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Pure Herbs Linaloe Berry (Bursera Delpechiana) Pure Natural Th

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Pure Herbs Linaloe Berry (Bursera Delpechiana) Pure Natural Th

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Product description

FINEST QUALITY ESSENTIAL OILS MONEY CAN BUY:- Top reputed brand - Pure Herbs oils are natural, undiluted amp; therapeutic grade. 100% RISK FREE PURCHASE. We believe our oils will impart lasting therapeutic. QUANTITY:- Container Type - High Quality Amber Glass Natural, Therapeutic Grade Essential Oil. BOTANICAL NAME:- Bursera Delpechiana. METHOD OF EXTRACTION:- Steam distillation BENEFITS amp; USES:- Linaloe Berry (Bursera Delpechiana) Essential Oil is used for Aromatherapy. Improve the complexion of dull, dry or oily skin. It has rejuvenating properties that stimulate tissue regeneration, making it helpful in preventing premature skin-aging, fading stretch marks, and soothing red, irritated skin. The relaxing qualities of Linaloe Berry Essential Oil can help ease stress and tension, as well as being invaluable in meditation since it helps to calm the mind. COLOUR amp; AROMA:- Colorless to pale yellow liquid. Fresh, woody, citrus, floral odor. HOW TO USE:- Diffuse, Bath and Body Massage. For External use only. PRECAUTION:- Do not apply directly to skin. Keep away from eyes and sensitive areas. Wash hands after touching essential oils.

Pure Herbs Linaloe Berry (Bursera Delpechiana) Pure Natural Th

Jason McEwen

Professor of Astrostatistics

University College London

I am a Professor of Astrostatistics and Astroinformatics at the Mullard Space Science Laboratory (MSSL) at University College London (UCL) and a Turing Fellow at the Alan Turing Institute, the UK’s national centre for data science and artificial intelligence (AI).

My research interests encompass a wide range of areas within astroinformatics and astrostatistics, including Bayesian inference, harmonic analysis, optimisation, and machine learning and artificial intelligence, with a focus on application to cosmology and radio interferometry.

I am also Founder and CEO of Kagenova, a startup company developing deep tech for virtual reality and beyond.

I am Director of Research (Astrophysics) of UCL’s Centre for Doctoral Training (CDT) in Data Intensive Science. I am a Core Team member of the ESA Planck satellite mission, a member of the Square Kilometre Array (SKA) Science Data Processor (SDP) working group, a member of the ESA Euclid satellite Science Consortium, and a member of the Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) and Informatics and Statistics Science Collaboration (ISSC).

Previously I was a Royal Society Newton Fellow and before that a Leverhulme Early Career Fellow at UCL. Prior to that I was a Scientist in the Electrical Engineering Institute at Ecole Polytechnique Federale de Lausanne (EPFL) and a Research Fellow of Clare College, Cambridge, after receiving a PhD in Astrophysics from the University of Cambridge.

Interests

  • Astrostatistics
  • Astroinformatics
  • Bayesian inference
  • Harmonic analysis
  • Optimisation
  • Machine Learning and Artificial Intelligence