Investigation of electronic and magnetic responses in topological semimetals

Numerous advancements and benefits of the digital age have been made possible by the advent of quantum computers, which is the result of a countless effort of researchers. The rate at which tasks are completed has significantly picked up, while at the same time, the size of these devices is continuing shrinking. When it became clear that even the silicon industry would soon reach its point of saturation, those in the research community became aware of the need to look for an alternative solution. And if we are talking about boosting the speed of computers and reducing the amount of storage space they occupy, there is yet another significant obstacle to overcome in terms of the conservation of energy. Researchers should be working on a solution right now because we are in the midst of a significant energy crisis, and this would be the best time for them to do so. It would be in their best interest to look into ways to reduce their energy consumption, given that we are already aware of how vital it is to pursue such avenues of inquiry. We are certain that the investigation of topological materials can make a contribution to the solution of a good deal of these issues, and we are very optimistic about this prospect (Figure 1.1). It is anticipated that perhaps up to 24 % of all materials will have some topological features [2]. As a consequence of this, the range of possible applications can be increased due to the wide variety of materials that are available. Over the course of the last decade, the expansion of the field of research that focuses on condensed matter physics has directly caused a sea change in the field as a direct result of the growth of materials [3]. These topological materials have the potential to bring scientists one step closer to discovering practical applications for unusual phases. Some of these applications include having the potential to revolutionize electronics and catalysis. These topological materials provide researchers with additional hope to find a solution for the energy crisis. Additionally, prior to the development of applications, it is necessary to identify materials that are suitable for these applications and to study the physical phenomena that are associated with these materials. There are a variety of topological materials that are currently being reexamined for use in improved thermoelectric devices, improved catalytic processes, and various spintronic devices. At the same time, researchers are also looking into new materials which can be used for technical applications in these fields. With this motivation of PhD thesis, several topological semimetals were synthesized to investigate their electronic and magnetic response, and the search for new topological materials with intriguing physical properties were also sought

Concurrent Constrained Optimization of Unknown Rewards for Multi-Robot Task Allocation

Task allocation can enable effective coordination of multi-robot teams to accomplish tasks that are intractable for individual robots. However, existing approaches to task allocation often assume that task requirements or reward functions are known and explicitly specified by the user. In this work, we consider the challenge of forming effective coalitions for a given heterogeneous multi-robot team when task reward functions are unknown. To this end, we first formulate a new class of problems, dubbed COncurrent Constrained Online optimization of Allocation (COCOA). The COCOA problem requires online optimization of coalitions such that the unknown rewards of all the tasks are simultaneously maximized using a given multi-robot team with constrained resources. To address the COCOA problem, we introduce an online optimization algorithm, named Concurrent Multi-Task Adaptive Bandits (CMTAB), that leverages and builds upon continuum-armed bandit algorithms. Experiments involving detailed numerical simulations and a simulated emergency response task reveal that CMTAB can effectively trade-off exploration and exploitation to simultaneously and efficiently optimize the unknown task rewards while respecting the team's resource constraints.Comment: 9 pages, 5 figures, to be published in RSS 202

ELECTRODEPOSITION AND CHARACTERIZATION OF VERY THIN FILM II-VI COMPOUNDS FOR NOVEL SUPERLATTICE SOLAR CELLS

Abstract Thin films of lead telluride (PbTe) and zinc telluride (ZnTe) have been electrodeposited on indium tin oxide (ITO)-coated glass substrates. Uniform dense films of ~ 100 nm have been obtained for both materials. The electrochemical deposition procedures for fabricating these films are described. The asdeposited films have been characterized by scanning electron microscopy, energy dispersive spectroscopy, and optical absorption spectrophotometry. Multi layer structures, up to 3 layers, of ZnTe/PbTe films, have been fabricated

Tanimoto Random Features for Scalable Molecular Machine Learning

The Tanimoto coefficient is commonly used to measure the similarity between molecules represented as discrete fingerprints, either as a distance metric or a positive definite kernel. While many kernel methods can be accelerated using random feature approximations, at present there is a lack of such approximations for the Tanimoto kernel. In this paper we propose two kinds of novel random features to allow this kernel to scale to large datasets, and in the process discover a novel extension of the kernel to real-valued vectors. We theoretically characterize these random features, and provide error bounds on the spectral norm of the Gram matrix. Experimentally, we show that these random features are effective at approximating the Tanimoto coefficient of real-world datasets and are useful for molecular property prediction and optimization tasks.Comment: Camera-ready version presented at NeurIPS 2023. Updates include: notation changes, better description of features in section 4, updated experiments, link to cod

Estimation of Concept Explanations Should be Uncertainty Aware

Model explanations can be valuable for interpreting and debugging predictive models. We study a specific kind called Concept Explanations, where the goal is to interpret a model using human-understandable concepts. Although popular for their easy interpretation, concept explanations are known to be noisy. We begin our work by identifying various sources of uncertainty in the estimation pipeline that lead to such noise. We then propose an uncertainty-aware Bayesian estimation method to address these issues, which readily improved the quality of explanations. We demonstrate with theoretical analysis and empirical evaluation that explanations computed by our method are robust to train-time choices while also being label-efficient. Further, our method proved capable of recovering relevant concepts amongst a bank of thousands, in an evaluation with real-datasets and off-the-shelf models, demonstrating its scalability. We believe the improved quality of uncertainty-aware concept explanations make them a strong candidate for more reliable model interpretation. We release our code at https://github.com/vps-anonconfs/uace

Summative Approach for Slum Adolescents

Background: Urban slums in India are neglected communities as far as public health facilities are concerned. There is no health infrastructure since these slums are largely illegal and unauthorized. This community has poor awareness of health schemes and other social security benefits provided by the government. No initiatives have been taken to provide vocational training to empower this economically weaker and neglected section of the society.Objectives: To generate health awareness among the slum adolescents on various issues related to health, especially menstrual hygiene, personal hygiene, household methods of water purification as well as safe disposal of waste and also make them economically independent.Methodology: A summer workshop was conducted for a period of one week by MBBS students in the urban slums of Bhangel, during the summer vacations time of school going children. Two groups of slum adolescents were recognized. One group had younger adolescents and the other had older adolescents who acted as guides for the younger group. Health awareness sessions were conducted for these children everyday on community relevant health topics like personal hygiene, menstrual hygiene, water purification techniques, etc., along with teaching them some vocational skills like first aid box making, mehendi application, lipstick making, making of dust bins, etc. They were also taught marketing and selling skills. Both these groups were asked to identify another group of young adolescents and teach them what they learnt in the workshop, under observation of the medical students.Results: On comparing the pre and post workshop assessment, the results were very encouraging.Conclusion: Marked improvement was observed in the knowledge levels related to health issues and vocational independence could be promoted. However, there is a need to explore the possibility of replicating the same at a larger scale

The Center for Innovations in Business and Management Practice CO-RELATIONAL REVIEW INTERFACE BETWEEN ACADEMIC ACHIEVEMENT AND PROFESSIONAL SUCCESS

Abstract The performance of real life achievers vis-à-vis academic achievers has long been a subject of debate and discussion. It has often been witnessed that real life achievers often do no

Smoking cessation and its significant role in the Indian scenario

Given the increased health dangers of tobacco use, particularly in developing countries, smoking cessation intervention is crucially important. The aim of this study is to determine and assess the effectiveness of a comprehensive smoking cessation intervention program, incorporating behavior modification, counseling, and pharmacologic treatments, in the context of the Indian scenario. The process of initiating smoking or tobacco cessation begins with the evaluation of the distinct stages that smokers undergo as part of their journey toward behavioral change. There are five different levels of preparation for quitting smoking, i.e., i) not prepared (pre-contemplation); ii) unsure (contemplation); iii) prepared (preparation); iv) action; and v) maintenance. Behavior modification and counseling are essential. The "5 A's"-based intervention uses ask, advise, assess, assist, and arrange as part of its strategy. First-line treatments such as nicotine replacement therapy, bupropion, and varenicline, as well as second-line treatments such as clonidine, cytisine, and nortriptyline, are the foundation of pharmacologic care. Every healthcare professional has a duty to help smokers stop using tobacco, and the intervention should be both therapeutic and diagnostic. Combining behavioral and social support yields the best results, along with pharmacotherapy whenever needed

W-GUN: Whale Optimization for Energy and Delay centric Green Underwater Networks

Underwater Sensor Networks (UWSNs) has witnessed significant R&D attention in both academia and industries due to its growing application domain such as border security, freight via sea or river, natural petroleum production, etc. Considering the deep underwater oriented access constraints, energy centric communication for lifetime maximization of tiny sensor nodes in UWSNs is one of the key research themes in this domain. Existing literature on green UWSNs are majorly adapted from the existing techniques in traditional wireless sensor network without giving much attention to the realistic impact of underwater network environments resulting in degraded performance. Towards this end, this paper presents an adapted whale optimization algorithm-based energy and delay centric green UWSNs framework (W-GUN). It focuses on exploiting dynamic underwater network characteristics by effectively utilizing underwater whale centric optimization in relay node selection. Firstly, an underwater relay- node optimization model is mathematically derived focusing on whale and wolf optimization algorithms for incorporating realistic underwater characteristics. Secondly, the optimization model is used to develop an adapted whale and grey wolf optimization algorithm. Thirdly, a complete work-flow of the W-GUN framework is presented with the optimization flowchart. The comparative performance evaluation attests the benefits of the proposed framework as compared to the state-of-the-art techniques considering various metrics related to underwater network environments