701 research outputs found
sj-docx-1-ejo-10.1177_11206721221078152 - Supplemental material for Corneal scarring following collagen cross-linking: evidence of increased lysyl oxidase activity
No full textSupplemental material, sj-docx-1-ejo-10.1177_11206721221078152 for Corneal scarring following collagen cross-linking: evidence of increased lysyl oxidase activity by Sushmita G Shah, Rohit Shetty, Arkasubra Ghosh and Gaurav Y Shah in European Journal of Ophthalmology</p
Tables_3-14 – Supplemental material for Repeatability and reproducibility of corneal biomechanical parameters derived from Corvis ST
No full textSupplemental material, Tables_3-14 for Repeatability and reproducibility of corneal biomechanical parameters derived from Corvis ST by Nermin Serbecic, Sven Beutelspacher, Lovro Markovic, Abhijit Sina Roy and Rohit Shetty in European Journal of Ophthalmology</p
Analysing a central implementation of an electronic lab notebook (eLabFTW) at the University of Innsbruck
No full textauthor: Rohit KarthikeyanMasterarbeit University of Innsbruck 202
Analysing a central implementation of an electronic lab notebook (eLabFTW) at the University of Innsbruck
No full textauthor: Rohit KarthikeyanMasterarbeit University of Innsbruck 202
Utilizing photoswitchable lipids to photoregulate facilitated ion transport across membranes
No full textAuthor Rohit YadavDissertation Johannes Kepler Universität Linz 2025Arbeit gesperr
Utilizing photoswitchable lipids to photoregulate facilitated ion transport across membranes
No full textAuthor Rohit YadavDissertation Johannes Kepler Universität Linz 2025Arbeit gesperr
COVID-19: Time Series Datasets India versus World
No full textThis dataset consists of COVID-19 time series data of India since March 24th, 2020.
The data set is for all the States and Union Territories of India and is divided into five parts, including
i) Confirmed cases;
ii) Death Count;
iii) Recovered Cases;
iv) Temperature of that place; and
v) Percentage humidity in the region.
The data set also provides basic details of confirmed cases and death count for all the countries of the world updated daily since 30 January 2020.
The end user can contact the corresponding author (Rohit Salgotra : [email protected]) for more details.
.
The Authors can Refer to and CITE our latest Papers on COVID:
1. Salgotra, Rohit, Mostafa Gandomi, and Amir H. Gandomi. "Time Series Analysis and Forecast of the COVID-19 Pandemic in India using Genetic Programming." Chaos, Solitons & Fractals (2020): 109945.
2. Salgotra, Rohit, Mostafa Gandomi, and Amir H. Gandomi. "Evolutionary modelling of the COVID-19 pandemic in fifteen most affected countries." Chaos, Solitons & Fractals 140 (2020): 110118.
3. Mousavi, Mohsen, et al. "COVID-19 Time Series Forecast Using Transmission Rate and Meteorological Parameters as Features." IEEE Computational Intelligence Magazine 15.4 (2020): 34-50.
.
[Dataset is updated Once a Week
COVID-19: Time Series Datasets India versus World
No full textThis dataset consists of COVID-19 time series data of India since 24th March 2020.
The data set is for all the States and Union Territories of India and is divided into five parts, including
i) Confirmed cases;
ii) Death Count;
iii) Recovered Cases;
iv) Temperature of that place; and
v) Percentage humidity in the region.
The data set also provides basic details of confirmed cases and death count for all the countries of the world updated daily since 30 January 2020.
The end user can contact the corresponding author (Rohit Salgotra : [email protected]) for more details.
.
The Authors can Refer to and CITE our latest Papers on COVID:
1. Salgotra, Rohit, Mostafa Gandomi, and Amir H. Gandomi. "Time Series Analysis and Forecast of the COVID-19 Pandemic in India using Genetic Programming." Chaos, Solitons & Fractals (2020): 109945.
2. Salgotra, Rohit, Mostafa Gandomi, and Amir H. Gandomi. "Evolutionary modelling of the COVID-19 pandemic in fifteen most affected countries." Chaos, Solitons & Fractals 140 (2020): 110118.
3. Mousavi, Mohsen, et al. "COVID-19 Time Series Forecast Using Transmission Rate and Meteorological Parameters as Features." IEEE Computational Intelligence Magazine 15.4 (2020): 34-50.
.
[Dataset is updated Once a Week
COVID-19: Time Series Datasets India versus World
No full textThis dataset consists of COVID-19 time series data of India since March 24th, 2020.
The data set is for all the States and Union Territories of India and is divided into five parts, including
i) Confirmed cases;
ii) Death Count;
iii) Recovered Cases;
iv) Temperature of that place; and
v) Percentage humidity in the region.
The data set also provides basic details of confirmed cases and death count for all the countries of the world updated daily since 30 January 2020.
The end user can contact the corresponding author (Rohit Salgotra : [email protected]) for more details.
.
The Authors can Refer to and CITE our latest Papers on COVID:
1. Salgotra, Rohit, Mostafa Gandomi, and Amir H. Gandomi. "Time Series Analysis and Forecast of the COVID-19 Pandemic in India using Genetic Programming." Chaos, Solitons & Fractals (2020): 109945.
2. Salgotra, Rohit, Mostafa Gandomi, and Amir H. Gandomi. "Evolutionary modelling of the COVID-19 pandemic in fifteen most affected countries." Chaos, Solitons & Fractals 140 (2020): 110118.
3. Mousavi, Mohsen, et al. "COVID-19 Time Series Forecast Using Transmission Rate and Meteorological Parameters as Features." IEEE Computational Intelligence Magazine 15.4 (2020): 34-50.
.
[Dataset is updated Once a Week
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