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Astrometry has long been a promising technique for exoplanet detection. At the theoretical limits, astrometry would allow for the detection of smaller planets than previously seen by current exoplanet search methods, but stellar activity may make these theoretical limits unreachable. Astrometric jitter of a Sun-like star due to magnetic activity in its photosphere induces apparent variability in the photocenter of order $0.5\ \textrm{m}R_\odot$. This jitter creates a fundamental astrophysical noise floor preventing detection of lower-mass planets in a single spectral band. By injecting planet orbits into simulated solar data at five different passbands, we investigate mitigation of this fundamental astrometric noise using correlations across passbands. For a true solar analog and a planet at 1 au semimajor axis, the $6\sigma$ detection limit set by stellar activity for an ideal telescope at the best single passband is $0.01$ Earth masses. We found that pairs of passbands with highly correlated astrometric jitter due to stellar activity, but with less motion in the redder band, enable higher-precision measurements of the common signal from the planet. Using this method improves detectable planet masses at 1 au by up to a factor of $10$, corresponding to at best $0.005$ Earth masses for a Sun-like star with a perfect telescope. Given these results, we recommend that future astrometry missions consider proceeding with two or more passbands to reduce noise due to stellar activity., Comment: 11 pages, 9 figures. Published in AJ

Computer aided diagnostics often requires analysis of a region of interest (ROI) within a radiology scan, and the ROI may be an organ or a suborgan. Although deep learning algorithms have the ability to outperform other methods, they rely on the availability of a large amount of annotated data. Motivated by the need to address this limitation, an approach to localisation and detection of multiple organs based on supervised and semi-supervised learning is presented here. It draws upon previous work by the authors on localising the thoracic and lumbar spine region in CT images. The method generates six bounding boxes of organs of interest, which are then fused to a single bounding box. The results of experiments on localisation of the Spleen, Left and Right Kidneys in CT Images using supervised and semi supervised learning (SSL) demonstrate the ability to address data limitations with a much smaller data set and fewer annotations, compared to other state-of-the-art methods. The SSL performance was evaluated using three different mixes of labelled and unlabelled data (i.e.30:70,35:65,40:60) for each of lumbar spine, spleen left and right kidneys respectively. The results indicate that SSL provides a workable alternative especially in medical imaging where it is difficult to obtain annotated data., Comment: 16 pages, 12 figures

Manufacturing industries have widely adopted the reuse of machine parts as a method to reduce costs and as a sustainable manufacturing practice. Identification of reusable features from the design of the parts and finding their similar features from the database is an important part of this process. In this project, with the help of fully convolutional geometric features, we are able to extract and learn the high level semantic features from CAD models with inductive transfer learning. The extracted features are then compared with that of other CAD models from the database using Frobenius norm and identical features are retrieved. Later we passed the extracted features to a deep convolutional neural network with a spatial pyramid pooling layer and the performance of the feature retrieval increased significantly. It was evident from the results that the model could effectively capture the geometrical elements from machining features., Comment: Submitted to 9th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2021)

Handwritten documents are often characterized by dense and uneven layout. Despite advances, standard deep network based approaches for semantic layout segmentation are not robust to complex deformations seen across semantic regions. This phenomenon is especially pronounced for the low-resource Indic palm-leaf manuscript domain. To address the issue, we first introduce Indiscapes2, a new large-scale diverse dataset of Indic manuscripts with semantic layout annotations. Indiscapes2 contains documents from four different historical collections and is 150% larger than its predecessor, Indiscapes. We also propose a novel deep network Palmira for robust, deformation-aware instance segmentation of regions in handwritten manuscripts. We also report Hausdorff distance and its variants as a boundary-aware performance measure. Our experiments demonstrate that Palmira provides robust layouts, outperforms strong baseline approaches and ablative variants. We also include qualitative results on Arabic, South-East Asian and Hebrew historical manuscripts to showcase the generalization capability of Palmira., Comment: Accepted at ICDAR-21. Watch teaser video https://www.youtube.com/watch?v=V4XWngkrtxQ , code and pretrained models https://github.com/ihdia/Palmira , project page https://ihdia.iiit.ac.in/Palmira

Role of the Coulomb interaction, mean fissility, mass asymmetry, and charge asymmetry parameters on the synthesis of heavy and superheavy elements has been examined with respect to the deformation parameters of the projectile and target nuclei explicitly in light of the experimental results. The observed facts are classified into four categories and are then used to study several unsuccessful as well as planned reactions to synthesize the new superheavy elements $Z= 119, 120$. Concrete inference is too difficult to draw from these results because of excessive deviations in evaporation residue cross-section data. It is found that the arbitrary choice of excitation energy for the experiments studied was the root cause of such large deviations. Such a complex issue can be resolved well by theoretical excitation function studies using the advanced statistical model or the dinuclear system model and choosing the excitation energy corresponding to the energy where the excitation function curve shows the maximum. We believe this method may help us to predict whether the estimated evaporation residue cross-section can be measurable within the experimental limit of the existing facilities for the future reactions planned., Comment: 5 figures

Ensuring nominal asymptotic stability of the Nonlinear Model Predictive Control controller is not trivial. Stabilizing ingredients such as terminal penalty term and terminal region are crucial in establishing the asymptotic stability. Current work presents alternate approaches namely arbitrary controller based approach and linear quadratic regulator based approach, which provide larger degrees of freedom for enlarging the terminal region as against conservative approaches from the literature. Efficacy of the proposed approaches is demonstrated using benchmark two state continuous stirrer tank reactor system around an unstable operating point. Terminal regions obtained using the arbitrary controller based approach and linear quadratic regulator based approach are approximately 45 and 412 times larger by area measure when compared to the largest terminal region obtained using the approach from the literature. As a result, there is significant reduction in the prediction and control horizon time., Comment: 19 pages, 6 figures, 4 tables. arXiv admin note: substantial text overlap with arXiv:2107.09267

Ensuring nominal asymptotic stability of the Non-linear Model Predictive Control (NMPC) controller is not trivial. Stabilizing ingredients such as terminal penalty term and terminal region are crucial in establishing the asymptotic stability. Approaches available in the literature provide limited degrees of freedom for the characterization of the terminal region for the discrete time Quasi Infinite Horizon NMPC (QIH-NMPC) formulation. Current work presents alternate approaches namely arbitrary controller based approach and LQR based approach, which provide large degrees of freedom for enlarging the terminal region. Both the approaches are scalable to system of any state and input dimension. Approach from the literature provides a scalar whereas proposed approaches provide a linear controller and two additive matrices as tuning parameters for shaping of the terminal region. Proposed approaches involve solving modified Lyapunov equations to compute terminal penalty term, followed by explicit characterization of the terminal region. Efficacy of the proposed approaches is demonstrated using benchmark two state system. Terminal region obtained using the arbitrary controller based approach and LQR based approach are approximately 10.4723 and 9.5055 times larger by area measure when compared to the largest terminal region obtained using the approach from the literature., Comment: 6 pages, 1 figure, 6 tables

Ultra-precise astrometry from the Gaia mission is expected to lead to astrometric detections of more than 20,000 exoplanets in our Galaxy. One of the factors that could hamper such detections is the astrometric jitter caused by the magnetic activity of the planet host stars. In our previous study, we modeled astrometric jitter for the Sun observed equator-on. In this work, we generalize our model and calculate the photocenter jitter as it would be measured by the Gaia and Small-JASMINE missions for stars with solar rotation rate and effective temperature, but with various values of the inclination angle of the stellar rotation axis. In addition, we consider the effect of metallicity and of nesting of active regions (i.e. the tendency of active regions to emerge in the vicinity of each other). We find that, while the jitter of stars observed equator-on does not have any long-term trends and can be easily filtered out, the photocenters of stars observed out of their equatorial planes experience systematic shifts over the course of the activity cycle. Such trends allow the jitter to be detected with continuous measurements, in which case it can interfere with planet detectability. An increase in the metallicity is found to increase the jitter caused by stellar activity. Active-region nesting can further enhance the peak-to-peak amplitude of the photocenter jitter to a level that could be detected by Gaia., Comment: 24 pages, 20 figures in the main body and 4 in the appendix, accepted for publication in ApJ

Pervasiveness of tracking devices and enhanced availability of spatially located data has deepened interest in using them for various policy interventions, through computational data analysis tasks such as spatial hot spot detection. In this paper, we consider, for the first time to our best knowledge, fairness in detecting spatial hot spots. We motivate the need for ensuring fairness through statistical parity over the collective population covered across chosen hot spots. We then characterize the task of identifying a diverse set of solutions in the noteworthiness-fairness trade-off spectrum, to empower the user to choose a trade-off justified by the policy domain. Being a novel task formulation, we also develop a suite of evaluation metrics for fair hot spots, motivated by the need to evaluate pertinent aspects of the task. We illustrate the computational infeasibility of identifying fair hot spots using naive and/or direct approaches and devise a method, codenamed {\it FiSH}, for efficiently identifying high-quality, fair and diverse sets of spatial hot spots. FiSH traverses the tree-structured search space using heuristics that guide it towards identifying effective and fair sets of spatial hot spots. Through an extensive empirical analysis over a real-world dataset from the domain of human development, we illustrate that FiSH generates high-quality solutions at fast response times.

Space observatories have provided unprecedented depictions of the many variability behaviors typical of low-mass, young stars. However, those studies have so far largely omitted more massive objects ($\sim$2 $M_\odot$ to 4-5 $M_\odot$), and were limited by the absence of simultaneous, multi-wavelength information. We present a new study of young star variability in the $\sim$1-2 Myr-old, massive Lagoon Nebula region. Our sample encompasses 278 young, late-B to K-type stars, monitored with Kepler/K2. Auxiliary $u,g,r,i,H\alpha$ time series photometry, simultaneous with K2, was acquired at the Paranal Observatory. We employed this comprehensive dataset and archival infrared photometry to determine individual stellar parameters, assess the presence of circumstellar disks, and tie the variability behaviors to inner disk dynamics. We found significant mass-dependent trends in variability properties, with B/A stars displaying substantially reduced levels of variability compared to G/K stars for any light curve morphology. These properties suggest different magnetic field structures at the surface of early-type and later-type stars. We also detected a dearth of some disk-driven variability behaviors, particularly dippers, among stars earlier than G. This indicates that their higher surface temperatures and more chaotic magnetic fields prevent the formation and survival of inner disk dust structures co-rotating with the star. Finally, we examined the characteristic variability timescales within each light curve, and determined that the day-to-week timescales are predominant over the K2 time series. These reflect distinct processes and locations in the inner disk environment, from intense accretion triggered by instabilities in the innermost disk regions, to variable accretion efficiency in the outer magnetosphere., Comment: 36 pages, 15 figures; accepted for publication in AJ

Readability assessment is the task of evaluating the reading difficulty of a given piece of text. Although research on computational approaches to readability assessment is now two decades old, there is not much work on synthesizing this research. This article is a brief survey of contemporary research on developing computational models for readability assessment. We identify the common approaches, discuss their shortcomings, and identify some challenges for the future. Where possible, we also connect computational research with insights from related work in other disciplines such as education and psychology., Comment: To appear in LREC 2022 proceedings

NLP's sphere of influence went much beyond computer science research and the development of software applications in the past decade. We see people using NLP methods in a range of academic disciplines from Asian Studies to Clinical Oncology. We also notice the presence of NLP as a module in most of the data science curricula within and outside of regular university setups. These courses are taken by students from very diverse backgrounds. This paper takes a closer look at some issues related to teaching NLP to these diverse audiences based on my classroom experiences, and identifies some challenges the instructors face, particularly when there is no ecosystem of related courses for the students. In this process, it also identifies a few challenge areas for both NLP researchers and tool developers., Comment: To appear in the Teaching NLP workshop at NAACL 2021

COVID 19 is an acute disease that started spreading throughout the world, beginning in December 2019. It has spread worldwide and has affected more than 7 million people, and 200 thousand people have died due to this infection as of Oct 2020. In this paper, we have forecasted the number of deaths and the confirmed cases in Los Angeles and New York of the United States using the traditional and Big Data platforms based on the Times Series: ARIMA and ETS. We also implemented a more sophisticated time-series forecast model using Facebook Prophet API. Furthermore, we developed the classification models: Logistic Regression and Random Forest regression to show that the Weather does not affect the number of the confirmed cases. The models are built and run in legacy systems (Azure ML Studio) and Big Data systems (Oracle Cloud and Databricks). Besides, we present the accuracy of the models., Comment: 8 pages, 7 figures, 4 tables

The emission in the near ultraviolet Ca II H & K lines is modulated by stellar magnetic activity. Although this emission, quantified via the S-index, has been serving as a prime proxy of stellar magnetic activity for several decades, many aspects of the complex relation between stellar magnetism and Ca II H & K emission are still unclear. The amount of measured Ca II H & K emission is suspected to be affected not only by the stellar intrinsic properties but also by the inclination angle of the stellar rotation axis. Until now such an inclination effect on S-index has remained largely unexplored. To fill this gap, we develop a physics-based model to calculate S-index, focusing on the Sun. Using the distributions of solar magnetic features derived from observations together with Ca II H & K spectra synthesized in non-local thermodynamic equilibrium, we validate our model by successfully reconstructing the observed variations of solar S-index over four activity cycles. Further, using the distribution of magnetic features over the visible solar disk obtained from surface flux transport simulations, we obtain S-index time series dating back to 1700 and investigate the effect of inclination on S-index variability, both on the magnetic activity cycle and the rotational timescales. We find that when going from an equatorial to a pole-on view, the amplitude of S-index variations decreases weakly on the activity cycle timescale and strongly on the rotational timescale (by about 22% and 81%, respectively, for a cycle of intermediate strength). The absolute value of S-index depends only weakly on the inclination. We provide analytical expressions that model such dependencies., Comment: 23 pages, 13 figures in the main body and 2 in the appendix, accepted for publication in ApJ

Observations of electron-hole asymmetry in transport through graphene devices at high magnetic field challenge prevalent models of the graphene quantum Hall effect. Here, we study this asymmetry both in conventional magnetotransport and in scanning gate microscopy maps measured in an encapsulated graphene constriction. We reveal that the presence of upstream modes and local doping in the vicinity of electrical contacts leads to a totally different picture of topological breakdown for electrons and holes, explaining the observed asymmetry., Comment: 5 pages, 5 figures

Besides right choice of entrance channel, selection of optimal beam energies for synthesis of superheavy elements plays a crucial role. A thorough investigation with the advanced statistical and dinuclear system models on all the experiments performed for the synthesis of the successful superheavy elements Z=104-118 and failed superheavy elements Z=119-120 leads us to infer that improper choice of the beam energies may be responsible for too low production cross sections to measure and thus the cause for the debacle. We have predicted the optimal beam energies to obtain the maximum production cross sections for all the reactions used for the superheavy elements Z=104-120. Hope exploitation of these predictions may be on the cards soon to extend the periodic table for the eighth period, Comment: 5 figures

Coulomb fission mechanism may take place if the maximum Coulomb-excitation energy transfer in a reaction exceeds the fission barrier of either the projectile or target. This condition is satisfied by all the reactions used for the earlier blocking measurements except one reaction 208 Pb + Natural Ge crystal, where the measured timescale was below the measuring limit of the blocking measurements < 1 as. Hence, inclusion of the Coulomb fission in the data analysis of the blocking experiments leads us to interpret that the measured time longer than a few attoseconds (about 2-2.5 as) is nothing but belonging to the Coulomb fission timescale and shorter than 1 as are due to the quasifission. Consequently, this finding resolves the critical discrepancies between the fission timescale measurements using the nuclear and blocking techniques. This, in turn, validates the fact that the quasifission timescale is indeed of the order of zeptoseconds in accordance with the nuclear experiments and theories. It thus provides a radical input in understanding the reaction mechanism for heavy element formation via fusion evaporation processes, Comment: 2 figures

Development of language proficiency models for non-native learners has been an active area of interest in NLP research for the past few years. Although language proficiency is multidimensional in nature, existing research typically considers a single "overall proficiency" while building models. Further, existing approaches also considers only one language at a time. This paper describes our experiments and observations about the role of pre-trained and fine-tuned multilingual embeddings in performing multi-dimensional, multilingual language proficiency classification. We report experiments with three languages -- German, Italian, and Czech -- and model seven dimensions of proficiency ranging from vocabulary control to sociolinguistic appropriateness. Our results indicate that while fine-tuned embeddings are useful for multilingual proficiency modeling, none of the features achieve consistently best performance for all dimensions of language proficiency. All code, data and related supplementary material can be found at: https://github.com/nishkalavallabhi/MultidimCEFRScoring., Comment: 10 pages