Abstract

Walking in a Virtual Environment is a bounded task. It is challenging for a subject to navigate a large virtual environment designed in a limited physical space. External hardware support may be required to achieve such an act in a concise physical area without compromising navigation and virtual scene rendering quality. This paper proposes an algorithmic approach to let a subject navigate a limitless virtual environment within a limited physical space with no additional external hardware support apart from the the regular Head-Mounted-Device (HMD) itself. As part of our work, we developed a Virtual Art Gallery as a use-case to validate our algorithm. We conducted a simple user-study to gather feedback from the participants to evaluate the ease of locomotion of the application. The results showed that our algorithm could generate limitless paths of our use-case under predefined conditions and can be extended to other use-cases

Abstract

Earthquakes cause disasters only when the built environment fails to resist the earthquake shaking experienced in the affected area, thereby causing losses of life and property. Ensuring structural safety of the built environment alone will result in earthquake safety of India. India needs suffcient number of competent structural, geotechnical engineers and architects to design and construct its new earthquake resistant buildings and facilities and to retroft its existing ones. This paper urges quantum changes in the educational, social, technical, fnancial, techno-legal, industrial and administrative governance systems of the country, and re-iterates the stand of the nation of zero tolerance to avoidable deaths due to earthquakes.

Abstract

The Koyna-Warna region of Maharashtra, India, is one of the most signifcant worldwide examples for reservoir-induced seismicity. The area is highly vulnerable to earthquakes, and it has experienced over 1 lakh number of shocks since 1963. The largest known earthquake of magnitude 6.5 (Richter scale) occurred on 10th December 1967. Many low and moderate earthquake events have occurred over the past 50 years. A structured survey using rapid visual screening was carried out for existing RC buildings. The seismic risk index depends on three parameters, viz. hazard, exposure, and vulnerability. Many existing RC buildings in the Koyna-Warna region are designed to resist the gravity loads only without any seismic resistant provisions. Hence, there is a need to study the risk index of these RC buildings to assess future serious risks. In this study, the rapid visual survey of 120 existing RC buildings has been done through a modifed EDRI method (Earthquake Disaster Risk Index) to evaluate the seismic risk index of the Koyna-Warna region (Zone-IV as per IS: 1893–2016). The results depict that the risk index of RC buildings in the Koyna-Warna region is in severe damage condition and hence there is a need to take an initiatives for earthquake preparedness plan, with emphasis on retroftting measures, to reduce the loss of human life and damage to physical infrastructure in future seismic events.

Abstract

Determination of seismic safety of existing buildings is a time consuming and challenging process. Instead, rapid survey methods were developed which identify deficient structures from a large building stock in a city or town. This paper presents a comparison and critical review of existing rapid visual survey methods used for seismic assessment of existing reinforced concrete buildings. The study focuses on rapid visual survey methods developed for the safety assessment of reinforced concrete buildings in the Indian subcontinent and a widely used method in the United States. Comparison is carried out in various ways. Initially, a direct comparison is made based on vulnerable parameters and damage grades proposed by each method. Later, a scoring system is developed to highlight the differences and rank the selected methods. This system considers the general description, physical parameters, and damage …

Abstract

Machine learning (ML) has been increasingly adopted due to its ability to model complex and non-linearities between river water temperature (RWT) and its predictors (e.g., Air Temperature, AT). Most of these ML approaches have been applied using average AT without any detailed sensitivity analysis of other forms of AT (e.g., maximum and minimum). The present study demonstrates how new ML approaches, such as ridge regression (RR), K-nearest neighbors (KNN) regressor, random forest (RF) regressor, and support vector regression (SVR), can be coupled with Sobol’ global sensitivity analysis (GSA) to predict accurate RWT estimates with the most appropriate form of AT. Furthermore, the proposed ML approaches have been combined with the Ensemble Kalman Filter (EnKF), a data assimilation (DA) technique to improve the predicted values based on the measured data. The proposed modelling …

Abstract

Understanding the relevance of potential (PET) and actual evapotranspiration (AET) in the drought characterization over energy and water-limited regions is unexplored. The present study tries to restructure the Standardized Precipitation Evapotranspiration Index (SPEI) with AET to represent the anomalies of actual water availability in addition to precipitation over India. The AET is estimated using the Budyko hypothesis at annual scale which was validated with Global Land Evaporation Amsterdam Model (GLEAM) satellite-based AET data. AET-based drought index was in more agreement with remote sensing-based drought severity index (DSI) for major drought events compared to PET-based drought index for water-limited zone compared to energy-limited. For water-limited zones, the PET-based drought index has overestimated the drought intensities, while for energy-limited zones such effect is not …

Abstract

Search strategies for the third-generation leptoquarks (LQs) are distinct from other LQ searches, especially when they decay to a top quark and a τ lepton. We investigate the cases of all TeV-scale scalar and vector LQs that decay to either a top-tau pair (charge-1/3 and 5/3 LQs) or a top-neutrino pair (charge2/3 LQs). One can then use the boosted top (which can be tagged efficiently using jet-substructure techniques) and high-pT τ leptons to search for these LQs. We consider two search channels with either one or two taus along with at least one hadronically decaying boosted top quark. We estimate the high luminosity LHC (HL-LHC) search prospects of these LQs by considering both symmetric and asymmetric pair and single production processes. Our selection criteria are optimised to retain events from both pair and single production processes. The combined signal has better prospects than the traditional searches. We include new three-body single production processes to enhance the single production contributions to the combined signal. We identify the interference effect that appears in the dominant single production channel of charge-1/3 scalar LQ (S 1/3 ). This interference is constructive if S 1/3 is weak-triplet and destructive, for a singlet one. As a result, their LHC prospects differ appreciably

Abstract

The U1 leptoquark (LQ) is known to be a suitable candidate for explaining the semileptonic B-decay anomalies. We derive precise limits on its parameter space relevant for the anomalies from the current LHC high-pT dilepton data. We consider an exhaustive list of possible B-anomalies-motivated simple scenarios with one or two new couplings that can also be used as templates for obtaining bounds on more complicated scenarios. To obtain precise limits, we systematically consider all possible U1 production processes that can contribute to the dilepton searches including the resonant pair and single productions, nonresonant t-channel U1 exchange, as well as its large interference with the Standard Model background. We demonstrate how the inclusion of generally ignored resonant productions and signal-background interference contributions in the dilepton signal can lead to stringent exclusion limits. We point out new search channels of U1 that can act as unique tests of the flavour-motivated models. The template scenarios can also be used for future U1 searches at the LHC. We compare the LHC limits with other relevant flavor bounds and find that a TeV-scale U1 can accommodate both RD(∗) and RK(∗) anomalies while satisfying all the bounds.

Abstract

The advent of digital pathology presents opportunities for computer vision for fast, accurate, and objective solutions for histopathological images and aid in knowledge discovery. This work uses deep learning to predict genomic biomarkers - TP53 mutation, PIK3CA mutation, ER status, PR status, HER2 status, and intrinsic subtypes, from breast cancer histopathology images. Furthermore, we attempt to understand the underlying morphology as to how these genomic biomarkers manifest in images. Since gene sequencing is expensive, not always available, or even feasible, predicting these biomarkers from images would help in diagnosis, prognosis, and effective treatment planning. We outperform the existing works with a minimum improvement of 0.02 and a maximum of 0.13 AUROC scores across all tasks. We also gain insights that can serve as hypotheses for further experimentations, including the presence of lymphocytes and karyorrhexis. Moreover, our fully automated workflow can be extended to other tasks across other cancer subtypes.

Abstract

Accuracy on Minnesota Solvation Database (MNSOL) There are classical and quantum-mechanical simulation studies that use the MNSOL as the reference database. We choose solvation model based on density(SMD) for comparison with our CIGIN Model. We also compared CIGIN Model with semi-empirical methods, pure COSMO, and COSMO-RS.