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We present a technique which predicts the energy dependent fractional r.m.s for linear correlated variations of a pair of spectral parameters and apply it to an XMM-Newton observation of Mrk 335. The broadband X-ray spectrum can be interpreted as a patchy absorber partially covering the primary emission, a warm and hot coronal emission or a relativistically blurred reflection along with the primary emission. The fractional r.m.s has a non-monotonic behavior with energy for segments of lengths 3 and 6 ksecs. For each spectral model, we consider every pair of spectral parameters and fit the predicted r.m.s with the observed ones, to get the pair which provides the best fit. We find that a variation in at least two parameters is required for all spectral interpretations. For both time segments, variations in the covering fraction of the absorber and the primary power law index gives the best result for the partial covering model, while a variation in the normalization and spectral index of the warm component gives the best fit in the two corona interpretation. For the reflection model, the best fit parameters are different for the two time segment lengths, and the results suggests that more than two parameters are required to explain the data. This, combined with the extreme values of emissivity index and reflection fraction parameters obtained from the spectral analysis, indicates that the blurred reflection model might not be a suitable explanation for the Mrk 335 spectrum. We discuss the results as well as the potential of the technique to be applied to other data sets of different AGN., Comment: Accepted for publication in JHEAP

Among very metal-poor (VMP) stars, $\alpha$-poor VMP ($\alpha$PVMP) stars that have sub-solar values of ${\rm [X/Fe]}$ for Mg and other $\alpha$ elements are rare and are thought to have been formed from gas polluted by Type 1a supernova (SN 1a). However, recent analyses indicate that pure core-collapse supernova (CCSN) ejecta can also be a likely source. We perform a detailed analysis of 17 $\alpha$PVMP stars by considering six different scenarios relevant to the early Galaxy. We consider a single pair-instability supernova (PISN) and a single CCSN. Additionally, we consider the combination of ejecta from a CCSN with ejecta from another CCSN, a PISN, a near-Chandrasekhar mass (near-${\rm M_{Ch}}$) SN 1a, and a sub-Chandrasekhar mass (sub-${\rm M_{Ch}}$) SN 1a. A clear signature can only be established for sub-${\rm M_{Ch}}$ SN 1a with a near-smoking-gun signature in SDSSJ0018-0939 and a reasonably clear signature in ET0381. The majority ($82\%$) of $\alpha$PVMP stars can be explained by pure CCSN ejecta and do not require any SN 1a contribution. However, the combination of CCSN and sub-${\rm M_{Ch}}$ SN 1a ejecta can also explain most ($76\%$) of $\alpha$PVMP stars. In contrast, the combination of ejecta from CCSN with near-${\rm M_{Ch}}$ SN 1a and PISN can fit $41\%$ and $29\%$ of the stars, respectively. The single PISN scenario is strongly ruled out for all stars. Our results indicate that $\alpha$PVMP stars are equally compatible with pure CCSN ejecta and a combination of CCSN and SN 1a ejecta, with sub-${\rm M_{Ch}}$ SN 1a being roughly twice as frequent as near-${\rm M_{Ch}}$ SN 1a., Comment: 20 pages, 5 figures, 6 tables, submitted

Signature from Pop III massive stars of $140$--$260\,{\rm M_\odot}$ that end their lives as pair-instability supernovae (PISNe) are expected to be seen in very metal-poor (VMP) stars of ${\rm [Fe/H]}\leq -2$. Although thousands of VMP stars have been discovered, the identification of a VMP star with a PISN signature has been elusive. Recently, the VMP star LAMOST J1010+2358 was claimed to be the first star with a clear PISN signature. A subsequent study showed that ejecta from low-mass core-collapse supernovae (CCSNe) can also fit the abundance pattern equally well and additional elements such as C and Al are required to differentiate the two sources. Follow-up observations of LAMOST J1010+2358 by two independent groups were able to detect both C and Al. Additionally, key odd elements such as Na and Sc were also detected whose abundances were found to be higher than the upper limits found in the original detection. We perform a detailed analysis of the newly observed abundance patterns by exploring various possible formation channels for VMP stars. We find that purely low-mass CCSN ejecta as well as the combination of CCSN and Type 1a SN ejecta can provide an excellent fit to the newly observed abundance pattern. Our results confirm earlier analysis that the newly observed abundance pattern is peculiar but has no signatures of PISN., Comment: 5 pages, 4 figures, 1 table

Very metal-poor (VMP) stars (${\rm [Fe/H]}\leq -2$) that have sub-solar values of ${\rm [X/Fe]}$ for $\alpha$ elements such as Mg, Si, and Ca, are referred to as $\alpha$-poor VMP stars. They are quite rare among VMP stars and are thought to have formed from gas enriched predominantly by a single Type Ia supernovae (SN1a) in contrast to most VMP stars which are $\alpha$-enhanced and usually associated with core-collapse supernovae. The observed abundance pattern in such stars can provide a direct way to probe the nucleosynthesis in individual SN1a. Although the abundance patterns in some $\alpha$-poor VMP stars have been shown to be consistent with SN1a ejecta, a clear nucleosynthetic signature for SN1a resulting from the explosion of a near Chandrasekhar mass (near-${\rm M_{Ch}}$) or a sub-Chandrasekhar mass (sub-${\rm M_{Ch}}$) white dwarf, has not been unambiguously detected. We perform a detailed analysis of various formation channels of VMP stars and find that the $\alpha$-poor VMP star SDSSJ0018-0939, which was earlier reported as a star with potential pair-instability supernova origin, provides almost a smoking-gun signature of a sub-${\rm M_{Ch}}$ SN1a resulting from He detonation. We find that compared to other $\alpha$-poor VMP stars that were previously identified with SN1a, SDSSJ0018-0939 is the only star that has a clear and unambiguous signature of SN1a. Interestingly, our results are consistent with constraints on SN1a from recent galactic chemical evolution studies that indicate that sub-${\rm M_{Ch}}$ SN1a account for $\sim 50\hbox{--}75\,\%$ of all SN1a and are possibly the dominant channel in the early Galaxy., Comment: 14 pages, 4 figures, 2 tables. Submitted to journal

We present the results from a long term X-ray analysis of Mrk 279 during the period 2018-2020. We use data from multiple missions - AstroSat, NuSTAR and XMM-Newton, for the purpose. The X-ray spectrum can be modelled as a double Comptonisation along with the presence of neutral Fe K${\alpha}$ line emission, at all epochs. We determined the source's X-ray flux and luminosity at these different epochs. We find significant variations in the source's flux state. We also investigated the variations in the source's spectral components during the observation period. We find that the photon index and hence the spectral shape follow the variations only over longer time periods. We probe the correlations between fluxes of different bands and their photon indices, and found no significant correlations between the parameters., Comment: Accepted for publication in Research in Astronomy and Astrophysics

This paper provides a few approaches to automating computer programming and project submission tasks, that we have been following for the last six years and have found to be successful. The approaches include using CodeRunner with Learning Management System (LMS) integration for programming practice and evaluation, and Git (GitHub) for project submissions and automatic code evaluation. In this paper, we describe the details of how we set up the tools and customized those for computer science courses. Based on our experiences, we also provide a few insights on using these tools for effective learning., Comment: 14 pages, 15 figures

Low-metallicity very massive stars with an initial mass of $\sim 140$--$260\, {\rm M_\odot}$ are expected to end their lives as pair-instability supernovae (PISNe). The abundance pattern resulting from a PISN differs drastically from regular core-collapse supernova (CCSN) models and is expected to be seen in very metal-poor (VMP) stars of ${\rm[Fe/H]}\lesssim -2$. Despite the routine discovery of many VMP stars, the unique abundance pattern expected from PISNe has not been unambiguously detected. The recently discovered VMP star LAMOST J1010+2358, however, shows a peculiar abundance pattern that is remarkably well fit by a PISN, indicating the potential first discovery of a bonafide star born from gas polluted by a PISN. In this paper, we study the detailed nucleosynthesis in a large set of models of CCSN of Pop III and Pop II star of metallicity ${\rm[Fe/H]}=-3$ with masses ranging from $12$--$30\,{\rm M_\odot}$. We find that the observed abundance pattern in LAMOST J1010+2358 can be fit at least equally well by CCSN models of $\sim 12$--$14\,{\rm M_\odot}$ that undergo negligible fallback following the explosion. The best-fit CCSN models provide a fit that is even marginally better than the best-fit PISN model. We conclude the measured abundance pattern in LAMOST J1010+2358 could have originated from a CCSN and therefore cannot be unambiguously identified with a PISN given the set of elements measured in it to date. We identify key elements that need to be measured in future detections in stars like LAMOST J1010+2358 that can differentiate between CCSN and PISN origin., Comment: 7 pages, 5 figures, Accepted in MNRAS

Very metal-poor stars that have $[\text{Fe}/\text{H}]<-2$ and that are enhanced in C relative to Fe ($[\text{C}/\text{Fe}]>+0.7$) but have no enhancement of heavy elements ($[\text{Ba}/\text{Fe}]<0$) are known as carbon-enhanced metal-poor (CEMP-no) stars. These stars are thought to be produced from a gas that was polluted by the supernova (SN) ejecta of the very first generation (Pop III) massive stars. The very high enrichment of C ($A(\text{C})\gtrsim 6$) observed in many of the CEMP-no stars is difficult to explain by current models of SN explosions from massive Pop III stars when a reasonable dilution of the SN ejecta, that is consistent with detailed simulation of metal mixing in minihaloes, is adopted. We explore rapidly rotating Pop III stars that undergo efficient mixing and reach a quasi-chemically homogeneous (QCH) state. We find that QCH stars can eject large amounts of C in the wind and that the resulting dilution of the wind ejecta in the interstellar medium can lead to a C enrichment of $A(\text{C})\lesssim7.75$. The core of QCH stars can produce up to an order of magnitude of more C than non-rotating progenitors of similar mass and the resulting SN can lead to a C enrichment of $A(\text{C})\lesssim7$. Our rapidly rotating massive Pop III stars cover almost the entire range of $A(\text{C})$ observed in CEMP-no stars and are a promising site for explaining the high C enhancement in the early Galaxy. Our work indicates that a substantial fraction of Pop III stars were likely rapid rotators., Comment: 16 pages, 8 figures, and 8 tables. Accepted in MNRAS

Recursive neural networks (Tree-RNNs) based on dependency trees are ubiquitous in modeling sentence meanings as they effectively capture semantic relationships between non-neighborhood words. However, recognizing semantically dissimilar sentences with the same words and syntax is still a challenge to Tree-RNNs. This work proposes an improvement to Dependency Tree-RNN (DT-RNN) using the grammatical relationship type identified in the dependency parse. Our experiments on semantic relatedness scoring (SRS) and recognizing textual entailment (RTE) in sentence pairs using SICK (Sentence Involving Compositional Knowledge) dataset show encouraging results. The model achieved a 2% improvement in classification accuracy for the RTE task over the DT-RNN model. The results show that Pearson's and Spearman's correlation measures between the model's predicted similarity scores and human ratings are higher than those of standard DT-RNNs.

GW170817 has confirmed binary neutron star mergers as one of the sites for rapid neutron capture ($r$) process. However, there are large theoretical and experimental uncertainties associated with the resulting nucleosynthesis calculations and additional sites may be needed to explain all the existing observations. In this regard, abundances of short-lived radioactive isotopes (SLRIs) in the early solar system (ESS), that are synthesized exclusively by $r$-process, can provide independent clues regarding the nature of $r$-process events. In this work, we study the evolution of $r$-process SLRIs $^{129}$I and $^{247}$Cm as well as the corresponding reference isotopes $^{127}$I and $^{235}$U at the Solar location. We consider up to three different sources that have distinct $^{129}$I/$^{247}$Cm production ratios corresponding to the varied $r$-process conditions in different astrophysical scenarios. In contrast to the results found by C\^ot\'e et al. (2021), we find that $^{129}$I and $^{247}$Cm in the ESS do not come entirely from a single major event but get contributions from at least two more minor contributors. This has a dramatic effect on the evolution of the $^{129}$I/$^{247}$Cm ratio, such that the measured ESS value in meteorites may not correspond to that of the "$last$" major $r$-process event. Interestingly, however, we find that the $^{129}$I/$^{247}$Cm ratio, in combination with the observed $^{129}$I/$^{127}$I and $^{247}$Cm/$^{235}$U ratio in the ESS, can still provide important constraints on the properties of proposed $r$-process sources operating in the Milky Way., Comment: 14 pages, 5 figures, 7 tables

Cerebrovascular accident (CVA) or stroke is the rapid loss of brain function due to disturbance in the blood supply to the brain. Statistically, stroke is the second leading cause of death. This has motivated us to suggest a two-tier system for predicting stroke; the first tier makes use of Artificial Neural Network (ANN) to predict the chances of a person suffering from stroke. The ANN is trained the using the values of various risk factors of stroke of several patients who had stroke. Once a person is classified as having a high risk of stroke, s/he undergoes another the tier-2 classification test where his/her neuro MRI (Magnetic resonance imaging) is analysed to predict the chances of stroke. The tier-2 uses Non-negative Matrix Factorization and Haralick Textural features for feature extraction and SVM classifier for classification. We have obtained an accuracy of 96.67% in tier-1 and an accuracy of 70% in tier-2., Comment: arXiv admin note: text overlap with arXiv:1706.08227

Tree-based Long short term memory (LSTM) network has become state-of-the-art for modeling the meaning of language texts as they can effectively exploit the grammatical syntax and thereby non-linear dependencies among words of the sentence. However, most of these models cannot recognize the difference in meaning caused by a change in semantic roles of words or phrases because they do not acknowledge the type of grammatical relations, also known as typed dependencies, in sentence structure. This paper proposes an enhanced LSTM architecture, called relation gated LSTM, which can model the relationship between two inputs of a sequence using a control input. We also introduce a Tree-LSTM model called Typed Dependency Tree-LSTM that uses the sentence dependency parse structure as well as the dependency type to embed sentence meaning into a dense vector. The proposed model outperformed its type-unaware counterpart in two typical NLP tasks - Semantic Relatedness Scoring and Sentiment Analysis, in a lesser number of training epochs. The results were comparable or competitive with other state-of-the-art models. Qualitative analysis showed that changes in the voice of sentences had little effect on the model's predicted scores, while changes in nominal (noun) words had a more significant impact. The model recognized subtle semantic relationships in sentence pairs. The magnitudes of learned typed dependencies embeddings were also in agreement with human intuitions. The research findings imply the significance of grammatical relations in sentence modeling. The proposed models would serve as a base for future researches in this direction., Comment: Accepted manuscript submitted to Journal of Information Processing and Management ( Elsevier ) on June 11, 2020