India’s energy demand is predicted to rise by 135% within a span of 20 years. Coping up with surging energy demands requires several reforms in both renewable and non-renewable sectors. Factors such as rising population, reduction in the cost of renewable energy technology and their effect on the nation’s GDP, can make policy making a herculean task and the justification for such policies, quite opaque to the public. Artificial Intelligence technology can help decision makers to quickly draw conclusions from voluminous (...) datasets under different heads. However, AI results need to be post-processed so that they are easily understood by the layperson. This paper focuses on using Sankey diagrams as a post-processing tool for AI systems. Policy formulation often requires an overall assessment of energy sources, production pathways, end used destinations and wastage encountered—these can be easily visualized with a Sankey diagram. For this work, a Sankey protocol was written out in a form where a prompt asks the user to supply information through a spreadsheet interfaced with a customized mobile app—a first anywhere in the subcontinent. India’s mobile sector is vibrant, and the paper presents a enabling the user to have a handle on the dynamics of energy distribution locally. The app gives an instant feel of the apportioned energy across grids, the projected changes for the next decade, the efficiency and feasibility of each sector and lastly a telling visual representation showing the main strengths and weaknesses in the energy sector. (shrink)

BackgroundCommunity engagement in research has gained momentum as an approach to improving research, to helping ensure that community concerns are taken into account, and to informing ethical decision-making when research is conducted in contexts of vulnerability. However, guidelines and scholarship regarding community engagement are arguably unsettled, making it difficult to implement and evaluate.DiscussionWe describe normative guidelines on community engagement that have been offered by national and international bodies in the context of HIV-related research, which set the stage for similar work (...) in other health related research. Next, we review the scholarly literature regarding community engagement, outlining the diverse ethical goals ascribed to it. We then discuss practical guidelines that have been issued regarding community engagement. There is a lack of consensus regarding the ethical goals and approaches for community engagement, and an associated lack of indicators and metrics for evaluating success in achieving stated goals. To address these gaps we outline a framework for developing indicators for evaluating the contribution of community engagement to ethical goals in health research.SummaryThere is a critical need to enhance efforts in evaluating community engagement to ensure that the work on the ground reflects the intentions expressed in the guidelines, and to investigate the contribution of specific community engagement practices for making research responsive to community needs and concerns. Evaluation mechanisms should be built into community engagement practices to guide best practices in community engagement and their replication across diverse health research settings. (shrink)

Broadening access to both computational and educational resources is crit- ical to diffusing machine learning (ML) innovation. However, today, most ML resources and experts are siloed in a few countries and organizations. In this article, we describe our pedagogical approach to increasing access to applied ML through a massive open online course (MOOC) on Tiny Machine Learning (TinyML). We suggest that TinyML, applied ML on resource-constrained embedded devices, is an attractive means to widen access because TinyML leverages low-cost and globally (...) accessible hardware and encourages the development of complete, self-contained applications, from data collection to deployment. To this end, a collaboration between academia and industry produced a four part MOOC that provides application-oriented instruction on how to develop solutions using TinyML. The series is openly available on the edX MOOC platform, has no prerequisites beyond basic programming, and is designed for global learners from a variety of backgrounds. It introduces real-world applications, ML algorithms, data-set engineering, and the ethi- cal considerations of these technologies through hands-on programming and deployment of TinyML applications in both the cloud and on their own microcontrollers. To facili- tate continued learning, community building, and collaboration beyond the courses, we launched a standalone website, a forum, a chat, and an optional course-project com- petition. We also open-sourced the course materials, hoping they will inspire the next generation of ML practitioners and educators and further broaden access to cutting-edge ML technologies. (shrink)

Within international development [1], public health [2], and clinical medicine [3]–[5], there is increasing interest in determining whether cash payments or other economic incentives can be used to influence the choices and behavior of individuals and groups in order to promote desired health goals. However, a number of complex issues affect the review and approval by research ethics committees of research studying the effectiveness of using financial incentives to promote desired health goals. Current ethical and regulatory frameworks regard the provision (...) of gifts or cash payments to participants in human research as potentially problematic. Specifically, these frameworks imply that such incentives may undermine the autonomy of participant choice, hinder the disclosure of medical information, exacerbate social inequalities, or result in the exploitation or degradation of vulnerable populations [6]–[9]. Typically, these frameworks provide guidance about payment to research participants to reimburse expenses, to compensate for time and effort, to provide insurance coverage, or as an incentive to participate in the research itself. However, the issue of payment as a component of the research intervention is relatively new. RECs thus lack explicit guidance about ethical issues surrounding research that evaluates the use of financial incentives as an intervention to promote health. (shrink)

Introduction The goal of this project was to develop and validate a new tool to evaluate learners' knowledge and skills related to research ethics. Methods A core set of 50 questions from existing computer-based online teaching modules were identified, refined and supplemented to create a set of 74 multiple-choice, true/false and short answer questions. The questions were pilot-tested and item discrimination was calculated for each question. Poorly performing items were eliminated or refined. Two comparable assessment tools were created. These assessment (...) tools were administered as a pre-test and post-test to a cohort of 58 Indian junior health research investigators before and after exposure to a new course on research ethics. Half of the investigators were exposed to the course online, the other half in person. Item discrimination was calculated for each question and Cronbach's α for each assessment tool. A final version of the assessment tool that incorporated the best questions from the pre-/post-test phase was used to assess retention of research ethics knowledge and skills 3 months after course delivery. Results The final version of the REKASA includes 41 items and had a Cronbach's α of 0.837. Conclusion The results illustrate, in one sample of learners, the successful, systematic development and use of a knowledge and skills assessment tool in research ethics capable of not only measuring basic knowledge in research ethics and oversight but also assessing learners' ability to apply ethics knowledge to the analytical task of reasoning through research ethics cases, without reliance on essay or discussion-based examination. These promising preliminary findings should be confirmed with additional groups of learners. (shrink)