ORCID Profile
0000-0003-1590-7716
Current Organisation
Federation University
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Publisher: Elsevier BV
Date: 07-2012
Publisher: AIP Publishing
Date: 2019
DOI: 10.1063/1.5117588
Publisher: Elsevier BV
Date: 10-2020
Publisher: Informa UK Limited
Date: 11-03-2021
Publisher: AIP Publishing
Date: 2019
DOI: 10.1063/1.5117542
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Elsevier BV
Date: 09-2013
Publisher: Elsevier BV
Date: 11-2014
Publisher: Springer Science and Business Media LLC
Date: 15-01-2018
DOI: 10.1038/S41598-017-18487-4
Abstract: The Tsuruoka Metabolomics Cohort Study included subjects aged 35–74 years from participants in annual health check-up programs in Tsuruoka, Japan. The gender-specific associations of early age-related macular degeneration (AMD) with systemic and genetic factors was assessed cross-sectionally. Of these, 3,988 subjects had fundus photographs of sufficient quality, and early AMD was present in 12.3% and 10.3% of men and women, respectively. In men, higher levels of high-density lipoprotein cholesterol and lower levels of triglycerides were associated with increased odds of having early AMD after adjusting for potential risk factors (for each 1 mmol/L increase, odds ratio [OR]: 1.61 and 0.78, 95% confidence interval [CI]: 1.17–2.23 and 0.64–0.96, respectively). In women, higher levels of total cholesterol and low-density lipoprotein cholesterol were associated with increased risk of having early AMD (OR: 1.21 and 1.26, 95% CI: 1.01–1.44 and 1.03–1.53, respectively). Sub-analysis demonstrated that women with ARMS2 A69S polymorphisms had a stronger risk for early AMD (OR: 3.25, 95% CI: 2.10–5.04) than men (OR: 1.65, 95% CI: 1.02–2.69). Differential associations of early AMD with both systemic and genetic factors by sex were demonstrated in a Japanese cohort, which suggests that disease process of early AMD could be different by sex.
Publisher: Elsevier BV
Date: 10-2010
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 10-2022
Publisher: Elsevier BV
Date: 10-2021
Publisher: Springer Science and Business Media LLC
Date: 11-09-2017
DOI: 10.1038/S41598-017-11718-8
Abstract: Growth Factor Independence 1 (GFI1) is a transcriptional repressor that plays a critical role during both myeloid and lymphoid haematopoietic lineage commitment. Several studies have demonstrated the involvement of GFI1 in haematological malignancies and have suggested that low expression of GFI1 is a negative indicator of disease progression for both myelodysplastic syndromes (MDS) and acute myeloid leukaemia (AML). In this study, we have stratified AML patients into those defined as having a normal karyotype (CN-AML). Unlike the overall pattern in AML, those patients with CN-AML have a poorer survival rate when GFI1 expression is high. In this group, high GFI1 expression is paralleled by higher FLT3 expression, and, even when the FLT3 gene is not mutated, exhibit a FLT3-ITD signature of gene expression. Knock-down of GFI1 expression in the human AML Fujioka cell line led to a decrease in the level of FLT3 RNA and protein and to the down regulation of FLT3-ITD signature genes, thus linking two major prognostic indicators for AML.
Publisher: Elsevier BV
Date: 2020
Publisher: Public Library of Science (PLoS)
Date: 18-11-2020
DOI: 10.1371/JOURNAL.PGEN.1009175
Abstract: The SARS-CoV-2 pandemic has led to unprecedented, nearly real-time genetic tracing due to the rapid community sequencing response. Researchers immediately leveraged these data to infer the evolutionary relationships among viral s les and to study key biological questions, including whether host viral genome editing and recombination are features of SARS-CoV-2 evolution. This global sequencing effort is inherently decentralized and must rely on data collected by many labs using a wide variety of molecular and bioinformatic techniques. There is thus a strong possibility that systematic errors associated with lab—or protocol—specific practices affect some sequences in the repositories. We find that some recurrent mutations in reported SARS-CoV-2 genome sequences have been observed predominantly or exclusively by single labs, co-localize with commonly used primer binding sites and are more likely to affect the protein-coding sequences than other similarly recurrent mutations. We show that their inclusion can affect phylogenetic inference on scales relevant to local lineage tracing, and make it appear as though there has been an excess of recurrent mutation or recombination among viral lineages. We suggest how s les can be screened and problematic variants removed, and we plan to regularly inform the scientific community with our updated results as more SARS-CoV-2 genome sequences are shared ( /issues-with-sars-cov-2-sequencing-data/473 and /masking-strategies-for-sars-cov-2-alignments/480 ). We also develop tools for comparing and visualizing differences among very large phylogenies and we show that consistent clade- and tree-based comparisons can be made between phylogenies produced by different groups. These will facilitate evolutionary inferences and comparisons among phylogenies produced for a wide array of purposes. Building on the SARS-CoV-2 Genome Browser at UCSC, we present a toolkit to compare, analyze and combine SARS-CoV-2 phylogenies, find and remove potential sequencing errors and establish a widely shared, stable clade structure for a more accurate scientific inference and discourse.
Publisher: Elsevier BV
Date: 09-2021
Publisher: Elsevier BV
Date: 03-2014
Publisher: Springer Science and Business Media LLC
Date: 17-04-2023
DOI: 10.1007/S10470-023-02153-Z
Abstract: Seizure prediction algorithms have been central in the field of data analysis for the improvement of epileptic patients’ lives. The most recent advancements of which include the use of deep neural networks to present an optimized, accurate seizure prediction system. This work puts forth deep learning methods to automate the process of epileptic seizure detection with electroencephalogram (EEG) signals as input both a patient-specific and general approach are followed. EEG signals are time structure series motivating the use of sequence algorithms such as temporal convolutional neural networks (TCNNs), and long short-term memory networks. We then compare this methodology to other prior pre-implemented structures, including our previous work for seizure prediction using machine learning approaches support vector machine and random under-s ling boost. Moreover, patient-specific and general seizure prediction approaches are used to evaluate the performance of the best algorithms. Area under curve (AUC) is used to select the best performing algorithm to account for the imbalanced dataset. The presented TCNN model showed the best patient-specific results than that of the general approach with, AUC of 0.73, while ML model had the best results for general classification with AUC of 0.75.
Publisher: Author(s)
Date: 2017
DOI: 10.1063/1.4984354
Publisher: Association for Research in Vision and Ophthalmology (ARVO)
Date: 17-03-2020
DOI: 10.1167/IOVS.61.3.23
Publisher: Elsevier BV
Date: 10-2010
Publisher: Elsevier BV
Date: 09-2021
Publisher: ASME International
Date: 26-06-2018
DOI: 10.1115/1.4040290
Abstract: Radiation absorption is investigated in a particle curtain formed in a solar free-falling particle receiver. An Eulerian–Eulerian granular two-phase model is used to solve the two-dimensional mass and momentum equations by employing computational fluid dynamics (CFD) to find particle distribution in the curtain. The radiative transfer equation (RTE) is subsequently solved by the Monte Carlo (MC) ray-tracing technique to obtain the radiation intensity distribution in the particle curtain. The predicted opacity is validated with the experimental results reported in the literature for 280 and 697 μm sintered bauxite particles. The particle curtain is found to absorb the solar radiation most efficiently at flowrates upper-bounded at approximately 20 kg s−1 m−1. In comparison, 280 μm particles have higher average absorptance than 697 μm particles (due to higher radiation extinction characteristics) at similar particle flowrates. However, as the absorption of solar radiation becomes more efficient, nonuniform radiation absorption across the particle curtain and hydrodynamic instability in the receiver are more probable.
Publisher: Elsevier BV
Date: 08-2022
Publisher: Elsevier BV
Date: 10-2020
Publisher: Inderscience Publishers
Date: 2010
Publisher: Author(s)
Date: 2017
DOI: 10.1063/1.4984372
Publisher: Elsevier BV
Date: 06-2020
Publisher: American Society of Mechanical Engineers
Date: 09-07-2017
DOI: 10.1115/HT2017-5117
Abstract: Radiation absorption by a particle curtain formed in a solar free falling particle receiver is investigated using a Eulerian-Eulerian granular two-phase model to solve the two-dimensional mass and momentum equations (CFD). The radiative transfer equation is subsequently solved by the Monte-Carlo (MC) ray-tracing technique using the CFD results to quantify the radiation intensity through the particle curtain. The CFD and MC results provide reliable opacity predictions and are validated with the experimental results available in literature. The particle curtain was found to absorb the solar radiation efficiently for smaller particles at high flowrates due to higher particle volume fraction and increased radiation extinction. However, at low mass-flowrates the absorption efficiency decreases for small and large particles.
Publisher: Wiley
Date: 24-03-2021
Abstract: Two‐step solar thermochemical water splitting is a promising pathway for renewable fuel production due to its potential for high thermal efficiency via full‐spectrum sunlight utilization. Such a promise critically relies on simultaneous innovation in the redox materials and the reactor systems. Most prior efforts on material design are focused on improving the fuel yield at lower reduction temperatures. However, developing materials with both high fuel output and efficiency remains a key challenge, requiring a rigorous understanding of the effects of material thermodynamic properties. Herein, a generic thermodynamic framework is described to decipher the material effects by studying both the state‐of‐the‐art and hypothetical materials within a counterflow reactor system. A global efficiency map is presented for redox materials, revealing inevitable tradeoffs among competing factors such as thermal losses, sweep gas and oxidizer demand, solid preheating, and reduction enthalpy. The choice of the most efficient material is closely linked to the system conditions. Ceria‐based materials outperform perovskites under most scenarios, and the optimal hypothetical materials tend to favor higher reduction enthalpies and entropies than existing materials. This work offers a valuable material design roadmap to identify solutions toward efficient solar fuel production.
Publisher: Informa UK Limited
Date: 13-09-2020
Publisher: Elsevier BV
Date: 05-2021
Publisher: Elsevier BV
Date: 04-2011
No related grants have been discovered for Apurv Kumar.