Time-domain thru-reflect-line (TRL) calibration error assessment and its mitigation and modeling of multilayer printed circuit boards (PCB) with complex area fills

Part 1 for this thesis is on the error assessment of a time-domain (t-TRL) calibration technique. Application of the Thru-Reflect-Line (TRL) calibration to time-domain measurements of S-parameters (t-TRL) can be used for the characterization of the printed circuit boards (PCBs). However, t-TRL calibrated results still have deviations from the reference frequency-domain vector network analyzer (VNA) calibrated results. There are two main sources of errors in the t-TRL calibration. They are random errors, such as an additive noise and jitter, and systematic errors associated with cables, connectors, and port mismatches. This work addresses these two types of errors by proper selection of the number of sampling points, waveform averages, and time record. Methods tried out to eliminate or reduce these errors are detailed in this work. Measurements and simulations were performed for implementing these methods, and the results are explained. A t-TRL calibration automation tool based on TDR/TDT measurements has been developed. Part 2 of this thesis is on the modeling of multilayer PCBs with complex area fills and floating planes. Noise on the power distribution network (PDN) and between the power area fills in multilayer PCBs with complex geometries is a significant concern. Modeling of such PCBs can be done with a cavity model approach. Correlation of a 3D EM solver results with the Multilayer Via Transition Tool (MVTT) results based on cavity model is explained here. Additional modeling and validation was done using the equivalent inductance method --Abstract, page iii

An altmetric approach to measure the social media attention of COVID-19 articles

The 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

Misinfodemic and cyberchondria experiences among Indians during COVID-19 pandemic

The 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

Solar Flare Prediction and Feature Selection using Light Gradient Boosting Machine Algorithm

Solar 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 $\geq$C ($\geq$M) class solar flares.Comment: Accepted for publication in Solar Physics journa

Citations v/s Altmetric Attention Score: A Comparison of Top 10 Highly Cited Papers in Nature

This 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

Examining the Association between Citations and Altmetric Indicators of LIS Articles indexed in Dimensions Database

Social media attention to scholarly articles has become a novel measure for assessing the broader impact of research, which complements the traditional citation metrics. This article examined the correlation between citations with major altmetric indicators for 1951 LIS articles published in 2020. Altmetric Explorer was used for collecting the data, and analysis was done using Excel and SPSS. The result showed that LIS articles were well engaged on social media platforms gaining more societal attention than their scientific reference in terms of citations. Mendeley (69.40%) and Twitter (28.72%) were the top intakes of LIS articles, and Pinterest (0.001%) and F1000 (0.001%) were the least ones. The users from the USA were the major Twitterati for the LIS articles, with average Tweeters of -0.58 across the globe. The users from the UK were the top mentioner of the articles on Facebook (2.7%), while the USA was on the News and mainstream media (55.6%). Except for Peer review (r= -0.05), all other altimetric indicators were positively associated with Dimensions citations. The study's findings allow the authors to analyze the societal impact of their scholarship through altmetric indicators and use altmetric indicators as supplementary to the citation metrics for measuring the immediate impact of the LIS scientific outputs

An overview on single nucleotide polymorphism studies in mastitis research

Mastitis is an inflammatory condition of the mammary gland caused by microorganisms as diverse as bacteria, viruses, mycoplasma, yeasts and algae. Mastitis is an economically devastating disease mainly affecting the crossbred cattle in India. Control strategies against mastitis includes antibiotic therapy, vaccination, improvements in dairy cattle husbandry, farm and feeding management etc. but has met with little success.. Mastitis tolerance/susceptibility is difficult to measure directly and hence milk somatic cell count (SCC) or milk somatic cell score (SCS) is used as an indicator trait for mastitis as both traits are highly positively correlated. Single nucleotide polymorphism (SNP) marker is a single base change in a DNA sequence at a given position. SNP markers are the most preferred genetic markers nowadays. Currently most researches worldwide have been targeting molecular high density SNP markers that are linked to mastitis tolerance in an attempt to incorporate to understand the genetics of host resistance to mastitis and this knowledge will be helpful in formulating breeding programmes in an attempt to control mastitis. This article reviews various SNPs which are reported to be significantly associated with mastitis tolerance/susceptibility

Sequence and de novo assembly of the genome of the Indian oil sardine, Sardinella longiceps

The Indian oil sardine, Sardinella longiceps, is a widely distributed and commercially important small pelagic fish of the Northern Indian Ocean. The genome of the Indian oil sardine has been characterized using Illumina and Nanopore platforms. The assembly is 1.077 Gb (31.86 Mb Scaffold N50) in size with a repeat content of 23.24%. The BUSCO (Benchmarking Universal Single Copy Orthologues) completeness of the assembly is 93.5% when compared with Actinopterygii (ray finned fishes) data set. A total of 46316 protein coding genes were predicted. Sardinella longiceps is nutritionally rich with high levels of omega-3 polyunsaturated fatty acids (PUFA). The core genes for omega-3 PUFA biosynthesis, such as Elovl 1a and 1b,Elovl 2, Elovl 4a and 4b,Elovl 8a and 8b,and Fads 2, were observed in Sardinella longiceps. The presence of these genes may indicate the PUFA biosynthetic capability of Indian oil sardine, which needs to be confirmed functionally

Sphingosine-1-phosphate receptor 3 promotes leukocyte rolling by mobilizing endothelial P-selectin

Sphingosine-1-phosphate (S1P) participates in inflammation;however, its role in leukocyte rolling is still unclear. Here we use intravital microscopy in inflamed mouse cremaster muscle venules and human endothelial cells to show that S1P contributes to P-selectin-dependent leukocyte rolling through endothelial S1P receptor 3 (S1P(3)) and G alpha(q), PLC beta and Ca2+. Intraarterial S1P administration increases leukocyte rolling, while S1P(3) deficiency or inhibition dramatically reduces it. Mast cells involved in triggering rolling also release S1P that mobilizes P-selectin through S1P(3). Histamine and epinephrine require S1P(3) for full-scale effect accomplishing it by stimulating sphingosine kinase 1 (Sphk1). In a counter-regulatory manner, S1P1 inhibits cAMP-stimulated Sphk1 and blocks rolling as observed in endothelial-specific S1P(1)(-/-) mice. In agreement with a dominant pro-rolling effect of S1P(3),FTY720 inhibits rolling in control and S1P(1)(-/-) but not in S1P(3)(-/-) mice. Our findings identify S1P as a direct and indirect contributor to leukocyte rolling and characterize the receptors mediating its action