As the annual air passenger traffic in India is increasing steeply, an environmental impact assessment on important cities connected by air is becoming increasingly indispensable. This study proposes an innovative screening method that uses a modified Environmental Vulnerability Index. This modified EVI calculator includes aviation-related parameters and can be used to assess the environmental vulnerabilities of political states and cities, in addition to countries as is being already done. This study also suggests the need to include aspects of human comfort (...) in the screening process through the use of state-of-the-art computational fluid dynamical software and large eddy simulations which can be used to estimate forces experienced by aircraft of different sizes during in-flight turbulence for various weather conditions. A comparative analysis is presented on how changing the size of the aircraft operating in a particular route between the cities of Chennai and Bengaluru has better implications on both passenger comfort and the environment. It is observed that if commercial airlines incorporated fewer medium-sized aircraft, there would be a significant reduction in the environmental vulnerability of the two connected cities. (shrink)

Connected vehicle fleets have formed significant component of industrial internet of things scenarios as part of Industry 4.0 worldwide. The number of vehicles in these fleets has grown at a steady pace. The vehicles monitoring with machine learning algorithms has significantly improved maintenance activities. Predictive maintenance potential has increased where machines are controlled through networked smart devices. Here, benefits are accrued considering uptimes optimization. This has resulted in reduction of associated time and labor costs. It has also provided significant increase (...) in cost benefit ratios. Considering vehicle fault trends in this research predictive maintenance problem is addressed through hybrid deep learning-based ensemble method (HDLEM). The ensemble framework which acts as predictive analytics engine comprises of three deep learning algorithms viz modified cox proportional hazard deep learning (MCoxPHDL), modified deep learning embedded semi supervised learning (MDLeSSL) and merged LSTM (MLSTM) networks. Both sensor as well as historical maintenance data are collected and prepared using benchmarking methods for HDLEM training and testing. Here, times between failures (TBF) modeling and prediction on multi-source data are successfully achieved. The results obtained are compared with stated deep learning models. This ensemble framework offers great potential towards achieving more profitable, efficient and sustainable vehicle fleet management solutions. This helps better telematics data implementation which ensures preventative management towards desired solution. The ensemble method's superiority is highlighted through several experimental results. (shrink)

Increasing evidence indicates that extracellular vesicles (EVs) secreted from tumor cells play a key role in the overall progression of the disease state. EVs such as exosomes are secreted by a wide variety of cells and transport a varied population of proteins, lipids, DNA, and RNA species within the body. Gliomas constitute a significant proportion of all primary brain tumors and majority of brain malignancies. Glioblastoma multiforme (GBM) represents grade IV glioma and is associated with very poor prognosis despite the (...) cumulative advances in diagnostic procedures and treatment strategies. Here, the authors describe the progress in understanding the role of EVs, especially exosomes, in overall glioma progression, and how new research is unraveling the utilities of exosomes in glioma diagnostics and development of next‐generation therapeutic systems. Finally, based on an understanding of the latest scientific literature, a model for the possible working of therapeutic exosomes in glioma treatment is proposed. (shrink)

This paper presents four theorems that connect continuity postulates in mathematical economics to solvability axioms in mathematical psychology, and ranks them under alternative supplementary assumptions. Theorem 1 connects notions of continuity (full, separate, Wold, weak Wold, Archimedean, mixture) with those of solvability (restricted, unrestricted) under the completeness and transitivity of a binary relation. Theorem 2 uses the primitive notion of a separately continuous function to answer the question when an analogous property on a relation is fully continuous. Theorem 3 provides (...) a portmanteau theorem on the equivalence between restricted solvability and various notions of continuity under weak monotonicity. Finally, Theorem 4 presents a variant of Theorem 3 that follows Theorem 1 in dispensing with the dimensionality requirement and in providing partial equivalences between solvability and continuity notions. These theorems are motivated for their potential use in representation theorems. (shrink)

The book deals with philosophical issues concerning the understanding of the literary text and its distinctive nature, meaning, and relevance to life. It also provides an occasion to revisit many of the seminal ideas towards these ends by contextualizing them in the current ongoing philosophical discourse on art, in general, and literary art, in particular. Some of the questions addressed in this book are: What is a literary text? What do we understand by the concept of intention in the context (...) of literary arts? Are the feelings experienced in a literary text real? What then is the sense of “truth” in literature which is fictional in character? What relevance do moral concerns and perceptions have in appreciation of the literary text? These are some of the seminal questions that are dealt with by critically responding to views of contemporary thinkers. In short, the book makes an attempt to provide a critical overview of contemporary debates and discussions of literary aesthetics mainly from a Western analytical perspective. The author argues that understanding a literary text is not a purely cognitive exercise; on the contrary, we experience aesthetic meaning or truth in terms of valuable insights that play a role in our understanding of life and emotions. This book is useful for scholars, researchers and students of philosophy and literature interested in aesthetics. (shrink)

Minichromosome maintenance (Mcm) proteins are well‐known for their functions in DNA replication. However, their roles in chromosome segregation are yet to be reviewed in detail. Following the discovery in 1984, a group of Mcm proteins, known as the ARS‐nonspecific group consisting of Mcm13, Mcm16‐19, and Mcm21‐22, were characterized as bonafide kinetochore proteins and were shown to play significant roles in the kinetochore assembly and high‐fidelity chromosome segregation. This review focuses on the structure, function, and evolution of this group of Mcm (...) proteins. Our in silico analysis of the physical interactors of these proteins reveals that they share non‐overlapping functions despite being copurified in biochemically stable complexes. We have discussed the contrasting results reported in the literature and experimental strategies to address them. Taken together, this review focuses on the structure‐function of the ARS‐nonspecific Mcm proteins and their evolutionary flexibility to maintain genome stability in various organisms. (shrink)

A Pali Grammar. William Geiger. Translated into English by Batakrishna Ghosh, revised and edited by K. R. Norman. Pali Text Society, Oxford 1994. xxix, 220 pp. Hardback £12.95, paperback £6.75.

Product Dimensions: 8.6 x 5.6 x 1.1 inches Description: Very little is known about the author of this book apart from the facts that he is a retired Government of India officer, now in his late nineties, apparently hoary, but healthy. When requested for more bio-data, he wrote back…The Real author of the Original Yoga is the Lord Siva. In the mundane world, Patanjali is the prime propagator of yoga. Any other claim to authorship, therefore, cannot but be spurious. …It (...) is Truth that matters, not the utterer of the Truth. No Truth ever becomes a bit truer even when repeated by the most distinguished person. …Hence all genuine aspirants of yoga should be content to remain unknown and unnoticed by others. His other published work is Hindu Concept of Life and Death. (shrink)

Since the conceptualization of unethical pro-organizational behavior ten years ago, scholarly interest in exploring this phenomenon has multiplied. Given a burgeoning body of empirical research, a review of unethical pro-organizational behavior literature is warranted. This study, therefore, systematically reviews the extant literature on unethical pro-organizational behavior and presents a comprehensive theory-based review of the past developments in this field. We classify previous studies based on their underlying theoretical perspectives and discuss the antecedents and consequences of unethical pro-organizational behavior in work (...) context. We also explicate the boundary conditions under which the influence of these antecedents gets accentuated or alleviated. Overall, this study synthesizes past knowledge to elucidate why, how, and when unethical pro-organizational behavior unfolds in the workplace. Finally, the gaps in the extant theorization are identified and an agenda for future research is proposed. (shrink)

In the domain of legal information retrieval, an important challenge is to compute similarity between two legal documents. Precedents play an important role in The Common Law system, where lawyers need to frequently refer to relevant prior cases. Measuring document similarity is one of the most crucial aspects of any document retrieval system which decides the speed, scalability and accuracy of the system. Text-based and network-based methods for computing similarity among case reports have already been proposed in prior works but (...) not without a few pitfalls. Since legal citation networks are generally highly disconnected, network based metrics are not suited for them. Till date, only a few text-based and predominant embedding based methods have been employed, for instance, TF-IDF based approaches, Word2Vec and Doc2Vec based approaches. We investigate the performance of 56 different methodologies for computing textual similarity across court case statements when applied on a dataset of Indian Supreme Court Cases. Among the 56 different methods, thirty are adaptations of existing methods and twenty-six are our proposed methods. The methods studied include models such as BERT and Law2Vec. It is observed that the more traditional methods that rely on a bag-of-words representation performs better than the more advanced context-aware methods for computing document-level similarity. Finally we nominate, via empirical validation, five of our best performing methods as appropriate for measuring similarity between case reports. Among these five, two are adaptations of existing methods and the other three are our proposed methods. (shrink)

We discuss a simple logic to describe one of our favourite games from childhood, hide and seek, and show how a simple addition of an equality constant to describe the winning condition of the seeker makes our logic undecidable. There are certain decidable fragments of first-order logic which behave in a similar fashion and we add a new modal variant to that class of logics. We also discuss the relative expressive power of the proposed logic in comparison to the standard (...) modal counterparts. (shrink)

When agents know a protocol, this leads them to have expectations about future observations. Agents can update their knowledge by matching their actual observations with the expected ones. They eliminate states where they do not match. In this paper, we study how agents perceive protocols that are not commonly known, and propose a semantics-driven logical framework to reason about knowledge in such scenarios. In particular, we introduce the notion of epistemic expectation models and a propositional dynamic logic-style epistemic logic for (...) reasoning about knowledge via matching agentsÊ expectations to their observations. It is shown how epistemic expectation models can be obtained from epistemic protocols. Furthermore, a characterization is presented of the effective equivalence of epistemic protocols. We introduce a new logic that incorporates updates of protocols and that can model reasoning about knowledge and observations. Finally, the framework is extended to incorporate fact-changing actions, and a worked-out example is given. © 2013 Elsevier B.V. (shrink)

We make a proposal for formalizing simultaneous games at the abstraction level of player’s powers, combining ideas from dynamic logic of sequential games and concurrent dynamic logic. We prove completeness for a new system of ‘concurrent game logic’ CDGL with respect to finite non-determined games. We also show how this system raises new mathematical issues, and throws light on branching quantifiers and independence-friendly evaluation games for first-order logic.

In a Common Law system, legal practitioners need frequent access to prior case documents that discuss relevant legal issues. Case documents are generally very lengthy, containing complex sentence structures, and reading them fully is a strenuous task even for legal practitioners. Having a concise overview of these documents can relieve legal practitioners from the task of reading the complete case statements. Legal catchphrases are (multi-word) phrases that provide a concise overview of the contents of a case document, and automated generation (...) of catchphrases is a challenging problem in legal analytics. In this paper, we propose a novel supervised neural sequence tagging model for the extraction of catchphrases from legal case documents. Specifically, we show that incorporating document-specific information along with a sequence tagging model can enhance the performance of catchphrase extraction. We perform experiments over a set of Indian Supreme Court case documents, for which the gold-standard catchphrases (annotated by legal practitioners) are obtained from a popular legal information system. The performance of our proposed method is compared with that of several existing supervised and unsupervised methods, and our proposed method is empirically shown to be superior to all baselines. (shrink)

The task of rhetorical role labeling is to assign labels (such as Fact, Argument, Final Judgement, etc.) to sentences of a court case document. Rhetorical role labeling is an important problem in the field of Legal Analytics, since it can aid in various downstream tasks as well as enhances the readability of lengthy case documents. The task is challenging as case documents are highly various in structure and the rhetorical labels are often subjective. Previous works for automatic rhetorical role identification (...) (i) mainly used Conditional Random Fields over manually handcrafted features, and (ii) focused on certain law domains only (e.g., Immigration cases, Rent law), and a particular jurisdiction/country (e.g., US, Canada, India). In this work, we improve upon the prior works on rhetorical role identification by proposing novel Deep Learning models for automatically identifying rhetorical roles, which substantially outperform the prior methods. Additionally, we show the effectiveness of the proposed models over documents from five different law domains, and from two different jurisdictions—the Supreme Court of India and the Supreme Court of the UK. Through extensive experiments over different variations of the Deep Learning models, including Transformer models based on BERT and LegalBERT, we show the robustness of the methods for the task. We also perform an extensive inter-annotator study and analyse the agreement of the predictions of the proposed model with the annotations by domain experts. We find that some rhetorical labels are inherently hard/subjective and both law experts and neural models frequently get confused in predicting them correctly. (shrink)

The Transforming growth factor beta (TGF‐β) family of secreted proteins regulates a variety of key events in normal development and physiology. In mammals, this family, represented by 33 ligands, including TGF‐β, activins, nodal, bone morphogenetic proteins (BMPs), and growth and differentiation factors (GDFs), regulate biological processes as diverse as cell proliferation, differentiation, apoptosis, metabolism, homeostasis, immune response, wound repair, and endocrine functions. In Drosophila, only 7 members of this family are present, with 4 TGF‐β/BMP and 3 TGF‐β/activin ligands. Studies in (...) the fly have illustrated the role of TGF‐β/BMP ligands during embryogenesis and organ patterning, while the TGF‐β/activin ligands have been implicated in the control of wing growth and neuronal functions. In this review, we focus on the emerging roles of Drosophila TGF‐β/activins in inter‐organ communication via long‐distance regulation, especially in systemic lipid and carbohydrate homeostasis, and discuss findings relevant to metabolic diseases in humans. -/- . (shrink)

Summarization of legal case judgement documents is a practical and challenging problem, for which many summarization algorithms of different varieties have been tried. In this work, rather than developing yet another summarization algorithm, we investigate if intelligently ensembling (combining) the outputs of multiple (base) summarization algorithms can lead to better summaries of legal case judgements than any of the base algorithms. Using two datasets of case judgement documents from the Indian Supreme Court, one with extractive gold standard summaries and the (...) other with abstractive gold standard summaries, we apply various ensembling techniques on summaries generated by a wide variety of summarization algorithms. The ensembling methods applied range from simple voting-based methods to ranking-based and graph-based ensembling methods. We show that many of our ensembling methods yield summaries that are better than the summaries produced by any of the individual base algorithms, in terms of ROUGE and METEOR scores. (shrink)

Student support services are the cardinal features of the Open and Distance Learning System. In India, the Indira Gandhi National Open University, 13 state open universities and over 200 Distance Education Institutes attached to conventional universities and private/autonomous institutes offering programmes through the distance mode have all created adequate provisions for learner support services and the systems, rules, regulations and norms have been put in place. However, it is significant that a learner in the ODL system remains away from the (...) teacher and the peer group. Thus, the learner feels isolated and needs the empathy of all the functionaries concerned. It has been our experience at IGNOU that more often than not the functionaries fail to realize the value of a learner and the learner fails to understand the value attributed to him by the ODL system. Without such realization the rules and regulations lose their significance. Hence, inculcation of values is of paramount importance in the functioning of the ODL system. In this article we have discussed about ‘inculcation of values’ among the ‘learners’ as well as the ‘functionaries’ for developing ‘best practices’ in learner support services in the ODL system. The inputs are based primarily on direct experiences of the authors. (shrink)