Faculty Publications

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    Rural nonfarm employment, income, and inequality: Evidence from Bhutan
    (MIT Press Journals, 2015) Rahut, D.B.; Jena, P.R.; Ali, A.; Behera, B.; Chhetri, N.B.
    Using the 2012 Bhutan Living Standard Survey, this paper finds that rural nonfarmactivities comprise 60.7% of rural household income in Bhutan and this contribution increases with higher income and education levels. The poor and less educated participate less in the nonfarm sector.When they do, they are selfemployed in petty nonfarmactivities, which require little investment and little or no skills. Accounting for endogeneity and sample selection issues, we estimate the determinants of participation in nonfarm activities and nonfarm incomes. We find that a household’s education and labor supply play an important role in accessing more remunerative nonfarm employment. Interestingly, we find that women play an important role in self-employment in nonfarm activities. Decomposition shows that nonfarm income has a disequalizing effect and farm income has an equalizing effect, indicating the need to increase the endowment of poor households to enable them to access the lucrative rural nonfarm sector. Further decomposition reveals that self-employment in petty nonfarm activities reduces inequality. © 2015 Asian Development Bank and Asian Development Bank Institute.
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    Segmentation of focal cortical dysplasia lesions from magnetic resonance images using 3D convolutional neural networks
    (Elsevier Ltd, 2021) Niyas, S.; Chethana Vaisali, S.; Show, I.; Chandrika, T.G.; Vinayagamani, S.; Kesavadas, C.; Rajan, J.
    Computer-aided diagnosis using advanced Artific ial Intelligence (AI) techniques has become much popular over the last few years. This work automates the segmentation of Focal Cortical Dysplasia (FCD) lesions from three-dimensional (3D) Magnetic Resonance (MR) images. FCD is a type of neuronal malformation in the brain cortex and is the leading cause of intractable epilepsy, irrespective of gender or age differences. Since the neuron related abnormalities are usually resistant to drug therapy, surgical resection has been the main treatment approach for patients with intractable epilepsy. Automating the identification and segmentation of FCD is useful for neuroradiologists in pre-surgical evaluations. Convolutional Neural Networks (CNNs) have the ability to learn appropriate features from the training data without any human intervention. But, most of the state-of-the-art FCD segmentation approaches use two-dimensional (2D) CNN models despite the availability of 3D Magnetic resonance imaging (MRI) volumes, and hence fail to leverage the inter-slice information present in the MRI volumes. The major hurdles in considering a 3D CNN model are the need for a large 3D dataset, big memory, and high computation cost. A deep 3D CNN segmentation model, which can extract inter-slice information and overcomes the drawbacks of conventional 3D CNN methods to an extent, is proposed in this paper. The model uses a 3D version of U-Net with residual blocks that works on shallow depth 3D sub-volumes generated from MRI volumes. The proposed method shows superior performance over the state-of-the-art FCD segmentation methods in both qualitative and quantitative analysis. © 2021 Elsevier Ltd
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    Masculinities, femininities, and the patriarchal family: a reading of The Great Indian Kitchen
    (Routledge, 2024) Karimpaniyil, R.; Bhat, P.
    This article seeks to examine the representation of masculinities and femininities in the renowned South Indian drama film The Great Indian Kitchen. The research construes the manner in which the two dominant genders promote and/or modify patriarchal norms within the institution of family. The functioning of women as ancillary members of patriarchy, the interplay between masculinities and femininities, their evolution in contemporary times, etc., are also critically engaged in the paper. The paper argues that the movie The Great Indian Kitchen not only illustrates different masculinities and femininities but also reconstructs the patriarchal family structure which institutionalises gender inequality. It further argues that the movie proposes an alternative image of the family based on gender equality, where men and women live with mutual respect and complementation. © 2023 Informa UK Limited, trading as Taylor & Francis Group.