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Background: Mobile learning (M- learning) is the process of using a mobile device to access and study learning materials and to communicate with fellow students, instructors, or institutions. It can be utilized by both medical students as well as doctors to enhance educational and workplace activities, with the potential to enhance overall patient care and knowledge. This study aims to find out the perception of medical students towards the usage of M- learning in medical education and to determine the patterns of usage of M-learning among medical students. Methodology: This cross-sectional study was conducted among 469 students of Kasturba Medical College, Mangalore. The data was collected using a self- administered questionnaire- consisting of 2 sections: 1) General information of study participants 2) Perception of the mobile learning applications and its advantages and disadvantages. Data was analyzed using SPSS version 25. Descriptive statistics were expressed in mean (±SD), medians and percentages. Appropriate statistical tests were applied, and results were interpreted. P value > 0.05 was considered statistically significant. Results: The survey reveals a significant level of awareness and utilization of medical apps among medical students of the study settings, with 97.9% aware of their existence and 69.9% using them for educational purposes. More than half (55%) prefer smartphones for M-learning, primarily for reference (47.8%) and handy features (49.0%). The majority (76.0%) believe these apps save time and enhance knowledge (73.2%), express interest in college- specific apps (75.1%) and promote M-learning within the curriculum (60.8%). However, about 57.0% of students disagree with the usage of these app by non-medical personnel. Conclusions: This study demonstrates that M-learning is common among medical students and that it is utilized to supplement and expand the substantial amount of medical information that students must learn and comprehend. [ABSTRACT FROM AUTHOR]

The American academy of nutrition introduced the nutrition care process (NCP) in 2003. The introduction of nutrition care process has resulted in achievement of higher quality of care due to reduction in variance in nutrition care, better communication due to use of standardized language, help in outcome research. Although of immense benefit, its introduction and adaptation has been slow in India. Although of immense benefit, its introduction and adaptation has been slow in India. This article aims to introduce the concept of NCP and highlight the ways in which it has been implemented in other countries. It discusses the enablers and barriers to its implementation as seen in other countries and proposes a road map to its implementation in India. Going by the reviewed literature, the major steps which would facilitate the adaptation of NCP in India would be its endorsements by leading associations of nutritionists, its introduction in the syllabus of postgraduate studies of clinical nutrition in universities, the training of practicing nutritionists by regular workshops, and the introduction and integration of apps to carry out repetitive tasks in NCP implementations in patient care. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to understand the evolution, current competitive scenario, and future direction for the food-tech business in the Indian market. Design/methodology/approach: The paper is based on press reports, industry reports, and secondary information about companies based on interviews of CEOs, analysts, industry trend watchers, and academicians. Findings: The incumbents are competing on the basis of various parameters such as capital infusion (especially, funding), tie-ups with restaurants, customer loyalty, fleet size and management, and management of employees. High growth is driving volumes for all companies, although there is lack of differentiation in offerings. Companies need to build customer loyalty and seek diverse monetization models for profitability in the future. Research limitations/implications: First, food-tech companies need to identify means of differentiation to gain competitive advantage. Second, customer loyalty is the key to long-term profitability and firms need to identify ways to build it. Promotions and offers cannot build loyalty. Third, firms would need to expand into different types of monetization methods, such as cloud kitchens, B2B food delivery services, to build revenues and profits. Practical implications: Incumbents and prospective entrants in the food-tech industry need to understand the structure of the industry and the structure of competition to be able to succeed in the long term. They need to understand that promotions cannot be a differentiator and that funding will dry up. Therefore, it is critical to identify means of differentiation to build a loyal customer base. Social implications: The food-tech industry in India has strong social foundation. More than 50 per cent of the Indian population is below the age of 25, the percentage of working population is increasing in India and so are income levels. In this context, the food-tech business is important as order outs are increasing. This, however, has also led to problems in the workforce for such startups as companies do not want to invest in employee training, safety or work conditions owning to high attrition rate because of the standardized nature of the job. Originality/value: This paper makes an attempt to assimilate information about the progress of the food-tech industry in India in the last few years. It attempts to identify various factors that decide the nature of competition among incumbent players. It also identifies what factors these incumbents need to bear in mind while looking ahead. [ABSTRACT FROM AUTHOR]

In recent years, Reliance Jio's offer of 4G services, guaranteeing free voice calls and 'unlimited' data streaming, lead to disruption in the Indian telecom market with other cellular operators losing their revenue and customer base. To comprehensively analyze this churn in the Indian telecom industry and its impact on mobile phone customers, the article argues for observing the entanglement of infrastructural and platform-related discourses at three levels of operation: Jio's strategies to capture the Indian telecom market and the responses by the leading incumbent service provider (Airtel), ordinary citizens' phone use practices and infrastructural encounters, and the government's vision for India's digital future. Connecting pipes to platforms, Jio made infrastructural investments (in spectrum, cell towers, and fiber optics networks) to promote its suite of apps (JioTV, JioChat, and JioMoney). Ordinary citizens relate their access/proximity to telecom infrastructure (cell antennas) to their ability to effectively use apps on their phones. 'Digital India' vision purportedly facilitated infrastructural growth to create platforms that would support demonetization and facilitate transparent governance. Through such a three-pronged analysis, I conceptualize 'infrastructural imaginaries' that are coproduced by states and citizens, and lie at the intersection of structured state policy/corporate initiatives and lived experiences/affective encounters of ordinary citizens. [ABSTRACT FROM AUTHOR]

Internet usage is one the rise, and with it the increasing proliferation of social media. As computer mediated communication enters a new phase of digitalisation and integration, increasingly the urge to be connected is becoming more of an incessant craving. Empirical evidence suggests the new generation to be particularly prone to that habit. There is a fear that utility of the internet may soon be overshadowed by the amusement and entertainment part it provides. But is te user aware of the problem. In this paper, we look deeply into that problem. [ABSTRACT FROM AUTHOR]

From the inside of a software-intensive system, there are many different styles of implementation, each with its own subtle characteristics. From the outside, it all looks the same: its completely invisible. The Web extra at http://youtu.be/fWJEZ4vEEco is an audio podcast of author Grady Booch reading his On Computing column, in which he discusses how from the inside of a software-intensive system, there are many different styles of implementation, each with its own subtle characteristics. From the outside, it all looks the same: it's completely invisible. [ABSTRACT FROM PUBLISHER]

The publishing sector in India is growing at an estimated 30 per cent annually. New publishing technologies are creating opportunities tor book publishers in the country. The current ebook market is said to be less than one per cent of the total book market, but expected to grow multifold in the next 2-3 years. This paper scopes out the factors that will lead to the growth of ebooks, namely, growth of literacy; internet penetration; proliferation of personal handheld devices; localization; and the government's policies and initiatives. It lists the epublishing efforts of private publishers and new enterprises in education and trade segments of the industry. The article observes that although ebook publishing is at a nascent stage with potential for remarkable growth, print runs of printed books are increasing simultaneously. A hybrid model for the book industry, of both printed books and ebooks, is suggested as a viable option for the needs of a developing country such as India, where access to digital content continues to be a significant challenge. [ABSTRACT FROM AUTHOR]

Background: According to the World Health Organization, achieving targets for control of leprosy by 2030 will require disease elimination and interruption of transmission at the national or regional level. India and Brazil have reported the highest leprosy burden in the last few decades, revealing the need for strategies and tools to help health professionals correctly manage and control the disease., Objective: The main objective of this study was to develop a cross-platform app for leprosy screening based on artificial intelligence (AI) with the goal of increasing accessibility of an accurate method of classifying leprosy treatment for health professionals, especially for communities further away from major diagnostic centers. Toward this end, we analyzed the quality of leprosy data in Brazil on the National Notifiable Diseases Information System (SINAN)., Methods: Leprosy data were extracted from the SINAN database, carefully cleaned, and used to build AI decision models based on the random forest algorithm to predict operational classification in paucibacillary or multibacillary leprosy. We used Python programming language to extract and clean the data, and R programming language to train and test the AI model via cross-validation. To allow broad access, we deployed the final random forest classification model in a web app via shinyApp using data available from the Brazilian Institute of Geography and Statistics and the Department of Informatics of the Unified Health System., Results: We mapped the dispersion of leprosy incidence in Brazil from 2014 to 2018, and found a particularly high number of cases in central Brazil in 2014 that further increased in 2018 in the state of Mato Grosso. For some municipalities, up to 80% of cases showed some data discrepancy. Of a total of 21,047 discrepancies detected, the most common was "operational classification does not match the clinical form." After data processing, we identified a total of 77,628 cases with missing data. The sensitivity and specificity of the AI model applied for the operational classification of leprosy was 93.97% and 87.09%, respectively., Conclusions: The proposed app was able to recognize patterns in leprosy cases registered in the SINAN database and to classify new patients with paucibacillary or multibacillary leprosy, thereby reducing the probability of incorrect assignment by health centers. The collection and notification of data on leprosy in Brazil seem to lack specific validation to increase the quality of the data for implementations via AI. The AI models implemented in this work had satisfactory accuracy across Brazilian states and could be a complementary diagnosis tool, especially in remote areas with few specialist physicians., (©Márcio Luís Moreira De Souza, Gabriel Ayres Lopes, Alexandre Castelo Branco, Jessica K Fairley, Lucia Alves De Oliveira Fraga. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 07.04.2021.)