1 00:00:09,300 --> 00:00:10,967 Hi, I’m David Weindorf, 2 00:00:10,967 --> 00:00:14,133 Associate Vice President of Research at Texas Tech University. 3 00:00:14,133 --> 00:00:17,200 And today I have the pleasure of visiting with Julia Kagiliery. 4 00:00:17,200 --> 00:00:19,533 Julia, tell me a little bit about yourself and where you’re from. 5 00:00:19,533 --> 00:00:22,467 I’m a junior at the Episcopal School of Jacksonville, 6 00:00:22,467 --> 00:00:26,567 from Jacksonville Florida and I am seventeen years old. 7 00:00:26,567 --> 00:00:29,733 And you and I had an opportunity to do some research together 8 00:00:29,733 --> 00:00:31,600 which was kind of the first of its kind. 9 00:00:31,600 --> 00:00:32,767 Walk me through that a little bit. 10 00:00:32,767 --> 00:00:35,400 What did you do, like kind of how did we kick that whole thing off? 11 00:00:35,400 --> 00:00:38,300 So this research, we focused on predicting 12 00:00:38,300 --> 00:00:40,833 the sulphur content of lignite coal 13 00:00:40,833 --> 00:00:43,800 because high concentrations of sulphur in lignite coal 14 00:00:43,800 --> 00:00:49,533 are actually linked to acidic rain and producing highly acidic and caustic acid 15 00:00:49,533 --> 00:00:51,367 that can actually fall from the rain cloud 16 00:00:51,367 --> 00:00:56,200 and erode different soils and eco-systems and forests. 17 00:00:56,200 --> 00:00:58,367 And in doing that research I think you used 18 00:00:58,367 --> 00:01:00,967 some pretty cutting edge technology made by Olympus. 19 00:01:00,967 --> 00:01:02,533 Yes. Talk a little about that. 20 00:01:02,533 --> 00:01:04,467 So one of the things that we were working with 21 00:01:04,467 --> 00:01:05,933 that was really important for our research 22 00:01:05,933 --> 00:01:07,633 was actually the portable X-ray fluorescence 23 00:01:07,633 --> 00:01:11,433 which we used to actually talk and look at 24 00:01:11,433 --> 00:01:13,900 the iron and sulphur content in lignite 25 00:01:13,900 --> 00:01:15,600 and that way predicted. 26 00:01:15,600 --> 00:01:18,400 Fantastic. And did you just use the XRF 27 00:01:18,400 --> 00:01:21,567 or were there other technologies that you also used as well? 28 00:01:21,567 --> 00:01:24,200 Well, so in this research the really kind of revolutionary part 29 00:01:24,200 --> 00:01:26,567 was the fact that we were actually using proximal sensing methods, 30 00:01:26,567 --> 00:01:29,267 and multiple sensors to get these predictive algorithims. 31 00:01:29,267 --> 00:01:33,000 So we looked at actually a couple other kind of technologies 32 00:01:33,000 --> 00:01:35,567 and one of those would be the Nix™ Pro Color Sensor 33 00:01:35,567 --> 00:01:38,633 and then also a VIS-NIR spectroradiometer. 34 00:01:38,633 --> 00:01:41,000 OK, fantastic. So do you have plans 35 00:01:41,000 --> 00:01:44,833 after this to continue your research using these proximal sensors, 36 00:01:44,833 --> 00:01:46,933 maybe in other future projects? 37 00:01:46,933 --> 00:01:50,233 Yes. Hopefully we will be taking this research international next year 38 00:01:50,233 --> 00:01:53,000 at the Federal University of Lavras in Brazil 39 00:01:53,000 --> 00:01:54,967 to look at plant compositions. 40 00:01:54,967 --> 00:01:57,300 OK, fantastic well thanks for visiting with us today 41 00:01:57,300 --> 00:01:59,200 Thank you. Alright.