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821 items in total found

Journal Articles | 2018

Transition Experiences in MD–PhD Programs

Devasmita Chakraverty, Donna B. Jeffe, and Robert H. Tai

MD–PhD training takes, on average, 8 years to complete and involves two transitions, an MD-preclinical to PhD-research phase and a PhD-research to MD-clinical phase. There is a paucity of research about MD–PhD students’ experiences during each transition. This study examined transition experiences reported by 48 MD–PhD students who had experienced at least one of these transitions during their training. We purposefully sampled medical schools across the United States to recruit participants. Semistructured interviews were audio-recorded and transcribed for analysis; items focused on academic and social experiences within and outside their programs. Using a phenomenological approach and analytic induction, we examined students’ transition experiences during their MD–PhD programs. Five broad themes emerged centering on multiple needs: mentoring, facilitating integration with students in each phase, integrating the curriculum to foster mastery of skills needed for each phase, awareness of cultural differences between MD and PhD training, and support. None of the respondents attributed their transition experiences to gender or race/ethnicity. Students emphasized the need for mentoring by MD–PhD faculty and better institutional and program supports to mitigate feelings of isolation and help students relearn knowledge for clinical clerkships and ease re-entry into the hospital culture, which differs substantially from the research culture.

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Journal Articles | 2018

Land and livelihoods in rural India: Does farm size matter?

Sukhpal Singh

Indian Journal of Agricultural Marketing

This paper examines the question of role of land in rural livelihoods and that of small farms in the Indian smallholder and large landlessness context by focusing on the issue of size of the farm. It reviews evidence on the changing profile of farms globally and in India from the perspective of small and landless farmers. The paper argues that the size of the farm is not an issue for modern and sustainable agriculture and makes inferences about managing land in a sustainable way, including institutional approaches like group approaches and contract farming, from a smallholder and farm worker perspective.

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Journal Articles | 2018

Food value chain investments and the small farmer linkage: Indian experience, potential, and policy

Sukhpal Singh

World Food Policy

The agri-food value chains in the developing world are evolving fast due to many changes in policy and practice. In India, modern domestic food supermarkets have been present for more than 15 years now. Furthermore, in late 2012, foreign direct investment in multi-brand retail trade, including food, was permitted up to 51% of equity with other conditions of investment and operations. This paper tries to understand the role of investment (both domestic and foreign) in food/fibre value chains in improving the farmer/producer linkage. It uses empirical evidence from the experience of Indian domestic food retail supermarkets, and (mostly) foreign investment-based wholesale supermarkets in India, to examine the role such investments can play. It specifically examines the role and implications of investments in supermarkets for farmer income improvement, from a value chain perspective. It also explores various mechanisms which could be used to leverage the presence of such investments in food supermarkets and analyses the role of policy and regulation to promote/protect the small producer interests in food markets.

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Journal Articles | 2018

Mining top-k high utility itemsets with effective threshold raising strategies

Srikumar Krishnamoorthy

Expert Systems With Applications

Top-K High Utility Itemset (HUI) mining problem offers greater flexibility to a decision maker in specifying her/his notion of item utility and the desired number of patterns. It obviates the need for a decision maker to determine an appropriate minimum utility threshold value using a trial-and-error process. The top-k HUI mining problem, however, is more challenging and requires use of effective threshold raising strategies. Several threshold raising strategies have been proposed in the literature to improve the overall efficiency of mining top-k HUIs. This paper advances the state-of-the-art and presents a new Top-K HUI method (THUI). A novel Leaf Itemset Utility (LIU) structure and a threshold raising strategy is proposed to significantly improve the efficiency of mining top-k HUIs. A new utility lower bound estimation method is also introduced to quickly raise the minimum utility threshold value. The proposed THUI method is experimentally evaluated on several benchmark datasets and compared against two state-of-the-art methods. Our experimental results reveal that the proposed THUI method offers one to three orders of magnitude runtime performance improvement over other related methods in the literature, especially on large, dense and long average transaction length datasets. In addition, the memory requirements of the proposed method are found to be lower.

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Journal Articles | 2018

Efficiently mining high utility itemsets with negative unit profits

Srikumar Krishnamoorthy

Knowledge-Based Systems

A High Utility Itemset (HUI) mining is an important problem in the data mining literature that considers utilities of items (such as profits and margins) to discover interesting patterns from transactional databases. Several data structures, pruning strategies and algorithms have been proposed in the literature to efficiently mine high utility itemsets. Most of these works, however, do not consider itemsets with negative unit profits that provide greater flexibility to a decision maker to determine profitable itemsets. This paper aims to advance the state-of-the-art and presents a generalized high utility mining (GHUM) method that considers both positive and negative unit profits. The proposed method uses a simplified utility-list data structure for storing itemset information during the mining process. The paper also introduces a novel utility based anti-monotonic property to improve the performance of HUI mining. Furthermore, GHUM adapts key pruning strategies from the basic HUI mining literature and presents new pruning strategies to significantly improve the performance of mining. The proposed method is evaluated on a set of benchmark sparse and dense datasets and compared against a state-of-the-art method. Rigorous experimental evaluation is performed and implications of the key findings are also presented. In general, GHUM was found to deliver more than an order of magnitude improvement at a fraction of the memory over the state-of-the-art FHN method.

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Journal Articles | 2018

Efficient mining of high utility itemsets with multiple minimum utility thresholds

Srikumar Krishnamoorthy

Engineering Applications of Artificial Intelligence

Mining high utility itemsets is considered to be one of the important and challenging problems in the data mining literature. The problem offers greater flexibility to a decision maker in using item utilities such as profits and margins to mine interesting and actionable patterns from databases. Most of the current works in the literature, however, apply a single minimum utility threshold value and fail to consider disparities in item characteristics. This paper proposes an efficient method (MHUI) to mine high utility itemsets with multiple minimum utility threshold values. The presented method generates high utility itemsets in a single phase without an expensive intermediate candidate generation process. It introduces the concept of suffix minimum utility and presents generalized pruning strategies for efficiently mining high utility itemsets. The performance of the algorithm is evaluated against the state-of-the-art methods (HUI-MMU-TE and HIMU-EUCP) on eight benchmark datasets. The experimental results show that the proposed method delivers two to three orders of magnitude execution time improvement over the HUI-MMU-TE method. In addition, MHUI delivers one to two orders of magnitude execution time improvement over the HIMU-EUCP method, especially on moderately long and dense benchmark datasets. The memory requirements of the proposed algorithm was also found to be significantly lower.

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Journal Articles | 2018

Informed trading around earnings announcements Spot, futures, or options?

Sobhesh Kumar Agarwalla, Jayanth R. Varma, and Ajay Pandey

Journal of Futures Markets

Recent literature reports higher single stock options (SSO) volume before earnings announcements (EA). There are no studies that explore single stock futures (SSF) in this context because of illiquid SSF markets in developed countries. Similar to SSO, SSF provide embedded leverage and facilitate short selling although at a lower cost, but do not provide downside-risk protection. India’s liquid SSO and SSF provide a unique setting to study the preference of informed traders. We observe an increase in both SSO and SSF volume before EA. Further, SSF dominate SSO possibly due to SSO becoming expensive before EA and higher information leakage in India.

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Journal Articles | 2018

Qasab: Kutch Craftswomen's Producer Co. Ltd.

Shweta Mittal, Vishal Gupta, and Manoj Motiani

Asian Case Research Journal

This case was prepared by Assistant Professor Shweta Mittal of Institute of Management & Research, Ghaziabad, India, Associate Professor Vishal Gupta of Indian Institute of Management Ahmedabad, India and Assistant Professor Manoj Motiani of Indian Institute of Management Indore, India, as a basis for classroom discussion rather than to illustrate either effective or ineffective handling of an administrative or business situation.

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Journal Articles | 2018

How can mindfulness enhance moral reasoning? An examination using business school students

Ashish Pandey, Rajesh Chandwani, and Ajinkya Navare

Business Ethics: A European Review

Given the comprehensive influence of mindfulness on human thought and behavior, and the importance of moral reasoning in business decisions, we examine the role of mindfulness as an antecedent to moral reasoning through two studies. In Study 1, we propose and test a theoretically derived model that links mindfulness and moral reasoning, mediated by compassion and egocentric bias using a survey design. In Study 2, we examine whether mindfulness training enhances moral reasoning using an experimental design with graduate students of business management. The findings of Study 1 substantiate the positive association of mindfulness with moral reasoning. We found that this relationship is fully mediated by compassion and egocentric bias. The results of Study 2 suggest that mindfulness meditation training has a positive impact on individuals' states of mindfulness, compassion, and moral reasoning, and decreases egocentric bias. We relate the findings of the study with contemporary neurological research and discuss the theoretical, pedagogical, and managerial implications.

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Journal Articles | 2018

Racial/ethnic parity in disciplinary consequences using student threat assessment

Dewey Cornell, Jennifer Maeng, Francis Huang, Kathan Shukla, and Timothy Konold

School Psychology Review

School psychologists are frequently called upon to assess students who have made verbal or behavioral threats of violence against others, a practice commonly known as threat assessment. One critical issue is whether the outcomes of a threat assessment generate the kind of racial disparities widely observed in school disciplinary practices. In 2013, Virginia became the first state to mandate threat assessment teams in all public schools. This study examined the disciplinary consequences for 1,836 students who received a threat assessment in 779 Virginia elementary, middle, and high schools during the 2014–2015 school year. Multilevel logistic regression models found no disparities among Black, Hispanic, and White students in out-of-school suspensions, school transfers, or legal actions. The most consistent predictors of disciplinary consequences were the student's possession of a weapon and the team classification of the threat as serious. We discuss possible explanations for the absence of racial/ethnic disparities in threat assessment outcomes and cautiously suggest that the threat assessment process may reflect a generalizable pathway for achieving parity in school discipline.

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IIMA