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Classifying Yang-Baxter operators is an essential first step in the study of the simulation of integrable quantum systems on quantum computers. One of the earliest initiatives was taken by Hietarinta in classifying constant Yang-Baxter solutions for a two-dimensional local Hilbert space (qubit representation). He obtained 11 families of invertible solutions, including the one generated by the permutation operator. While these methods work well for 4 by 4 solutions, they become cumbersome for higher dimensional representations. In this work, we overcome this restriction by constructing the constant Yang-Baxter solutions in a representation independent manner by using ans\"{a}tze from algebraic structures. We use four different algebraic structures that reproduce 10 of the 11 Hietarinta families when the qubit representation is chosen. The methods include a set of commuting operators, Clifford algebras, Temperley-Lieb algebras, and partition algebras. We do not obtain the $(2,2)$ Hietarinta class with these methods., Comment: 26 pages + References

Quantum simulations of many-body systems using 2-qubit Yang-Baxter gates offer a benchmark for quantum hardware. This can be extended to the higher dimensional case with $n$-qubit generalisations of Yang-Baxter gates called $n$-simplex operators. Such multi-qubit gates potentially lead to shallower and more efficient quantum circuits as well. Finding them amounts to identifying unitary solutions of the $n$-simplex equations, the building blocks of higher dimensional integrable systems. These are a set of highly non-linear and over determined system of equations making it notoriously hard to solve even when the local Hilbert spaces are spanned by qubits. We systematically overcome this for higher simplex operators constructed using two methods: from Clifford algebras and by lifting Yang-Baxter operators. The $n=3$ or the tetrahedron case is analyzed in detail. For the qubit case our methods produce 13 inequivalent families of unitary tetrahedron operators. 12 of these families are obtained by appending the 5 unitary families of 4 by 4 constant Yang-Baxter operators of Dye-Hietarinta, with a single qubit operator. As applications, universal sets of single, two and three qubit gates are realized using such unitary tetrahedron operators. The ideas presented in this work can be naturally extended to the higher simplex cases., Comment: 34 pages of main text + 4 pages of appendices + 8 pages of references; v2 Fixed minor typos, updated Acknowledgments

The advancements in computer vision and image processing techniques have led to emergence of new application in the domain of visual surveillance, targeted advertisement, content-based searching, and human-computer interaction etc. Out of the various techniques in computer vision, face analysis, in particular, has gained much attention. Several previous studies have tried to explore different applications of facial feature processing for a variety of tasks, including age and gender classification. However, despite several previous studies having explored the problem, the age and gender classification of in-wild human faces is still far from the achieving the desired levels of accuracy required for real-world applications. This paper, therefore, attempts to bridge this gap by proposing a hybrid model that combines self-attention and BiLSTM approaches for age and gender classification problems. The proposed models performance is compared with several state-of-the-art model proposed so far. An improvement of approximately 10percent and 6percent over the state-of-the-art implementations for age and gender classification, respectively, are noted for the proposed model. The proposed model is thus found to achieve superior performance and is found to provide a more generalized learning. The model can, therefore, be applied as a core classification component in various image processing and computer vision problems., Comment: 22 pages

We compute the $\text{PSL}(2,\mathbb{C})$ Chern-Simons partition function of a closed 3-manifold obtained from Dehn fillings of the link complement $\mathbf S^3\backslash {\mathcal{L}}$, where $\mathcal{L}=\mathcal{K}# H$ is the connected sum of the knot $\mathcal {K}$ with the Hopf link $H$. Motivated by our earlier work on topological entanglement and the reduced density matrix $\sigma$ for such link complements, we wanted to determine a choice of Dehn filling so that the trace of the matrix $\sigma$ becomes equal to the $\text{PSL}(2,\mathbb{C})$ partition function of the closed 3-manifold. We use the SnapPy program and numerical techniques to show this equivalence up to the leading order. We have given explicit results for all hyperbolic knots $\mathcal{K}$ up to six crossings., Comment: 25 pages, 5 figures, 5 tables

The fusion basis of Fibonacci anyons supports unitary braid representations that can be utilized for universal quantum computation. We show a mapping between the fusion basis of three Fibonacci anyons, $\{|1\rangle, |\tau\rangle\}$, and the two length 4 Dyck paths via an isomorphism between the two dimensional braid group representations on the fusion basis and the braid group representation built on the standard $(2,2)$ Young diagrams using the Jones construction. This correspondence helps us construct the fusion basis of the Fibonacci anyons using Dyck paths as the number of standard $(N,N)$ Young tableaux is the Catalan number, $C_N$ . We then use the local Fredkin moves to construct a spin chain that contains precisely those Dyck paths that correspond to the Fibonacci fusion basis, as a degenerate set. We show that the system is gapped and examine its stability to random noise thereby establishing its usefulness as a platform for topological quantum computation. Finally, we show braidwords in this rotated space that efficiently enable the execution of any desired single-qubit operation, achieving the desired level of precision($\sim 10^{-3}$)., Comment: 30 pages, 20 figures

For invasive breast cancer, immunohistochemical (IHC) techniques are often used to detect the expression level of human epidermal growth factor receptor-2 (HER2) in breast tissue to formulate a precise treatment plan. From the perspective of saving manpower, material and time costs, directly generating IHC-stained images from Hematoxylin and Eosin (H&E) stained images is a valuable research direction. Therefore, we held the breast cancer immunohistochemical image generation challenge, aiming to explore novel ideas of deep learning technology in pathological image generation and promote research in this field. The challenge provided registered H&E and IHC-stained image pairs, and participants were required to use these images to train a model that can directly generate IHC-stained images from corresponding H&E-stained images. We selected and reviewed the five highest-ranking methods based on their PSNR and SSIM metrics, while also providing overviews of the corresponding pipelines and implementations. In this paper, we further analyze the current limitations in the field of breast cancer immunohistochemical image generation and forecast the future development of this field. We hope that the released dataset and the challenge will inspire more scholars to jointly study higher-quality IHC-stained image generation., Comment: 12 pages, 12 figures, 2tables

The increase in abusive content on online social media platforms is impacting the social life of online users. Use of offensive and hate speech has been making so-cial media toxic. Homophobia and transphobia constitute offensive comments against LGBT+ community. It becomes imperative to detect and handle these comments, to timely flag or issue a warning to users indulging in such behaviour. However, automated detection of such content is a challenging task, more so in Dravidian languages which are identified as low resource languages. Motivated by this, the paper attempts to explore applicability of different deep learning mod-els for classification of the social media comments in Malayalam and Tamil lan-guages as homophobic, transphobic and non-anti-LGBT+content. The popularly used deep learning models- Convolutional Neural Network (CNN), Long Short Term Memory (LSTM) using GloVe embedding and transformer-based learning models (Multilingual BERT and IndicBERT) are applied to the classification problem. Results obtained show that IndicBERT outperforms the other imple-mented models, with obtained weighted average F1-score of 0.86 and 0.77 for Malayalam and Tamil, respectively. Therefore, the present work confirms higher performance of IndicBERT on the given task in selected Dravidian languages.

Images generated by high-resolution SAR have vast areas of application as they can work better in adverse light and weather conditions. One such area of application is in the military systems. This study is an attempt to explore the suitability of current state-of-the-art models introduced in the domain of computer vision for SAR target classification (MSTAR). Since the application of any solution produced for military systems would be strategic and real-time, accuracy is often not the only criterion to measure its performance. Other important parameters like prediction time and input resiliency are equally important. The paper deals with these issues in the context of SAR images. Experimental results show that deep learning models can be suitably applied in the domain of SAR image classification with the desired performance levels., Comment: 6 pages, 9 figures

We obtain a quiver representation for a family of knots called double twist knots $K(p,-m)$. Particularly, we exploit the reverse engineering of Melvin-Morton-Rozansky(MMR) formalism to deduce the pattern of the charge matrix for these quivers., Comment: 16 pages, 1 figures, published version

The shift from 'trust-based funding' to 'performance-based funding' is one of the factors that has forced institutions to strive for continuous improvement of performance. Several studies have established the importance of collaboration in enhancing the performance of paired institutions. However, identification of suitable institutions for collaboration is sometimes difficult and therefore institutional collaboration recommendation systems can be vital. Currently, there are no well-developed institutional collaboration recommendation systems. In order to bridge this gap, we design a framework that recognizes thematic strengths and core competencies of institutions, which can in turn be used for collaboration recommendations. The framework, based on NLP and network analysis techniques, is capable of determining the strengths of an institution in different thematic areas within a field and thereby determining the core competency and potential core competency areas of that institution. A major advantage of the system is that it can help to determine and improve the research portfolio of an institution within a field through suitable collaboration, which may lead to the overall improvement of the performance of the institution in that field. The framework is demonstrated by analyzing the performance of 195 Indian institutions in the field of 'Computer Science'. Upon validation using standard metrics for novelty, coverage and diversity of recommendation systems, the framework is found to be of sufficient coverage and capable of tossing novel and diverse recommendations. The article thus presents an institutional collaboration recommendation system which can be used by institutions to identify potential collaborators.

India is now among the major knowledge producers of the world, ranking among the top 5 countries in total research output, as per some recent reports. The institutional setup for Research & Development (R&D) in India comprises a diverse set of Institutions, including Universities, government departments, research laboratories, and private sector institutions etc. It may be noted that more than 45% share of India's Gross Expenditure on Research and Development (GERD) comes from the central government. In this context, this article attempts to explore the quantum of research contribution of centrally funded institutions and institution systems of India. The volume, proportionate share and growth patterns of research publications from the major centrally funded institutions, organised in 16 groups, is analysed. These institutions taken together account for 67.54% of Indian research output during 2001 to 2020. The research output of the centrally funded institutions in India has increased steadily since 2001 with a good value for CAGR. The paper presents noteworthy insights about scientific research production of India that may be useful to policymakers, researchers and science practitioners in India. It presents a case for increased activity by the state governments and private sector to further the cause of sustainable and inclusive research and development in the country.

Future Generation Computer Systems (FGCS), published by Elsevier, is a prestigious peer reviewed journal that started in 1984. As on date of writing this article, the journal is in its 137th volume. Owing to its publication quality and continued academic standards, it has been indexed by major academic databases such as Web of Science, Scopus, DOAJ etc. It is now ranked among the top journals in the area of Computer Science (General). Motivated by the long history, academic reputation and prestige of the journal, the present study attempts to do a bibliometric and text-based analysis of publications in the journal during the period of 1984-2020 (37 years). Bibliometric analysis helped to identify publishing and citation patterns, authorship and collaboration structure, funding patterns of the published research, open access and altmetric impact, gender distribution and SDG connections etc. The text-integrated path analysis helped in identifying the thematic structure and major concept evolution trajectories. The results of the analysis indicate that the FGCS journal is a high-quality research journal that has grown over time in terms of publications, citations and rankings. It publishes articles in specified thematic areas, with cloud, grid, IoT, Blockchain etc. found as the major themes addressed. Knowledge extension from cloud computing to multi-domain networks is witnessed and a divergence towards service function chains, distributed machine learning and edge computing systems is visible. The article thus presents very informative and useful insight about research publication trends in FGCS.

Biomarkers identify a patients response to treatment. With the recent advances in artificial intelligence based on the Transformer networks, there is only limited research has been done to measure the performance on challenging histopathology images. In this paper, we investigate the efficacy of the numerous state-of-the-art Transformer networks for immune-checkpoint biomarker, Inducible Tcell COStimulator (ICOS) protein cell segmentation in colon cancer from immunohistochemistry (IHC) slides. Extensive and comprehensive experimental results confirm that MiSSFormer achieved the highest Dice score of 74.85% than the rest evaluated Transformer and Efficient U-Net methods., Comment: Accepted MIUA conference (Abstract short paper)

Scientific collaboration at international level has increased manifolds during last two decades. Collaboration is not only associated with higher research productivity but has also been found to be positively correlated with impact. Considering the benefits and advantages of international collaboration for the national science and technology systems of a country, policymakers in different countries have designed programs to promote international collaboration in science. This paper attempts to measure and characterize the international collaboration patterns in Indian scientific research. Research publication data for the last 20 years (2001-2020), obtained from Web of Science, is analysed for the purpose. Analytical results show that India's international collaboration has grown at a rate of 12.27% during this period, rising from only 20.73% internationally collaborated papers in 2001 to 32.35% internationally collaborated papers in 2020. USA, Germany, England, South Korea and China are found to be the top collaborating partners for India during his period, however, some subject area-wise variations are also seen. Among the internationally collaborated papers, about 50% papers have an Indian researcher as lead (first) author, and more than 50% authors of such internationally collaborated papers are from India. The internationally collaborated papers from India are also found to have a slight advantage in terms of citation impact and social media visibility. The probable factors shaping the Indian international collaboration and the major policy implications are discussed.

Obtaining a closed-form expression for the colored HOMFLY-PT polynomials of knots from $3$-strand braids carrying arbitrary $SU(N)$ representation is a challenging problem. In this paper, we confine our interest to twisted generalized hybrid weaving knots which we denote hereafter by $\hat{Q}_3(m_1,-m_2,n,\ell)$. This family of knots not only generalizes the well-known class of weaving knots but also contains an infinite family of quasi-alternating knots. Interestingly, we obtain a closed-form expression for the HOMFLY-PT polynomial of $\hat{Q}_3(m_1,-m_2,n,\ell)$ using a modified version of the Reshitikhin-Turaev method. In addition, we compute the exact coefficients of the Jones polynomials and the Alexander polynomials of quasi-alternating knots $\hat{Q}_3(1,-1,n,\pm 1)$. For these homologically-thin knots, such coefficients are known to be the ranks of their Khovanov and link Floer homologies, respectively. We also show that the asymptotic behaviour of the coefficients of the Alexander polynomial is trapezoidal. On the other hand, we compute the $[r]$-colored HOMFLY-PT polynomials of quasi alternating knots for small values of $r$. Remarkably, the study of the determinants of certain twisted weaving knots leads to establish a connection with enumerative geometry related to $m^{th}$ Lucas numbers, denoted hereafter as $L_{m,2n}$. At the end, we verify that the reformulated invariants satisfy Ooguri-Vafa conjecture and we express certain BPS integers in terms of hyper-geometric functions ${}_2 {\bf F}_1\left[a,b, c;z\right]$., Comment: 39 pages, version appearing in Nuclear Physics B

This paper examines long-term temporal and spatial fluctuations in the solar rotation (more than four solar cycles) by investigating radio emission escapes from various layers of the solar atmosphere during the years 1967-2010. The flux modulation approach can also be used to investigate variations in solar rotation, which is a contentious topic in solar physics. The current study makes use of a time series of radio flux data at different frequencies (245-15400 MHz) obtained at Sagamore Hill Solar Radio Observatory in Massachusetts, USA, and other observatories from 1967 to 2010. The periodicity present in the temporal variation of time series is estimated through Lomb Scargle Periodogram (LSP). The rotation period estimated for five radio emissions (606, 1415, \& 2695 MHz; from corona, and 4995 \& 8800 MHz; from transition region) through statistical approach shows continuous temporal and spatial variation throughout the years. The smoothed rotation period shows the presence of $\sim$ 22-yrs periodic and $\sim$ 11-yrs components in it. The 22-year component could be linked to the reversal of the solar magnetic field (Hale's) cycle, while the 11-yrs component is most likely related to the sunspot (Schwabe's) cycle. Besides these two components, random components are also prominently present in the analyzed data. The cross-correlation between the sunspot number and the rotation period obtained shows a strong correlation with 11-yrs Schwabe's and 22-yr Hale cycle. The corona rotates faster or slower than transition region in different epoch. The swap of faster rotation speed between corona and transition region also follows the 22-yrs cycle.

The entanglement entropy of many quantum systems is difficult to compute in general. They are obtained as a limiting case of the R\'enyi entropy of index $m$, which captures the higher moments of the reduced density matrix. In this work, we study pure bipartite states associated with $S^3$ complements of a two-component link which is a connected sum of a knot $\mathcal{K}$ and the Hopf link. For this class of links, the Chern-Simons theory provides the necessary setting to visualise the $m$-moment of the reduced density matrix as a three-manifold invariant $Z(M_{\mathcal{K}_m})$, which is the partition function of $M_{\mathcal{K}_m}$. Here $M_{\mathcal{K}_m}$ is a closed 3-manifold associated with the knot $\mathcal K_m$, where $\mathcal K_m$ is a connected sum of $m$-copies of $\mathcal{K}$ (i.e., $\mathcal{K}\#\mathcal{K}\ldots\#\mathcal{K}$) which mimics the well-known replica method. We analyse the partition functions $Z(M_{\mathcal{K}_m})$ for SU(2) and SO(3) gauge groups, in the limit of the large Chern-Simons coupling $k$. For SU(2) group, we show that $Z(M_{\mathcal{K}_m})$ can grow at most polynomially in $k$. On the contrary, we conjecture that $Z(M_{\mathcal{K}_m})$ for SO(3) group shows an exponential growth in $k$, where the leading term of $\ln Z(M_{\mathcal{K}_m})$ is the hyperbolic volume of the knot complement $S^3\backslash \mathcal{K}_m$. We further propose that the R\'enyi entropies associated with SO(3) group converge to a finite value in the large $k$ limit. We present some examples to validate our conjecture and proposal., Comment: 38 pages, 24 figures & 15 tables; v2: Introduction & Conclusion modified, new subsection added in section 3, three new references added; matches published version

ResearchGate has emerged as a popular professional network for scientists and researchers in a very short span of time. Similar to Google Scholar, the ResearchGate indexing uses an automatic crawling algorithm that extracts bibliographic data, citations and other information about scholarly articles from various sources. However, it has been observed that the two platforms often show different publication and citation data for the same institutions, journals and authors. This paper, therefore, attempts to analyse and measure the differences in publication counts, citations and different metrics of the two platforms for a large data set of highly cited authors. The results indicate that there are significantly high differences in publication counts and citations for the same authors in the two platforms, with Google Scholar having higher counts for a vast majority of the cases. The different metrics computed by the two platforms also differ in their values, showing different degrees of correlations. The coverage policy, indexing errors, author attribution mechanism and strategy to deal with predatory publishing are found to be the main probable reasons for the differences in the two platforms., Comment: Pre-print

The present work is an effort to investigate possible radial variations in the solar coronal rotation by analyzing the solar radio emission data at 15 different frequencies (275-1755 MHz) for the period starting from July 1994 to May 1999. We used a time series of disk-integrated radio flux recorded daily at these frequencies through radio telescopes situated at Astronomical Observatory of the Jagellonian University in Cracow. The different frequency radiation originates from different heights in the solar corona. Existing models, indicate its origin at the height range from nearly $\sim12,000$ km (for emission at 275 MHz), below up to $\sim2,400$ km (for emission at 1755 MHz). There are some data gaps in the time series used for the study, so we used statistical analysis using the Lomb-Scargle Periodogram (LSP). This method has successfully estimated the periodicity present in time series even with such data gaps. The rotation period estimated through LSP shows variation in rotation period, which is compared with the earlier reported estimate using auto correlation technique. The present study indicates some similarity as well as contradiction with studies reported earlier. The radial and temporal variation in solar rotation period are presented and discussed for the whole period analyzed., Comment: 6 pages, 6 figures

Recently three foreign academic publishers filed a case of copyright infringement against Sci-Hub and LibGen before the Delhi High Court and prayed for complete blocking these websites in India. In this context, this paper attempted to assess the impact that blocking of Sci-Hub may have on Indian research community. The download requests originating from India on a daily-basis are counted, geotagged and analysed by discipline, publisher, country and publication year etc. Results indicate that blocking Sci-Hub in India may actually hurt Indian research community in a significant way.

Scientific journals are currently the primary medium used by researchers to report their research findings. The transformation of print journals into e-journals has simplified the process of submissions to journals and also their access has become wider. Journals are usually published by commercial publishers, learned societies as well as Universities. There are different number of journals published from different countries. This paper attempts to explore whether the number of journals published from a country influences its research output. Scopus master journal list is analysed to identify journals published from 50 selected countries with significant volume of research output. The following relationship are analysed: (a) number of journals from a country and its research output, (b) growth rate of journals and research output for different countries, (c) global share of journals and research output for different countries, and (d) subject area-wise number of journals and research output in that subject area for different countries. Factors like journal packing density are also analysed. The results obtained show that for majority of the countries, the number of journals is positively correlated to their research output volume, though some other factors also play a role in growth of research output. The study at the end presents a discussion of the analytical outcomes and provides useful suggestions on policy perspectives for different countries., Comment: 6 figures and 4 tables

Weaving knots $W(p, n)$ of type $(p, n)$ denote an infinite family of hyperbolic knots which have not been addressed by the knot theorists as yet. Unlike the well-known $(p,n)$ torus knots, we do not have a closed-form expression for HOMFLY-PT and the colored HOMFLY-PT for $W(p,n)$. In this paper, we confine to a hybrid generalization of $W(3,n)$ which we denote as $\hat{W}_3(m,n)$ and obtain a closed-form expression for HOMFLY-PT using the Reshitikhin and Turaev method involving $\mathcal R$-matrices. Further, we also compute $[r]$-colored HOMFLY-PT for $W(3,n)$. Surprisingly, we observe that trace of the product of two dimensional $\hat{\mathcal{R}}$-matrices can be written in terms of an infinite family of Laurent polynomials $\mathcal{V}_{n,t}[q]$ whose absolute coefficients has an interesting relation to the Fibonacci numbers $\mathcal{F}_{n}$. We also computed reformulated invariants and the BPS integers in the context of topological strings. From our analysis, we propose that certain refined BPS integers for weaving knot $W(3,n)$ can be explicitly derived from the coefficients of Chebyshev polynomials of the first kind., Comment: 32 pages, typos corrected

Conventional transfer learning leverages weights of pre-trained networks, but mandates the need for similar neural architectures. Alternatively, knowledge distillation can transfer knowledge between heterogeneous networks but often requires access to the original training data or additional generative networks. Knowledge transfer between networks can be improved by being agnostic to the choice of network architecture and reducing the dependence on original training data. We propose a knowledge transfer approach from a teacher to a student network wherein we train the student on an independent transferal dataset, whose annotations are generated by the teacher. Experiments were conducted on five state-of-the-art networks for semantic segmentation and seven datasets across three imaging modalities. We studied knowledge transfer from a single teacher, combination of knowledge transfer and fine-tuning, and knowledge transfer from multiple teachers. The student model with a single teacher achieved similar performance as the teacher; and the student model with multiple teachers achieved better performance than the teachers. The salient features of our algorithm include: 1)no need for original training data or generative networks, 2) knowledge transfer between different architectures, 3) ease of implementation for downstream tasks by using the downstream task dataset as the transferal dataset, 4) knowledge transfer of an ensemble of models, trained independently, into one student model. Extensive experiments demonstrate that the proposed algorithm is effective for knowledge transfer and easily tunable.

Power laws are a characteristic distribution that are ubiquitous, in that they are found almost everywhere, in both natural as well as in man-made systems. They tend to emerge in large, connected and self-organizing systems, for example, scholarly publications. Citations to scientific papers have been found to follow a power law, i.e., the number of papers having a certain level of citation x are proportional to x raised to some negative power. The distributional character of altmetrics has not been studied yet as altmetrics are among the newest indicators related to scholarly publications. Here we select a data sample from the altmetrics aggregator Altmetrics.com containing records from the platforms Facebook, Twitter, News, Blogs, etc., and the composite variable Alt-score for the period 2016. The individual and the composite data series of 'mentions' on the various platforms are fit to a power law distribution, and the parameters and goodness of fit determined using least squares regression. The log-log plot of the data, 'mentions' vs. number of papers, falls on an approximately linear line, suggesting the plausibility of a power law distribution. The fit is not very good in all cases due to large fluctuations in the tail. We show that fit to the power law can be improved by truncating the data series to eliminate large fluctuations in the tail. We conclude that altmetric distributions also follow power laws with a fairly good fit over a wide range of values. More rigorous methods of determination may not be necessary at present., Comment: 18 pages

The increased social media attention to scholarly articles has resulted in efforts to create platforms & services to track and measure the social media transactions around scholarly articles in different social platforms (such as Twitter, Blog, Facebook) and academic social networks (such as Mendeley, Academia and ResearchGate). Altmetric.com and PlumX are two popular aggregators that track social media activity around scholarly articles from a variety of social platforms and provide the coverage and transaction data to researchers for various purposes. However, some previous studies have shown that the social media data captured by the two aggregators have differences in terms of coverage and magnitude of mentions. This paper aims to revisit the question by doing a large-scale analysis of social media mentions of a data sample of 1,785,149 publication records (drawn from multiple disciplines, demographies, publishers). Results obtained show that PlumX tracks more wide sources and more articles as compared to Altmetric.com. However, the coverage and average mentions of the two aggregators vary across different social media platforms, with Altmetric.com recording higher mentions in Twitter and Blog, and PlumX recording higher mentions in Facebook and Mendeley, for the same set of articles. The coverage and average mentions captured by the two aggregators across different document types, disciplines and publishers is also analyzed., Comment: 23 pages including 4 figures and 7 tables

Traditionally, Web of Science and Scopus have been the two most widely used databases for bibliometric analyses. However, during the last few years some new scholarly databases, such as Dimensions, have come up. Several previous studies have compared different databases, either through a direct comparison of article coverage or by comparing the citations across the databases. This article attempts to compare the journal coverage of the three databases: Web of Science, Scopus and Dimensions. The most recent master journal lists of the three databases have been used for the purpose of identifying the overlapping and unique journals covered in the databases. The results indicate that the databases have significantly different journal coverage, with the Web of Science being most selective and Dimensions being the most exhaustive. About 99.11% and 96.61% of the journals indexed in Web of Science are also indexed in Scopus and Dimensions, respectively. Scopus has 96.42% of its indexed journals also covered by Dimensions. Dimensions database has the most exhaustive coverage, with 82.22% more journals covered as compared to Web of Science and 48.17% more journals covered as compared to Scopus. We also analysed the research outputs for 20 highly productive countries for the 2010-2019 period, as indexed in the three databases, and identified database-induced variations in research output volume, rank and global share of different countries. In addition to variations in overall coverage of research output from different countries, the three databases appear to have differential coverage of different disciplines., Comment: Submitted to Scientometrics

Knot theory is actively studied both by physicists and mathematicians as it provides a connecting centerpiece for many physical and mathematical theories. One of the challenging problems in knot theory is distinguishing mutant knots. Mutant knots are not distinguished by colored HOMFLY-PT polynomials for knots colored by either symmetric and or antisymmetric representations of $SU(N)$. Some of the mutant knots can be distinguished by the simplest non-symmetric representation $[2,1]$. However there is a class of mutant knots which require more complex representations like $[4,2]$. In this paper we calculate polynomials and differences for the mutant knot polynomials in representations $[3,1]$ and $[4,2]$ and study their properties., Comment: 22 pages + 3 Appendices

Open Access has emerged as an important movement worldwide during the last decade. There are several initiatives now that persuade researchers to publish in open access journals and to archive their pre- or post-print versions of papers in repositories. Institutions and funding agencies are also promoting ways to make research outputs available as open access. This paper looks at open access levels and patterns in research output from India by computationally analyzing research publication data obtained from Web of Science for India for the last five years (2014-2018). The corresponding data from other connected platforms -- Unpaywall and Sci-Hub -- are also obtained and analyzed. The results obtained show that about 24% of research output from India, during last five years, is available in legal forms of open access as compared to world average of about 30%. More articles are available in gold open access as compared to green and bronze. On the contrary, more than 90% of the research output from India is available for free download in Sci-Hub. We also found disciplinary differentiation in open access, but surprisingly these patterns are different for gold-green and black open access forms. Sci-Hub appears to be complementing the legal gold-green open access for less covered disciplines in them. The central institutional repositories in India are found to have low volume of research papers deposited.

We study the multi-boundary entanglement structure of the state associated with the torus link complement $S^3 \backslash T_{p,q}$ in the set-up of three-dimensional SU(2)$_k$ Chern-Simons theory. The focal point of this work is the asymptotic behavior of the R\'enyi entropies, including the entanglement entropy, in the semiclassical limit of $k \to \infty$. We present a detailed analysis for several torus links and observe that the entropies converge to a finite value in the semiclassical limit. We further propose that the large $k$ limiting value of the R\'enyi entropy of torus links of type $T_{p,pn}$ is the sum of two parts: (i) the universal part which is independent of $n$, and (ii) the non-universal or the linking part which explicitly depends on the linking number $n$. Using the analytic techniques, we show that the universal part comprises of Riemann zeta functions and can be written in terms of the partition functions of two-dimensional topological Yang-Mills theory. More precisely, it is equal to the R\'enyi entropy of certain states prepared in topological $2d$ Yang-Mills theory with SU(2) gauge group. Further, the universal parts appearing in the large $k$ limits of the entanglement entropy and the minimum R\'enyi entropy for torus links $T_{p,pn}$ can be interpreted in terms of the volume of the moduli space of flat connections on certain Riemann surfaces. We also analyze the R\'enyi entropies of $T_{p,pn}$ link in the double scaling limit of $k \to \infty$ and $n \to \infty$ and propose that the entropies converge in the double limit as well., Comment: 68 pages, 13 figures and 11 tables. Matches with the published version

Social media platforms have now emerged as an important medium for wider dissemination of research articles; with authors, readers and publishers creating different kinds of social media activity about the article. Some research studies have even shown that articles that get more social media attention may get higher visibility and citations. These factors are now persuading journal publishers to integrate social media plugins in their webpages to facilitate sharing and dissemination of articles in social media platforms. Many past studies have analyzed several factors (like journal impact factor, open access, collaboration etc.) that may impact social media attention of scholarly articles. However, there are no studies to analyze whether the presence of social media plugin in a journal could result in higher social media attention of articles published in the journal. This paper aims to bridge this gap in knowledge by analyzing a sufficiently large-sized sample of 99,749 articles from 100 different journals. Results obtained show that journals that have social media plugins integrated in their webpages get significantly higher social media mentions and shares for their articles as compared to journals that do not provide such plugins. Authors and readers visiting journal webpages appear to be a major contributor to social media activity around articles published in such journals. The results suggest that publishing houses should actively provide social media plugin integration in their journal webpages to increase social media visibility (altmetric impact) of their articles., Comment: in press

During the last two decades, India has emerged as a major knowledge producer in the world, however different reports put it at different ranks, varying from 3rd to 9th places. The recent commissioned study reports of Department of Science and Technology (DST) done by Elsevier and Clarivate Analytics, rank India at 5thand 9th places, respectively. On the other hand, an independent report by National Science Foundation (NSF) of United States (US), ranks India at 3rd place on research output in Science and Engineering area. Interestingly, both, the Elsevier and the NSF reports use Scopus data, and yet surprisingly their outcomes are different. This article, therefore, attempts to investigate as to how the use of same database can still produce different outcomes, due to differences in methodological approaches. The publication counting method used and the subject selection approach are the two main exogenous factors identified to cause these variations. The implications of the analytical outcomes are discussed with special focus on policy perspectives.

India is emerging as a major knowledge producer of the world in terms of proportionate share of global research output and the overall research productivity rank. Many recent reports, both of commissioned studies from Government of India as well as independent international agencies, show India at different ranks of global research productivity (variations as large as from 3rd to 9th place). The paper examines this contradiction; tries to analyse as to why different reports places India at different ranks and what may be the reasons thereof. The research output data for India, along with the ten most productive countries in the world, is analysed from three major scholarly databases: Web of Science, Scopus and Dimensions for this purpose. Results show that both, the endogenous factors (such as database coverage variation and different subject classification schemes) and the exogenous factors (such as subject selection and publication counting methodology) cause the variations in different reports. This paper reports first part of the analysis, focusing mainly on variations due to use of data from different databases. The policy implications of the study are also discussed., Comment: 12 pages Submitted to Journal of Scientific Research

We evaluate the differences of HOMFLY-PT invariants for pairs of mutant knots colored with representations of $SL(N)$, which are large enough to distinguish between them. These mutant pairs include the pretzel mutants, which require at least the representation, labeled by the Young diagram $[4,2]$. We discuss the differential expansion for the differences, it is non-trivial in the case of mutants, which have the non-zero defect. The most effective technical tool, in this case, turns out to be the standard Reshetikhin-Turaev approach., Comment: 6 pages

Using event-by-event fluctuations, we study the diffusion parameters of net-charge, net-pion, net-kaon, and net-proton in the heavy-ion jet interaction generator (HIJING), and ultra-relativistic quantum molecular dynamics (UrQMD) models at different collision energies \sqsn available at BNL Relativistic Heavy Ion Collider (RHIC). The diffusion parameter ($\sigma$) of net-charge and identified particles are estimated in rapidity space at various \sqsn. It is observed that, the $\sigma$ values are independent of collision energies but emphasises the particle-species dependence of diffusion coefficient in the QGP medium. The present work on particle-species dependence of diffusion coefficient provides a baseline for comparison with the experimental data., Comment: arXiv admin note: substantial text overlap with arXiv:1907.02850

The popular social media platforms are now making it possible for scholarly articles to be shared rapidly in different forms, which in turn can significantly improve the visibility and reach of articles. Many authors are now utilizing the social media platforms to disseminate their scholarly articles (often as pre- or post- prints) beyond the paywalls of journals. It is however not very well established if the level of social media coverage and attention of scholarly articles is same across all research disciplines or there exist discipline-wise variations. This paper aims to explore the disciplinary variations in coverage and altmetric attention by analyzing a significantly large amount of data from Web of Science and Altmetric.com. Results obtained show interesting patterns. Medical Sciences and Biology are found to account for more than 50% of all instances in Altmetrics. In terms of coverage, disciplines like Biology, Medical Science and Multidisciplinary Sciences have more than 60% of their articles covered in Altmetrics, whereas disciplines like Engineering, Mathematics and Material Science have less than 25% of their articles covered in Altmetrics. The coverage percentages further vary across different altmetric platforms, with Twitter and Mendeley having much higher overall coverage than Facebook and News. Disciplinary variations in coverage are also found in different altmetric platforms, with variations as large as 7.5% for Engineering discipline to 55.7% for Multidisciplinary in Twitter. The paper also looks into the possible role of source of publication in altmetric coverage level of articles. Interestingly, some journals are found to have a higher altmetric coverage in comparison to the average altmetric coverage level of that discipline., Comment: 12 pages, 1 figure, revised paper accepted at the 17th International Conference on Scientometrics & Informetrics (ISSI 2019), Rome, Italy

Scholarly articles are now increasingly being mentioned and discussed in social media platforms, sometimes even as pre- or post-print version uploads. Measures of social media mentions and coverage are now emerging as an alternative indicator of impact of scholarly articles. This article aims to explore how much scholarly research output from India is covered in different social media platforms, and how similar or different it is from the world average. It also analyses the discipline-wise variations in coverage and altmetric attention for Indian research output, including a comparison with the world average. Results obtained show interesting patterns. Only 28.5% of the total research output from India is covered in social media platforms, which is about 18% less than the world average. ResearchGate and Mendeley are the most popular social media platforms in India for scholarly article coverage. In terms of discipline-wise variation, medical sciences and biological sciences have relatively higher coverage across different platforms compared to disciplines like information science and engineering., Comment: 8 pages, 4 figures, Published in CURRENT SCIENCE, VOL. 117, NO. 5, 2019

We study the fluctuations of net-charge, net-pion, net-kaon and net-proton using $D$-measure and $\nu_{dyn}$ variables in heavy-ion jet interaction generator (HIJING), ultra-relativistic quantum molecular dynamics (UrQMD), and hadron resonance gas (HRG) model at different collision energies \sqsn. It has been observed that, the values of $D$ strongly dependent on $\Delta \eta$ in HIJING and UrQMD models and independent in HRG model. The diffusion coefficients ($\sigma$) of identified particles are estimated at various \sqsn. It is observed that, the $\sigma$ values are independent of collision energies but emphasizes the particle species dependence of diffusion coefficient in the QGP medium. This study provides a realistic baseline for comparison with the experimental data.