Weibull Distribution and the multiplicity moments in pp (ppˉ)pp\,(p\bar{p}) collisions

A higher moment analysis of multiplicity distribution is performed using the Weibull description of particle production in $pp\,(p\bar{p})$ collisions at SPS and LHC energies. The calculated normalized moments and factorial moments of Weibull distribution are compared to the measured data. The calculated Weibull moments are found to be in good agreement with the measured higher moments (up to 5$^{\rm{th}}$ order) reproducing the observed breaking of KNO scaling in the data. The moments for $pp$ collisions at $\sqrt{s}$ = 13 TeV are also predicted.Comment: 5 pages, 3 figure

PROTEOLYTIC AND MILK CLOTTING ACTIVITY OF FRACTIONATED PROTEIN OF CITRULLUS LANATUS

Objective: The objective of the present investigation was to evaluate milk clotting activity as well as proteolytic activity of protein fractions of seeds of Citrullus lanatus.Methods: Storage proteins were extracted by differential solubility, and their contents were estimated using the Bradford method. The effect of pH and temperature on the milk-clotting activity and proteolytic activity was also evaluated.Results: Citrullus lanatus showed highest milk clotting activity over a broad temperature range of 30-80 ºC and pH range of 3-9.Conclusion: These findings showed that Citrullus lanatus have proteolytic activity which might be a potentially suitable substitute for commercial animal rennet for cheese-ripening.Â

FORMULATION AND STATISTICAL OPTIMIZATION OF BILAYER SUBLINGUAL TABLETS OF LEVOCETIRIZINE HYDROCHLORIDE AND AMBROXOL HYDROCHLORIDE

Objective: The aim of the present study is to formulate and optimize bilayer sublingual tablets of Levocetrizine hydrochloride and Ambroxolhydrochloride using a 23 response surface methodology employing design expert-10.0. Sodium starch glycolate and Camphor were selected asindependent variables while disintegration time (sec) and water absorption ratio (%) were considered as responses.Methods: The bilayer sublingual tablets were prepared by direct compression and evaluated for various evaluation parameters including hardness,thickness, friability, drug content uniformity, wetting time, water absorption ratio and disintegration time. The prepared optimized bilayer sublingualtablets of Levocetrizine hydrochloride and Ambroxol hydrochloride having above 2 responses-disintegration time (sec) and water absorption ratio.Results: The optimized batch having concentration of sodium starch glycolate and camphor was found within the standard limit of parametersdisintegrationtime (sec) and water absorption ratio (%) as 61 sec and 69.67%.Conclusion: The direct compression method in this study is relatively simple and safe and a stable, effective and pleasant tasting bilayer sublingualtablet, which has a good balance over disintegration time and water absorption ratio, was formulated.Keywords: Levocetirizine hydrochloride, Ambroxol hydrochloride, Croscarmellose sodium, Sodium starch glycolate, Camphor, Statistical optimization

Agricultural Waste based Biocomposite for Electromagnetic Shielding Application

The enhanced significant use of electromagnetic wave introduces new type of pollution in the environment called Electromagnetic Interference (EMI). Different shielding techniques though successfully works in the present scenario but small efficiency of attenuation and absorption capacity of traditional ceramics demands some alternative potential material for enhanced shielding efficiency, which can be realised from agricultural waste such as rice husk, sugarcane bagasse, etc. Further, the shielding structure and composition of composite are the current issues which depend on the dielectric properties of the fabricated materials. In the current work, rice husk, an organic biomaterial rich in carbon, is combined with epoxy The enhanced significant use of electromagnetic wave introduces new type of pollution in the environment called Electromagnetic Interference (EMI). Different shielding techniques though successfully works in the present scenario but small efficiency of attenuation and absorption capacity of traditional ceramics demands some alternative potential material for enhanced shielding efficiency, which can be realised from agricultural waste such as rice husk, sugarcane bagasse, etc. Further, the shielding structure and composition of composite are the current issues which depend on the dielectric properties of the fabricated materials. In the current work, rice husk, an organic biomaterial rich in carbon, is combined with epoxy to create a microwave absorber that is flexible, inexpensive, and eco-friendly. The different microwave absorbing property such as complex dielectric, tangent loss, attenuation constant and Reflection Loss (RL) of −14.5 dB at frequency 10 GHz are found to be possessed by the synthesized composite of thickness 3 mm which is determined from composite’s dielectric values. The attenuation coefficient supports the measured values of RL, highlighting the significance of the suggested composite material with a power attenuation efficiency of around 87% for legitimate microwave absorption applications. The presence of good percentage of elemental combination like carbon, oxygen and silicon makes it possible for increasing the percentage of activated carbon which is not present in any other synthetic component for the same purpose. Further use of carbon rich waste material is an advantageous impetus for material industries to enhance the percentage of activated carbon for shielding purpose

Identification and quantification of biological active constituents of Amritarishta, a herbal formulation

Herbal formulations have been used by Indian and Chinese traditional systems of medication for a long time. Amritarishtais one of the herbal formulations that possess various biological activity viz., antioxidant, anticancer, analgesic, antipyretic,antidiabetic, etc. The active constituents include gallic acid, tannic acid, piperine, and quercetin, etc. Ethanolic extract of theformulation was analysed and quantified. Rf (Retardation factor), functional groups and amount of some of the major chemicalconstituents were analysed by TLC, FTIR, LC/MS, HPTLC and HPLC, respectively. LC/MS results reveal the presence ofquercetin, piperine, tannic acid and gallic acid in the formulation. With the help of HPTLC and HPLC, the quantity of 4chemical constituents in the formulation was estimated. This type of study is completely new to herbal research

Genomic characterization and epidemiology of an emerging SARS-CoV-2 variant in Delhi, India

Delhi, the national capital of India, experienced multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks in 2020 and reached population seropositivity of >50% by 2021. During April 2021, the city became overwhelmed by COVID-19 cases and fatalities, as a new variant, B.1.617.2 (Delta), replaced B.1.1.7 (Alpha). A Bayesian model explains the growth advantage of Delta through a combination of increased transmissibility and reduced sensitivity to immune responses generated against earlier variants (median estimates: 1.5-fold greater transmissibility and 20% reduction in sensitivity). Seropositivity of an employee and family cohort increased from 42% to 87.5% between March and July 2021, with 27% reinfections, as judged by increased antibody concentration after a previous decline. The likely high transmissibility and partial evasion of immunity by the Delta variant contributed to an overwhelming surge in Delhi

Shape recognition through multi-level fusion of features and classifiers

Shape recognition is a fundamental problem and a special type of image classification, where each shape is considered as a class. Current approaches to shape recognition mainly focus on designing low-level shape descriptors, and classify them using some machine learning approaches. In order to achieve effective learning of shape features, it is essential to ensure that a comprehensive set of high quality features can be extracted from the original shape data. Thus we have been motivated to develop methods of fusion of features and classifiers for advancing the classification performance. In this paper, we propose a multi-level framework for fusion of features and classifiers in the setting of gran-ular computing. The proposed framework involves creation of diversity among classifiers, through adopting feature selection and fusion to create diverse feature sets and to train diverse classifiers using different learn-Xinming Wang algorithms. The experimental results show that the proposed multi-level framework can effectively create diversity among classifiers leading to considerable advances in the classification performance