1 00:00:00,520 --> 00:00:04,000 Speaker 1: Already, and this is the daily This is the Daily 2 00:00:04,120 --> 00:00:06,840 Speaker 1: os oh Now it makes sense. 3 00:00:14,640 --> 00:00:17,520 Speaker 2: Good morning and welcome to the Daily Ohs. It's Saturday, 4 00:00:17,560 --> 00:00:18,680 Speaker 2: the eleventh of January. 5 00:00:18,680 --> 00:00:19,920 Speaker 1: I'm Zara, I'm Sam. 6 00:00:20,040 --> 00:00:21,880 Speaker 2: There's no better way to start a new year, I 7 00:00:21,880 --> 00:00:24,759 Speaker 2: think than talking about some of the brighter stories, right. 8 00:00:24,800 --> 00:00:26,680 Speaker 1: I feel like it's going to be a year, hopefully 9 00:00:26,880 --> 00:00:27,920 Speaker 1: of more good news. 10 00:00:27,720 --> 00:00:29,320 Speaker 2: Than tween filled with good news. 11 00:00:29,480 --> 00:00:31,560 Speaker 1: I've got good vibes. I've got good vibes about the 12 00:00:31,600 --> 00:00:35,720 Speaker 1: good news for a week circuit, watch this podcast get 13 00:00:35,840 --> 00:00:38,400 Speaker 1: longer and longer. Because there's going to be so much good. 14 00:00:38,240 --> 00:00:40,279 Speaker 2: News to share, such a good problem to have. 15 00:00:40,520 --> 00:00:43,040 Speaker 1: Why don't we start with what I think was the 16 00:00:43,240 --> 00:00:44,159 Speaker 1: good news story of the. 17 00:00:44,080 --> 00:00:47,680 Speaker 2: Work, like absolute stand out. It is, of course, the 18 00:00:47,960 --> 00:00:52,320 Speaker 2: safe discovery of twenty three year old Hardy Nazari, now 19 00:00:52,680 --> 00:00:56,440 Speaker 2: Hardi Nazari. If you haven't been watching the news this week. 20 00:00:56,760 --> 00:01:00,440 Speaker 2: He went missing on Boxing days. So he and his 21 00:01:00,560 --> 00:01:04,720 Speaker 2: mates were hiking in and around Kosiosco National Park in 22 00:01:04,840 --> 00:01:08,200 Speaker 2: New South Wales and he split off to take some 23 00:01:08,360 --> 00:01:11,800 Speaker 2: photos and was then meant to meet the group at 24 00:01:11,840 --> 00:01:15,000 Speaker 2: a camping ground. He failed to show up, and what 25 00:01:15,160 --> 00:01:20,280 Speaker 2: followed was thirteen very long, very scary days where over 26 00:01:20,440 --> 00:01:23,960 Speaker 2: three hundred people were sent out to look for and 27 00:01:24,120 --> 00:01:28,000 Speaker 2: hopefully find Hardi Nazari. I think the reason that this 28 00:01:28,040 --> 00:01:30,280 Speaker 2: story ended up being such a good news story is 29 00:01:30,319 --> 00:01:33,920 Speaker 2: that very rarely, after the passage of time has been 30 00:01:34,000 --> 00:01:37,039 Speaker 2: that long, do you find somebody, let alone in good 31 00:01:37,080 --> 00:01:41,600 Speaker 2: health alas that is what happened. Hardi Nazari was found 32 00:01:41,680 --> 00:01:45,479 Speaker 2: by other hikers on Wednesday, and New South Wales police 33 00:01:45,480 --> 00:01:48,640 Speaker 2: confirmed that the student had been found in good health. 34 00:01:49,200 --> 00:01:51,720 Speaker 2: Here's a clip of the ABC announcing the discovery. 35 00:01:52,000 --> 00:01:54,240 Speaker 3: Breaking news and a twenty three year old man missing 36 00:01:54,240 --> 00:01:57,960 Speaker 3: in the New South Wales Snowy Mountain since Boxing Day. Wow, 37 00:01:58,760 --> 00:02:01,320 Speaker 3: so cool to bring the US this news has been 38 00:02:01,440 --> 00:02:02,400 Speaker 3: found alive. 39 00:02:02,800 --> 00:02:06,200 Speaker 2: I do think that that clip highlights why everyone who 40 00:02:06,360 --> 00:02:10,040 Speaker 2: is in the business of news was so excited, because again, 41 00:02:10,240 --> 00:02:12,320 Speaker 2: it is just so rare to have a happy ending 42 00:02:12,320 --> 00:02:13,200 Speaker 2: to a story like this. 43 00:02:13,639 --> 00:02:17,160 Speaker 1: And I wasn't really following the search too closely in 44 00:02:17,200 --> 00:02:20,320 Speaker 1: those thirteen days, but it sounded like authorities were somewhat 45 00:02:20,400 --> 00:02:22,320 Speaker 1: encouraged by the fact that they were finding these little 46 00:02:22,320 --> 00:02:23,560 Speaker 1: clues along the way. 47 00:02:23,639 --> 00:02:27,320 Speaker 2: The remnants of a campfire, some Musli bars, some musley bars, 48 00:02:27,320 --> 00:02:29,560 Speaker 2: which it turns out was a thing that sustained Hoddy. 49 00:02:29,680 --> 00:02:34,320 Speaker 2: He ate two musli bars and foraged berries for two weeks. 50 00:02:34,560 --> 00:02:35,200 Speaker 2: That's it. 51 00:02:35,200 --> 00:02:37,799 Speaker 1: It was amazing seeing the reaction also of his friends 52 00:02:38,320 --> 00:02:42,160 Speaker 1: after he was so beautiful, beautiful. They were speechless and shocked, 53 00:02:42,280 --> 00:02:45,640 Speaker 1: and I'm sure there was a level of surprise completely. 54 00:02:46,160 --> 00:02:50,480 Speaker 2: Yeah, and look, obviously Huddy has been through quite the ordeal, 55 00:02:50,639 --> 00:02:53,079 Speaker 2: so I think the media is being very careful about 56 00:02:53,160 --> 00:02:55,920 Speaker 2: giving him space, and that's what he has requested. But 57 00:02:56,000 --> 00:02:59,440 Speaker 2: he did thank emergency service crews for their tireless work 58 00:02:59,480 --> 00:03:03,120 Speaker 2: searching for thirteen days in tough conditions, and he also 59 00:03:03,200 --> 00:03:05,680 Speaker 2: thanked the public, his friends, and his family for their 60 00:03:05,680 --> 00:03:06,280 Speaker 2: well wishers. 61 00:03:06,600 --> 00:03:09,200 Speaker 1: It led to a quite animated discussion in the TDA 62 00:03:09,280 --> 00:03:11,480 Speaker 1: office about how long we all think we could survive? 63 00:03:11,680 --> 00:03:12,120 Speaker 2: One hour? 64 00:03:12,320 --> 00:03:15,120 Speaker 1: Yeah, flats about that and two musley bars I can 65 00:03:15,160 --> 00:03:17,640 Speaker 1: go through in about six minutes. So Haddy has done 66 00:03:17,680 --> 00:03:20,840 Speaker 1: an incredible job and we hope that his recovery remains 67 00:03:20,919 --> 00:03:24,440 Speaker 1: on track. Now let's move to the world of tech. Yep, 68 00:03:24,560 --> 00:03:28,639 Speaker 1: And it's rare for AI to have a good news angle, Yeah, 69 00:03:28,680 --> 00:03:29,520 Speaker 1: but this time it does. 70 00:03:29,840 --> 00:03:34,320 Speaker 2: It does so researchers from Newcastle University have developed an 71 00:03:34,360 --> 00:03:38,040 Speaker 2: AI system and that AI system is able to predict 72 00:03:38,120 --> 00:03:42,680 Speaker 2: the trajectory of aggressive skin cancers. Obviously, here in Australia 73 00:03:42,760 --> 00:03:45,640 Speaker 2: we have a very big problem with skin cancer and 74 00:03:45,840 --> 00:03:48,520 Speaker 2: especially when it comes to young Australians, so I think 75 00:03:48,520 --> 00:03:51,760 Speaker 2: that this is very important good news. Now the technology 76 00:03:51,880 --> 00:03:55,440 Speaker 2: they've called deep Merkle can find out how severe certain 77 00:03:55,480 --> 00:03:58,200 Speaker 2: skin cancers are, such as and this is where the 78 00:03:58,280 --> 00:04:02,680 Speaker 2: name comes from, Merkles cell carcinoma. Now deep Merkle uses 79 00:04:02,720 --> 00:04:06,840 Speaker 2: personal and tumor characteristics to essentially just predict the results 80 00:04:06,880 --> 00:04:10,760 Speaker 2: of different treatments that are commonly used for MCC, so 81 00:04:10,800 --> 00:04:14,680 Speaker 2: that Merkle cell carcinoma and researchers think that this tech 82 00:04:14,800 --> 00:04:17,080 Speaker 2: could also be used for other types of aggressive skin 83 00:04:17,160 --> 00:04:20,560 Speaker 2: cancer to help inform decisions around which type of treatment 84 00:04:20,560 --> 00:04:24,599 Speaker 2: would be the most effective on different types of people. 85 00:04:25,120 --> 00:04:27,560 Speaker 2: The lead author of this is doctor Tom Andrew and 86 00:04:27,600 --> 00:04:30,400 Speaker 2: he said that the technology allows us to understand subtle 87 00:04:30,520 --> 00:04:33,280 Speaker 2: new patterns and trends in data, which means on an 88 00:04:33,279 --> 00:04:36,599 Speaker 2: individual level, we're able to provide more accurate predictions for 89 00:04:36,640 --> 00:04:37,400 Speaker 2: each patient. 90 00:04:37,680 --> 00:04:40,760 Speaker 1: It's really interesting watching the intersection of AI and health 91 00:04:40,800 --> 00:04:44,440 Speaker 1: and how different AI products seem to be intercepting medical 92 00:04:44,480 --> 00:04:47,360 Speaker 1: issues at various points. So this one is not necessarily 93 00:04:47,360 --> 00:04:49,560 Speaker 1: about the detection of skin cancer. And I've read some 94 00:04:49,600 --> 00:04:52,599 Speaker 1: stuff around different ways that even you know, photography on 95 00:04:52,640 --> 00:04:56,000 Speaker 1: your phone can start to identify whether something is of 96 00:04:56,240 --> 00:04:58,240 Speaker 1: concern you should go get it checked out. This is 97 00:04:58,240 --> 00:05:01,320 Speaker 1: coming in at the poster tech point then about how 98 00:05:01,360 --> 00:05:04,400 Speaker 1: to treat it. It's super interesting it is. Now let's 99 00:05:04,400 --> 00:05:08,160 Speaker 1: go overseas. I want to talk about Indonesia. 100 00:05:08,279 --> 00:05:12,000 Speaker 2: Yes, So in Indonesia, the government there has launched a 101 00:05:12,040 --> 00:05:15,120 Speaker 2: free meal program for school students and it's especially for 102 00:05:15,160 --> 00:05:18,920 Speaker 2: those who are in remote areas. Now, this was part 103 00:05:19,160 --> 00:05:21,840 Speaker 2: of an election promise and has now begun to be 104 00:05:22,040 --> 00:05:25,719 Speaker 2: rolled out. So it's called the Free Nutritious Meals Program, 105 00:05:25,760 --> 00:05:28,760 Speaker 2: and this week it launched at one hundred and ninety venues, 106 00:05:28,880 --> 00:05:31,920 Speaker 2: with each venue designed to produce thousands of portions every 107 00:05:32,000 --> 00:05:35,599 Speaker 2: day and to also empower local communities as workers to 108 00:05:35,640 --> 00:05:38,880 Speaker 2: work in those kitchens to then provide those meals for people. 109 00:05:39,080 --> 00:05:40,880 Speaker 1: What a huge effort. I mean, this is a country 110 00:05:40,880 --> 00:05:42,839 Speaker 1: of two hundred and seventy million plus. 111 00:05:42,880 --> 00:05:45,320 Speaker 2: Well, I mean there's an incredibly ambitious goal. So the 112 00:05:45,320 --> 00:05:48,679 Speaker 2: Indonesian government has aimed to feed nearly eighty three million 113 00:05:48,760 --> 00:05:52,320 Speaker 2: residents by twenty twenty nine with this program, and that's 114 00:05:52,360 --> 00:05:54,440 Speaker 2: part of a broader trend to try to tackle child 115 00:05:54,520 --> 00:05:57,760 Speaker 2: mail nutrition in the country. So there's a lofty ambition 116 00:05:57,839 --> 00:06:00,040 Speaker 2: there as to how this program will be rolled out. 117 00:06:00,279 --> 00:06:02,920 Speaker 2: There's billions of dollars being put into it. 118 00:06:03,000 --> 00:06:05,119 Speaker 1: But importantly, Zara is the food good. 119 00:06:05,480 --> 00:06:08,560 Speaker 2: We did get a testimony from a high school student 120 00:06:08,760 --> 00:06:11,040 Speaker 2: who spoke to media and said the food is delicious 121 00:06:11,040 --> 00:06:13,400 Speaker 2: and nutritious. Well, there you go, I mean it rhymes, 122 00:06:13,520 --> 00:06:14,680 Speaker 2: so what more could you want. 123 00:06:14,800 --> 00:06:17,239 Speaker 1: I've heard of some of these programs exist in other countries. 124 00:06:17,279 --> 00:06:18,919 Speaker 2: I think we've spoken about it in the pod, like 125 00:06:19,240 --> 00:06:22,160 Speaker 2: the specific areas in the US might be doing. 126 00:06:22,240 --> 00:06:25,960 Speaker 1: Yes, breakfast breakfast is often cited as kind of because 127 00:06:25,960 --> 00:06:28,360 Speaker 1: you can crack breakfast, you're setting kids up on a 128 00:06:28,400 --> 00:06:29,560 Speaker 1: much healthier trajectory. 129 00:06:29,680 --> 00:06:33,080 Speaker 2: Yeah, and the vice presidential picked for Kamala Harris tim 130 00:06:33,120 --> 00:06:36,359 Speaker 2: Woles that was something that he had implemented in Minnesota 131 00:06:36,400 --> 00:06:39,520 Speaker 2: across schools there. But I certainly haven't heard of it 132 00:06:39,680 --> 00:06:42,520 Speaker 2: on this scale. You know, as I said, they're aiming 133 00:06:42,560 --> 00:06:45,680 Speaker 2: to feed eighty three million people by twenty twenty nine, 134 00:06:45,680 --> 00:06:48,640 Speaker 2: which is not that far away. So definitely one to 135 00:06:48,720 --> 00:06:52,360 Speaker 2: keep an eye on. And a really really important and 136 00:06:52,520 --> 00:06:53,760 Speaker 2: significant story there. 137 00:06:54,320 --> 00:06:56,600 Speaker 1: And last story, Zara, This one's a funny one, I 138 00:06:56,600 --> 00:07:00,680 Speaker 1: think honestly, I think it's just to me this story. Yeah, 139 00:07:00,760 --> 00:07:03,320 Speaker 1: you're pretty bad at it. So there's a big fear 140 00:07:03,320 --> 00:07:06,400 Speaker 1: you've got, and it's now being recognized. 141 00:07:06,600 --> 00:07:11,160 Speaker 2: There's a name for it, institutional level telephobia telephobia. Hello, 142 00:07:11,400 --> 00:07:14,400 Speaker 2: dear listeners, if you have telephobia, let me know. If 143 00:07:14,440 --> 00:07:16,640 Speaker 2: you don't know what telephobia is, probably means you don't 144 00:07:16,640 --> 00:07:19,720 Speaker 2: have it. But it is the fear of making phone calls. 145 00:07:20,120 --> 00:07:22,120 Speaker 2: A bad fear to have when you run your own company. 146 00:07:22,480 --> 00:07:23,120 Speaker 1: Hey, well. 147 00:07:25,000 --> 00:07:29,320 Speaker 2: It is so. A you switch survey of two thousand 148 00:07:29,360 --> 00:07:32,840 Speaker 2: people found that nearly seventy percent of those aged eighteen 149 00:07:32,840 --> 00:07:35,760 Speaker 2: to thirty four prefer a text to a phone call, 150 00:07:35,880 --> 00:07:38,200 Speaker 2: and twenty three percent of the same age group said 151 00:07:38,240 --> 00:07:40,920 Speaker 2: they would never pick up calls. I am in that camp. 152 00:07:40,960 --> 00:07:43,320 Speaker 2: My phone is perpetually on do not disturb, do not 153 00:07:43,360 --> 00:07:44,760 Speaker 2: try call me. I will not answer. 154 00:07:44,920 --> 00:07:46,720 Speaker 1: Got to admit you haven't really gotten to the good 155 00:07:46,720 --> 00:07:47,200 Speaker 1: news past. 156 00:07:47,240 --> 00:07:48,480 Speaker 2: Sorry, So yes, why. 157 00:07:48,320 --> 00:07:49,120 Speaker 1: Are we talking about this? 158 00:07:49,240 --> 00:07:53,440 Speaker 2: Is that a program at Nottingham College is now offering 159 00:07:53,560 --> 00:07:58,400 Speaker 2: coaching sessions on phone etiquette and phone confidence for students 160 00:07:58,680 --> 00:08:01,960 Speaker 2: because they're saying that it's really important for job interviews 161 00:08:02,000 --> 00:08:05,400 Speaker 2: and for recruitment processes for these young people to feel 162 00:08:05,400 --> 00:08:09,200 Speaker 2: confident on the phone, and that they are perhaps undercutting 163 00:08:09,240 --> 00:08:11,720 Speaker 2: their potential by being scared of these phone calls, and 164 00:08:11,800 --> 00:08:15,520 Speaker 2: so this college is offering these sessions to build their confidence. 165 00:08:15,560 --> 00:08:17,280 Speaker 2: And I think that that's an excellent thing to do. 166 00:08:17,600 --> 00:08:21,240 Speaker 1: I'll get those details off Nottingham College and enroll you. 167 00:08:21,400 --> 00:08:22,920 Speaker 1: I think I could also jump in that one. 168 00:08:23,000 --> 00:08:26,200 Speaker 2: No, I think like I remember in my very first job, 169 00:08:26,280 --> 00:08:28,280 Speaker 2: I was required to do a lot of cold calls 170 00:08:28,440 --> 00:08:30,760 Speaker 2: and I would work up the courage for like a 171 00:08:30,760 --> 00:08:32,800 Speaker 2: good half an hour to make those calls. I wouldn't 172 00:08:32,800 --> 00:08:34,360 Speaker 2: be able to do it in the open plan office. 173 00:08:34,400 --> 00:08:36,560 Speaker 2: I'd have to walk outside to do them. Yeah, and 174 00:08:36,679 --> 00:08:40,120 Speaker 2: my boss thought that I was insane, But it was 175 00:08:40,200 --> 00:08:43,720 Speaker 2: genuinely a really uncomfortable thing that I have had to 176 00:08:43,800 --> 00:08:45,079 Speaker 2: work through and had to learn. 177 00:08:45,320 --> 00:08:46,880 Speaker 1: So what is it? What do you think makes young 178 00:08:46,880 --> 00:08:48,640 Speaker 1: people petrified of the phone. 179 00:08:48,320 --> 00:08:52,559 Speaker 2: That were conditioned to text. Interesting, like I grew up texting, 180 00:08:52,600 --> 00:08:54,640 Speaker 2: I didn't grow up. I mean, sure, I grew up 181 00:08:54,640 --> 00:08:56,840 Speaker 2: with the home phone, but I just am much more 182 00:08:56,840 --> 00:08:59,880 Speaker 2: accustomed to texting someone that I am to calling. 183 00:09:00,120 --> 00:09:02,400 Speaker 1: Why don't we start with voice notes first and then 184 00:09:02,400 --> 00:09:03,240 Speaker 1: we'll get you to the phone. 185 00:09:03,240 --> 00:09:05,240 Speaker 2: Well, I can listen to them on three X speeds. 186 00:09:05,320 --> 00:09:08,800 Speaker 2: It's excellent anyway, we digress. That is the good news 187 00:09:08,840 --> 00:09:10,560 Speaker 2: wrap of the week, and I think it's a pretty 188 00:09:10,600 --> 00:09:13,160 Speaker 2: good note to start twenty twenty five on. But Sam, 189 00:09:13,360 --> 00:09:16,080 Speaker 2: tell me what you're doing to set yourself up for 190 00:09:16,120 --> 00:09:18,360 Speaker 2: a good year God or a recommendation. 191 00:09:19,120 --> 00:09:22,000 Speaker 1: I think something that I'm going to do this year 192 00:09:22,080 --> 00:09:25,200 Speaker 1: to try and bring myself a bit of joy is 193 00:09:25,240 --> 00:09:27,760 Speaker 1: I used to be obsessed with finding new music, and 194 00:09:27,800 --> 00:09:29,360 Speaker 1: that's kind of died off a little bit in the 195 00:09:29,440 --> 00:09:31,280 Speaker 1: last couple of years, probably with a bit of an 196 00:09:31,280 --> 00:09:33,640 Speaker 1: increased workload. I'm going to bring that back. I'm going 197 00:09:33,679 --> 00:09:36,600 Speaker 1: to find new songs rather than listen to the same 198 00:09:36,679 --> 00:09:38,959 Speaker 1: kind of two hundred and fifty songs that are on repeat. 199 00:09:38,760 --> 00:09:39,199 Speaker 3: Quite a lot. 200 00:09:39,320 --> 00:09:41,520 Speaker 2: You do have a tendency to listen to elevator music, 201 00:09:41,640 --> 00:09:43,840 Speaker 2: so that's good news for everyone. Who's to listen to 202 00:09:43,920 --> 00:09:44,760 Speaker 2: music in the office. 203 00:09:44,840 --> 00:09:47,760 Speaker 1: Some call it elevator music, some call it just Olivia 204 00:09:47,800 --> 00:09:50,959 Speaker 1: dean Zara. Do you have anything that's going to keep 205 00:09:50,960 --> 00:09:52,160 Speaker 1: you happy in twenty twenty five? 206 00:09:52,600 --> 00:09:55,800 Speaker 2: I do so. I wrote actually about it in the 207 00:09:55,960 --> 00:09:59,040 Speaker 2: final newsletter of twenty twenty four. But the thing that 208 00:09:59,120 --> 00:10:01,800 Speaker 2: is setting me up for a good year is investing 209 00:10:01,840 --> 00:10:04,280 Speaker 2: in a good alarm clock. Okay, so I am someone 210 00:10:04,360 --> 00:10:07,240 Speaker 2: that checks my phone incessantly at all hours of the 211 00:10:07,320 --> 00:10:11,120 Speaker 2: day and night, and my way of combating that and 212 00:10:11,160 --> 00:10:14,400 Speaker 2: creating better sleep hygiene practices has been to invest in 213 00:10:14,440 --> 00:10:17,280 Speaker 2: a sunrise clock. So it's an alarm clock that wakes 214 00:10:17,280 --> 00:10:20,200 Speaker 2: you up with light and birds chirping, rather than a 215 00:10:20,240 --> 00:10:23,160 Speaker 2: mobile phone that I then proceed to scroll endlessly on. 216 00:10:23,400 --> 00:10:26,840 Speaker 2: And so far, so good. Couldn't recommend more. I just 217 00:10:26,880 --> 00:10:29,240 Speaker 2: bought a really cheap one off Amazon, but you know 218 00:10:29,280 --> 00:10:31,719 Speaker 2: they range in price, and I just think that it's 219 00:10:31,720 --> 00:10:33,480 Speaker 2: a really nice way to start the morning and it 220 00:10:33,520 --> 00:10:34,480 Speaker 2: brings me a lot of joy. 221 00:10:34,760 --> 00:10:39,400 Speaker 1: New music, sunshine clocks, free meals, and incredible survival stories. 222 00:10:39,640 --> 00:10:42,320 Speaker 1: Bit of AI medical innovation in there as well. What 223 00:10:42,440 --> 00:10:45,000 Speaker 1: a good note to end on. That's all we've got 224 00:10:45,000 --> 00:10:47,400 Speaker 1: time for on today's edition of the Good News pot 225 00:10:47,480 --> 00:10:48,960 Speaker 1: from the Daily Ours. We're going to be back on 226 00:10:49,000 --> 00:10:53,120 Speaker 1: Monday morning with your regular news explainer. Until then, have 227 00:10:53,200 --> 00:10:58,360 Speaker 1: a wonderful weekend. My name is Lily Maddon and I'm 228 00:10:58,360 --> 00:11:02,839 Speaker 1: a proud Arunda Bungelung Cargoton woman from Gadighl Country. The 229 00:11:02,920 --> 00:11:06,040 Speaker 1: Daily oz acknowledges that this podcast is recorded on the 230 00:11:06,080 --> 00:11:09,000 Speaker 1: lands of the Gadighl people and pays respect to all. 231 00:11:08,920 --> 00:11:11,200 Speaker 2: Aboriginal and Torrestrate island and nations. 232 00:11:11,520 --> 00:11:14,440 Speaker 1: We pay our respects to the first peoples of these countries, 233 00:11:14,559 --> 00:11:15,760 Speaker 1: both past and present,