242 research outputs found
Corrigendum to "Familial determinants of bone health parameters - a dual X-ray absorptiometry (DXA) and peripheral quantitative computed tomography (pQCT)-based parent and offspring study in rural Indian children" [Bone (2026), volume 202, article 117685].
No full textThe affiliation of the second author, Dr. Nikhil Shah, was listed incorrectly. His correct affiliations are “a” (Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, Pune, India) and “d” (Department of Pediatric Endocrinology, MRR Children's Hospital, Mumbai)
EXTERNAL PHOTOEVAPORATION OF THE SOLAR NEBULA: JUPITER's NOBLE GAS ENRICHMENTS
No full textabstract: We present a model explaining the elemental enrichments in Jupiter's atmosphere, particularly the noble gases Ar, Kr, and Xe. While He, Ne, and O are depleted, seven other elements show similar enrichments (~3 times solar, relative to H). Being volatile, Ar is difficult to fractionate from H[subscript 2]. We argue that external photoevaporation by far-ultraviolet (FUV) radiation from nearby massive stars removed H[subscript 2], He, and Ne from the solar nebula, but Ar and other species were retained because photoevaporation occurred at large heliocentric distances where temperatures were cold enough (lesssim 30 K) to trap them in amorphous water ice. As the solar nebula lost H, it became relatively and uniformly enriched in other species. Our model improves on the similar model of Guillot & Hueso. We recognize that cold temperatures alone do not trap volatiles; continuous water vapor production is also necessary. We demonstrate that FUV fluxes that photoevaporated the disk generated sufficient water vapor in regions [< over ~]30 K to trap gas-phase species in amorphous water ice in solar proportions. We find more efficient chemical fractionation in the outer disk: whereas the model of Guillot & Hueso predicts a factor of three enrichment when only <2% of the disk mass remains, we find the same enrichments when 30% of the disk mass remains. Finally, we predict the presence of ~0.1 M [subscript ⊕] of water vapor in the outer solar nebula and protoplanetary disks in H II regions.Copyright IOP Publishing. This is the authors' final, peer-reviewed manuscript. Monga, Nikhil, & Desch, Steven (2015). EXTERNAL PHOTOEVAPORATION OF THE SOLAR NEBULA: JUPITER's NOBLE GAS ENRICHMENTS. ASTROPHYSICAL JOURNAL, 798(1), 0-0. http://dx.doi.org/10.1088/0004-637X/798/1/9. The final version as published can be viewed online at http://dx.doi.org/10.1088/0004-637X/798/1/
Detection results of NMC particles in composite battery cathodes
No full textThis dataset shows more examples of the NMC particles detection overlayed with the original images in composite battery cathodes.
@journal{li2022networkevolution,
title={Dynamics of particle network in composite battery cathodes},
author={Li, Jizhou and Sharma, Nikhil and Jiang, Zhisen and Yang, Yang and Monaco, Federico and Xu, Zhengrui and Hou, Dong and Ratner, Daniel and Pianetta, Piero and Cloetens, Peter and Lin, Feng and Zhao, Kejie and Liu, Yijin},
year={2022},
journal={Science}
Pattern Discovery of Sequential Symbolic Data using Automata with an application to Author Identification
No full textAuthor Identification is the process of identifying a piece of text to ascertain if it has an inherent writing style or pattern based on a certain author. Almost all literary books can be accredited to a certain author since it has been signed. However, there also exist a plethora of unfinished books or manuscripts that could be attributed to a range of possible authors. For example, William Shakespeare has written many plays that have not been signed by him. In order to assess the importance of such texts that do not bear the authors signature, it could be vital to know who was the writer. I plan to solve this dilemma using the characteristics of finite state automata coupled with the ALERGIA algorithm
Dynamics of particle network in composite battery cathodes
No full textThis repository contains the source codes for the study of active particle-network evolution in Ni-rich LiNi0.8Mn0.1Co0.1O2 (NMC) composite battery cathodes, as described in the following paper:
@journal{li2021networkevolution,
title={Dynamics of particle network in composite battery cathodes},
author={Li, Jizhou and Sharma, Nikhil and Jiang, Zhisen and Yang, Yang and Monaco, Federico and Xu, Zhengrui and Hou, Dong and Ratner, Daniel and Pianetta, Piero and Cloetens, Peter and Lin, Feng and Zhao, Kejie and Liu, Yijin},
year={2022},
journal={Science}
Citation Author Topic Model in Expert Search
No full textThis paper proposes a novel topic model, Citation-Author-Topic (CAT) model that addresses a semantic search task we define as expert search – given a research area as a query, it returns names of experts in this area. For example, Michael Collins would be one of the top names retrieved given the query Syntactic Parsing. Our contribution in this paper is two-fold. First, we model the cited author informa-tion together with words and paper au-thors. Such extra contextual information directly models linkage among authors and enhances the author-topic association, thus produces more coherent author-topic distribution. Second, we provide a prelim-inary solution to the task of expert search when the learning repository contains ex-clusively research related documents au-thored by the experts. When compared with a previous proposed model (Johri et al., 2010), the proposed model pro-duces high quality author topic linkage and achieves over 33 % error reduction evaluated by the standard MAP measure-ment.
Shear strengthening of prestressed concrete beams with UHPFRC – a numerical study
No full textAccepted Author ManuscriptConcrete Structure
A numerical study of the thermal effects on local water bodies due to changes in the environment
No full textThe study of global warming and its effects is becoming increasingly popular due to steady increase in the environmental pollution. Local warming of a particular place which in turn contributes to the global warming can be studied through temperature variations of the local water bodies due to changes in the environment. In the present work, using the weather data obtained for New Brunswick, a general trend for variation in ambient temperature during the year is determined by fitting suitable curves using curve-fitting technique. Using this, the transient temperature distribution in the lake is determined numerically. The effect of many driving parameters such as ambient temperature, relative humidity, wind speed, solar flux, equilibrium temperature, diffusivity and surface heat loss on the temperatures of the lake are studied in detail using a one-dimensional transient model. The governing equations are solved numerically using finite differences method. The results of this work show the transient temperature distribution in the lake over the year and the variation in temperatures due to external changes in the environment.M.S.Includes bibliographical referencesby Nikhil Bharadwa
RAS: an end to end suite for single-cell and standard RNA-Seq data analysis
No full textAs RNA sequencing (RNA-Seq) becomes more affordable to process, the number of sequencing data has increased at a rapid rate. A major challenge in RNA-Seq experiments is the analysis of large amount of data generated by next-generation sequencing. RNA-Seq data analysis usually requires advanced Linux/Unix experience for software installation and tedious commands. This required skill set hinders scientists who are interested in analyzing RNA-Seq data but do not have Linux/Unix experience. Here, we describe an end to end pipeline for RNA-Seq Data Analysis Suite (RAS), which streamlines and speeds up analysis time for both standard and single-cell and standard RNA-Seq data. In addition, RAS is a standalone web application and contains an interface where Linux/Unix skills are not required for the data analysis. RAS creates a web server, where the user can interact with the pipeline on a browser. In addition, Since since RAS utilizes distributed computing, it uses computational resources efficiently. RAS The pipeline was validated on single-cell RNA-Seq datasets publicly available at the Gene Expression Omnibus (GEO) from the NCBI.M.S.Includes bibliographical referencesby Nikhil Kuma
Building a similarity engine
No full textThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (page 53).In the seventeenth century, Philosophers such as Leibniz and Descartes put forward proposal for codes to relate words between languages. The first patents for "translating machines" were applied for in the mid-1930s. Up to the 1980s, most Natural Language Processing (NLP) systems were based on complex sets of hand-written rules. At that time however, the introduction of machine learning algorithms for language processing revolutionized NLP.[5] In 2008, Collobert and Weston exhibited the power of pre-trained word embed- dings in a paper called A unified architecture for natural language processing. Here, word embeddings is highlight for its ability in downstream tasks. They also discuss a neural network architecture that many of todays approaches are built upon. In 2013, Mikolov created word2vec, a toolkit that enabled the training and use of pre-trained embeddings. In 2014, Pennington introduced GloVe, a competitive set of pre-trained embeddings. Starting off, a single word or group of words can be converted into a vector. This vector can be created using the Skip gram method, which predicts the possible words nearby, the LSTM-RNN method, which forms semantic representations of sentences by learning more about the sentence as it iterates through a sentence, using single convolution neural networks, and several other methods. Using these theories, we are trying to build a Similarity Engine which provides machine learning based content search and classification of data.by Nikhil Narendra Punwaney.M. Eng
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