Production of Native Advertising in the New Media Economy

The need to study the production of advertising content from an academic standpoint, particularly advertising content that mimics or is embedded in other editorial content, in some form or the other, is greater than ever. Emerging marketing techniques such as native advertising, content marketing, and sponsored content have disrupted traditional media eco-systems and created a new media economy. While traditional advertising research is skewed in the favor of the consumer experience, researching the production and the lived experiences of journalists involved in the production of native advertising can yield promising results. This project discusses native ethnographic fieldwork that has been conducted in the study of advertising practices and its place in society and culture. I discuss and reflect on my own experience of conducting on-site fieldwork on how advertising and journalism are intersecting at Lessiter Media, a contemporary publishing firm, in an attempt to build further on this growing body of advertising research. It is also an attempt to participate in the larger conversation about the blurring lines between advertising and news. My research explores questions that attempt to situate native advertising in the new media economy and understand the idea of disruption in the context of native advertising

Evolution of Primordial Black Holes in Loop Quantum Gravity

In this work, we study the evolution of Primordial Black Holes within the context of Loop Quantum Gravity. First we calculate the scale factor and energy density of the universe for different cosmic era and then taking these as inputs we study evolution of primordial black holes. From our estimation it is found that accretion of radiation does not affect evolution of primordial black holes in loop quantum gravity even though a larger number of primordial black holes may form in early universe in comparison with Einstein's or scalar-tensor theories.Comment: 8 pages, 1 figur

Evolution of Primordial Black Hole Mass Spectrum in Brans-Dicke Theory

We investigate the evolution of primordial black hole mass spectrum by including both accretion of radiation and Hawking evaporation within Brans-Dicke cosmology in radiation, matter and vacuum-dominated eras. We also consider the effect of evaporation of primordial black holes on the expansion dynamics of the universe. The analytic solutions describing the energy density of the black holes in equilibrium with radiation are presented. We demonstrate that these solutions act as attractors for the system ensuring stability for both linear and nonlinear situations. We show, however, that inclusion of accretion of radiation delays the onset of this equilibrium in all radiation, matter and vacuum-dominated eras.Comment: 18 pages, one figur

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

Optimized hybrid nanospheres immobilizing Rhizomucor miehei lipase for chiral biotransformation

[EN] In this study, the immobilization of Rhizomucor miehei lipase into hybrid nanospheres containing a liposomal core was reported. Organic internal liposomal enzyme phase was protected by inorganic silica matrix, obtained with and without surfactant, that stabilizes the internal organic phase and isolates and protects the bioactive molecules. The optimized heterogeneous catalyst thus prepared was used for enantioselective esterification of (R,S)-ibuprofen. The influence of several catalytic parameters on the activity of hybrid nanospheres (type of solvent, nature of the alcohol, reaction temperature, etc.,) was investigated. The heterogeneous biocatalysts best performed at 37 degrees C, using isooctane as solvent and 1-propanol as alcohol (with ester yield ranging between 78 and 93%). High activity and stability (up to nine reaction cycles) of enzyme-immobilized hybrid nanospheres, with respect to the free form, were observed. R. miehei lipase, both in its free and immobilized forms, reacts only with the S(+) enantiomer of (R,S)-ibuprofen, in all the tested reaction conditions. (C) 2015 Elsevier Ltd. All rights reserved.The authors thank the financial support from Consolider-Ingenio MULTICAT CSD2009-00050, MAT2014-52085-C2-1-P, and Severo Ochoa Excellence Program SEV-2012-0267.Verri, F.; Díaz Morales, UM.; Macario, A.; Corma Canós, A.; Giordano, G. (2016). Optimized hybrid nanospheres immobilizing Rhizomucor miehei lipase for chiral biotransformation. Process Biochemistry. 51(2):240-248. https://doi.org/10.1016/j.procbio.2015.11.020S24024851

Efficient graph neural networks for travelling salesman problem using multilevel clustering

The goal of the Travelling Salesman Problem is to find the shortest route that visits each city exactly once and returns to the origin, given a list of cities and the distances between each pair of cities. Such combinatorial optimization problems are difficult to solve efficiently given large problem sizes. Algorithms that solve such problems have applications in many fields such as transportation, operations, and networks. Most solutions formulate heuristics which are policies used by algorithms to search for approximate solutions. These heuristics are designed manually and require specialized knowledge. Graph neural networks have recently been used to automate the creation of these heuristics. However, current state-of-the-art graph neural networks have slow training and inference times due to their O(n2) time complexity. In this paper, we introduce a Multilevel Graph Neural Network (MGNN) for approximating solutions to the TSP by using graph clustering which solves the TSP at multiple resolutions. We train our models on input graph sizes of up to 128 nodes and measure the accuracy as well as experimental time complexity with respect to the graph size. Our divide-and-conquer strategy effectively combats combinatorial explosion by enabling a linear runtime of O(n) at the cost of model accuracy.Bachelor of Engineering (Computer Engineering

Scientometric analysis of biotechnology research output in India during 2008-2017

In this study a scientometric analysis of the biotechnology research output of India during 2008-2017 was performed based on the information available in SCOPUS database. This study analyses the research output of India in biotechnology research on different parameters including the growth, global publication share and rank, contribution of major international collaborative partners and subject areas, contribution and citation impact of the most productive authors, institutions and journals. The United States ranks first in terms of number of publications, h-index and average citations per paper. A total of 5573 papers were published by India during 2008-2017, which received 80530 citations with an average of 14.45 citations per paper. Almost 48.79% publications are in the field of biochemistry, genetics and molecular biology. The most productive Indian institution in biotechnology research was Indian Institute of Technology, Delhi followed by Council of Scientific and Industrial Research and Vellore Institute of Technology. Top twenty most productive institutions contributed 30.50% share of total publications with an average of 85 publications per institute

FUNCTIONAL ELECTRICAL STIMULATION FOR FOOT DYSTONIA A CASE REPORT

Background: Functional Electrical Stimulation (FES) can be used as an alternative to ankle foot orthosis (AFO) for foot drop following upper motor neuron lesions. A few patients with stroke might experience dystonia as part of its symptomatology. Dystonia can appear at presentation of the stroke or they may be delayed. Post stroke dystonia can affect either one side of the body (hemidystonia) or can be segmental or focal. Method: A 20 year old male, known case of post stroke right foot dystonia was put on Functional Electrical Stimulation (FES) for walking. The ODFS pace device was used for stimulating his right evertors and dorsiflexors while walking. He was made to practice walking with the help of FES for 30 minutes every day, 6 days a week for 4 weeks. The outcome measures were 10 meter walk test, Berg Balance Score (BBS) and ankle range of motion. Result: Despite using the FES, patient continued to experience the same gait difficulty i.e. twisting of right leg while walking although he reports having gained confidence while walking. Conclusion: FES could be used as a novel symptomatic treatment for the abnormal contractions present during dystonia. There, however, is limited data for the role of FES in treating dystonia