In a revealing TEDxKC talk entitled "How My Mind Came Back to Life—And No One Knew", Martin Pistorius, author of Ghost Boy, shares his harrowing experience of living in a vegetative state with a locked-in syndrome for two long years. When his consciousness returned, Pistorius reflects on how he was unable to communicate the news of his recovery. Using his augmented and alternative communication device, Pistorius observes, "Your personality appears to vanish into a heavy fog and all of your emotions (...) and desires are constricted, stifled and muted within you. … It's a very dark place to find yourself because in a sense, you have vanished."Pistorius's speech is a commentary on voice and identity, and... (shrink)

The Nuclear Threat Initiative focuses on preventing catastrophes related to weapons of mass destruction, with a wide range of attacks including nuclear, biologic, radiologic, chemical and cyb...

Volume 20, Issue 4, May 2020, Page 92-94.

Volume 19, Issue 12, December 2019, Page 74-77.

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)

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)

Comatose survivors of cardiac arrest may die following withdrawal of life-sustaining therapy (WLST) due to poor neurologic prognosis. Family members, acting as surrogate decision makers, are frequently asked to decide whether the patient should continue to receive ongoing life-sustaining therapy such as mechanical ventilation in this context of risk of death following removal. Sometimes, physicians and family members disagree about what is in the patient's best interest, and this conflict causes distress for both families and medical personnel. This article examines (...) themes recorded in the medical records of 24 cardiac arrest patients at Columbia University Medical Center (CUMC) whose families chose to pursue continued life support despite physician recommendations for withdrawal. In documented conversations between patients' families and their providers, the most prominent themes included faith in miracles, the inappropriateness of "playing God," the value of more time with the patient, and differences in how providers and family members perceived the patient's status. (shrink)

The economic pastoral letter states that employees have rights to employment, non-discriminatory treatment, adequate wages, health care, old age and disability insurance, healthy working conditions, rest and holidays, reasonable protection from arbitrary dismissal, notice of plant closings, unionization and collective bargaining. In addition, the bishops call for better cooperation between labor and management. This paper discusses how these rights can be protected by good personnel/human resource policies and procedures.

In today's world the need for cultivating non-violence is becoming more pronounced. Gandhi extrapolated an ideal society based on truth and nonviolence. The Bombay Chronicle in its issue of 5th April, 1930, reported "...For the first time a nation is asked by its leader to win freedom by itself accepting all the suffering and sacrifice involved. Mahatma Gandhi's success does not, therefore, merely mean the freedom of India. It will also constitute the most important contribution that any country yet made (...) towards the elimination of force as an arbiter between one nation and another..." For him, two cardinal principles of life, non-violence and truth, were the essence of sociopolitical good. "Satyagraha" was Gandhi's gift to the world. The word was coined by him in South Africa. In the West it was known as passive resistance. Satyagraha signified pure soul-force. Truth or Love is the very substance of the soul. To quote Gandhi in this context: "Non-violence as supreme dharma is the proof of this power of Love. Nonviolence is a dormant state. In the working state, it is Love, ruled by Love, the world goes on.... we are alive solely because of Love....we are all ourselves the proof of this..." In a centrifugal world, Gandhi's views expressed on non-violence and love are guidance to the world today more than at any other time. (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)

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)

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)

Atish R. Ghosh is Chief of the Policy Review Division of the Policy Development and Review Department of the International Monetary Fund.

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)

Introduction: Intimate Partner Violence (IPV) has unfavorable consequences for women as well as for newborn babies, which is very serious and preventable public health problem. It is believed to have an excessive occurrence in lives of women in South Asia. The objective of this study is to describe the prevalence, risk factors and consequences of IPV in Bangladesh. Methods: A scoping review was carried out based on the past 12 years of posted and gray literature about IPV in Bangladesh using (...) Arksey and O’Malley’s framework. Only the literature addressing abuses or violence in households or outside including physical, sexual or mental violence on the married woman in Bangladesh were taken into consideration for the study. Results: The overall prevalence of IPV in Bangladesh, the latest reviews of rates ranging from 15.5-82.7%.Most of the IPV in Bangladesh was based totally on the experience of legally married women. The main risk factors of IPV in Bangladesh were women being younger, from lower socioeconomic reputation, from lower academic attainment and lower education of husband, dowry, child marriage, perceived disobedience of wives, family conflict, children had recently been ill, and incapability of to furnish sexual satisfaction. Maternal depressive symptoms, signs of stress, anxiety and constraint to the better health of young children are the main consequences of IPV in Bangladesh. Besides, IPV causes unwanted pregnancy, pregnancy loss in the form of miscarriage, induced abortion, or stillbirth and termination of pregnancy in Bangladesh. Conclusions: Woman’s empowerment may reduce IPV and understanding attitudes towards IPV in cultural context could be crucial for developing interventions to reduce IPV and its consequences. (shrink)

We have studied the dynamics and symmetries of a particle constrained to move in a torus knot. The Hamiltonian system turns out to be Second Class in Dirac’s formulation and the Dirac brackets yield novel noncommutative structures. The equations of motion are obtained for a path in general where the knot is present in the particle orbit but it is not restricted to a particular torus. We also study the motion when it is restricted to a specific torus. The rotational (...) symmetries are studied as well. We have also considered the behavior of small fluctuations of the particle motion about a fixed torus knot. (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)

This paper presents an attempt to bridge the gap between logical and cognitive treatments of strategic reasoning in games. There have been extensive formal debates about the merits of the principle of backward induction among game theorists and logicians. Experimental economists and psychologists have shown that human subjects, perhaps due to their bounded resources, do not always follow the backward induction strategy, leading to unexpected outcomes. Recently, based on an eye-tracking study, it has turned out that even human subjects who (...) produce the outwardly correct ‘backward induction answer’ use a different internal reasoning strategy to achieve it. The paper presents a formal language to represent different strategies on a finer-grained level than was possible before. The language and its semantics help to precisely distinguish different cognitive reasoning strategies, that can then be tested on the basis of computational cognitive models and experiments with human subjects. The syntactic framework of the formal system provides a generic way of constructing computational cognitive models of the participants of the Marble Drop game. (shrink)

An intellectual biography of Max Weber which uses his most famous work, The Protestant Ethic and the Spirit of Capitalism as its starting point, with wider reference to the social, political, and religious thought of the time.

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)

Ghosh introduces the term 'plastic turn' and gives a new direction for how we can interpret and experience the turn today. By what he calls the material-aesthetic, he opens up a fresh direction in our experience and understanding of plastic through the correspondence that plastic as a material brings with the aesthetic that it inspires and figures"-.

When formal literacy instruction begins, around the age of 5 or 6, children from families low in socioeconomic status tend to be less prepared than children from families of higher SES. The goal of our study is to explore one route through which SES may influence children's early literacy skills: informal conversations about letters. The study builds on previous studies of parent–child conversations that show how U. S. parents and their young children talk about writing and provide preliminary evidence about (...) similarities and differences in parent–child conversations as a function of SES. Focusing on parents and children aged three to five, we conducted five separate analyses of these conversations, asking whether and how family SES influences the previously established patterns. Although we found talk about letters in both upper and lower SES families, there were differences in the nature of these conversations. The proportion of letter talk utterances that were questions was lower in lower SES families and, of all the letter names that lower SES families talked about, more of them were uttered in isolation rather than in sequences. Lower SES families were especially likely to associate letters with the child's name, and they placed more emphasis on sequences in alphabetic order. We found no SES differences in the factors that influenced use of particular letter names, but there were SES differences in two-letter sequences. Focusing on the alphabet and on associations between the child's name and the letters within it may help to interest the child in literacy activities, but they many not be very informative about the relationship between letters and words in general. Understanding the patterns in parent–child conversations about letters is an important first step for exploring their contribution to children's early literacy skills and school readiness. (shrink)