Study of Sunspot Penumbra to Umbra Area Ratio using Kodaikanal White-light Digitized Data

We study the long-term behaviour of sunspot penumbra to umbra area ratio by analyzing the recently digitized Kodaikanal white-light data (1923-2011). We implement an automatic umbra extraction method and compute the ratio over eight solar cycles (Cycles 16-23). Although the average ratio doesn't show any variation with spot latitudes, cycle phases and strengths, it increases from 5.5 to 6 as the sunspot size increases from 100 $\mu$hem to 2000 $\mu$hem. Interestingly, our analysis also reveals that this ratio for smaller sunspots (area $<$ 100 $\mu$hem) does not have any long-term systematic trend which was earlier reported from the Royal Observatory, Greenwich (RGO) photographic results. To verify the same, we apply our automated extraction technique on Solar and Heliospheric Observatory (SOHO)/Michelson Doppler Imager (MDI) continuum images (1996-2010). Results from this data not only confirm our previous findings, but also show the robustness of our analysis method.Comment: Accepted for publication in Solar Physics (15 pages, 10 figures

CURRENT DEVELOPMENTS ON ANTI-INFLAMMATORY NATURAL MEDICINES

New anti-inflammatory substances are still vitally necessary due to intolerable side effects of the marketed anti-inflammatory drugs; however, the search for the novel entity against inflammation is challenging because of the complexity of the inflammatory process and its role in host defense to infections. Nature is the source of remedies for the mankind. Among the different biological activities of natural products that have been published till date, anti-inflammation is one of the most reported effects. In this review, we have discussed the current (2009–2018) information of some single natural products (quercetin, parthenolide, resveratrol, curcumin, cucurbitacin, capsicin, 1,8-cineole, bromelain, boswellic acid, lyprinol, and coumarin), plant products (garlic, ginger, papaya, blueberry, aloe, broccoli, olive, and rosemary), and non-plant products (marine sponges, mushrooms, and honey) having anti-inflammatory effects. Current information is mainly based on the molecular mechanisms of the above-mentioned products

High pressure-temperature proton migration in P-3 brucite [Mg(OH)2]: Implication for electrical conductivity in deep mantle

Hydrous minerals contribute largely to the transport and distribution of water into the mantle of earth to regulate the process of deep-water cycle. Brucite is one of the simplest layered dense hydrous mineral belonging to MgO-SiO2-H2O ternary system, which contains significant amount of water in the form of OH- groups, spanning a wide range of pressure stability. Simultaneously, the pressure (p) and temperature (T) induced mobility of protons within the layered structure of brucite is crucial for consequences on electrical conductivity of the mantle. Using ab initio molecular dynamics (AIMD) simulations, we investigate the diffusion of H in high-pressure trigonal P-3 polymorph of brucite in a combined p-T range of 10-85 GPa and 1250-2000K, relevant to the mantle of earth. The AIMD simulations reveal an unusual pressure-dependence of the proton migration in brucite characterized by maximum H-diffusion in the pressure range of 72-76 GPa along different isotherms. We predict that in the P-3 brucite the H mobility is onset only when a critical hydrostatic pressure is attained. The onset pressure is observed to drop with increasing temperature. The H-diffusion in brucite phase at elevated p-T takes place in such a manner that the process results in the amorphization of the H-sublattice, without disturbing the Mg- and O-sublattices. This selective amorphization yields a pool of highly mobile protons causing a subsequent increment in the electrical conductivity in P-3 brucite. Our calculated values of conductivity are compared with ex-situ geophysical magnetic satellite data indicating that brucite can be present in larger quantities in the lower mantle than previously observed. This hydroxide phase can occur as segregated patches between the dominant constituents e.g., silicates and oxides of the lower mantle and thus can explain the origin of high electrical conductivity therein.Comment: Preliminary draft, 6 figures, presented in Goldschimdt 2023 Conference (Lyon, France), comments are welcom

FORMULATION DEVELOPMENT AND CHARACTERIZATION OF EFFERVESCENT TABLETS ALONG WITH LEVOCETIRIZINE DIHYDROCHLORIDE

Objective: Levocetirizine dihydrochloride is also known as “Xyzol.” Levocetirizine dihydrochloride is a second-generation piperazine derivative, potent H1 selective agent. Levocetirizine dihydrochloride is the active R (-) enantiomer of cetirizine dihydrochloride. In the case of an allergic or histaminic reaction, the medication must respond rapidly. Many older patients, infants, and dysphagia patients have trouble swallowing traditional tablets or capsules. Hence, a need exists for a relatively fast-acting effervescent tablet form. Methods: The tablets were prepared by direct compression method using citric acid and sodium bicarbonate as effervescent agents. Then, they were tested for parameters of pre- and post-compression. Tablets were evaluated for studies of general appearance, uniformity of substance, hardness, friability, and in vitro dissolution. Results: More than 90% of the drug was released from almost all the formulations within 1 min. More formulations underwent rapid 90-day stability trials. Conclusion: No major changes in the taste, disintegration, and dissolution profiles were found in tablets

FORMULATION AND EVALUATION OF ANTI-ACNE GEL CONTAINING MURRAYA KOEINIGII EXTRACT

Objective: Acne, one among the very fashionable socially distressing skin conditions created by Propionibacterium acne have generally been treated by antibiotics. Within the light of the growing threat of antibiotic resistance, natural plant products are applied as a safer alternative. Keeping the very fact in the background, during this research work, the formulation of gel from the extracts of Murraya koeinigii leaves are prepared and evaluated as an anti-acne drug. Methods: The fresh leaf extracts were subjected to phytochemical and antimicrobial screening. Minimum Inhibitory Concentration (MIC) decided. Gel formulation of the extracts was developed and evaluated. The manufactured formulations were subjected to In vitro antibacterial activity against P. acnes, S. epidermidis and S. aureus. The marker compound, clindamycin, in herbal anti-acne preparation, was kept for the comparison with the zones of inhibition for antibacterial activity. Results: Anti-acne property was explored with the help of a standard curve and by comparing diffusion profiles by taking clindamycin as a reference. Conclusion: From the present study it can be concluded that addition of permeation enhancer in the test formulation will improve the diffusion profile and thus it was designed to add permeation enhancer

Is Attention always needed? A Case Study on Language Identification from Speech

Language Identification (LID) is a crucial preliminary process in the field of Automatic Speech Recognition (ASR) that involves the identification of a spoken language from audio samples. Contemporary systems that can process speech in multiple languages require users to expressly designate one or more languages prior to utilization. The LID task assumes a significant role in scenarios where ASR systems are unable to comprehend the spoken language in multilingual settings, leading to unsuccessful speech recognition outcomes. The present study introduces convolutional recurrent neural network (CRNN) based LID, designed to operate on the Mel-frequency Cepstral Coefficient (MFCC) characteristics of audio samples. Furthermore, we replicate certain state-of-the-art methodologies, specifically the Convolutional Neural Network (CNN) and Attention-based Convolutional Recurrent Neural Network (CRNN with attention), and conduct a comparative analysis with our CRNN-based approach. We conducted comprehensive evaluations on thirteen distinct Indian languages and our model resulted in over 98\% classification accuracy. The LID model exhibits high-performance levels ranging from 97% to 100% for languages that are linguistically similar. The proposed LID model exhibits a high degree of extensibility to additional languages and demonstrates a strong resistance to noise, achieving 91.2% accuracy in a noisy setting when applied to a European Language (EU) dataset.Comment: Accepted for publication in Natural Language Engineerin