All right. Well, hi, everybody. Happy Wednesday. My name is Valerie Sloan. I work at the National Center for Atmospheric Research. My background is in Arctic and Alpine Glacier history. And I work in more like career development now at higher education, supporting people and preparing for grad school and for jobs and that kind of thing. And my co-presenter is Rose, who I'll let you introduce yourself. Hi, everyone. My name is Rose Santana. I'm a graduate student at the University of South Florida in St. Petersburg. And I study biological oceanography. So yeah. Yeah, thanks. And Rose, she has worked with me on this for the last year and this year. And she is an awesome YouTuber and video maker and things like that with Black and Marine Sciences BIMS. OK, so before we go to the next slide, I just wanted to say two things. One is welcome. And I hope that it's going well. I know this is an intense kind of program to do. And so you can give yourselves a pat on the back for getting this far and working so hard. So congratulations. And give yourself some credit for that. OK, and then what we're going to just do first, we're going to talk about abstracts and then about slides in particular. But before that, I want to do a little bit of just introducing where I live. So Rose, if you could go to the next slide. So Boulder is in Colorado. Just real quick also, if you guys could let us know if this is your first RU or if you've done an RU before, that'd be great. You could let us know in the chat. Cool. Mm-hmm. So this is a picture of the Boulder area on the right. And on the left is the place where I'm actually right now. It's an NCAR lab called National Center for Atmospheric Research. And so people come here, it's beautiful. We have trails. It's pretty sunny, this kind of thing. But it's also got this sort of dark history that people don't talk about. But it's coming out of it. So click on the slide again, please. So first of all, people, you'll see this. This is for real. I got these off the web yesterday. It's like Boulder, Colorado is the number one best place to live. Is it a good place to go to college? Yes, it is. It's the happiest city in America. And it's like, well, yeah, it's also rich and it's really expensive. It's not the best college town in America if you don't have a lot of money. So it's definitely a sort of privileged kind of place. Next slide, please. So part of the history of this land is that around 1850, just a quick history here, silver and gold were discovered in the area. And European settlers came into the Boulder area and moved the people from the Arapaho, Cheyenne, and Mute nations who were living in this region moved away so that the settlers could build on the land right next to the canyon and Boulder Canyon. That map on the left shows all the different tribes and nations in North America. And it's really staggering how many there are. And there's overlap as well. So I just want to first of all acknowledge that this land that I live on and work on was the land of people who didn't give it up willingly. And the next slide shows, I mean, the next click will show a picture of if you can click on it. So this shows sort of 100 years ago in Boulder and black people initially were not allowed to live in Boulder. Like when they started settling Boulder, the Europeans, they made lots cost $1,000 each. And black people were not allowed to live in Boulder and they were also not allowed to have very good jobs. And so when things happened like the big flood, then that impacted them more than others. Click again, please. And again. So there's this film I just want to recommend. It's on PBS, Public Broadcasting Station. And it's recent. And it's a one hour or less documentary about Boulder and the history and how people here perceive it as this cool, non-racist place. But the history is just rich with racism. And it's a really good documentary. So just want to and also you can check out for where you live or study. Look up things about like what's the history and what are the racist events and issues that have come up. And it's kind of astonishing what you learn. OK, so on to the abstract. So can you click again, please Rose? Thanks for all of your your puts in the chat. It looks like there's so many people. OK, so if you could go back one click, please. So what so in the chat or if you want to un-mic, just explain to us all like what you think that an abstract of to be of or in a scientific paper does or is and what purpose it serves. But mostly what it is, how would you describe it? It should be a summary of the research giving like very not not in depth as much as you want to save that for your near the body of your research mostly. Well, I should give a summary of which just what your research enthous. Yes, right, it's a short summary. And in the chat, we have thank you for speaking up. Yeah, it's a summary explains, you know, it's really succinct. It's super succinct. So it can be basically like eight sentences long, for example. Yeah, so I definitely feel like that it should be like a hook to kind of just touch base on what you're doing and kind of get someone interested in wanting to read more and learn more about your project. But you don't want to like over explain. You want to leave some room for your talk, but you want to. Yeah, right, you're going to be able to be interested. Exactly, it's the it's really the only thing that mostly gets read by it by the vast majority of people. Partly because some some papers are not all that accessible, but also it's like people figure out do I want to read it? And as Ethan says, make it compelling, like have a hook. It's like something that makes you want to find out what more about it. So it really it really is an it has an important place. I think often we just think about like people at universities, professors and so on.  But it's actually super important if you're if your title is is really engaging versus not, it's like people will actually come in here, your talk or see your poster. Click on the next one, Rose. Yeah, so we've covered it. Ethan, do you want to add anything about what could make it compelling? Yeah, of course, I can try. Is my audio coming through? It is. OK. I mean, I'm no I'm no expert on this. I just worked on my first abstract and I just did my first scientific proposal, so I'm very, very new at all this. But I kind of just wanted to input that I think everyone can kind of agree that like when you're doing like literature review or like looking through scientific papers that. I mean, we're all skimming like we we have to skim. There's so much stuff out there having an important title and like the quickly compelling abstract is pretty much the only thing that will draw me into reading someone's papers. And I mean, I feel like it's got to be one of the most important steps. Yeah, yeah, I don't have like any great pointers. I'm actually still having my first one reviewed and I'm super excited to hear about it. But yeah, I just I know from from my perspective, like what like being a person that consumes them, it feels really, really important, you know. Yeah, right. I mean, it's it's true. It really is. And then as Chris wrote, it's a summary or synopsis of what the paper discusses. So it's super succinct. So let's go to the next slide. So this is kind of the formula for an abstract. First, you kind of give some of the general background and situation of roughly, you know, the topic that you're looking at. And then next, you go into a little more detail about something specific, more specific and something that's sort of like a question that's there. So it could be like, we know that that in Brazil, that the that the incidence of rabies in cities looks like it's maybe closer to for cities, proximity to the jungle from squirrels. And but we don't really know if that's true. And so then in this study, we test or we identify or we investigate or show X, Y and Z. We look at we look at the data from the rabies, the currencies in Brazil and their distances from the jungles where the squirrels are, where they primarily get the rabies. And then the basically hardly say anything about how I mean, you can sort of say, well, we measured this and that, but it doesn't really, it's not a lot. And then results with some concrete values, ideally, and what this could imply. Now, that's not to say everybody does this at all, like you'll read loads of abstracts where people don't actually give the results. And at conferences, that's very common, because we're writing them so far ahead of the conference that that's what happens. Next slide, please. So here's just like you to take a look at this one, it's, it's a little mind or your eyes probably blur over looking at it, but you can sort of see the pattern that was itemized in the last slide, first the general background, and then specific background. What's the question? What what's what's the gap in the knowledge? And then, you know, here we report. The white is the paragraph of data. The value is the concrete evidence. And then the pink at the bottom is sort of like the meaning of the results. This kind of outline, by the way, applies to in science and the physical sciences, it applies to most types of communication, except for when you're getting into social media or journalism and that kind of thing. But in science talks and papers and posters, you generally follow this kind of order. So, Rose, did you want to add just add anything if you have any questions? Otherwise, you can go to the next slide.  So don't like freak out if like your first abstract isn't good. My first abstract was absolute garbage. And it was just a learning thing was learning what works for me, what works like what is mostly expected and just kind of making it your own. Yeah, good point. Next slide. So here's another example. So in recent years, high profile fatalities involving school age pedestrians crossing the street at designated crosswalks have elevated the issue of pedestrian safety, especially excuse me with respect to highly vulnerable pedestrians like children. While section 136 one of the highway traffic act clearly outlines the requirement to stop at post and stop signs, little is known about the average driver's propensity or tendency to comply with this law. So they've set the broader context in green, a more specific context in blue, and the question more or less in purple. Next is this study gained insight into this question by observing motorists as they approached a suburban stop sign and then coding their behavior. That just means like recording it into one of three categories, full stop, rolling stop, and slow and go. And I don't know about you, but I'm guilty of the rolling stop slow and good. Okay, now in red, the study's findings suggest that the majority of drivers do not comply with the requirement to stop at stop signs with more than one and four drivers almost completely disregarding the stop sign. Well, that's worrying. These findings suggest a need to solicit greater compliance rates among Ontario, that's in Canada, where I'm from, drivers with respect to section 136 of the Highway Traffic Act. So that this is kind of a nice clean example where you've got those pieces are really clear. Okay, so let's go to an example where I want your help analyzing it. So next slide, please. So this is this is a long one. And it's an area of like geomorphology and sediments and lakes and that kind of thing. So take a look at it and see if you can identify the different, the first section, the broader context. And then if you think that if you can find the next one, which is the more specific context with the question, a lot of most abstracts are longer like this. Medical abstracts are actually really pretty good. They follow it really well. So what do you think we're a rule of thumb Val, is it like usually 250 words for abstracts? I think it's about 150 to two, but sometimes 300. Yeah, good point. So can you offer up what might be the, the, you know, context setting sentence or sentences, where would you, where would you draw a line between that and say more specific information or question? And you can either put the chat or you can unmute. It's not as clear cut as it as the last one. There we go. First two sentences. Oh, there we go. Thank you for chiming in. So yes, everything before Glacier National Park was very, was background. The first two sentences. Yeah, so also before Glacier National Park. General Alpine Basins versus Glacier National Park specifically. After that, it gets more specific. Yes, I agree. Okay, so then we go to the sentence Glacier National Park, Montana has experienced dramatic geomorphic and environmental change since the end of the peak of the last continental glaciation, which is about 20,000 years ago, when almost all of Canada was covered by a giant ice sheet and part of the northern parts of the US, as well as documented change prior to the founding of the park in 1910. So as somebody point out, this is more detailed. Okay, so now in the next sentence to better understand sediment, transport and records of environmental change in Glacier National Park from the late Holocene, which is recent and geological to the present, we collected sediment cores from the floor of Fisher Cap Lake and Swift Kern Valley. I would argue that there are two sort of types of information in that sentence. What what would you say if you were to split it into two? What would the first half prior to the comma be? And the second half, more or less, it's not super clearly identifiable. But I'm just wondering if you can see that to better understand sediment transport, blah, blah, blah, comma, we collected sediment cores, right? Okay. Uh huh. Yes. And yes, exactly. So the knowledge gap, so to better understand the sediment transport and records. So in other words, we don't know very much about it. This is a sort of an interesting thing that could provide us with good information. They haven't really explained why this is important. But trust them for the moment. It's basically part of understanding climate history. And then as you say, the methods, we collected sediment cores from blah, blah, blah. So yes, and you could you could sort of say that the first half is sort of like the question, right, as well. Yes, so somebody did write that Matthew. Thank you. Cool. Okay, so good. Now, in addition, we use ground penetrating radar to explore subsurface sedimentary structures of Fisher Cat Lake, which is only one meter deep. Approximately, there is below 65 centimeters below, there is a dense gravel layer. And that represents maybe a desiccation means dried out. So the lake was fine grained sediment is thickest here and so on. So then the last sentence changes in sediment sources and transport vary between lakes and overtime with the big size, with the size of Alpine glaciers like bathymetry, which is the depths and run off variability, driving sediment transport and storage dynamics, centennial to millennial timescales. And I see that somebody pointed out that the last sentence to cut that the last sentence is is really the, you know, the result thesis that they're coming out with. What would you call the part between, in addition, down to sedimentary sediment delivery? What section is that? I guess it's also partly methods, right, the ground penetrating radar and then approximately 65 centimeters. Yeah, it's the results, right, with the concrete values. Cool. Okay, very good. And you know, there's like science community just uses so much jargon, it's just astonishing. I mean, there's all kinds of jargon in here. Next slide, please. Well, let's do the same again for this one. Are they identifying the different sections for this one as well? Yeah, sorry. So yes, you can maybe identify the first, you know, the first two sections like that you would call the general background, maybe more specific background and the question. So please go ahead and either type it or, or a mic and unmute rather. Michael, were you going to speak up? Yes, Ruth. Slides actually will give you the link before the day is done. So where would we put the, okay, so methods to results? Is that this? Are you talking Elizabeth, are you talking about this one or the previous one? No, that was for the previous one. Okay. Yes. So where would you say that it goes from being general background to more specific background? So you would say everything up to 2018 is general information. So I think that's more or less true. What do other people think? Yeah, more specific. Actually, it's, it sort of moves into the methods here. You know, you've got these groups are meeting. This interdisciplinary group came together. And that's actually sort of methods. Now, let's see the first two sentences. So the first three lines is sentence one. And then the next two lines is sentence two. So the first one is very general. The second one is a little bit more context, right, right, Sarah. And then the third one is like focusing, zooming in more on the problem, which is that, well, actually, sentence two does to that it's the rice abundance has been declining. And that's that's a problem being mentioned. And then the third sentence, stewardship indigenous voices have not been adequately involved in the decision making. So that's another problem, right, being articulated. So in 2018, this group from the university came together with natural resource managers from tribes and intertribal organizations to study manuman with its socio environmental context. The collaborative that formed was given the Ojibwe name. This is I think it's a I hope I can say it nicely. Kawe, Gida, Nana, Gada, Wen, Damin, manuman, or first, we must consider manuman in Ojibwe. Okay, so let's see. So that that sort of ties in a bit with like the purpose doesn't purpose as well as like how what they're doing. Is that does that do you agree with that or not? That is that let's see, from 2018, the next two sentences articulate sort of the purpose and then and then what they're doing the methods. Okay, and let's see. And one of the products or results is if you look at additionally, the non tribal manuman harvesters and researchers and students on our team, we are understanding a wide diversity of perspectives and relationships with manunan. So that's that's definitely a result. And then we will share key questions, challenges and insights. Going forward kind of thing. Okay, cool. Okay, next slide, please. Okay, so what we're going to do is give you a few minutes to just catch out your own abstract, and it just just doesn't have to be at all like don't worry about words nothing at or making it read well. This is just for you. You don't have to share it and the idea is to just kind of get you to think about your own project, trying to copy with them. Hold on. Put it in there but you can simply you can read you can you read this okay. So now it's in the chat as well.  And you can mute yourself if you like, you're not already. And take maybe, you know, seven to 10 minutes or something to try and sketch out some information here. And like she said, it's just for you guys. But if any of you wants to send it to us, you know, in private to get some feedback, you're more than welcome to do so as well. And through the private chat, whatever it's called, by the way, you don't have to follow this exactly. This is kind of a recipe or a guideline. You aren't sure what to put in some of these later categories, you can feel free to leave them blank, or you can hypothesize what you might find out. Make something up. It's fine. You can just try and sketch it out. Sometimes if a project is not going well, and then you kind of have to shift your focus on to something else, hopefully that isn't happening, but it does sometimes, like focusing on methodology, for example. And an abstract will be needed if you plan to attend a conference and present a paper or a poster. So you would write an abstract as part of your submitting to present. Are there any questions or comments? How is it going? I have a question. So I guess I assume, I'll open my video to you. I assume that in an abstract, it's not like writing the introduction to an essay, it's not like we want to conceal anything to say for the conclusion. Is that assumption correct? You know, I know that when I read abstracts, and I do it a lot with medical ones, because I find them interesting, is that in general, they do provide the outcome and the results. And then I think, okay, that's, that's really interesting. I'm going to read this. And when they don't, I know I'm really annoyed, like, oh, come on, you want me to read this whole paper so I can find out the answer. However, yeah, sorry, I just got distracted. But when it's, when it's a proposal for conference, there's I think there's a fair bit of forgiveness for people writing sort of a promissory abstract, like we, you know, we are doing such and such, and we will be doing such and such. So because it's like right now, like here, I'm asking you to write an abstract when you're not finished with your research. So I think it's good if you can. If you can't, then you say, you know, it looks like such and such is happening, but we have to do more to figure that out. Does that, does that answer your question? Yeah, that makes sense. Thank you. Yeah, good question. Julia, yeah, you know, no worries at all about not being able to fill out some stuff. And, you know, like I said, you can make up stuff if you want. And Sebastian had a great question of how to decide how technical to keep your terminology. For example, kind of audience, should you be writing to? And I mean, Val, feel free to correct me here.  It fully depends where you're submitting it to. And you kind of need to cater it specifically to that. Yeah, that's exactly right. In general, you know, abstracts don't go to it's not like it's going to a high school or public. In general, it's more it's a narrower audience so it can be somewhat technical. Personally, I like to see like when I'm reading an abstract of a talk that's being given where I work, the less jargon it is, the more I'm drawn to it as a non specialist. But it's pretty much fine to be pretty, pretty jargony here. What is kind of missing from this whole thing with recipe in my opinion is, is like why it's sort of like why is this important, which, as you get deeper into research of your own project and topic, it seems obvious why it's important, or at least that little particular thing is important. But, you know, if you're explaining it to your neighbor, your grandmother or somebody, you know, why is this important? You have to sort of step back and say, Well, we're trying overall to solve such and such a question. I think, you know, Julie, I'd say it's, it's probably slightly more in a journal than a conference, but not necessarily a lot more. Okay, so can you put up thumbs or something if you are good or you or something like if you need more time, you can do a thumbs down. Thanks, Sebastian. So I don't see I can't see what's happening. Oh, eight, nine ups. Oh, there they are. Okay. So let's, let's do this. Let's take a five minute break, four minute break and be back at 145. You need to get a drink or anything. And then when you're back, just turn on your camera, at least briefly so that we know you're back. Okay, so take a few minutes break. Stretching all that. Hey, well, before we move on to the talks, do you have any observations about the abstract that writing it or what you think of it as a, as a thing as a structure or anything like that? Do you feel like you got a start on your decent start on your abstract? You're going to walk away with at least a rough, a rough draft. Yay. Let us know what the easiest or the hardest part about writing an abstract is for you, like, for you personally, like I know for me, I always struggle with how much of the results I should actually include. Well, that's good, Sebastian. And I'm glad Jaden wrote the neck. It's helping. Yeah, I should probably use this when I'm writing my next abstract. That's Gormula. Yeah, it does any whittling down, doesn't it? Sebastian start and then you make it smaller and smaller. It is really hard to be concise, super hard. It's actually, I don't know if they still do this in courses, but pricey writing where you have to condense some kind of writing is really a good activity to get skill to get good at. All right. So would you say this, just for future reference, excuse me. Well, I'm just gonna assume maybe that it's from the answers we got a few that this this is a worthwhile activity or exercise. Yeah, give it a thumbs up or a thumbs down and we don't see your your name or anything. But if you think this was worthwhile. Okay, let's move on to the next slide, please. Okay, so how to give a good talk and avoid giving a bad one. All right. Next slide, please. So what are some situations when it might be important that you are able to give a good presentation? Feel free to speak or write. Not that it's ever important to give a bad one, but when do you particularly want to give a good presentation? Yeah, conferences, doctoral defense, job interview, job interview for sure, or on the job, maybe if you're getting one, you know, to your for your work. Yep, those are definitely proposals. Yeah, project proposals. Yeah, these are excellent. Class presentations. Yeah, lectures, right. So I think after this present after this workshop today, what you're going to notice I find as I go to talks, lectures or to conferences, I'm like, Oh, my God, they're doing everything wrong on their slide. Okay, next slide, please. Okay, so this is probably a familiar scene, you know, you're in the auditorium with the university, and some professors got the slide up with this tiny print.  And it's not very engaging. And it's like, Okay, he really wants me to pay attention to that highlighted bit. And it's just it's tough, right? It's like, no wonder the phone is appealing. Next slide, please. So actually, let's skip this one for now. And we'll go back to this. So let's skip this. So one of the things that we'll get to in a minute, but is that research has found about in the 1980s that people can't listen and read at the same time, because it uses the same part of the brain, they can listen and look at images. But listening and reading together doesn't work very well, our brains get overloaded. And that's part of why it's no fun when we get slides that have tons of text on it. The way that people learn the best point into research is by listening and having images, whether that's maps, photos, graphs, that kind of thing. Of course, if you don't have good, you know, auditory processing skills, it's different. Okay, so next slide, please. Okay, so I'd like you to think about tech slides that you see in classes, or talks. And sorry, and see, what do you what do you what do you think about this? Or what are the problems with this particular slide? If it's a slide, it may have been a poster, but let's presume it's let's just assume it's a slide, or maybe both. And David, we'll come back to your question. So what do you think of this slide? Too much info to process? Yeah, too, too much to understand. Too busy. Real busy. Yeah, busy. Yep. Too many words. Yep. It is. It's probably too small for part of it. Pardon? The text for part of it will probably be too small. If it was on a projector. Oh, right. That's a good point. Too small to read. Yeah. And too many different sections pulling focus away from each other. Exactly. Yeah, it's like, where do I look? And, you know, I don't know about you, but I can't read what's on the right hand graph. And the text is pretty tiny. Yeah, so next slide, please. And not colorblind friendly, right? It has like orange and green. Okay, so this is really the big mistake. So I just want to tell you a story about this fellow he gentleman he died a few years ago, but there's a video of him giving a talk about how to give a good talk. And so I guess this is his area of expertise. And he is sitting in a cafe. And somebody comes up to him and recognizes him and says, Oh, Professor, I'm, I'm going to Europe on Wednesday to present a talk. And I was wondering if you could look at my slides and give me some feedback. And then this fellow the professor, he says, Oh, sure, I'd be happy to. You have too many. And there are too many words on them. So he hadn't even seen it, but he could say, you have too many slides, and you have too many words on the slides. So people think we sort of think that we have to put all the words up here, because now we can help us remember what to say, or if people didn't hear me, they can read it, that kind of thing. But it's just not really great for the brain. You could click on, yeah, let's click on another one too, Rose, I think you're a couple of, yeah. So yeah, this is another, I mean, this is a, what's the big problem here with these graphs? Similar to before, but yeah, too small to read, can you read the axes? Only a little bit on that top right one, right? Yeah, illegible and not explained, right? I mean, you could explain it verbally, but it's pretty hard to, you'd have to really be clear about explaining the axes and things. Yeah, kind of intense. And we know sometimes we try to do it because it's like, well, we only want to have 10 slides and it's like, well, let's cram all this stuff in there. Next slide, please. Oh, hold on. So if you go back and see the top right one, which is too tiny, if you go on the next slide, it's bigger. And it's a little blurry, but you can actually read the axes. So it's year along the bottom, and heat content along the side of y axis. And so this is the global ocean heat content in the top 2000 meters of the ocean probably combined, figured out through both data and modeling. And you can see that there's been a large rise. This is in jewels. So I'm not that familiar with how that translates into other things. But anyway, you get the idea, it's gone up a lot in this time, the heat content of the ocean. Next please. So there's an approach that that we want to introduce to you today that is called the assertion evidence approach. And this approach asks for you to build your talks messages, not topics. And so in this approach, you support those messages with visual evidence, not bulletin lists. This is the website, you can just look up assertion evidence slides. And the fellow's name is Michael Ali, with a pen, pen state. And Rose, do you want to switch to that video video that we can watch? It's about five, it's less than five minutes long. And we can't hear it. I don't know. Can you not hear it? I couldn't hear it. I don't know about others. version of this approach is to build your talks on messages, not topics. Most engineers and scientists, unfortunately, follow PowerPoints defaults for the headline and build their talks on topic phrases. Two problems arise from that choice. First, the topic phrase does not focus the speaker on the most important details of the work. Second, members of the audience are not sure what to grab on to should they lose track of the speaker. As an example, for a slide on the effect of using a green roof on an urban building, most presenters would follow PowerPoints defaults and write a headline such as effective green roofs. Then those presenters would create a bulleted list of all the messages that they wanted to say about this topic. If room still existed on the slide, those engineers and scientists would add visual evidence. The result would be a cluttered slide with too many words for the audience to comprehend. A better way would be to begin the slide, not with a phrase, but with an assertion, namely a succinct sentence that states the takeaway message of the slide. Many presenters who use the assertion evidence approach actually draft those assertions on paper or posted notes away from the computer. Then once they have their messages ordered in the way that they want for the talk, they go to the computer to create a slide for each message. Notice that once the speaker knows what the assertion or main takeaway is for each slide, the speaker is more focused in selecting support for that assertion. So another question that you might have is why should we choose green roofs over any other method? Well, as we already discovered, urban heat islands make cities have higher temperatures in the surrounding rural areas. And these images show really great representation of that. So take a look at the picture on your left. That's showing Chicago City Hall with the green roof. And then next to it is a building with a conventional rooftop. Now take a look at the picture on your right. This is showing the drastic difference between the temperatures and the service temperatures of these two surfaces. We can see the conventional rooftop is reaching temperatures of 150 degrees Fahrenheit, whereas the green roof is only reaching temperatures about 70 to 80 degrees. So this is a big difference. And the green roof not only has a cooler surface temperature, but it also has a cooler air around it as well as inside the building. Another benefit to greeners is actually the cost. And although greeners have a higher upfront cost, that cost is then offset by the lower energy bills in the future. Studies have shown that on average for 21,000 square foot roof, you can save about $200,000 US dollars over the lifetime of that greener. Notice how the speaker folded transitions, secondary assertions, and background details into the spoken words of the talk put another way. For the one sentence written, there were seven to 10 sentences spoken. The result was that the audience was not burdened with having to read too much text. And the speaker built credibility and projected confidence from owning so much of the information. Now, after watching that scene, you might be thinking that you understood that scene, but never read the sentence headline. What we would say would be fantastic. The speaker was on her game as a presenter, and you were on your game as the listener. However, at a scientific conference or in a technical meeting, if an audience member becomes distracted or tired, that sentence headline is a safety rope that helps the audience member stay with the speaker. Although the audience member will not understand everything from the scene, she or he will know the main takeaway, and then can stay with the talk. Thank you, Rose. And they have several different videos with excuse me, examples. Well, people talking about this method and also using it at this assertion evidence.com that you see at the bottom here. So this is so in this slide, like I'm modeling what they're doing by saying make a statement in the heading to convey the take home message of the slide. And then in the example slide, they have fillets, fillets reduce leading edge vertices in nature and in engineering. Fill it on a dorsal fin of a shark, fill it on a sea wolf submarine. And so excuse me, then as a speaker, you can talk about the details of this and what how it happens. Next slide, please. So here's this is this is actually from the Penn State group and website. So bullets are not memorable because bullets do not show the connections and they also do not convey anything quickly. So you check out these it's like accelerometer outputs and analog voltage. And then hardware converts analog signal to digital. And then you know, in fact, you don't even know that there's an event. But if you go to the next slide, that it's actually put into a figure. And so these are basically that's these are the same points these little white text lines are actually the bullet points from the previous slide. However, with this sort of math of what's happening, you get to see, oh, okay, an accelerometer puts out output, and then the hardware converts it and along to digital. And then the computer samples number of points, and then it's exported exported the data is exported to pop. So you get a feel for like what's going on. So if you ever have a bulleted list, see if you can turn it into something like this, and have a few, you know, figures, so that you can avoid just a plain old blood list that kind of puts people to sleep. And what I have heard and read is the text on the slide is really hardly for you the speaker just to help you remember what to do but mostly they don't people don't need it the audience doesn't need it. Of course, that depends on their hearing ability and everything. Next slide. So this is another slide from that same group. So on the left, they had two classes being taught at the same time, like same semester geology. And in one of the classes, the professor used the traditional method of making a slide, which is on the left, you know, now we're going to talk about iron, and all the bullet points about iron on earth, and it accounts for 95% of metals used and so on. And then in the other class, the teacher used the assertion evidence way of making a statement for an observation but into into the title, which is iron ores make up 5.6% of the earth's crust and account for 95% of the metals used. Now, I don't know about you, but I didn't really get that from the left slide. And then they're able to show pictures of it with a little bit of descriptors, a map of where you can find it. And then you can speak or can talk about it. And what they found was so testing people later that, as you see there, the left hand side, there was 59% recall of this information. And on the right with those slides, it was a 77% recall. And that's at a level of significance, 0.001. So they're significantly different. I think that's a nice example. Next, please.  And then how does that affect resources, maybe along fault lines or subduction zones, that kind of thing. So next slide, please. And then you can tie it in to, you know, following one, the best places to harness geothermal energy are at the plate boundaries. With a nice photo, and then an example, Iceland is almost entirely run on geothermal energy. And so again, they're using the title, that's, you know, a message. Next slide, please. And then this is one more that they have. So in summary, only a small percentage of water on earth is readily available. So this could be a last slide of a talk. In the US, water is mainly used for agriculture and power plant cooling. And so that's also a statement. No, it's not just like figure one pie chart, or something like that. It's making the conclusions, helping the audience get the point of what you want to make the point. Next slide, please. So here's here's a comparison of just like, you know, good and good and bad. So this is here we are. It's like, okay, this is a typical scientific presentation, using PowerPoints default pattern. So it's, we were talking about the MacBook Air here. And, you know, we're really excited to introduce this really thin light notebook computer. It's got a 13 inch display back with keyboard Intel processor and it really is cool and exciting. And I hope you get you get what I'm saying. And then go to the next slide and this is actually what Steve Jobs did. And it's like, Oh, well, this looks like the world's thinness notebook, MacBook Air. So it doesn't have all that data, it has a photo, it has lots of space, that's in white space. And then there's a, I guess when he was presenting it, if you click again, Rose, there's a shot of him showing how the MacBook Air could fit into one of these envelopes. So it was very simple and effective. And it's kind of more appealing, you look more like a CEO and give when you give talks like this. Next slide, please. Okay, so here's their recipe, they provide us with templates for this idea, like with the message and the supporting images of PowerPoint templates that we'll share with you. And here's an example of a concluding slide. So in summary, this sentence headline states the most important assertion of the presentation. And then there's an image that supports that conclusion. And then a supporting point, and then another supporting point, the logo, and then have an anime come in, but if the questions come in after that. Next slide, please. So here's an example that they provide of one of these. So in summary, the detector failed because of a short circuit created by the abrasion of wire insulation. And then they, you know, have this good figure and a little bit of information there in the logo down on the right. So that the audience comes away like, okay, this is the main point. Because if you remember some of those cluttery slides, it's like, you would not even have any idea what the main point was because it's like your eyeballs go nuts. Next slide, please. Okay, so now I'd like you to take a minute and think about what could be a possible title for your talk. If you want to if you'd like to convey a message rather than simply a topic. So if you are putting together one of these sentence topics that convey the message, even if you don't know what your results are, you can just make it up and just pretend that it's either significant or not significant or something like that. So go ahead in the chat and Rose, did you want to add anything? Oh, there's a good one. So Arianna, is that your is that your suggestion right now? I love it. What went wrong? If that's your title. Okay, this is some title. Oh, right, for a slide. Yeah. Right, or a title for the slide. Right. How much are the CO2 levels changing in Portland? And you might want to add, whether you're talking about like, near surface air or or what it is. Some people say don't ask questions in the in the title, but I think that it's it can be, I think it lures people in personally. Or if you want to speak up, please do. Well, let's go to the next slide. So this formula that we used in the abstract is similar to what you use in a talk. Basically, it's sort of like the what like what are we talking about? Why is it important? Remember that part? Why is it important for when you give a talk or you make a poster? How how are you doing this? And what happened? And then what does this imply for the future in terms of society or future research? I like that. Sebastian, that's great. So if you can include something from everyday life in the title, like a mirror that can convey an idea really well, it's really excellent. So the ionosphere a moving mirror. I love that. Other examples from the past have been that were became quite famous where let's see the flickering light switch. And it was about it was about climate change being really rapid at times in the past. There's a good professor who does good analogies and he describes a big glacier as a pile of molasses, which just helps you envision that it's like oozing and flowing and that kind of thing. Sebastian, can you just elaborate a little bit about what the moving mirror means? Yeah, so my topic mainly focuses on like seeing how waves bounce off of the ionosphere. And so describing it as a mirror is a really easy way of sort of, yeah, saying how the waves would move instead of going into the entire like, you know, oh, it's because of Doppler shift and the changing, you know, index of refraction, it's easier to say a mirror because we intrinsically know that mirrors reflect. That's really cool. Nice job. Okay, so let's go to the next slide. So here we're going to take some time to build a draft for you to build a draft. Maybe you've already started one last time. A slideshow for your talk. And it doesn't have to be it doesn't have to be at all perfect, but what we want is for you to create, say three, four or five slides on your project. And you can use random photos, pretend title, you can if you have a logo, don't spend too much time getting the logo because you can do that later. If you have graphs, you can put them in there, try to keep a lot of space, and try out the assertion evidence way of writing about the message, and then using the images to really convey. And if you want to be super cool, leave a lot of space around it, and you can do legit Steve Jobs thing. So I am going to what I'm going to do is share with you a folder a Google folder where you can find four different templates for PowerPoint, one of them two of them are four by three ratio and two of them are 12 by nine. And one of each is black or white background. Hopefully this is the right corner. So maybe if somebody could just click on it and let me know if that let you into a folder that has some PowerPoint slides called AE for assertion evidence, and then hopefully can download one of those to use. Great. Okay, so we'll talk to you in a minute about that. So what I'd like you to do is to take say 25 minutes or so maybe 30, 20, 25 minutes to create a few slides of your own slideshow. And you can just use regular PowerPoint if you want the these PowerPoints from the assertion evidence templates, they have examples like they'll have a slide with an example and a blank one and another one example. So you can delete whatever from there. And it's really meant to help with reminding us like how big it should be the text and that kind of thing. Please let us know if you're having any troubles with that. I'm just going to get this. And by the end of the 25 minutes, we're going to have volunteers give us a little talk, like maybe three people, just to get a sense of what you were able to do in a few minutes. Rose, maybe you can go to this website for a minute. That's in the chat. I'm on the website. Okay, can you share it? Can you guys see it? Yes. So you can see that excuse me, they have these templates and the ones on the top are the four by three, which is the old style older style PowerPoint. And then the ones that you on the bottom are 16 by nine ratio. So they're wider.  And then Rose, if you could move that away. And go back to the slides and then go to the next slide. Here's the way I have a frog in my trunk. Here's the sort of recipe again, same same thing, kind of thing. And to make, for example, if you had four or five slides, can you have one for, you know, some of the first several of these? Any questions? I have a question about titles. Sorry, sorry, I was muted. Yes, go ahead. I was wondering, I guess, like, since we're making presentations, and not research papers, I guess I'm having trouble writing, like, I guess, more of a snappy title that other people seem to be doing. I was just writing like, here, I'll just put mine. I'll put mine in the chat. And it's just like a literally like what the project is about. I'm wondering if like, that's okay, if that works or if for a presentation, if it's better to be a bit more snappy? Well, I think, I think first, I would maybe try to make sure it's just a bit more clear. So, so you're using drones. Model the flood stages of the LA River with greater accuracy. So I mean, even saying like, using drones, because drones are so popular, using drones to improve accuracy and modeling flood stages of the LA River. And I think that given that you've grown in your title, it's especially if you put it at the front of your title beginning, it'll be it'll be catchy, I think. I hear you, I'm not particularly good at coming up with super catchy.  Maybe Sebastian can help. Like, flying over the flood. I don't know. Oh, we're trapped in it. But thank you. Okay, Ethan, what about you? What is your current title? Oh, I mean, it's pretty good. The only thing that would be nice to remove would be the Latin name, you know, just because it's like it makes it more a little bit jargony, but it's not as I mean, you probably want to keep it there. But I think that the predator prey piece is very interesting, I might personally move that to be the first topic, predator prey interactions and dietary analysis. Because predator prey interactions is just, you know, innately more interesting than dietary analysis on the surface of it. But I think it's, it's fine. You could potentially take out the two commas. Anybody else feel free? Sure, you're welcome. Feel free to put your title in. I have the worst title for my PhD worst title ever. I think there was also someone else had said, like, in their project, they're probably having a lot of technical issues. I'm also having a lot of technical issues. And they're, they were wondering if that's worth putting into the method results. What do you think? I think so. I mean, this is just my take on it. If if you have interesting results, like scientific results from in spite of the technical struggles with equipment, then, you know, for sure highlight that highlight those results, and then kind of have it be, you know, this piece was overcoming those challenges. And that's interesting, like that's part of the story is like, Oh, this was really hard to do. It wasn't just like doing this and that. If, if on the other hand, that you're not getting data or results because of the struggles with the instrumentation, that kind of thing. What people sometimes do will be to shift their entire focus to the methodology. And, you know, you can change your title to be like, issues with the method of, you know, using Graham ground penetrating radar under water. That makes a lot of sense. So, so Chris, would you, I guess, in this case, I mean, you could say the challenges, for instance, the challenges of using drone imagery to model flood stage modeling, model flood stages of a river. If you feel like, if you, in the end, if you and your mentor kind of conclude, oh, well, you know, we weren't really able to do this, but we can certainly help people understand what the challenges are. I think for my project, it certainly is feasible. But I think that we have just been having issues with precision and it's, I'm sure that we could figure out the issue is just that we don't have enough time to really get down to it and work out the kinks. Right. And so therefore it feels sort of like our project may be incomplete at the end of this RU. And so I, it feels a little bit dissatisfactory to end on the conclusion of being like, I only, we had more time to work out the kinks, you know. Yeah. And I think that's, I think that's honestly partly the culture in science. It's like people don't report negative results or results that don't show something. And it's all about, you know, well, we found this conclusion and made this discovery. When in fact, sometimes the other, the other things like the problems end up leading to great discoveries and they are more interesting. So it's, it's definitely a cultural thing like, you know, oh, I really wish I had some results and yeah, it's such a short period of time. I mean, you're all doing basically, it's like a mini master's thesis in 10 weeks or so. And so it doesn't allow for those kinds of issues. I guess I think when you're, when you're looking at your title to just make sure that it's accurate, like if you're not actually dealing with improving the accuracy of the models with drones, then I wouldn't say that. I would say more like, you know, using drones and leave out accuracy because, you know, if you're not quite getting the results, does that make sense? I don't know if it aligns with what you're doing. That makes sense. Thank you. Sure. This is more fun doing it in person, but unfortunately we are all scattered all over the place. I don't know, Val, did you already mention like the length the title should be? I did not. I'm looking at Ethan's title and it looks a little bit long to me. Is there any way, like, is there a yay or nay for how long a title should be where it's like it's frowned upon or it's fine if it's longer? Well, I think if you're right, I think it's, if it can be shortened, then that's good. For example, maybe Ethan, you could stick summer, the word summer, in between, let's see, let's say predator-prey summer interactions or something like that. Just choose, take it out of the during the summer of 2023 or you could put, like, interactions of the summer of 2023, California, Moray, just a little bit shorter. But I think it's fine really in terms of length, especially if you spread it out like horizontally. How's it going? Does anybody need help with anything? It's unfortunate we're not able to jump over and see what you're doing, but I could, I would send out chocolate cover to espresso beans to anybody who wanted them. I'm going to share the title of one of the people in the room, sent it to me, which is a nice one, canopy transpiration of mocker nut pickery, red oak, and white oak in temperate forests of New Jersey and their response to environmental parameter life. So what we're hoping is that you'll walk away today with at least a start on your talk, kind of a rough, rough draft. I am curious about how if you, if you like the template or did you go back to just plain old PowerPoint? Cool. Thanks, Ariana. Let's see. Temporal degradation of H-mini detection of PCR following storage in 70% ethical. Ethical? Is it ethical? One storage in ethanol. Got it. Is PCR the method? Let's use the COVID detection. Maybe you might consider moving, Ariana, moving, having it be like temporal degradation of H-mini, or detected by PCR, or by PCR detection, or maybe move that to the very end and have following storage in 70% ethanol. And maybe, yeah, using PCR detection. Thank you, everybody, for hanging in. And we really hope this will all be helpful. Right? That's interesting within, yes, revealing that laying out your thoughts. We have, the paper is very different. I think it was interesting the point that Michael Ali made about putting your messages on sticky notes. It's not, you know, and you're used to using PowerPoint, it's not what you naturally go to. Paper, you know, whiteboards are great. If you can have a big piece of paper to explain to your roommate or somebody what you're doing or to your mentor, it shows you how it's like, well, you have to really go back to basics. Wow, that's some, I think that's a good title, Sarah. What do you think, Rose, if you're there? It sounds complex to me. It does, but it sounds good. I think it's not bad to be a little bit sometimes. I know some people get like super specific in their titles. And it's like, that sounds a lot more complicated than I need to speak. Sometimes keeping it broad isn't that, like keeping it broader, especially if you're covering various topics, isn't that bad? I think it's possible that you could reorganize some of the words to get the relationship of the two things up the front of the sentence. Something like subsurface marine, or something like that. Characteristics and mechanisms of formation or something like that. Does that make sense, Sarah? Just a few more minutes, and then maybe in five minutes we'll see who wants to volunteer to give us their talks. Even if it's just two slides, that's fine. Or even one slide. Yeah, I, I, Julia, I hear you. I actually haven't sort of sat down and really tried to use their templates, but I can see what you're saying. Like it's hard to come up with, and even for each slide, like, you know, and narrow it down. Let's see. Linking early Cretaceous Ocean Basin Records in the Southern Patagonian Andes. I mean, to me, that makes sense. I mean, I have a background in geology, so I understand, you know, what it means, but can you, can you un-mic maybe and tell us a little bit about what the goals are, or implications might be, or if you don't want to un-mic, if you want to write it, that's fine. And if anybody wants to put their name down to volunteer to give us their short talk, we'd love to sign you up. Val, how much longer do you want to give them? Just, that was a good point too. Maybe two more minutes to quarter to. Good job working on this. I know it takes a lot of concentration. Oh, that's interesting, Julia. I think it would be worth, even if you don't have answers, but if you can say, you know, maybe phrase it like a question even. It's a kind of, I guess, you know, considering that it's so interesting what you got up here for this, I think the title is a little bit, it doesn't reflect how exciting this is, or could be sort of a little bit bland, like, oh, just linking this and that, you know. For instance, this would be probably going maybe further than you want, but tectonic, global tectonic changes versus local water, local changes as reflected by the linked geocranology of two sites in the Andes. I got it, Julia. Okay. Can we get three people to volunteer to give us many presentations? I don't know. I have all these people, there's got to be a few who are willing to do this. Feeling comfortable and confident. Again, it can be one slide, two slides, four slides. Ethan, would you consider doing it? One of them. I was just typing. I'm a bit apprehensive. I am trying to work through it right now. But I think one of my. I don't know. I don't know. I don't know. I think I'm way too picky right now for. Oh yeah. Making like. For making any sort of slide. I don't, that's not a very good excuse, but like. With, with more research and stuff. I'm like, I'm really running into problems of like finding. Permanent visuals and. Making anything that looks. More than like a. I don't know, like a door of the explorer slide show or something is just, it's pretty rough. At this point. I'm trying to work there, but I've, I've been like working on doing my little speed talks in the past few days. So, I mean, if we really need to. Spill space, I can try to do that. Elevator touches. You're right. I mean, I think that would be terrific. Actually. So let's see if we could, if you are up for it. You know, I couldn't relate about the slides. It's like, I get carried away with details and.   I spent all that time on. Ruth. Yeah. Ruth, can I share mine? You're more than welcome to. Thank you. Do I need the screen share? Yes, please. If somebody else is interested, please just. Message us. Thank you for doing this. Ruth. Yeah, no worries. I mean, it's a little burned together, but. I had a photo of the diagram. But I drew so I could use that. Oh, cool. Yeah. And if you can go into slideshow. Yeah. You all this today, did you? All of those slides. I did just now. That's amazing. Thank you. That's amazing. Look at that seven slides. Okay. Yeah, go into. I'm not, not all of them. These are some of them in the default. I just have five slides. Oh, okay. Fine is still amazing. Really. Okay. Can you put it into the slideshow mode? Yeah. How do you do that? See over to the right. On the top. It says slideshow. Yeah. Okay. So. I just started only the third week of my RU, but what I'm going to be doing is measuring the CO2 levels in downtown Portland. With my mentor, Dr. Right. And also. With the help of a couple of the people that work there. So CO2 levels. They're always changing. So even though they have been recorded in downtown Portland before. We still need to record them continuously. And that seems to be what Dr. Rice's lab specializes in. And there's a line to draw an air. From the root to over it. I'm using a lot of different methods. I'm using a monitor. It's called a Lycor system. Because the main machine is from the company Lycor, but there's a diagram. Everything else that's on it. Thank you. It's Frankenstein together from the multiple parts. It's awesome. And. It's just showing. But. The Lycor machine that measures. Each two L content. And CO2 content. So it's called a. Or is that right? It's called the company is Lycor. And the machine is the. The company is Lycor. And the machine is the. Lie 840. Oh, got it. And. So as far as I got. First we need to drive the air. So. We're also working on. Making. An air basically an expensive dehumidifier to dry the air from. And then we can attach it to the system. So can you walk us through that diagram? This is actually not, it's not the one we're using. I just pulled a stock image. But it's similar concept. I just wanted to have a visual. No, it's actually a great. And graph. I was just trying to, I guess if you're dehumidifying, you're getting. You're pulling the water out. So it's. That's the last thing is on the right, bottom right. The trap. Yeah. I believe it's sort of similar to the one we have. And there's like two of these chambers with. Drying. Balls in them. And then a suction line. To the roof. And then there's like sort of a glass flask that the two goes into. So it's sort of like this one. Okay. Cool. Can you go back through those slides just so we can see them again? Yeah. This is, I believe it's the same one. The same exact one. We're using. Nice. Layout of the slide. Thank you. And. This is the actual. Yeah, we actually have. The main component is the data logger. Okay. Yeah, keep this in your talk. It's refreshing. Yeah. And then. Okay. And so the, I guess the one thing that I haven't heard you talk about is why, why this is important to do. If you can in the first or second slide, maybe the first slide. The title slide is to include that. Why, like, why are you measuring CO2 levels and downtown Portland? Like, yeah. That's good feedback. I have some. Okay, cool. What are you trying to figure out? Do we have another volunteer? Oh wait, before we move on. Does anybody have any comment for Ruth? Like. Starting with the positive, please. I think it's important to say that. I had a question about. Destructing that. In 25. And blown up. You could sort of cut out a little bit. I can hear you. I'm sorry. I basically just said you blew me out of the water. That was amazing. That you've constructed that in like roughly 25 minutes. That's wild. Thank you. I do a lot of everything on my spare time. Good for you. I mean, I think I'd be stuck on a slide. And Arianna says, awesome presentation. And Chris, this is the second day. Thank you, guys. It's really terrific. And that you can walk home, go home today, or maybe you're already at home. And just you have a beginning of your slides for your talk, which is awesome. Can we have at least one more person present their slides? And as I say, it can be one or two slides or three slides. Ethan, do you want to, I mean, this takes a lot of courage and you don't have to do this. In addition, I was going to ask you to do your elevator pitch. But if you could show us even your slide that you're stuck on, like that can be helpful to see. Yeah, sure.  Yeah, let me see if I can share my screen. Let me pull up because I'm doing this on my phone. So let me make sure that this is all going to work out. Well, I have it up on my computer. Like the work I'm doing is on my computer, but the Zoom call is on my phone. Oh, got it. OK. So let me see if I can share. I can find the slideshow on my phone sheets here and share it. Upload a file in the chat is another way. Michael Salinas, any chance you would want to show us a slide or two or Sebastian? Yeah, I'm not really too. OK. I try to. They're kind of wordy. I didn't really have a lot of pictures. So yeah, I couldn't really follow the format. So yeah, yeah. OK. So something you can work on later getting images to represent things. For example, Sebastian, any chance you'd want to share a slide or two. And Ethan, if you haven't figured out, please go ahead. Oh, I absolutely don't have it completely figured out. But I will share my video right now. And I'll just point it at my screen here. I recognize you from another work. Here we go. This is what I mean. I've just been working on this graphic here. I've been adapting it from another. Sorry, I was just going to say to people if you go to the upper right corner and you change from gallery to speaker, you get to zoom in on the image. OK, yeah. So I mean, this is just the graphic that I've been working on. But essentially my. My work I'm going to be doing over the summer is on going to be doing a dietary census of the California Moray eels in the summer of 2023 on Catalina Island. I'm a great predator, right? Yes. Studying predator-prey interactions for specifically more eels is proving to be they're proving to be an excellent model organism for tertiary predators. And our goal throughout the summer is to essentially have a better understanding of how their diets are changing over the 13-year study that we've been conducting. Wow. Our methods are in line with what previous groups have done in the past. So essentially we're going out. We're deploying wire traps at different coves around the Two Harbors Bay on Santa Catalina Island. And we're leaving them in for 12 hours of soak time, pulling them out and aggregating more morphological feature data and dietary data in order to, jeez, yeah, I know this is where I start to break down a little bit. But let me try to work through it in my brain. I'm getting like I'm just still like this is like my first REU. I'm a it's like the first time I'm learning to do all this. This is great. It's terrific. And yeah, I'm is really it's and you can talk about the diagram in your talk. And and when you're talking about going around to the harbors or the bays and and dropping things in and show photos, you know, you can show because everybody likes to see water pictures. And and I mean, I understand what you're saying as you're trying to wrap your head around, like, what does the aggregated data tell you? Or, you know, why is this important? That kind of thing. But what I like is actually that you say, sorry. Go ahead. Oh, no, no, you keep going. Oh, it's going to say, I actually like that you were staying on one slide because then I could listen. And I wasn't again, I wasn't trying to read or anything. Oh, yeah. No, I just haven't worked on any other slides as well. But this is yeah. I mean, I think this is about as like, yeah. I mean, removing some stuff down here because this was just what I was working on. I mean, I think this was actually me putting in notes from the other day as well. But I mean, just even like a slide of something along the lines of this and making it extra pretty but to to help me have something visual just to cue me and to like, I don't know. I think I'm struggling with putting into practice what the speaker was sort of talking about that we or the video that we watched today where it was having more of like conclusions and like general ideas to like exactly at the top because I mean, that's what I struggle with the most. I have ADHD. So like my brain is all over the place and drawing the conclusions between what I'm doing in research is like by far the hardest thing for me. But yeah. And it can be it can be just sort of descriptive like, you know, this is what we do. This is this is how we did it. You know, it doesn't have to be like solutions or fancy, fancy results. I've sort of super lost my track with where I was. But I mean, that's essentially how I would start sort of explaining. And then the the why is like why is this important or valuable? I know it can be it can be hard because it's fascinating. But yeah, it's hard to try to hit that in the beginning with like talking about how like they're an excellent model for studying tertiary predator prey interactions. But that's really jargony, I think. And I think explaining. Yeah, I think one of like the goals of these talks is to sort of convince people that what you're doing has has like implications and whatnot. And I think for it's hard for me to articulate by having like a deeper ecological interaction understanding is important. But to me, it's really important. And it's like, I don't know, I need to work through how to like articulate that. Yeah, well, I mean, and I like I think that saying this is a good model is a great idea. And then, you know, if you want to just extrapolate or expand it to, you know, it's like this helps us understand the ecological relationships of the marine life and which is something like that. You know, I love that. You should be you should be writing my paper for me. Wonderful. That's a little bit of a nice thank you for sharing. And yes, Brina, it is a struggle. My family has lots of. Yeah, it's wonderful. Yeah, yeah. Yeah, a metaphor. That's a good idea. Yeah.  No, I love that. I love that. Yeah, if we can think of anything we can. Ruth, you can email me and I can email you them. Well, thanks, everybody.  That would be lovely. It's so nice to meet you and see you. Hi. Oh, thank you. Anyone has any ideas for how to turn on my camera? I tried on the suggestion in the chat, but it's not working still. Oh, OK, that's my technical issue. I have to deal with that after. OK, now for those of you who are on camera, can you smile while I do a screenshot? Oh, that's some more. Thank you. I'll do one more because somebody was fixing their hair. Oh, never mind. I'm forgetting. I don't know what I'm doing. OK, I did get one, though. Thank you. And so nice to see you. Wish we were in person. And thanks for hanging in there and sticking it out.  Like, how am I going to create a talk? But now you have a better idea. And I'll send you some of those links to those videos so you can check those out as well. Oh, now here. OK, I'm going to do another screenshot in case anybody wants to pop on it. I can have a question if you don't mind. Sure. Will these lecture slides be available somewhere? I don't know if somebody already asked. They are actually there in that folder. Let me just where you got the templates. There's a PDF in there. Was that in the chat? I think the chat is exploded. Yeah, let me just get it from before I have it here. Thank you so much. Oh, sure. Yeah, and if you have any suggestions how to do this, how to improve it, or what you'd like more resources, let us know. But thanks for joining. We're super psyched to have you here. And hopefully we'll see you next week. We have a career panel for careers outside of academia. It should be good. And we'll look forward to seeing you. Thank you. You're welcome. Bye. Thank you. Thank you, everybody. Have a nice rest of your days. Thank you for sharing your stuff. I'm just going to move people out. Well, the silence was sometimes painful, but. It was really hard to get people to share sometimes. Yeah. I'm glad, like, I think that we had about 50 people for a lot of it, which are my 58. And then it would drop down. And I don't know if you were noticing it, it dropped down, dropped down. Yeah. It's like 48, 45 by the end, I think, which is or 40, which is half of the original amount. But the majority, like 70-ish, 68 people hung in there for like an hour, maybe. Yeah, yeah, it seems like an hour sort of where people tend to kind of like. Yeah. Get a little Zoom fatigue. Yeah, especially if, you know, for those of you on the East Coast, it's like that hour. It's a sleep-the-nap hour. Yeah, it's about, it's been so hot here. So it's just like all I want to do is nap in the afternoon. Well, like today, like the real feel was 48 degrees Celsius. So it's just like not normal. That's insane. I just want to like either go lay in the pool or like just go like lay under the AC unit and pray that it doesn't freeze up and like some ice falls on my head. Right. Because it's working over time. Yeah, we had, I think the highest we had was 85. Oh, was it 85? OK, I saw it. Yeah, it was 85 and it stayed around 85. Like it stayed between like 80 and 85 for like the first hour. Oh, good. OK. Yeah. Yeah, which is fine. I think we lost like some people when we gave them the 20 minutes to do exercises. I think that's where we lost some of them to do the slides. I mean, I would probably do the same thing. I'd be like, yeah, I'm gone. I'm whereas if you're in person, you can't really do that.  Right. You kind of work through it.  So you want to edit some video? Am I editing this one? Yes, please.


And also the management page for pre-configure LTI tools in the course level. So currently, this process is not very user-friendly because in order to pre-configure an LTI tool in a course level, users need to start the process of creating an external tool. And during that process in that creation form, they have an option to create a pre-configured tool, which is not very intuitive. So to improve that, we've introduced a new centralized page, which can be accessed through the secondary navigation in the course. And there, users can manage, delete, and create new pre-configure LTIs in a course. And also, there's a list table where all the available pre-configure tools that can be used in the course are displayed. And that list also includes the ones that were pre-configured in the system level. But of course, users cannot modify those. And in addition to that, there's some additional information in this table, such as the number of usages each pre-configured tool has in the course. I'm Jake, developer with the Education Solutions team. I'm just going to run you through what we've been working on for some of the LTI work. And I'm just going to share my screen. So as Mahal mentioned, the way that we have to currently do this before we've started looking at this, oh, yes, John, is you have to go through external tool. And there's this really obvious plus sign here, which is allowing you to create course level tools. And there's a little, even less obvious, edit to edit those tools. So if you want to say, like, edit this tool, we have to go in and do this. But we have to do it through this instance form, which is a bit crazy because all you want to do is modify this thing. So I don't know why you come into this form. And then do that. So that's what we were looking at. And essentially, we've done the first bit of work on that. We've now got, in the More menu, LTI external tools, which is essentially mirroring this same list that you saw in that activity instance form, so that it's just in a nicer place. This is just using report builder. So we've got all the kind of niceties that you would get with that. We've got this usage column, which shows number of activity instances for the tool. You'll see lock in the actions column when it's a site tool. You can't do anything with that. It's been pre-configured for your use in the course. Somebody set it up at site level. You still can use that, but it's just you can't do anything with it. These ones are course tools that I've created. And so you've got edit, delete, actions there. If you want to create a tool, this is just a copy of that same form for creating a tool. This is one of our pieces of work for the next coming iteration or future iteration. You're actually heavily looking at this form and how to make this nice, because it's a bit of a mess at the moment. That's how you add, edit the same, go to that form. And deletion is just done via this and then gone. So that's pretty much just the basics of what we've got so far. Some of this is going to change in the future slightly, but that's kind of the foundation work that we've done. And this will eventually replace that select menu kind of control widget in the activity, edit instance form. So that's pretty much it for that short demo. But short demo is a good demo.


Hi, I'm Dr. Gautam Kumar. I'm the multi-organ transplant surgeon at Manipal Group of Hospital. Yes, after pancreas transplantation, the follow-up is lifelong. Initially, we have more regular follow-ups like weekly ones for first three months and after that, fortnightly for other three months and monthly for six months. And after a year, we do quarterly follow-ups.


Hello from Las Vegas. It's theCUBE live at AWS re-invent 2021. Lisa Martin and Dave Nicholson here. We're on our fourth day, Dave. We have two live sets at theCUBE. There's a dueling set right across them. It's kind of like dueling pianos, only a little bit louder. We have had about 100 guests on the program at AWS re-invent this year and we're pleased to welcome back one of our alumni. Richard Potter joins us, the CEO of Peak. Richard, welcome back to theCUBE. Thanks Lisa, great to be here. Talk to us, so we haven't seen you in a couple of years. Talk to us about what's going on at Peak. I know there's some news coming on this week. Yeah, yeah, loads of things going on at Peak. I mean, we've been growing really quick. So since the last time you saw us, which was, yeah, in London a few years ago, we've grown to be the sort of, essentially the global leader in decision intelligence systems. Us as an AI company, we specialize in putting artificial intelligence right into the heart of how companies run their businesses and make their day to day decisions, which is why we call it decision intelligence. We think it's the biggest thing in software and probably the biggest new category of software. We will see this decade. So it's super exciting to be in that position and great to be back chatting to you guys on theCUBE. Yeah, when were you guys founded? We were founded in 2016 and you can probably tell by my accent, English company, headquartered in Manchester, but we're global now. We have operations in India. We have a couple of development centers in India. We have a growing customer base in Asia and a growing customer base in the US as well. So yeah, we're kind of international, but born out of Northern English roots. I like it. Talk to me about, back in 2016, what were some of the gaps in the market that you saw from a, because you know, as here we are in almost 2022, every company's a data company, they have to be.  What gaps did you see back in 2016? Well, actually back then, read on the market was really simple, which was that companies that are going to harness data to run themselves well will win, but that most companies were struggling to make that change to be data-driven. So our itch was, you know, as founders as three of us who started the business was trying to explore that problem. Like what stops companies running on data? And there's loads of reasons, right? Tech ones, skills ones, even just like business people using data in their day-to-day decision-making rather than say their gut feel, which I think is also a data-driven decision. They just don't understand that necessarily. So we really honed in on that problem and we grew quite quickly to be the leading business in that sort of applied data space in the UK. You know, a market leader in helping companies perform better with data. And over time that's taken us on this journey to be the sort of global leader in decision intelligence, which is really cool. But the itch we were scratching was that, hey, you know, there's something in this. We think companies that do this and do it well are going to win, but no one's doing it. So why is that? And then we've built software that effectively responds to that opportunity. You mentioned harnessing data. How do you balance the harnessing of data successfully with being harnessed by data? Because if you're talking about the concept of DI, who's making the decision? If the machine is making the decision, I better trust it. Why should I trust it? So how do you strike that balance to get people to trust what you're doing, the work you're doing for them behind the scenes? Yeah, I think it's really important that humans trust the machines that they're working alongside. And I think that's the big change we're seeing, right? So this is a new industrial revolution, the intelligence era that we're in, but all previous industrial revolutions have all amplified human potential. They've amplified like our physical potential, whether it was machinery, steam power and so on, or computers have amplified our cognitive capability. But humans have always controlled those machines, if you think about it. Now in the intelligence era, our machines can think with us, they can think alongside us. So we have to learn how to, as people, how to coexist with those machines and let those machines amplify us and essentially make us super human in what we do. And that's part of the challenge we face at peak, is to how do we humanize that? How do we make it such that everyone trusts the machine? And we always have that. Human in the loop is the way we think about it. Decision intelligence empowers us to be awesome at our jobs, make the great decisions all the time. If we trust the machine so much that we just want it to make the decision for us, we can let it, but we're always in control. And we're in control of how it thinks and what it does. And it's our job as a software company to build software that lets you understand why that recommendation or that decision is being suggested to you. So I think the coexistence of our machines alongside people in a new way, that human-to-machine interface can completely change with artificial intelligence and decision intelligence. And as people, we're going to have to relearn how we work with our technology. You just mentioned a couple of really good words in terms of the people part of people process and technologies amplify and empower. Those are two things that stuck out at me is that's what you're giving people in any, whether they're in operations or finance or marketing, it's the amplification to do their jobs, empowering them to do their jobs with data that will help make them more skilled and better able to make decisions that benefit themselves, the company, consumers, et cetera. Yeah, because if you redact doing business to its basics, it's actually just making decisions, right? Companies that make great decisions, they win and those decisions could be anything. They could be product decisions, they could be pricing decisions, operational supply chain decisions, but it's a sequence of decisions that creates value for my company. And so that's why I believe this technology is so empowering because as people, we're actually great at making those decisions. What we're not great at is making those decisions 24 by seven, really, really quickly, very consistently. So humans are awesome at forecasting, they're awesome at choosing pricing that would appeal to other people, but alongside this technology, we can have machines that do a lot of that thinking for us, speed us up, help us make more quick, great, consistently awesome decisions and then that just makes us great at our jobs. If you're a marketer or in finance or in supply chain, you become awesome. And I think that that empowerment is key to the sort of humanization of AI in business and actually that's what it means in practice. It isn't AI coming for people's jobs or replacing jobs. It's AI helping us all be great and our companies grow faster with wider profit margins when we do that, which creates more jobs for people, which is really cool. So we talk about people trusting machines to do things for them. It's not necessarily a new concept, we just sort of take some of those things for granted. I trust my refrigerator at home to measure the internal temperature and make adjustments as necessary, turn the compressor on, turn the compressor off. And I'm sorry, you're from England. Refrigerator is this thing, it's a box, we use it to refrigerate our beer, to make it cold, which I know. We do warm beer in England, too. Yeah, so it's kind of, you know, got to love those cliches. But so can you give us an example of a situation where a customer is trusting something that it's gotten from DI, from peak, where if you as the CEO heard that anecdotal story, you would be absolutely delighted? Well, I think there's loads of great examples of that. So the reason we call decision intelligence, decision intelligence is because it's applying AI into that active decision making, right? Artificial intelligence or machine learning is making a prediction or a categorization over a huge data set, right? But that on its own is kind of useless. You need to take that prediction, that forward looking view and then effectively infuse it with business logic constraints and like knowledge of how your company works to give you a recommendation, right? So let's just say I'm a marketer and I'm trying to work out who I should send a particular offer to on Black Friday over email or even not even over email, over any channel. When, if I was CEO and I heard one of my teams say, hey, what I've done is I've used the decision intelligence platform to tell me who are my customers that are in market for X type of products at Y kind of price and what channel do they like to be communicated to over, I would think that's awesome. And then that marketer would typically infuse that message with the sort of language and content that would appeal to that customer, but they're using the artificial intelligence to be super targeted and really deliver the message to that person in the way they want to consume it, which creates a really enjoyable experience as a customer. You don't feel spammed or you don't feel like it's effectively used. You feel like you're having a direct one to one personal communication with the brand or retailer that's talking to you, which in itself creates loyalty and increases the lifetime value of that relationship, which is great for the retailer. But I think using AI for those kind of decisions is essentially a great example of amplifying the human potential of a marketing team, for example. Absolutely, because what we expect as consumers, regardless of what the product or service is, is that we want brands to know who we are, what we want, don't, if I just bought a tent on Amazon, don't show me more tents, show me other things that go with it. I want you to know that. And so we have this expectation that brands, whatever industry they're in, know, oh, Richard bought this, he needs this next. Exactly, exactly. So, and I think that it starts to really jar. Now you've got some retailers and brands doing this really well and you get really enjoyable communications at the frequency you want with the offers and the promotions that are relevant to you. When you just start to get effectively stalked around the internet for something you've already bought, it becomes really jarring and frustrating.  So it's super important that these retailers, CPG, everyone really moves to this way of thinking and tries to have a direct, and that's the beauty of AI and decision intelligence, I think, for retail. If we get into retail specifically, it allows us to treat every individual customer individually because we can use the machine to make decisions on a per customer basis and then our marketing can be amplified by that. Whereas in the past, we bucketed customers into groups and just treated them all the same. Which does create a rather impersonal experience. So yeah. Which can be a negative for a brand, as you mentioned, but give them the ability to treat people individually but at scale and in real time. Which one of the things we learned in the pandemic is that real-time data access is not a nice to have, it's an essential. Exactly. One of the themes too that Dave and I have been talking about the last few days is that we're hearing it reinvent is every company has to be a data company. Talk to me about, with that in mind, are you talking to more chief data officers, chief digital officers? Where are your customer conversations as we're in this explosion of data? It's a great question that. So if every company has to be a data company and a company that's powered by AI, that means you have to be talking to everyone really. So chief information officers, chief data officers, CEO, CFOs and every sort of head of business, head of line of business, it's really important. So what we do at Peak is, as a decision intelligence platform, Peak itself unifies everything you need in one cloud platform into a single software product. That gives you all the infrastructure for your technical teams to process data, for your data scientists to create the intelligence, but then it gives you a place to work for your business teams. So it unifies your whole business around a platform. And then that means our conversations as the provider of that technology are with technical teams, they're with business teams, they're with business leaders because it has to permeate everything. So I think that's the future. Companies will have to effectively run alongside, they'll create their own intelligence basically on a dedicated platform like Peak, and that intelligence will then be distributed across the whole business in the way we do it. So I think it's really cool and exciting, yeah. Let's say hypothetically, now this is something that would never happen, but just hypothetically, say I'm an American, goes to England to take over coaching a British soccer. Oh yeah. Soccer or football. Okay Ted. Football club. Sounds crazy kind of. But how would I use Peak and DI and BI to help improve my winning percentage if I cared about winning. Because it's possible that I'm really only interested in the personal development of my team as individuals, but in athletics, is that something that is possible? Yeah, for sure. I mean, you're seeing an explosion of data science and analytics and AI techniques being used in sport, right? I mean, Peak, we're very much focused on the commercial application of AI with our platform. So we work with commercial businesses and so on. But in that space, yeah, absolutely. I mean, if you think about it, what do you need to create that intelligence? You need data and you can see it on the back of every player's shirt. They've got the little devices that are gathering data in training, in matches, constantly monitored. Those data points, feed algorithms, those algorithms can show us if a player is fatigued, you know, or they can even show us deep learning techniques can help us see patterns of play and understand like, how should we better set our teams up? How should we get players to interact on a soccer field? And yeah, and you're seeing Premier League clubs use those sort of techniques all the time. We don't do that at Peak, but yeah, I mean, I think those sort of things are readily available now for those kind of clubs to do that kind of stuff. I think Dave's angling to be a consultant on Ted Lasso. I think that's what I'm hearing. Last question for you, you guys are from an AWS relationship perspective. You guys were announced just yesterday, you were named by AWS as an ISV partner, APN partner of the year for 2021 for UK. And I, congratulations. Tell us a little bit about that. Yeah, it's really, I kind of, yeah. It's super exciting for us. It's a great recognition. Obviously they give one of those awards out every year. As a global company, it's nice to have that sort of stamp of approval that AWS sees us as their independent software vendor partner of the year. It's a great recognition for us because we come from a heritage of starting peak as a consulting company actually, just to do whatever it took to help our customers be successful. And in doing that, we had an idea for a software platform. We got some venture funding to do that. And we've turned into, you know, we became a software company a couple of years after we founded. And to get to this point now a few years later where AWS are recognizing us as their software vendor partner of the year is a huge to fantastic. Yeah, it's a huge testament to our engineering teams and the technical teams at peak that we've built something so impactful, you know? Absolutely, that validation is really, really critical. Last question in our last 30 seconds or so, what are some of the things on the roadmap that you're excited for peak for 2022? 2022 is going to be a huge year for us because I think it's the year that our platform goes out there into the wild, into the mainstream. So we made a couple of big announcements in the last few weeks. We've launched some new products on the peak platform. So there's three big platform product sets now, one very much geared around creating your AI ready data set, that's called DOC. One that's very much geared around creating your intelligence, which is factory and then an area where our business, the business teams of our customers go to work, which is called work actually. So those three big feature sets are going to be available from January and the platform is being totally opened up as a self-serve platform for anyone, anywhere to build upon. So I think it's a huge moment for decision intelligence. Gartner is saying decision intelligence is the big tech trend of next year and we feel as the market leader we've got the platform that can help everyone get on that trend really. So I think we're really looking forward to 2022 and what it brings and we think that our platform and our company is in a great shape to help more and more businesses take that leap into being powered by decision intelligence, yeah. It sounds exciting, Richard. So we'll have to follow up with you next year as to what's going on. We appreciate you joining us on theCUBE, talking about peak, what you're doing, your relationship with AWS and how impactful decision intelligence can be for everybody. We appreciate it. Awesome, thanks Issa, thanks. For Dave Nicholson, I'm Lisa Martin. You're watching theCUBE, the global leader in live tech coverage.


O5-2 let the email alert fade from her terminal screen without opening it. She already knew that the Foundation had suffered more casualties in the past 24 hours than all the last 5 years put together. The only thing reading the details would accomplish would be the sapping of her resolve. The path forward was clear. Ensuring a future was worth any price. She wished she could tell each field commander personally, we're certain about this, just hold the line. Then again, desperation was on her side. People had a remarkable tenacity in the face of death. Nobody needed to remind anyone of what the consequences of failure were. The large video monitor on the wall beside her chimed with an incoming video conference notification, O5-3.  Did she not get her filibitrile during the council vote? Knowing O5-3 it was quite likely. She sat up, intranessing warfare with one of the few ways the council had to amuse itself in this world. Even now, those habits died hard. Maybe especially now.  Once O5-3, you lost. Does that still make you mad? The woman on the screen sighed, What I am is scared to. It had not been yet a full two days since SCP-2798 had gone down, and the toll had been horrific. There was no way that current operation was sustainable for more than a week. Fear was probably the only reasonable response. Knowing someone else that you're frightened isn't very therapeutic in our line of work three. Fear is contagious. Can I do something for you? O5-3 leaned a little closer to the monitor. You blocked the vote.   There were plenty of us with doubts. But none with the certainty of yours. Five and thirteen were never going to vote for it anyway, but six and twelve would have. I talked to them before. I know you talked to them out of it. That's still not enough. One was the difference, and even you can't tell me that I can make one bend to anything. O5-3 sighed again. Look, that doesn't matter, I guess. It's done, and that's that. But you owe me something, too. Do I? O5-2 moved herself closer now.  You're beyond absurd. I'm done with this now. Wait! Please! I need to know. I need to know what you know. I need you to tell me why we didn't just make the worst mistake in the history of the world. The real reason, too. O5-2's hand hovered over the red button in the call. She pulled it back. I went to the precog items. I peeked. The revelation washed over O5-3's hard features. Her determined upper lip and furrowed brow, softening as her face betrayed shock. It was the first time O5-2 had seen her face like that. You didn't. That can't possibly be- Is it really that hard to believe? With the gun in your own mouth, you're not the least bit curious about how things might turn out if you don't pull the trigger? Yes, I'm aware of the prohibitions. Who cares about that now? Are you going to report me? In a detail to come and detain me in the middle of all this? O5-3 sat in silence. There was no arguing the point. So what did you see? You know what it's like three, being old. Ideally you'd learn not to delude yourself with false hope, resign yourself. You remember the old eleven? His obsession with uploading his consciousness, like he could cheat death? Ridiculous. He was ridiculous. O5-2 trailed off, the wild eyes of the former O5-11 haunting her for a moment. But this? We've always fought to preserve what is three. We'd never thought about what could be. What do you mean by that? All of the precog items point to a future. I haven't seen how we get to it, but it's not just survival. I saw great spires of glass that pierced the clouds, unspoiled landscapes, great blocks of bird passing through city-skates built into mountaintops. I've seen people who don't fear sickness and death, no wars, no poverty. She grew more animated. All of the anomalies under our control that can tell us anything have all shown me this place, that it exists, someone survives to make it there. O5-3 looked skeptical. That's a very different place than the one we're seeing now. It's a different planet. We know that much. Do you think we're going to be able to mount a space colonization mission when we can't even keep ourselves alive right now? No, probably not, said O5-2. But at some point, someone does. And I want to give whoever that is the chance to do that. Don't you see? There is a point to all this now. There is an end goal for humanity, more than just living another night. Our children will have a chance not just to live, but to live in peace. Is that worth continuing on? That seems very ideal, doesn't it? Almost like it's designed to stay our hand. What reason do I have to make this up? And it was useless as a tool to influence the council. If I had brought this up during the vote, I very well would have been detained in. Yeah, you do seem to believe it. O5-3 frowned. You know that these things, they can be very untrustworthy. One or two, maybe they come up with the same deception, said O5-2. All of them? Vanishingly unlikely. Some of these things are kept in separate realities. No, this is all pointing to something, and I believe it is true, or rather, I believe in it enough to keep going for the chance to make it real. O5-3 was silent for a moment. She swallowed. You know that we've already had two activations of SCP-089 in two days? O5-2 took a moment. No, I did not know that, and really, I would prefer not to know things like that. She went on. Nothing we're doing now is anything that we haven't been called upon to do before. It's harder, but it's the same thing. We've always tried to preserve some sort of future, and now that we've got proof of it, we can't stop now. Proof. Said O5-3 quietly. God, I hope you know what you're doing too. Just help me hold things together, until we can't do it anymore, so that whoever it is that gets us out here and away from whatever the hell it is that's hunting us can do their duty.  She would not let them flow. O5-3, impossibly weary, looking sick and unwell, every one of her sixty-eight years on display, nodded barely. She ended the call, and O5-2 was left looking at her own reflection in the dark glass in the monitor. She studied her own face for a moment. She had more hope than three did, but for all that, she looked just as heart-sick, just as scared. I hope I know what I am doing too. O5-2 opened the message from Asian sub-command, and read the latest developments. More of the same.