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Krishnan Ganapathy Arjun Rajagopalan Gita Arjun Seshadri Suresh Krishnan Sriram 《Journal of the Medical Library Association》2022,110(1):146
The informed netizen of today is in a state of information overload. With 785 million broadband subscribers and an urban and rural teledensity of 138% and 60%, respectively [1], India is already the second-largest online digital market. Today, in theory, medical journals and textbooks can be accessed by anyone, anytime, anywhere, and at affordable rates. Fifty odd years ago, when the authors entered medical school, the use of computers in medical education was unknown in India, as in other parts of the world. It was in this milieu, thirty-seven years ago, that eleven young Madras (Chennai)-based doctors decided to make medical literature easily accessible, particularly to clinicians in suburban and rural India. The aim was to make relevant, affordable reprints easily available to the practitioner at their place of work or study. Photocopying and using the postal service was the chosen, and indeed the only available, mode of operation. This article will outline the methodology used, trials and tribulations faced, and persistence displayed. At that time, the processes deployed appeared relevant and truly innovative. Over the ensuing years, developments in information technology made the services redundant. Extensive, even revolutionary, changes such as universal digitization and availability of a cost-effective Internet radically changed how medical literature could be accessed in India. 相似文献
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ABSTRACTThis article proposes translingual dispositions as a way to move beyond the NES/NNES dichotomy in understanding language teacher identity. Recent scholarship in TESOL and Applied Linguistics has problematized the NES/NNES binary from a poststructuralist perspective, highlighting how NES/NNES subjectivities are discursively and performatively (co-)constructed and negotiated. Despite the efforts to empower NNESs, the very binary reifies monolingual ideologies. This article argues that translingual dispositions can help move beyond the binary and complicate theorization of teachers’ identities and practice. To illustrate, we report an ethnographic case study of a “NES” teacher, Daphne, and examine how Daphne’s translingual dispositions shape her teaching and facilitate her students’ creative negotiation of monolingual norms in a writing course. We conclude by discussing future research directions and the implications for language teacher education in fostering translingual dispositions. 相似文献
35.
Mallikarjuna BP Suresh Kumar GV Sastry BS Nagaraj Manohara KP 《Journal of Zhejiang University. Science. B》2007,8(7):526-532
In the present research, a series of 5,6-bis aryl 1,2,4-triazines 5a~5f were synthesized by condensation of various benzils 4a~4f with aminoguanidine bicarbonate and were screened in vivo, for their anticonvulsant and neurotoxicity studies. Compounds 5a, 5b and 5d were found to be potent molecules of this series, when compared with the reference drugs phenytoin sodium, diazepam and lamotrigine. The structures of these compounds were established by IR, 1H NMR, 13C NMR and mass spectroscopic data. 相似文献
36.
Yu-Dong Zhang Suresh Chandra Satapathy David S. Guttery Juan Manuel Górriz Shui-Hua Wang 《Information processing & management》2021,58(2):102439
AimIn a pilot study to improve detection of malignant lesions in breast mammograms, we aimed to develop a new method called BDR-CNN-GCN, combining two advanced neural networks: (i) graph convolutional network (GCN); and (ii) convolutional neural network (CNN).MethodWe utilised a standard 8-layer CNN, then integrated two improvement techniques: (i) batch normalization (BN) and (ii) dropout (DO). Finally, we utilized rank-based stochastic pooling (RSP) to substitute the traditional max pooling. This resulted in BDR-CNN, which is a combination of CNN, BN, DO, and RSP. This BDR-CNN was hybridized with a two-layer GCN, and yielded our BDR-CNN-GCN model which was then utilized for analysis of breast mammograms as a 14-way data augmentation method.ResultsAs proof of concept, we ran our BDR-CNN-GCN algorithm 10 times on the breast mini-MIAS dataset (containing 322 mammographic images), achieving a sensitivity of 96.20±2.90%, a specificity of 96.00±2.31% and an accuracy of 96.10±1.60%.ConclusionOur BDR-CNN-GCN showed improved performance compared to five proposed neural network models and 15 state-of-the-art breast cancer detection approaches, proving to be an effective method for data augmentation and improved detection of malignant breast masses. 相似文献
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Ananth N. Rao J. Kavitha Minakshi Koch V. Suresh Kumar 《Indian journal of clinical biochemistry : IJCB》2009,24(3):215-222
Inherited metabolic disorders are a heterogeneous group of genetic conditions mostly occurring in childhood. They are individually
rare but collectively numerous, causing substantial morbidity and mortality. We have retrospectively reviewed a total of eight
hundred and sixty nine cases with different age groups that had been referred from several diagnostic centers and hospitals
of India to the Department of Metabolism in Narayana Hrudayalaya, as cases suspected with inborn errors of metabolism. Advanced
techniques applied were to diagnose the disorders of inborn errors of metabolism. Data analyzed indicates occurrence of several
metabolic disorders in our population. The need to screen for an inborn error of metabolism arises out of the fact that most
cases take to irreversible effects as time progress. Emphasis has to be laid on early detection and prompt management, which
could help in alleviating symptoms and preventing complications and consequent incapacitation. 相似文献
39.
Dadi Ramesh;Suresh Kumar Sanampudi; 《European Journal of Education》2024,59(3):e12684
Automatic essay scoring (AES) is an essential educational application in natural language processing. This automated process will alleviate the burden by increasing the reliability and consistency of the assessment. With the advances in text embedding libraries and neural network models, AES systems achieved good results in terms of accuracy. However, the actual goals still need to be attained, like embedding essays into vectors with cohesion and coherence, and providing student feedback is still challenging. In this paper, we proposed coherence-based embedding of an essay into vectors using sentence-Bidirectional Encoder Representation for Transformers. We trained these vectors on Long short-term memory and bidirectional long short-term memory to capture sentence connectivity with other sentences' semantics. We used two datasets: standard ASAP Kaggle and a domain-specific dataset with almost 2500 responses from 650 students. Our model performed well on both datasets, with an average quadratic weighted kappa score of 0.76. Furthermore, we achieved good results compared to other prescribed models, and we also tested our model on adversarial responses of both datasets and observed decent outcomes. 相似文献
40.
Sajimon Thomas S. Suresh M. Sudheesh T. Vijayakumar 《Indian journal of clinical biochemistry : IJCB》2015,30(2):155-160
Metabolic syndrome (MetS) results from the derangement of adipocyte physiology and carbohydrate metabolism. Obesity and insulin resistance (IR) are integral features of MetS. The adipokine alterations in MetS often correlate with IR and body fat content. High adipose tissue content is associated with a decreased production of adiponectin and excessive production of tumour necrosis factor-α (TNF-α) and interleukin-6 (IL-6), all of which induce IR. The present study evaluated the adipokine alterations in MetS and their association with IR. The findings of the current study indicate that MetS is associated with significant decrease in adiponectin and increase in TNF-α and IL-6. The present study also found that the adipocyte derived inflammatory adipokines, TNF-α and IL-6 correlate with IR while the anti-inflammatory adipokines, adiponectin does not correlate with the degree and severity of IR. 相似文献