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The potential influence of bioluminescence from marine animals on a deep-sea underwater neutrino telescope array in the Mediterranean Sea
Stratigraphy and Reservoir Characterization of the Turner Sandstone, Southern Powder River Basin, Wyoming
- A. Heger
- Environmental Science, Geology
- 6 January 2017
The upper Turonian Turner Sandy Member of the Carlile Shale has long been a historic producer of hydrocarbons, and recently has become a significant horizontal target in the southern Powder River…
Deep-sea pelagic bioluminescence over the Mid-Atlantic Ridge
Distribution of bioluminescent organisms in the Mediterranean Sea and predicted effects on a deep-sea neutrino telescope
Benthic bioluminescence in the bathyal North East Atlantic: luminescent responses of Vargula norvegica (Ostracoda: Myodocopida) to predation by the deep-water eel (Synaphobranchus kaupii)
Benthic bioluminescence in the carbonate mound provinces was not directly linked to the presence of corals, and it is hypothesised that V. norvegica, attracted to bait, luminesce as a defence response against the predatory activity of S. kaupii that compete for bait but also feed on the ostracods.
Geo-Biological Investigations on Azooxanthellate Cold-Water Coral Reefs on the Carbonate Mounds Along the Celtic Continental Slope
Urban Fire Station Location Planning: A Systematic Approach using Predicted Demand and Service Quality Index
A machine learning model is developed, based on Random Forest, for demand prediction and utilize the model further to define a generalized index to measure quality of fire service in urban settings, built upon spatial data collected from multiple different sources.
Who's Eating Whom? Identification and Quantification of Deep-Pelagic Prey Fishes in the North Atlantic Ocean
In situ observations of benthic and pelagic bioluminescence in the deep Atlantic Ocean and Mediterranean Sea.
- A. Heger
- Environmental Science
Urban fire station location planning using predicted demand and service quality index
- Arnab Dey, A. Heger, D. England
- Computer ScienceInternational Journal of Data Science and…
- 5 September 2021
A systematic approach for fire station location planning is proposed and machine learning models, based on Random Forest and Extreme Gradient Boosting, are developed for demand prediction and a generalized index is defined to measure quality of fire service in urban settings.