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In this work, the cross-sections of 27 fission-like fragments within the mass range 76$\leq$A$\leq$141, expected to be populated via fission of moderately excited compound nucleus produced as a result of complete and/or incomplete fusion in $^{12}$C+$^{208}$Pb reaction at E$_{\rm lab}$ = 81.9 and 75.8 MeV, have been measured using activation technique followed by offline $\gamma$-ray spectroscopy. The yields of different fission-like fragments have been analyzed to generate isotopic and isobaric yield distributions. The value of the mass dispersion parameter, $\sigma^2_A$, is found to be 2.93 and 2.65 for Antimony (Sb) isotope at excitation energy E$^{\star}$ = 45.4 and 39.6 MeV, and 1.24 for Indium (In) isotope at E$^{\star}$ = 45.4 MeV. The charge dispersion parameter $\sigma_Z$ for Sb is estimated to be 0.769 and 0.714 at E$^{\star}$ = 45.4 and 39.6 MeV, respectively. For In isotopes, the value of $\sigma_Z$ is estimated to be 0.430 at E$^{\star}$ = 45.4 MeV. The value of mass and charge dispersion parameters for Sb and In isotopes have been found to be in good agreement with the values reported in the literature for similar systems. The mass distribution of fission-like fragments is found to be fitted with a Gaussian function, except for a few data points, indicating their population via compound nucleus fission. Further, the mass variance ($\sigma^2_M$) displays linear increment with an increase in excitation energy. Two medically important isotopes, $^{99m}$Tc and $^{111}$In, are populated in this system, suggesting a potential formation route.

Excitation functions of several evaporation residues populated via complete and/or incomplete fusion in $^{12}$C+$^{193}$Ir system have been measured at energies $\approx$ 64-84 MeV, and analyzed in the framework of theoretical model code PACE4. It has been found that the $xn$ channels are predominantly populated via complete fusion; however, some of the $pxn$ channels decay via their precursor. A significant enhancement has been observed in the case of $\alpha$-emitting channels over PACE4 calculations, indicating the onset of a reaction mechanism not included in this code, e.g., incomplete fusion. For better insights into the onset and influence of incomplete fusion, the percentage fraction of incomplete fusion has been deduced and analyzed in terms of different entrance-channel parameters. The findings of the present study underline the importance of projectile energy, entrance-channel mass-asymmetry, and the Coulomb factor of interacting partners. The impact of projectile break-up on complete fusion has also been discussed in the framework of the Universal Fusion Function, where suppression of $\approx$ 12$\%$ has been observed in the fusion function. The finding of the present work reinstates that the fusion suppression is affected by the projectile $\alpha$-break-up threshold.

This paper describes our submissions to SemEval 2020 Task 11: Detection of Propaganda Techniques in News Articles for each of the two subtasks of Span Identification and Technique Classification. We make use of pre-trained BERT language model enhanced with tagging techniques developed for the task of Named Entity Recognition (NER), to develop a system for identifying propaganda spans in the text. For the second subtask, we incorporate contextual features in a pre-trained RoBERTa model for the classification of propaganda techniques. We were ranked 5th in the propaganda technique classification subtask., Comment: 7 pages, 4 figures, 2 tables Accepted at Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval-2020)

Line art is arguably one of the fundamental and versatile modes of expression. We propose a pipeline for a robot to look at a grayscale line art and redraw it. The key novel elements of our pipeline are: a) we propose a novel task of mimicking line drawings, b) to solve the pipeline we modify the Quick-draw dataset to obtain supervised training for converting a line drawing into a series of strokes c) we propose a multi-stage segmentation and graph interpretation pipeline for solving the problem. The resultant method has also been deployed on a CNC plotter as well as a robotic arm. We have trained several variations of the proposed methods and evaluate these on a dataset obtained from Quick-draw. Through the best methods we observe an accuracy of around 98% for this task, which is a significant improvement over the baseline architecture we adapted from. This therefore allows for deployment of the method on robots for replicating line art in a reliable manner. We also show that while the rule-based vectorization methods do suffice for simple drawings, it fails for more complicated sketches, unlike our method which generalizes well to more complicated distributions., Comment: 9 pages, Accepted for the 2020 Winter Conference on Applications of Computer Vision (WACV '20); Supplementary Video: https://youtu.be/nMt5Dw04XhY