701 research outputs found
Alkaline rocks and their economic and geodynamic significance through geological time
No full textAlkaline igneous rocks have a relative excess of alkalis over silica. Most are silica undersaturated and contain normative nepheline and real feldspathoids (nepheline, leucite). Although alkaline rocks make up only about 1% of total igneous rocks by volume, their diverse mineralogy accounts for 90% of all igneous rock names proposed by the IUGS. They occur in all tectonic settings; in the ocean basins and on the continents, along mid-ocean ridges (rare), on oceanic islands, in subduction zones in the oceans and along continental margins, as well as along rift zones. Alkaline rocks commonly include alkali basalts and foidites, tephrites, phonolites, trachytes and their intrusive equivalents, including lamprophyres and carbonatites. In the literature, a plethora of local names for alkaline rocks from different localities have been created and many geoscientists still consider them as petrological curiosities. However, their study can significantly aid the interpretation of mantle evolution, ancient terranes and their geodynamic settings. Additionally, alkaline rocks may host world-class precious- and rare-metal mineralization. During recent years, the exploration interest in critical and rare metal deposits (Nb, rare earth elements (REEs) and Th) has increased dramatically as they represent vital resources for the so-called ‘green energy transition’. This Special Publication presents new comprehensive data, results and findings on alkaline rocks from different terranes worldwide and uses their mineralogy and geochemical fingerprints in order to elucidate their petrogenesis, tectonic settings and mineralization potential. This volume is not only of interest for igneous petrologists, but also for exploration geologists prospecting for precious- and rare-metal mineralization worldwide
sj-docx-1-ine-10.1177_15910199231196329 - Supplemental material for Device use trends in neuroendovascular procedures in the United States from 2015 to 2020
No full textSupplemental material, sj-docx-1-ine-10.1177_15910199231196329 for Device use trends in neuroendovascular procedures in the United States from 2015
to 2020 by Arjun Rohit Adapa, Fazeel M. Siddiqui and Aditya S. Pandey in Interventional Neuroradiology</p
Improved Black-Box Constructions of Composable Secure Computation
No full textWe close the gap between black-box and non-black-box constructions of composable secure multiparty computation in the plain model under the minimal assumption of semi-honest oblivious transfer. The notion of protocol composition we target is angel-based security, or more precisely, security with super-polynomial helpers. In this notion, both the simulator and the adversary are given access to an oracle called an angel that can perform some predefined super-polynomial time task. Angel-based security maintains the attractive properties of the universal composition framework while providing meaningful security guarantees in complex environments without having to trust anyone.
Angel-based security can be achieved using non-black-box constructions in max(R_OT,Õ(log n)) rounds where R_OT is the round-complexity of semi-honest oblivious transfer. However, current best known black-box constructions under the same assumption require max(R_OT,Õ(log² n)) rounds. If R_OT is a constant, the gap between non-black-box and black-box constructions can be a multiplicative factor log n. We close this gap by presenting a max(R_OT,Õ(log n)) round black-box construction. We achieve this result by constructing constant-round 1-1 CCA-secure commitments assuming only black-box access to one-way functions
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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