AIMC Topic: Minerals
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Nutritional, chemical and functional potential of Inga laurina (Fabaceae): A barely used edible species.
Food research international (Ottawa, Ont.)
Dec 20, 2023
Inga laurina is a plant species which produces edible fruits, and until now there is little information available concerning its nutritional, chemical and bioactive composition. In this study, we evaluated for the first time the proximate composition...
Predicting Unreported Micronutrients From Food Labels: Machine Learning Approach.
Journal of medical Internet research
Apr 12, 2023
BACKGROUND: Micronutrient deficiencies represent a major global health issue, with over 2 billion individuals experiencing deficiencies in essential vitamins and minerals. Food labels provide consumers with information regarding the nutritional conte...
On stars and spikes: Resolving the skeletal morphology of planktonic Acantharia using synchrotron X-ray nanotomography and deep learning image segmentation.
Acta biomaterialia
Jan 25, 2023
Acantharia (Acantharea) are wide-spread marine protozoa, presenting one of the rare examples of strontium sulfate mineralization in the biosphere. Their endoskeletons consist of 20 spicules arranged according to a unique geometric pattern named Mülle...
Prediction of fluid oil and gas volumes of shales with a deep learning model and its application to the Bakken and Marcellus shales.
Scientific reports
Dec 2, 2022
The fluid oil and gas volumes (S1) retained within the shales are one of the most important parameter of producible fluid oil and gas saturations of shales together with total organic carbon content. The S1 volumes can directly be obtained by Rock-Ev...
Research on Classification of Open-Pit Mineral Exploiting Information Based on OOB RFE Feature Optimization.
Sensors (Basel, Switzerland)
Mar 2, 2022
Mineral exploiting information is an important indicator to reflect regional mineral activities. Accurate extraction of this information is essential to mineral management and environmental protection. In recent years, there are an increasingly large...
Rapid identification of ore minerals using multi-scale dilated convolutional attention network associated with portable Raman spectroscopy.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Nov 13, 2021
Electron portable Raman spectroscopy tools for ore mineral identification are widely used in raw ore analysis and mineral process engineering. This paper demonstrates an extremely fast and accurate method for identifying unknown ore mineral samples b...
Applications of Machine Learning in Bone and Mineral Research.
Endocrinology and metabolism (Seoul, Korea)
Oct 21, 2021
In this unprecedented era of the overwhelming volume of medical data, machine learning can be a promising tool that may shed light on an individualized approach and a better understanding of the disease in the field of osteoporosis research, similar ...
Investigating Habitability with an Integrated Rock-Climbing Robot and Astrobiology Instrument Suite.
Astrobiology
Oct 14, 2020
A prototype rover carrying an astrobiology payload was developed and deployed at analog field sites to mature generalized system architectures capable of searching for biosignatures in extreme terrain across the Solar System. Specifically, the four-l...
Geographic origin discrimination of pork from different Chinese regions using mineral elements analysis assisted by machine learning techniques.
Food chemistry
Aug 5, 2020
Porkis thelargest-producedandmost-consumedmeat intheworld, and the food market globalization has increased public attention to food origin. Therefore, advanced techniques are required to determine the geographical origin of pork. This study investiga...
Radiomics for classification of bone mineral loss: A machine learning study.
Diagnostic and interventional imaging
Feb 4, 2020
PURPOSE: The purpose of this study was to develop predictive models to classify osteoporosis, osteopenia and normal patients using radiomics and machine learning approaches.
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