3nanoparticles with amorphous shells and ferromagnetic cores may become attractive candidates for the new types of electromagnetic wave absorption materials