98 research outputs found
Supplemental Material - Role of interleukin-6 and interferon-α in systemic lupus erythematosus: A case–control study and meta-analysis
No full textSupplemental Material for Role of interleukin-6 and interferon-α in systemic lupus erythematosus: A case–control study and meta-analysis by Sarit Sekhar Pattanaik, Aditya K Panda, Abhijit Pati, Sunali Padhi, Rina Tripathy, Saumya Ranjan Tripathy, Manoj Kumar Parida, and Bidyut Kumar Das in Lupus</p
A short-term decline in anthropogenic emission of CO<sub>2</sub> in India due to COVID-19 confinement
No full textTo curb the spread of novel coronavirus (COVID-19), confinement measures were undertaken, which altered the pattern of energy consumption and India’s anthropogenic CO2 emissions during the effective lockdowns periods (January to June 2020). Such changes are being analyzed using data of energy generated from coal and renewable sources and fossil-based daily CO2 emissions. Results revealed that coal-fired (fossil-based) energy generation fell by –13% in March, –29% in April, and –20% in May, and –16.6% in mid-June 2020 as compared with the same period in 2018–2019. Conversely, the renewable energy generation increased by 19% in March, 12% in April, 17% in May, and 7% in June 2020. The share of fossil-based energy fell by –6.55% in 2020 compared with mean levels, which was further offset by increases of renewable energy. India’s daily fossil-based CO2 emissions fell by –11.6% (–5 to –25.7%) by mid-June 2020 compared with mean levels of 2017–2019 with total change in fossil-based CO2 emission by –139 (–62 to –230) MtCO2, with the largest reduction in the industry (–41%), transport (–28.5%), and power (–21%) followed by the public (–5.4%), and aviation (–4%) sectors. If some levels of lockdown persist until December 2020, both energy consumption and CO2 emissions patterns would be below the 2019 level. The nationwide lockdown has led to a reduction in anthropogenic CO2 emissions and, subsequently, improved air quality and global environment and has also helped in reducing atmospheric CO2 concentrations at the local level but not on the global level. With suitable government policies, switching to a cleaner mode of energy generation other than fossil fuels could be a viable option to minimize CO2 emissions under increasing demand for energy.</p
Improvement in air quality and its impact on land surface temperature in major urban areas across India during the first lockdown of the pandemic
No full textThe SARS CoV-2 (COVID-19) pandemic and the enforced lockdown have reduced the use of surface and air transportation. This study investigates the impact of the lockdown restrictions in India on atmospheric composition, using Sentinel–5Ps retrievals of tropospheric NO2 concentration and ground-station measurements of NO2 and PM2.5 between March–May in 2019 and 2020. Detailed analysis of the changes to atmospheric composition are carried out over six major urban areas (i.e. Delhi, Mumbai, Kolkata, Chennai, Bangalore, and Hyderabad) by comparing Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) and land surface temperature (LST) measurements in the lockdown year 2020 and pre-lockdown (2015–2019). Satellite-based data showed that NO2 concentration reduced by 18% (Kolkata), 29% (Hyderabad), 32-34% (Chennai, Mumbai, and Bangalore), and 43% (Delhi). Surface-based concentrations of NO2, PM2.5, and AOD also substantially dropped by 32–74%, 10–42%, and 8–34%, respectively over these major cities during the lockdown period and co-located with the intensity of anthropogenic activity. Only a smaller fraction of the reduction of pollutants was associated with meteorological variability. A substantial negative anomaly was found for LST both in the day (–0.16 °C to –1 °C) and night (–0.63 °C to –2.1 °C) across select all cities, which was also consistent with air temperature measurements. The decreases in LST could be associated with a reduction in pollutants, greenhouse gases and water vapor content. Improvement in air quality with lower urban temperatures due to lockdown may be a temporary effect, but it provides a crucial connection among human activities, air pollution, aerosols, radiative flux, and temperature. The lockdown for a shorter-period showed a significant improvement in environmental quality and provides a strong evidence base for larger scale policy implementation to improve air quality
Electronic Resource Sharing of Libraries: A Footprint Toward Green-E Future
No full textThis paper discusses different benefits of electronic resource sharing and described it as a sector, i.e., space, energy, cost, time, organization, and reliability. The authors also have visualized the concept of "Green-E" in the field of libraries and information centers. Through the analysis of electronic resources as a renewable source of energy for libraries, the idea has been explained and supported by showing how electronic resources play an important role as greener energy and help save the earth from global warming and climate change. The future of e-libraries and green libraries may be called the "Green-E Library," and its electronic resources mark the footprint for a green future
Efficiency of depleted UO2 based semiconductor neutron detectors-A Monte Carlo simulation study
No full text
A novel embedded spherical semiconductor neutron detector efficiency estimation using GEANT4 simulation methodology
No full textThe present research work explores on the estimation of thermal neutron detection efficiency for the novel embedded spherical configuration design using GEANT4 toolkit. Initially, single and multiple layer of embedded spherical configurations were designed in geometry category class of GEANT4 toolkit using Boron (10B) converter material followed by, estimation of simulated thermal neutron detection efficiency at different radii which varies between 0.05 μm and 5 μm for both single and multiple layer embedded spherical detector configuration. The maximum thermal neutron detection efficiency obtained for the single layer embedded spherical detector configuration is ∼5.1 % at an optimum (critical) radius of ∼4.55 μm. It was noticed that with the rise in the number of layers of embedded spherical detector configuration the thermal neutron detection efficiency was also increasing. Furthermore, investigation the effect of varying level of Low Level Discriminator and different enrichment level of 10B on the efficiency was also studied. Finally, the histoplot was investigated for a typical 10 layers of embedded spherical detector configuration at typical lower (200 nm) and higher (3 μm) radius
Analysis of SMAW Parameters Using Self Organizing Maps and Probability Density Distributions
No full textOdiEnCorp 2.0
No full textData
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We have collected English-Odia parallel data for the purposes of NLP
research of the Odia language.
The data for the parallel corpus was extracted from existing parallel
corpora such as OdiEnCorp 1.0 and PMIndia, and books which contain both
English and Odia text such as grammar and bilingual literature books. We
also included parallel text from multiple public websites such as Odia
Wikipedia, Odia digital library, and Odisha Government websites.
The parallel corpus covers many domains: the Bible, other literature,
Wiki data relating to many topics, Government policies, and general
conversation. We have processed the raw data collected from the books,
websites, performed sentence alignments (a mix of manual and automatic
alignments) and released the corpus in a form suitable for various NLP
tasks.
Corpus Format
-------------
OdiEnCorp 2.0 is stored in simple tab-delimited plain text files, each
with three tab-delimited columns:
- a coarse indication of the domain
- the English sentence
- the corresponding Odia sentence
The corpus is shuffled at the level of sentence pairs.
The coarse domains are:
books ... prose text
dict ... dictionaries and phrasebooks
govt ... partially formal text
odiencorp10 ... OdiEnCorp 1.0 (mix of domains)
pmindia ... PMIndia (the original corpus)
wikipedia ... sentences and phrases from Wikipedia
Data Statistics
---------------
The statistics of the current release are given below.
Note that the statistics differ from those reported in the paper due to
deduplication at the level of sentence pairs. The deduplication was
performed within each of the dev set, test set and training set and
taking the coarse domain indication into account. It is still possible
that the same sentence pair appears more than once within the same set
(dev/test/train) if it came from different domains, and it is also
possible that a sentence pair appears in several sets (dev/test/train).
Parallel Corpus Statistics
--------------------------
Dev Dev Dev Test Test Test Train Train Train
Sents # EN # OD Sents # EN # OD Sents # EN # OD
books 3523 42011 36723 3895 52808 45383 3129 40461 35300
dict 3342 14580 13838 3437 14807 14110 5900 21591 20246
govt - - - - - - 761 15227 13132
odiencorp10 947 21905 19509 1259 28473 24350 26963 704114 602005
pmindia 3836 70282 61099 3836 68695 59876 30687 551657 486636
wikipedia 1896 9388 9385 1917 21381 20951 1930 7087 7122
Total 13544 158166 140554 14344 186164 164670 69370 1340137 1164441
"Sents" are the counts of the sentence pairs in the given set (dev/test/train)
and domain (books/dict/...).
"# EN" and "# OD" are approximate counts of words (simply space-delimited,
without tokenization) in English and Odia
The total number of sentence pairs (lines) is 13544+14344+69370=97258. Ignoring
the set and domain and deduplicating again, this number drops to 94857.
Citation
--------
If you use this corpus, please cite the following paper:
@inproceedings{parida2020odiencorp,
title={OdiEnCorp 2.0: Odia-English Parallel Corpus for Machine Translation},
author={Parida, Shantipriya and Dash, Satya Ranjan and Bojar, Ond{\v{r}}ej and Motlicek, Petr and Pattnaik, Priyanka and Mallick, Debasish Kumar},
booktitle={Proceedings of the WILDRE5--5th Workshop on Indian Language Data: Resources and Evaluation},
pages={14--19},
year={2020}
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