24 research outputs found
Synthesis of Au@Ni bimetallic core shell nanoparticle and nanochains in soyabean oil and their catalytic hydrogenation reactions
No full textSynthesis of Au@Ni bimetallic core shell nanostructures using commercially available soya bean oil as the solvent through a sequential reduction strategy is reported. The energy efficiency and economic viability comes from the much milder temperatures and replacement of expensive and environmentally hazardous solvents like long chain organic amines and acids previously reported for synthesis. Thus, core shell nanoparticles having size regime of 10‐15 nm with an excellent control over the nickel shell thickness (2 nm) over the gold core (8‐10 nm) and Au@Ni nanochains is achieved. The synthesized materials are demonstrated to synergistically catalyze hydrogenation of nitro and C‐C multiple bonds with much better efficiency as compared to individual nanoparticle counterparts
Citations v/s Altmetric Attention Score: A Comparison of Top 10 Highly Cited Papers in Nature
No full textThis study aims to analyze the correlation between citations and altmetric score of top 10 highly cited papers in Nature by extracting the data from Google metrics. It tries to investigate whether a highly cited paper has high altmetric score or not by using correlation method and the result show that there exists a high correlation. The study found that Mendeley is the main medium through which scientific papers are being disseminated more and contributing to the altmetric score intensely. The country wise tweeting data show that U.S and U.K holds the first and second position in tweeting with 1143 &14 tweets respectively. As the altmetric values the online attention, it prompts the entire research community to opt for social media for publication for getting good attentions and there by promoting open access. Even though, altmetrics is not at all a replacement of traditional metrics but acts as supplement to it
An altmetric approach to measure the social media attention of COVID-19 articles
No full textThe outbreak of COVID-19 pandemic has shaken the entire world. This study aimed to measure how well COVID-19 articles attracted in the social web during the deadly pandemic period. A total of 145 articles from Nature journal were collected and analyzed to gauge the major metrics from various social platforms. The results showed that social media attention to the articles was fluctuating in each month recording an upward and downward trend. Twitter was the major carrier of COVID-19 articles with total 143452 mentions followed by news outlets with 5251 mentions. Articles were yet to penetrate in many other platforms like Highlights, Wiki, Video uploading and F1000. No metrics were recorded from reference managers manifesting that COVID-19 articles were travelling fast in social media rather than reference managers. Open access articles did not find any social media attention benefits compared to Non-open access articles. The findings of the study would give a proper insight into how well the COVID-19 articles are penetrated and discussed in social media platforms
Who Reads Indian and Chinese LIS Articles on Mendeley? Scoping and Comparing User Categories Through Altmetrics
No full textMendeley reader count is good evidence of the early impact of scientific output since it appears before citations. This paper aims to scope and compare Mendeley readers of Library and Information Science (LIS) articles published from India and China. Mendeley readership data for the highly cited 1,000 articles in Web of Science are extracted using Webometric Analyst for both countries and are analysed using Excel and SPSS. The findings reveal that LIS articles that are published from China got more readers as compared to LIS articles published from India with an excess of 97 readers per paper on Mendeley. The occupational status of readers tells that PhD students are the top readers for both the countries' publications, followed by masters students. Discipline-wise readership shows that readers were spread across 29 different fields, with the highest readers from business, management and accounting, followed by computer science for both countries' publications. Location-wise readership depicts that the top engaged readers are from the United States for both the countries' publications. Finally, the study reports a positive association between citations and Mendeley bookmarks, justifying that Mendeley readership can be used to measure the early research impact of LIS scholarship in both countries
Solar Flare Prediction and Feature Selection using Light Gradient Boosting Machine Algorithm
No full textSolar flares are among the most severe space weather phenomena, and they have
the capacity to generate radiation storms and radio disruptions on Earth. The
accurate prediction of solar flare events remains a significant challenge,
requiring continuous monitoring and identification of specific features that
can aid in forecasting this phenomenon, particularly for different classes of
solar flares. In this study, we aim to forecast C and M class solar flares
utilising a machine-learning algorithm, namely the Light Gradient Boosting
Machine. We have utilised a dataset spanning 9 years, obtained from the
Space-weather Helioseismic and Magnetic Imager Active Region Patches (SHARP),
with a temporal resolution of 1 hour. A total of 37 flare features were
considered in our analysis, comprising of 25 active region parameters and 12
flare history features. To address the issue of class imbalance in solar flare
data, we employed the Synthetic Minority Oversampling Technique (SMOTE). We
used two labeling approaches in our study: a fixed 24-hour window label and a
varying window that considers the changing nature of solar activity. Then, the
developed machine learning algorithm was trained and tested using forecast
verification metrics, with an emphasis on evaluating the true skill statistic
(TSS). Furthermore, we implemented a feature selection algorithm to determine
the most significant features from the pool of 37 features that could
distinguish between flaring and non-flaring active regions. We found that
utilising a limited set of useful features resulted in improved prediction
performance. For the 24-hour prediction window, we achieved a TSS of 0.63
(0.69) and accuracy of 0.90 (0.97) for C (M) class solar flares.Comment: Accepted for publication in Solar Physics journa
ALVARADO SCORE AND C-REACTIVE PROTEIN PREDICTOR OF SEVERITY IN ACUTE APPENDICITIS- AN INSTITUTION BASED STUDY
No full textExploring the information security practices on the smartphone by the postgraduate students of University of Calicut
No full textThis paper aims to report on the information security practices on the smartphone by the students of the University of Calicut, Kerala. Data were gathered by using a survey questionnaire which was administered to 344 smartphone cohorts at the postgraduate level. The study findings reported the scanty knowledge of the participants regarding the issues and risks associated with smartphones even though most of the respondents were aware of the information security practices available in the smartphones. The data analysis delineated the habit of students storing secret and sensitive information like ATM password, bank or credit card account details and personal photos on their smartphones. Data leakage resulting from device loss or theft was the major security risk faced by the participants. The number of participants misplaces their smartphone also found high. Data backup and blocking the device once lost were the major security practices adopted by the participants to recover from the disaster. This is to be sure, first of its kind study to survey the postgraduate students at the university level in India and the findings of the study would help the smartphone users in general and students in particular to protect their information stored in their smartphones
Chromosome-level genome assembly and genome-wide characterisation of fox gene family in the asian green mussel (Perna viridis): insights into evolution and aquaculture genomics
No full textMarine Biotechnology, Fish Nutrition and Health Division, CMFRI, Kerala Mangalore University. Mangalagangotri. Mangalore. Karnataka, India Email: [email protected]
The Asian green musel. Perna viridis is an ecologically and economically significant bivalve species in aquaculture. We build a high-quality chromosome-level genome assembly of P. viridis, generated using PacBio SMRT sequencing, Illumina short read sequencing, Hi-C scaffolding, and Bionano optical mapping. The final assembly. spans 723.49 Mb with a scaffold N50 of 49.74 Mb, anchoring 99% of the genome into 15 chromosomes. A total of 49,654 protein-coding genes were identified. Using this genomic resource, we performed a comprehensive genome-wide characterisation of the Forchead bos (FOX) gene family, which plays a pivotal role in cellular regulation, development, and environmental adaptation. We identified 28 PvFox genes classified into 12 subfamilies, with lineage specific losses of Foxl and FoxQ1. Gene duplication in FoxLI, FoxB1, FoxHI, and FoxD2 suggests adaptive diversification in response to marine stressors. Structural analysis revealed cxan-intron variations, with some PvFox genes exhibiting intron loss, potentially facilitating regulatory plasticity. Phylogenetic analysis confirmed evolutionary conservation, while selection pressure analysis indicated strong purifying selection. GO enrichment highlighted FOX involvement in apoptosis, oxidative stress, and immune responses, reinforcing their functional significance in stresa tolerance and disease resistance. This study provides the first FOX gene landscape in P. viridis advancing our understanding of its adaptive success and offering insights into the evolutionary dynamics of key regulatory genes in marine bivalves
On 12 th to 14 th December Organized by DETERMINATION OF PERFORMANCE POINT IN CAPACITY SPECTRUM METHOD
No full textABSTRACT Performance based seismic design (PBSD) method is getting wide recognition as the most suitable seismic design process. PBSD is essentially a displacement based seismic design process involving the determination of performance point. The capacity spectrum method is one of the most established and widely accepted displacement based seismic design method which is used for performance based seismic design. ATC 40 report published by Applied Technology Council identifies three capacity spectrum procedures A, B and C for determination of performance point. Procedure A is the most direct application of the theory while procedure B is based on the simplifying assumption of constant post yield slope. Procedure C is a purely graphical method that is not convenient for programming. The assumption may introduce some error into the procedure B. The conventional software packages like ETABS, SAP2000 are based on procedure B. The current study involves developing a program based on procedure A and comparing the outputs of the developed program and conventional software ETABS
Misinfodemic and cyberchondria experiences among Indians during COVID-19 pandemic
No full textThe outbreak of the COVID-19 pandemic has fuelled the surge of various kinds of misinformation, hoax, conspiracy theories and rumours which have challenged the health systems all over the globe. The present study explored how Indians responded to the Misinfodemic, as a notice as well as an information sharer during the deadly pandemic. The study also elucidated the cyberchondria experiences among the Indians due to the misinfodemic. An online survey questionnaire was used to identify the respondents and to collect the needed data for the study (N=266). The result showed that the majority of the participants noticed misinformation regarding the outbreak on various internet platforms predominantly social media. The misinformation led the participants to a spectrum of mental health issues like stress, anxiety, anger, insomnia and depression. 9.80% of participants admitted themselves sharing misinformation regarding the outbreak and men did more compared to females (16.9% to 9.2%) (t143.006 = 1.572, p =.001). The misinfodemic resulted in increasing the health anxiety of the participants and there was no significant difference among the gender in experiencing health anxiety. The findings of the study provide functional insights for advancing communication research through misinformation correction and misperception management during these kinds of unknown (medicine and treatment) pandemic situations.https://dorl.net/dor/20.1001.1.20088302.2022.20.3.15.2
