Skilled yet lost? Challenges of international medical graduates in psychiatry: Australian perspective

Abstract of presentation at the 67th Annual National Conference of the Indian Psychiatric Society (ANCIPS 2015), at Hyderabad, India, 8-11 January 2015

EcoSupply: a machine learning framework for analyzing the impact of ecosystem on global supply chain dynamics

A global supply chain spans several regions and countries across the globe. A tremendous spurt in the extent of globalization has necessitated the need for modeling global supply chains in place of the conventional supply chains. In this paper, we propose a framework, EcoSupply, to analyze the supply chain ecosystem in a probabilistic setting unlike the existing methodologies, which presume a deterministic context. EcoSupply keeps track of the previous observations in order to facilitate improved prediction about the influence of uncertainties in the ecosystem, and provides a coherent mathematical exposition to construe the new associations, among the different supply chain stakeholders, in place of the existing links. To the best of our knowledge, EcoSupply is the first machine learning based paradigm to incorporate the dynamics of global supply chains

AbODE: Ab Initio Antibody Design using Conjoined ODEs

Antibodies are Y-shaped proteins that neutralize pathogens and constitute the core of our adaptive immune system. De novo generation of new antibodies that target specific antigens holds the key to accelerating vaccine discovery. However, this co-design of the amino acid sequence and the 3D structure subsumes and accentuates some central challenges from multiple tasks, including protein folding (sequence to structure), inverse folding (structure to sequence), and docking (binding). We strive to surmount these challenges with a new generative model AbODE that extends graph PDEs to accommodate both contextual information and external interactions. Unlike existing approaches, AbODE uses a single round of full-shot decoding and elicits continuous differential attention that encapsulates and evolves with latent interactions within the antibody as well as those involving the antigen. We unravel fundamental connections between AbODE and temporal networks as well as graph-matching networks. The proposed model significantly outperforms existing methods on standard metrics across benchmarks.Comment: Accepted at ICML 202

Analysis of multiple choice questions from a formative assessment of medical students of a medical college in Delhi, India

Background: Assessment is a dominant motivator to direct and drive students learning. Different methods of assessment are used to assess medical knowledge in undergraduate medical education. Multiple choice questions (MCQs) are being used increasingly due to their higher reliability, validity, and ease of scoring. Item analysis enables identifying good MCQs based on difficulty index (DIF I), discrimination index (DI), and distracter efficiency (DE).Methods: Students of second year MBBS appeared in a formative assessment test, that was comprised of 50 “One best response type” MCQs of 50 marks without negative marking. All MCQs were having single stem with four options including, one being correct answer and other three incorrect alternatives (distracter). Three question paper sets were prepared by disorganizing sequence of questions. One of the three paper sets was given to each student to avoid copying from neighboring students. Total 50 MCQs and 150 distracters were analyzed and indices like DIF I, DI, and DE were calculated.Results: Total Score of 87 students ranged from 17 to 48 (out of total 50). Mean for difficulty index (DIF I) (%) was 71.6+19.4. 28% MCQs were average and “recommended” (DIF I 30-70%). Mean for discrimination index (DI) was 0.3+0.17. 16% MCQs were “good” and 50% MCQs were in “excellent” criteria, while rests of the MCQs were “discard/poor” according to DI criteria. Mean for distracter efficiency (DE) (%) was 63.4+33.3. 90% of the items were having DE from 100 to 33%. It was found that MCQs with lower difficulty index (0.15) and higher distractor efficiency

The Study to Analyze the Impact of Green Supply Chain Management in India

Green supply chain management can be explained as a supply chain management system which is beneficial for the environment and which consists of designing of products , selection of raw material,manufacturing steps and delivery and preparation of final product through a stable and sustainable process.Sustainibility is the major key to supply chain ,which starts with the understanding through all the phases of production upto final distribution. This paper majorly focuses on the importance and need of term green and concepts or activities which are related to greener activities in areas like manufacturing and remanufacturing of products having a green impact ,controlling of travel costs and waste products , reverse logistics etc. The purpose is to understand the impact and also to make people aware about the major difficulties, problems and also the advantages and profits which are a part of such a great green concept if it is successfully implemented or installed during the process of supply chain management in various organisations.Keywords : Production, customer , supply chain , green , sustainability , manufacturing , materials