Priya Goyal

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Papers by Priya Goyal

Reprogramming of glucose metabolism in virus infected cells

Molecular and Cellular Biochemistry

Viral infection is a kind of cellular stress that leads to the changes in cellular metabolism. Ma... more Viral infection is a kind of cellular stress that leads to the changes in cellular metabolism. Many metabolic pathways in a host cell such as glycolysis, amino acid and nucleotide synthesis are altered following virus infection. Both oncogenic and non-oncogenic viruses depend on host cell glycolysis for their survival and pathogenesis. Recent studies have shown that the rate of glycolysis plays an important role in oncolysis as well by oncolytic therapeutic viruses. During infection, viral proteins interact with various cellular glycolytic enzymes, and this interaction enhances the catalytic framework of the enzymes subsequently the glycolytic rate of the cell. Increased activity of glycolytic enzymes following their interaction with viral proteins is vital for replication and to counteract the inhibition of glycolysis caused by immune response. In this review, the importance of host cell glycolysis and the modulation of glycolysis by various viruses such as oncogenic, non-oncogenic and oncolytic viruses are presented.

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Acoustic emission monitoring of steel fiber reinforced beams under simultaneous corrosion and sustained loading

European Journal of Environmental and Civil Engineering

Outcomes After Peripheral Vascular Interventions in Patients With End-Stage Renal Disease

Journal of Vascular Surgery, 2021

Good Long-term Motor and Sensory Outcomes of Infantile Esotropia: A Strabismus Surgeon's Goal

Journal of Pediatric Ophthalmology & Strabismus, 2021

PI-RADS v2 in Prostate Cancer and Correlation with T Staging, PSA Levels and ADC Values

Iranian Journal of Radiology, 2017

Background: Magnetic resonance imaging of the prostate is a major diagnostic tool in prostate can... more Background: Magnetic resonance imaging of the prostate is a major diagnostic tool in prostate cancer detection. In 2012, prostate imaging reporting and data system (PI-RADS) was published by the European society of urogenital radiology. Due to certain limitations in this version, a revised version named Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) was proposed by the American College of Radiology in 2014 Objectives: To evaluate the role of multiparametric magnetic resonance imaging based prostate imaging reporting and data system (PI-RADS) version 2 for the assessment of peripheral zone prostate cancer and its correlation with the T staging, prostatic specific antigen (PSA) levels and apparent diffusion coefficient (ADC) values. Patients and Methods: Eighty seven patients underwent MRI at 1.5 T units. Dynamic contrast enhanced (DCE) imaging was done in 73 patients as 14 patients had deranged renal functions. Patients with a PI-RADS v2 score of ≥ 2 underwent biopsy except in one patient with a score of 1. The histopathological report was used as gold standard. T staging was done based on MRI. The score was correlated with T staging, ADC values and serum prostate-specific antigen (S.PSA) levels by two experienced blinded radiologists. Statistical analysis was done. Results: Highly significant correlation was observed between PI-RADS v2 score, T staging, ADC values and s PSA levels with P value < 0.005. DCE had added advantage in one patient only for up-gradation of score from 3 to 4. Conclusion: The dominant MR imaging sequence for the peripheral zone prostate cancer is diffusion weighted sequence and the corresponding ADC values, with the role of DCE sequences in doubtful cases only. PI-RADS v2 gives a scoring system on MRI for prostate cancer assessment. It should be routinely incorporated in the reporting protocol. Our study concluded that there is a highly significant correlation between lesion score on PI-RADS v2 with the T stage, corresponding ADC values and S.PSA levels, although larger study groups may be required for further evaluation and beyond doubt PI-RADS version 3 is already in its earliest stages.

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A Study on 5G Evolution and Revolution

As the cellular technology is growing at a rapid pace, users always seek for a set of appropriate... more As the cellular technology is growing at a rapid pace, users always seek for a set of appropriate packages all together, including all the current features in use. Hence, the search for a new technology is always the main concern of the foremost cell phone companies to out innovate their competitors. The main purpose of the fifth generation wireless technology (5G) is formulated to design the ultimate wireless world that is free from limitations and impediments of the previous technologies. 5G technology will mend the way most users access their mobile networks. So, this paper presents the evolution of 1G (First Generation) to 4G yielding 5G, introduction to 5G technology- its need, advantages and architecture.

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Impact of Textile Waste Water on Agricultural Fields: A Case Study of Sanganer Town, Jaipur

Textile and Industrial waste water is discharged on land or into the running water streams, which... more Textile and Industrial waste water is discharged on land or into the running water streams, which is used for irrigating crops. Amanishah nallah, which is a great importance to Jaipur city particularly Sanganer area, now it has become one of the best example to get effluents and polluted water from different Textile industries. This waste water effluent of textile dyeing and printing industries of Sanganer is discharged without any treatment into Amanishah nallah drainage. This drainage water changes the Physico chemical properties of water. This paper contains results of Physico-chemical analysis of waste water collected from 5 different agricultural sites of Sanganer town adjoining the Amanishah nallah. Water from underground sources is drawn and used in tie and dye industries and converted into textile waste water. This waste water is used in several nearby located agricultural fields. The study was carried out during a period of two years (2011 – 2013). Results revealed that in ...

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Home Healthcare Services as an Extension of Intensive Care Unit

The Modern Hospital, 2019

On the modern hospital, the vast majority of patients will require ICU admission. The cost of car... more On the modern hospital, the vast majority of patients will require ICU admission. The cost of caring patients in the ICU in the USA is expected to increase to 6% of the gross national product by 2019. There are ways to provide ICU care to the growing number of patients; of all extending ICU care at home seems to be the best solution. Intensive home healthcare is a multidisciplinary effort among hospitals, physicians, nurses, and pharmaceutical and insurance companies. This chapter is an attempt to explore this revolutionary field.

Deep Neural Networks in Embedded Systems

This thesis explores possibilities of running deep neural networks on embedded systems for traffi... more This thesis explores possibilities of running deep neural networks on embedded systems for traffic monitoring. The main goal is to design, implement and test a prototype of the system for vehicle and people detection from video records and camera streams using neural networks. In this work, three different CNN architectures are compared, namely RetinaNet, YOLO and SqueezeDet. Software prototype is designed so that it can be deployed on commercial off-the-shelf devices, e.g. Jetson Xavier module from NVIDIA.

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Healthcare Provider-Centered: Ergonomics of Movement and Functionality

The Modern Hospital, 2019

There is a mutual interaction between health and the workplace. Ergonomics is the study of this i... more There is a mutual interaction between health and the workplace. Ergonomics is the study of this interaction. With the increase in healthcare sector productivity and activity, work-related mental stress and physical injuries are bound to increase. The distracted body and mind of a healthcare provider can lead to the compromised safety of patients and, ultimately, poor outcomes. Application of workplace ergonomics leads to healthier and better lifestyles for doctors, nurses, and allied healthcare providers. There are recommended guidelines in place for hospitals and administrators to ensure a healthy workforce. This chapter gives the introduction and application of ergonomics at hospitals to improve health and safety for all.

Self-supervised Pretraining of Visual Features in the Wild

ArXiv, 2021

Recently, self-supervised learning methods like MoCo [22], SimCLR [8], BYOL [20] and SwAV [7] hav... more Recently, self-supervised learning methods like MoCo [22], SimCLR [8], BYOL [20] and SwAV [7] have reduced the gap with supervised methods. These results have been achieved in a control environment, that is the highly curated ImageNet dataset. However, the premise of self-supervised learning is that it can learn from any random image and from any unbounded dataset. In this work, we explore if self-supervision lives to its expectation by training large models on random, uncurated images with no supervision. Our final SElf-supERvised (SEER) model, a RegNetY with 1.3B parameters trained on 1B random images with 512 GPUs achieves 84.2% top-1 accuracy, surpassing the best self-supervised pretrained model by 1% and confirming that self-supervised learning works in a real world setting. Interestingly, we also observe that selfsupervised models are good few-shot learners achieving 77.9% top-1 with access to only 10% of ImageNet.

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Geometrical meaning of statistical isotropy of smooth random fields in two dimensions

Physical Review D, 2021

We revisit the geometrical meaning of statistical isotropy that is manifest in excursion sets of ... more We revisit the geometrical meaning of statistical isotropy that is manifest in excursion sets of smooth random fields in two dimensions. Using the contour Minkowski tensor, W1, as our basic tool we first examine geometrical properties of single structures. For simple closed curves in two dimensions we show that W1 is proportional to the identity matrix if the curve has m-fold symmetry, with m ≥ 3. Then we elaborate on how W1 maps any arbitrary shaped simple closed curve to an ellipse that is unique up to translations of its centroid. We also carry out a comparison of the shape parameters, α and β, defined using W1, with the filamentarity parameter defined using two scalar Minkowski functionals-area and contour length. We show that they contain complementary shape information, with W1 containing additional information of orientation of structures. Next, we apply our method to boundaries of excursion sets of random fields and examine what statistical isotropy means for the geometry of the excursion sets. Focusing on Gaussian isotropic fields, and using a semi-numerical approach we quantify the effect of finite sampling of the field on the geometry of the excursion sets. In doing so we obtain an analytic expression for α which takes into account the effect of finite sampling. Finally we derive an analytic expression for the ensemble expectation of W1 for Gaussian anisotropic random fields. Our results provide insights that are useful for designing tests of statistical isotropy using cosmological data.

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Local patch analysis for testing statistical isotropy of the Planck convergence map

Journal of Cosmology and Astroparticle Physics, 2021

The small but measurable effect of weak gravitational lensing on the cosmic microwave background ... more The small but measurable effect of weak gravitational lensing on the cosmic microwave background radiation provide information about the large-scale distribution of matter in the universe. We use the all sky distribution of matter, as represented by the convergence map that is inferred from CMB lensing measurement by Planck survey, to test the fundamental assumption of Statistical Isotropy (SI) of the universe. For the analysis we use the α statistic that is devised from the contour Minkowski tensor, a tensorial generalization of the scalar Minkowski functional, the contour length. In essence, the α statistic captures the ellipticity of iso-field contours at any chosen threshold value of a smooth random field and provides a measure of anisotropy. The SI of the observed convergence map is tested against the suite of realistic simulations of the convergence map provided by the Planck collaboration. We first carry out a global analysis using the full sky data after applying the galactic and point sources mask. We find that the observed data is consistent with SI. Further we carry out a local search for departure from SI in small patches of the sky using α. This analysis reveals several sky patches which exhibit deviations from simulations with statistical significance higher than 95% confidence level (CL). Our analysis indicates that the source of the anomalous behaviour of most of the outlier patches is inaccurate estimation of noise. We identify two outlier patches which exhibit anomalous behaviour originating from departure from SI at higher than 95% CL. Most of the anomalous patches are found to be located roughly along the ecliptic plane or in proximity to the ecliptic poles.

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Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions

ArXiv, 2018

Deep learning models with convolutional and recurrent networks are now ubiquitous and analyze mas... more Deep learning models with convolutional and recurrent networks are now ubiquitous and analyze massive amounts of audio, image, video, text and graph data, with applications in automatic translation, speech-to-text, scene understanding, ranking user preferences, ad placement, etc. Competing frameworks for building these networks such as TensorFlow, Chainer, CNTK, Torch/PyTorch, Caffe1/2, MXNet and Theano, explore different tradeoffs between usability and expressiveness, research or production orientation and supported hardware. They operate on a DAG of computational operators, wrapping high-performance libraries such as CUDNN (for NVIDIA GPUs) or NNPACK (for various CPUs), and automate memory allocation, synchronization, distribution. Custom operators are needed where the computation does not fit existing high-performance library calls, usually at a high engineering cost. This is frequently required when new operators are invented by researchers: such operators suffer a severe perfor...

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Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

ArXiv, 2017

Deep learning thrives with large neural networks and large datasets. However, larger networks and... more Deep learning thrives with large neural networks and large datasets. However, larger networks and larger datasets result in longer training times that impede research and development progress. Distributed synchronous SGD offers a potential solution to this problem by dividing SGD minibatches over a pool of parallel workers. Yet to make this scheme efficient, the per-worker workload must be large, which implies nontrivial growth in the SGD minibatch size. In this paper, we empirically show that on the ImageNet dataset large minibatches cause optimization difficulties, but when these are addressed the trained networks exhibit good generalization. Specifically, we show no loss of accuracy when training with large minibatch sizes up to 8192 images. To achieve this result, we adopt a hyper-parameter-free linear scaling rule for adjusting learning rates as a function of minibatch size and develop a new warmup scheme that overcomes optimization challenges early in training. With these simp...

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Finite element modelling of reinforced concrete beam column joints

Transverse colon volvulus with Chiladiti Syndrome- Rare cause of large bowel obstruction

Volvulus of transverse colon is a rare cause of large bowel obstruction. To our knowledge,only 75... more Volvulus of transverse colon is a rare cause of large bowel obstruction. To our knowledge,only 75 cases have been reported in the world literature. Association with chilaiditi's syndrome is even rare.Â Diagnosis can be challenging and the effective management remains controversial.Â We report case of a 40 year old female presenting with features suggestive of large bowel obstruction and episodes of mild abdominal discomfort for a year. Typical findings of right colonic volvulus were seen on skiagram. On laparotomy, redundantÂ transverse colon withÂ long mesentery which was massivelyÂ dilated were found to be rotated on its own axis and lying between the right lobe of the liver and diaphragm. extended right hemicolectomy was performed with an uneventful post operative period. It is imporant to highlight this case, as many surgeons may never have seen a singe case of transverse colon volvulus with chilaiditi's syndrome. It may therefore not be considered in the differential d...

Does Endovascular Repair for Blunt Traumatic Aortic Injuries Provide Better Outcomes Compared to Its Open Technique? A Systematic Review and Meta-analysis

Surgical Technology Online, 2021

Introduction: Traumatic aortic injuries are devastating events in terms of high mortality and mor... more Introduction: Traumatic aortic injuries are devastating events in terms of high mortality and morbidity in most survivors. We aimed to compare the outcomes of endovascular repair (ER) vs. open repair (OR) in the treatment of traumatic aortic injuries. Methods: PubMed, Embase, and Cochrane Library were systematically searched. Postoperative mortality was the primary endpoint. Secondary endpoints included intensive care unit (ICU) length of stay, hospital length of stay, operating time, paraplegia, stroke, acute renal failure, and reoperation rate. The Mantel-Haenszel method (random-effects model) with odds ratios and 95% confidence intervals (OR (95% CI)), and the inverse variance method with the mean difference (MD (95% CI)), were used to measure the effects of continuous and categorical variables, respectively. Results: A total of 49 studies involving 12,857 patients were included. Postoperative mortality was not significantly different between the two groups (p=0.459). Among secon...

Experimental validation of influenza A virus matrix protein (M1) interaction with host cellular alpha enolase and pyruvate kinase

Virology, 2020

This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Scaling and Benchmarking Self-Supervised Visual Representation Learning

2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019

Self-supervised learning aims to learn representations from the data itself without explicit manu... more Self-supervised learning aims to learn representations from the data itself without explicit manual supervision. Existing efforts ignore a crucial aspect of self-supervised learning-the ability to scale to large amount of data because self-supervision requires no manual labels. In this work, we revisit this principle and scale two popular selfsupervised approaches to 100 million images. We show that by scaling on various axes (including data size and problem 'hardness'), one can largely match or even exceed the performance of supervised pre-training on a variety of tasks such as object detection, surface normal estimation (3D) and visual navigation using reinforcement learning. Scaling these methods also provides many interesting insights into the limitations of current self-supervised techniques and evaluations. We conclude that current self-supervised methods are not 'hard' enough to take full advantage of large scale data and do not seem to learn effective high level semantic representations. We also introduce an extensive benchmark across 9 different datasets and tasks. We believe that such a benchmark along with comparable evaluation settings is necessary to make meaningful progress.

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