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Now showing items 926-945 of 6405
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Deciphering the role of host protein HuR in RNA virus life cycle and pathogenesis: Hepatitis C Virus and SARS-CoV-2 as exemplars.
Viruses pose a major threat to human health and the ongoing SARS-CoV-2 pandemic proves as the best evidence for that. Historically, RNA viruses have a major potential to cause such pandemics. They utilise RNA binding ... -
Deciphering the Role of METTL3-Dependent m6A-epitranscriptome in Glioma Stem-like Cells
The major roadblocks in treatment for GBM are resistance to therapy and recurrence of GBM cells. Regardless of various treatment strategies, the average survival of GBM patients is poor and incidence of recurrence remains ... -
Deciphering the role of outer membrane porins in the pathogenesis of Salmonella enterica serovar Typhimurium
Porins are highly conserved barrel-shaped proteins bound to the bacterial outer membrane and involved in the selective transport of charged molecules across the membrane. They consist of parallel and anti-parallel β sheets ... -
Decision Making under Uncertainty : Reinforcement Learning Algorithms and Applications in Cloud Computing, Crowdsourcing and Predictive Analytics
In this thesis, we study both theoretical and practical aspects of decision making, with a focus on reinforcement learning based methods. Reinforcement learning (RL) is a form of semi-supervised learning in which the agent ... -
Decoding Epigenetic Regulators in Cancer: Acetylation of HIF2A by Histone Acetyltransferase 1 (HAT1) is essential for executing hypoxia response in glioma
Gliomas are tumors of the central nervous system arising from glial cells. Based on the origin of the cell type, it can be astrocytoma, oligodendroglioma, and ependymoma. Astrocytoma is the most common type of glioma, ... -
Decoding of Attention and Behavioral State Using Local Field Potentials
Visual attention has been shown to modulate perceptual behavior and neuronal activity. Early psychophysical studies on attention showed that the subjects detected a target presented at the attended location better (i.e., ... -
Decomposition of the tensor product of Hilbert modules via the jet construction and weakly homogeneous operators
Let ½ Cm be a bounded domain and K :£!C be a sesqui-analytic function. We show that if ®,¯ È 0 be such that the functions K® and K¯, defined on £, are non-negative definite kernels, then theMm(C) valued function ... -
Deep Convolutional and Generative Networks for Ocean Synoptic Feature Extraction and Super Resolution from Remotely Sensed Images
Accurate extraction of Synoptic Ocean Features and Downscaling of Ocean Features is crucial for climate studies and the operational forecasting of ocean systems. With the advancement of space and sensor technologies, the ... -
Deep Learning Based Channel Estimation in Wireless Communications
Deep learning techniques which employ trained neural networks to solve problems have witnessed widespread adoption in diverse fields like medicine, architecture, robotics, autonomous vehicles, wireless communications, ... -
Deep Learning for Bug Localization and Program Repair
In this thesis, we focus on the problem of program debugging and present novel deep learning based techniques for bug-localization and program repair. Deep learning techniques have been successfully applied to a variety ... -
Deep Learning for Hand-drawn Sketches: Analysis, Synthesis and Cognitive Process Models
Deep Learning-based object category understanding is an important and active area of research in Computer Vision. Most work in this area has predominantly focused on the portion of depiction spectrum consisting of ... -
Deep Learning in Computer Vision: Studies in Neuro-image Segmentation and Satellite Image Super-resolution
Single image super-resolution (SR) has been a topic of great interest in the computer vision and deep learning community and has found applications in many areas including quality enhancement of satellite images. As the ... -
Deep Learning Methods For Audio EEG Analysis
The perception of speech and audio is one of the defining features of humans. Much of the brain’s underlying processes as we listen to acoustic signals are unknown, and significant research efforts are needed to unravel ... -
Deep learning methods for light fluence compensation in two-dimensional and three-dimensional photoacoustic imaging
Photoacoustic imaging (PAI) employed the special properties of light or photons to obtain detailed images of organs, tissues, cells, and even molecules. The method allowed for a non-invasive or minimally invasive examination ... -
Deep Learning Models for Few-shot and Metric Learning
Deep neural network-based models have achieved unprecedented performance levels over many tasks in the traditional supervised setting and scale well with large quantities of data. On the other hand, improving performance ... -
Deep Learning over Hypergraphs
Graphs have been extensively used for modelling real-world network datasets, however, they are restricted to pairwise relationships, i.e., each edge connects exactly two vertices. Hypergraphs relax the notion of edges ... -
Deep Learning with Minimal Supervision
Abstract In recent years, deep neural networks have achieved extraordinary performance on supervised learning tasks. Convolutional neural networks (CNN) have vastly improved the state of the art for most computer vision ... -
Deep Visual Representations: A study on Augmentation, Visualization, and Robustness
Deep neural networks have resulted in unprecedented performances for various learning tasks. Particularly, Convolutional Neural Networks (CNNs) are shown to learn representations that can efficiently discriminate hundreds ... -
Deeply Scaled InAlN/GaN-on-Silicon High Electron Mobility Transistors for RF Applications
Wide bandgap gallium nitride (GaN) based high electron mobility transistors (HEMTs) are promising candidates for next-generation radio frequency (RF) power amplifier applications owing to high electron saturation velocity ...