Personal notice, danger's my stock and trade. If the job's too tough for you to handle, you got a job for me, George Valentine. Write full details. The oil company of California, on behalf of independent chevron gas stations and standard stations throughout the west, invites you to let George do it. Snow Blind, a transcribed adventure of George Valentine. Dear Mr. Valentine, I'm writing to you about my husband, Herbert Morris. Since I know he himself would never deign to ask anyone for help, particularly when it concerns a woman. But he is in danger. I can tell from his letters and the way he acts when he does. Herbert is a doctor. He can't do this practice. And so he is alone down there in the city, just as I am alone up here in the mountains. Oh! Just give kind man the bees and violins. Oh! You startled me. Hello, Hans. What is it? What? Oh, it's gift kind. There are no longer bears in this wood. You see, I have been studying. I have. No, no, no. That's what I say. I meant, what is it? Oh, the letter. Nothing. It's nothing, Hans. It is snowing outside. Good powder. Oh, yes. I noticed it's up a time. I can practice my Christie in the morning, can't I? You'll help me with it, won't you? Before any of the others. Of course, Mrs. Morris. A ski instructor is only to oblige. Oh, Hans. What is it? You won't tell me? Oh, well, it's just a note for supplies I need up at the cabin. Oh, Hans, wait! I'll be in in a moment. Isn't André Dahman? Yes, I know. There are other women, that's what you said, isn't it? Yeah. But I'll be just in a moment, Hans. Ich nein... No, no, stop it. Stop it. It's a dead language, like the people. Why bother? Don't say that, Hans. You'll wait for me, won't you? Whatever the lady says. Oh, please. Won't you? How else could I do? So, hurry to order the bacon that is dancing to be done. Hurry! Mr. Valentine, my husband is in danger from a woman. Her name is Dorothy Graham, and I believe she is at the Hotel Continental. I can be reached at a winter cabin several miles north of Sun Mountain Arch. Sincerely? Yes, Graham checked out half an hour ago, took all her baggage. I'm as sorry as you are. She was nice to hand her key to. All right, Wolf. She left half an hour ago, and we already found out Dr. Morris left for Sun Mountain last night. But, wait a minute. Did she have any heavy baggage? I mean, like skis, maybe? Nope. But she asked me for a railroad schedule in the name of a good sporting goods store. Is that healthy, honey? Yeah. I'll find it, Angel. Shall we join the broken legs? Uh-huh. In fact, if we make it fast, we might even catch the same ski special she does. Want a bet? Ma? Oh, Porter. Porter! That's me. Tell Graham, Miss Graham, deliver to the train at the station. Oh, of course. Here. Thank you. Thank you, Miss. Well, pardon me. May I? Chair's empty. Ah, yeah. Well, I guess everybody's a little friendly, headed for a vacation and all. I suppose so. Yeah. Uh, this is my first trip this year. You pretty good on the sticks? I don't ski. Ah. Skate? No. Well, then, what are you doing on the train? Oh, look, excuse me. You got a wire. You haven't had a chance to read it. I didn't notice. Would you please give me a match? That's all. Oh, sure. There you are. Thank you.  Yeah. I like fires in the ashtray, don't you? Now, if you'll excuse me, I think I'll get me sleep. Yeah, Brooks, he burned the telegram without looking at it. I wonder who she thought it was from. I don't know. Particularly since it was me. What? Sure, that's the wire I sent her, a fake one from her hotel. Just so it would be easy to find her here in this crowd. Well, while you were in the pub car, I took a simpler way. I asked the porter which was Dorothy Graham's compartment. You want? I looked through her handbag, George. She only has a one-way ticket to Sun Mountain, a lot of sleeping tablets, and a gun. Mrs. Morris, we came up here because you said your husband's in danger. We didn't come up here to escape. Please, Mr. Valentine. Please, not now. But when will you talk about it? Ever since you met us at the station, you've been... There's so little time with the good snow, it'll be storming again later on. And you do enjoy it, don't you? Oh, yeah, sure. Of course we do. But I also like to know what's going on. Why did your husband come up here unexpectedly? Why did Dorothy Graham? Why does she carry a gun? What's it all about? Well, I'm sure there's nothing to worry about. The gun or about her. Not now. You said she took a room back at the lodge. Well, her bed's mild from here. He stayed up at our cabin today. Next one. Where's the next one now? All day. It doesn't take the time up here. Oh, there. That's you, Miss Brooks. I haven't come by when yet. The lessons will help you. You'll fall down. Come, Miss Brooks. Bend your knees, Mr. Valentine. Go ahead. Go to it, Angel. I don't see a fall on something beside your face. Oh, here goes nothing. That's it. Lean. Lean on. Now, swing your arm, your shoulder. Like this? Now, swing it. Yeah, it's all a lot of fun, isn't it, Miss Morris? Mr. Valentine, I will tell you. But not in front of Hans. It's all right, Mrs. Morris. Show her how it's done. This is not all day. It's getting colder. Only the skis keep them together. Together. Swing. Now, that's it. All right, Hans. Watch now. Hey, she's not bad. Must have been practicing a lot. Yeah. But you, Mr. Valentine, you do not need lessons. Neither do you. Why not, Mr. Valentine? What else is to life except mountains and snow and women?  Now, look, Hans, you know, Mrs. Morris pretty well. You've been with us ever since we got off the train. Do you know her husband? The doctor? Yeah. Well, what's he like? Well, American. I don't know. It's just this morning I meet him. I drive to their cabin for coffee. I brought her back to meet you, her friends. He's, uh, well, he drives a new red convertible. Is that bad? Expensive. It is her money. Oh, I see. Of course.  No, no, I get the idea. You don't like him. No, why should you say that? He's nothing. One way or the other. Yeah, I understand. The instructors don't get so much dough. Mr. Valensky. I was making a test. Neither do I, Mrs. What? Yes, your husband. It was Hans, right? Worried, dearly? I did. All right, all right, here. Keep the towel on. I wasn't just trying to stop you from talking to him. He's outside now with Ms. Brooks, so forget it. All right, let's have it, Mrs. Morris. I don't like divorce cases. But that's what this is, isn't it? Well, I, I don't choose it my husband. Oh, sure. That Herbert was in danger from a blonde and I followed her and she's a weirdie, all right? But you're no more worried about him or about her than the price of eggs in Sweden. Mr. Valensky. The only thing that worries you is your boyfriend. The way you watch that Austrian ski boy out there is enough to... I beg your pardon. I love Hans very much. Okay, I beg yours. Only, let's be honest about it. Herbert is in... Well, stuffy about giving me my freedom, that's all. My friend in the city, his nurse, when she wrote me that Herbert had brought this Graham woman to town, I've been visiting her at her hotel all night. All you had to do was hire somebody like me and trade the doctor for us. First impression. But when you get to know Hans, it's just that he's been through so much in his own country and he's sensitive and proud. And ambitious? Mr. Valentine, I'm sorry I misled you, but I didn't expect everyone to come galloping after us to the mountain. Oh, it's you. You're kinder than this one. Oh, darling, I'm much better now. I thought you were hurt. Yeah, yeah, the bear he is slow, huh? But the road is always bad. It's dangerous. And now there's more... My egg is only a little swollen, don't you think? Oh, leaps in how shall we then dance? You should have a bandage. I will go bring it myself. A little tape on... No, I'll have one. Where do you keep your first-aid kit? My cabin, just out there beyond the ski-tow. Why? Give me your keys. I need some fresh air. But... No, no, let me go. I didn't mean to hit you. I mean, I didn't do that. I... I heard the key step the door out. I'm sorry. Yeah. Maybe you thought it was somebody else, huh? But you've been sitting here all keyed up waiting for the door to open. Yeah. Yeah, that was it. Just like you were keyed up on the train, cried all the way up here, only bought a one-way ticket. Well, there's only one guy you could have come up here to murder in Hans' cabin. To that impact!  You don't know how lucky you are to be able to open it. No, sir, please, Mr. Valentine. It has been years, I... She is my wife. You need time to think of answers. No, please, there is a road. It's their cabin to here. Beautiful new car, Dr. Morris. Like a sheriff. His car accident into the canyon is dead. Mr. Valentine, in just a moment. Every week, there will probably be... What's the big track all about? No country, but how will your... Trust climate tailored. It gets the best out of your car ride. That's because Chevron Supreme is specially tailored to the last different altitude and temperature zones. It's tailored also to the season.  Right away, you'll notice how much better your car performs. Faster start, smoother pickup and traffic, thing-free power on hills. In fact, you can't buy a better gasoline for today's high compression engines. Ask for premium quality Chevron Supreme at independent Chevron gas stations and standard stations where they say and mean we take better care of your car through tonight's adventure of George Valentine. You're hired by a wealthy married woman who has a sentimental eye on a handsome ski instructor, a married ski instructor at that. Yes, it's a quadrangle, or rather it was until Dr. Morris crashed to his death while driving down the dangerous road from the cabin to the lodge. So, when the sheriff asks you all to meet him at the Morris cabin, you think it's best for you to do the right on that dangerous road. And when you arrive at the cabin, you wish the sheriff would hurry up with his investigation. Hello? Yes, we're all up here at the Morris cabin, sheriff, but... Well, I just hoped you'd be here too, that's all. Um, no, no, I just want to know more about the accident. So, so does this wife. No, sheriff, there's no reason I can tell you yet for wanting you here fast, but... Well, it's just the weather, I guess. Sure. He's still down there in the canyon with a car. He phoned from the ranger station. Have they reached his body? Yes. Was there anything unusual about the accident? Mr. Valentine, why do you act the way you do? Is Han starting a fire that storms getting worse? Yes, and this Brooks has gone upstairs with... with Dorothy. You don't care much that your husband died, do you? I love him, that's what you mean. Why wouldn't he give you a divorce? I hope he didn't really get stubborn about it until... Until you met Hans. Hans is difficult to understand, so appreciate it. Unless you're a woman, sure. Well, I'm not. Sheer a woman, sure. Well, I'm not. Sheer a woman, sure. Well, I'm not. So how's this for size? Your husband dug around in Hans' past until he dug up a wife, Dorothy, that Hans had deserted. Of course Herbert didn't tell you about it. He wanted to bring her up there and let the situation explode itself while it almost did.  That's what she thinks of him. Mr. Valentine, he's told me about her. She's not normal. She's unbalanced. Yeah, I wonder what made her that way. It's a tragic situation. Their marriage isn't even legal. Their marriage? Oh no, not that too. Oh, what do you mean? That's too neat.  Dr. Morris, he was the only real obstacle. Well, lady, I never know anyone to die so conveniently. By accident. What else did the sheriff tell you, Mr. Valentine? You see, you too can't help thinking that. Was it really an accident? Or was Herbert really murdered? Mr. Valentine, I was just trying to persuade your lovely assistant. Oh yeah, sure. Somebody dies, so it's a great time to dance. Where's Dorothy? Upstairs, I suppose. She's all right, George. Long faces for the dead. Black pretense around the arm. Sentimentality, isn't it? In this household, maybe you're right, Buster. I talk to the sheriff on the phone. What did he say? Quick on the draw. What's the matter? You nervous? Well, why not? The man is on top of the world. A split second of ice, and he has slipped into the abyss. Even at the wheel of a fine convertible, a man gets...  I know that Dr. was driving alone, and that's what you're trying to remind me of. I go around in circles myself. My wife appearing from all these years. The accident, and you are unpleasant to him out. Yeah, be sure to remind me of the word accident. But if you were driving alone on a dangerous road, the accident would be easier if someone had tinkered with your car earlier. George! What is that, no? What you call a shot in the dark? No, an unpleasant remark, that's all. Ones that keeps bothering me how much you envy that man is convertible. You can't seem to forget it. All of the things Stella Morris' money would give to a man. You were up here earlier this morning, you said so. Both you and Mrs. Morris would have had a chance to... No, Angel, she wouldn't have known how. So you shoot at me? Because I am poor, huh? Because you cannot understand the simple envy of people who are persecuted. I'm not interested in what makes you tick, Buster.  And yet you haven't once offered to do the normal thing to knock off my block. Then, of course, I shall oblige. Saved by the bell. Stop it, please, both of you. Dorothy, you shouldn't have come. I'm feeling much better now, Miss Brooks. No. No, I'd like to see my husband alone, that's all. Whatever you wish. Oh, no, you don't. You've already tried once. Yes, I came up here to kill him. But I have no gun now. That's right. I am strange, aren't I? Huh? Can you imagine me wanting to kill you? Aloha, Miss Steigen. No, it's the same me. Isn't he wonderful, Miss Brooks? Okay, okay, go ahead. We'll be back in a few minutes. George! Come on, I can't stand it.  But she's liable to try. I'm able to kiss him, sure. What'd she say upstairs? Anything? That's what we thought. He deserted her a couple of years ago after he got into this country by being her husband. But she's so mixed up. George is her I'm worried about.  Why would he touch her? George, maybe he could be deported if they're married.  No, Angel, when the doctor died, it left nobody to interfere with Casanova's march to success. Except us, and we might be wrong. Come on out here. What I'm afraid of, Angel, is we won't ever know whether we're right or wrong. Ooh, brother, that's cool. Come on, stay under the eaves. The garage is out in fact. You won't find any evidence. Except for the sheriff. It's my only chance.  Hey, look out. Let me take your arm. The ground's frozen. At least maybe I can get that guy nervous enough to... George, what's the matter? What's this stuff on your jacket? The inside of your arm here. What? I couldn't have rubbed against anything, not there. Somebody else took your arm like this. Who was it? But I don't... Well, Dorothy did for a moment when she came downstairs just now to steady you. Dorothy, sure, sure. And she wanted to talk to him alone about it. Oh, brother, am I a sucker? Come on back to the house fast. But George, what is it? A mirror of grease, Angel, axle grease. And it came off a car. Where is she? Here, George. Here, George. Mr. Valentine, I was just going to call you. If you were talking, it seemed to start to fall asleep. Dorothy, can you hear me? It's those pills she takes. She must have taken all of them. Yeah, now she tried to kill herself and she was alone. Mrs. Morris. Mrs. Morris. What is it? What is it? She's not quite asleep yet, George. Get some baking soda, will you? Whatever you do, make it fast. I'll get it. That's it, Dorothy. Can you walk me? I'm holding it. Here's the keys to my car. As soon as you can, get it wrapped up in a blanket and down to the large as fast as you can drive. Only leave the windows open. But the road, it's worse all the time, even with chains. She's got a license, Buster. Only I might be a little careful, Angel. Don't worry, George. Mr.  We should go with them. They can do better than we can. Besides, you're not leaving this room, not yet. Now, let's see. A glass, maybe. How did you give her those pills? And whiskey? I don't know what you're talking about. She tried to murder me. She's upset.  Yeah, yeah. This glass might do it. Uh-huh. That's number one. Number one? Evidence. Things you show to a jury just in case she can't testify it doesn't know herself what happened. Oh, Mr. Valentine. Oh, yeah, sure. I'm way out on a limb, Buster. But I'm building a ladder fast. Now, let's see. No coat, no purse. Oh, you don't. I'll pick that up. Uh-huh. Yeah, here we are. You're covered with grease, man's handkerchief. Yours? Give me that. I said stand still, Buster.  Sure. Your initials. A guy tampers with a car, he gets a little greasy. Dorothy got this down below, didn't she? In your cabin near the lodge. Wonder what else she stumbled into. I've had this before. Identification card. You were in the Luftwaffe, huh? What's this long word? Machinism. Mr. Valentine, this? It's all circumstantial, is it not? Uh-huh. There they go. In the car. Yeah, let's see what... Plans? Well, now, don't get so... No, I use those on ski binding. Or maybe this is the type that comes out of the toolbox of a red converter. No, stop it! Stop it! Mr. Valentine, you are so ready to accuse me.   You are... Look, you see... Let go of me! Let go of me! Ha-ha-ha-ha! So, there, my suspicious friend. Now, you are looking at a gun. Thank you, Stella. Well, I... I didn't mean to. I just opened the door. They didn't need me to go with them, and I... I wanted to... Aleepsian, forgive me. Perhaps you will join me sometime. What? Of course, I am leaving. Your own sedan is still in the garage. How could I stay in a country with such a suspicious man? Hans, I've been listening. There isn't any real evidence against you. Nothing to prove you caused the accident. Nothing except me. I know what police can make people say to confess, whether it's true or not. Well, I won't be caught to find out. There is no one who can catch me alive to accuse me of things I don't do. Hans! Hans! If I run, it doesn't make me guilty. It makes me free, that's all. Free to get the things I want. Well, Mrs. Morris, there goes your ski boy. I know him, Mr. Valentine. You can't catch him. He won't be caught. Don't be angry. It's better this way. Yeah, well, I'll just get on the phone. No, please, you can't. What? The phone. You can't. I was talking on the phone when the storm put it out of order. Miss Brooks will reach the lodge, all right. But by then, no one will be able to get back here. It would take a day for the snow plows to reach us. He could be in Mexico in a town. He could... Hey, wait a minute. Who are you talking to on the phone? The sheriff. The sheriff. A minute ago, I told you the truth. All the evidence said it was definitely an accident. An accident? The sheriff was just as suspicious as you were. But he says there's no question about it. Herbert just skidded on one of those corners and went over. That was all it was. Oh, no, wait a minute. You've been wrong all along, Mr. Valentine, about that accident. What? That's Hans. Come on. Well, he's dead all right. There was no other way out for him. He would have been caught. I see what you mean.  He was a doctor. He was considerate. I would have been warmer, more comfortable if he brought my car. The sedan. Yeah. Which left nothing here in the garage for Hans to escape in, but the car he himself fixed as a death trap. A brand new red convertible. Talk about irony, George. Dr. Mars unexpectedly took his wife's sedan, not his convertible. We had an accident? Pure and simple. Yeah, but Hans never imagined that. He fixed up the convertible. Doc crashed in the canyon, so Hans took it for granted his plan at work. Dorothy, any better? No, she's been telling me a little more about Hans, his background. There were lots of women he stepped over, I guess. Well, I won't say women are suckers. George, he was good looking. I can see how it happened. Ah, maybe. But George, the way he skied, so gracefully, so beautiful. Well, what do you think I've been doing all afternoon? All I said is I could see how it happened. George, your ankle, a plaster cast.  How did you- How did this happen? I'm lucky you couldn't see that.  And you probably don't think highly of that car's owner. But when were the lights on your own car last checked? For your own safety, friends, make it a point to get your car lights checked at regular intervals. At standard stations and at independent chevron gas stations, a light check is one of their many protective services. And it's a speedy service, so why not play safe and have it done tomorrow? While you're there, ask them to inspect your windshield wiper, both the arm and the blade. If the arm is faulty, they can replace it quickly, so you won't have to risk its failing when you need it most. And remember, in stormy weather, a worn wiper blade is almost as bad as none at all. They sound like small items, lights and windshield wipers, but they're very important to your personal safety. And they're part of the protective service offered to you at independent chevron gas stations and at standard stations, where they say and mean, we take better care of your car. Tonight's adventure of George Valentine has been brought to you by Standard of California on behalf of independent chevron gas stations and standard stations throughout the West. Robert Bailey is starred as George. Let George Do It is written by David Victor and Jackson Gillis and directed by Don Clark. Virginia Gregg appeared as Bruxy. Larry Dobkin was heard as Hans, Lerene Cuddle as Stella, Gene Bates as Dorothy, and Joe DeVall as the clerk. The music is composed and presented by Eddie Dunstetter, your announcer, John Heaston. Listen again next week, same time, same station to Let George Do It. This is the Mutual Don Lee Broadcasting System.


Ieithio'r ysgol yma yn y 5th ar gyfer y dda, rwy'n ei wneud efo'r yr Efinfall, yn ei parwysydd o'r newid yma i'r union. Ieithio'r ysgol yma i'r ein bod yn ymdwy'r FF? Ieithio'r ysgol yma i'r ysgol yma i'r ymdwy'r FF? Ymdwy'r ysgol yma i'r ymdwy'r FF? Ymdwy'r ysgol yma i'r ymdwy'r FF? Ymdwy'r ysgol ymdwy'r FF? Mae hyn yw'r ysgol yma yn ymdwy'r FF? Mae hyn yma i'r ymdwy'r Efinfall, bod yn ymdwy'r ymdwy'r Ysgol yma i'r Ysgol yma i'r Ymdwy'r FF? Mae ymdwy'r Ysgol yma i'w mewn amdwy ymdwy'r Mae FF? ac yn ymgyrch chi'n bwysig hon o hyffordd fath o'r yrwyr i'r Ysgol? O tejad hynny'n meddwl am aros ymdwy ymdwy ymdwy ymdwy ymdwy ymdwy? Mae'r mynd i'w marwg o bobl i'r ymdwy? I know it's very difficult because they're very busy people but I would like to see further engagement. Perfect. What do you think are the most important issues for students at the moment? There are several issues and I do cover some of them in my manifesto but at the moment I would imagine accommodation is probably one of the biggest because the rent hike has been introduced just there recently so that's a very topical one but even across all three campuses facilities placement is a big one because it's integral to almost every faculty in the college so that is an issue I would like to improve the supports in and actually make the experience better for students. Sure. With the rise in accommodation how would you plan on combating this issue if elected? I think it needs to be combated at a national level because there's very little we can do by ourselves. Considering that the 4% raise has been nationwide I think we should lobby with other students unions across Ireland and actually lobby the government. Sure.  No problem. My manifesto is established on four points that affect all three campuses. The first one would be facilities because all three campuses are lacking basic facilities such as functional water fountains extra seating desks especially peak library times and exams along with more convenient amenities like microwaves, phone charging stations and just general facilities. My second point is placement because as a past student I'm home first in the placement for teachers and I know nurses and intra so there's a lot of placement that goes on round and people have said to me that they're left to their own devices when they get into placement which is the last thing you'd want. One of your entering the workforce for the first time. So I'm looking to bring in better supports and actually tailor a care package system for students entering the workplace. So which would offer nutritional guides, basic physical and mental exercises, promoting just mindfulness and healthy sleeping for people like entering the workforce. Just to actually give them a bit of structure because it can be heard when you have assignments and work and you're still doing a part time job at the weekend. So it's very hard to manage as a student. And finally why should students vote for you? That's a good question. I would like to say that I'm a very approachable person and I look forward to engaging with people even on the campaign trail. I love talking to people. It is the gift of the gab so I would like to say that I bring a friendly demeanor to the role. Thank you so much.


Hello everybody and welcome to yet another episode of Nicola Complains that some other projects announcement is not very useful or useful enough to his opinion. So today we're going to talk about Dipping23, which is actually an announcement that the more times goes on, the more it confuses me because it was announced in back in August actually. And it had some features that were maybe not immediately user facing, but actually rather interesting. Like as an example, a major one is this Linglong, whose name is trouble. Let's be honest. Let's be Linglong is not a name that you can try to marketize in our Western countries. But anyway, Linglong, which is like an alternative to flatbacks and snaps. So that is something I totally did not expect from Linglong, from Dipping, sorry. And then there is atomic updates, which is actually something that in my opinion is very useful to have in distribution. So it was an interesting announcement. It was actually very technical. And just after this one, we had a series of very specific and technical blog posts about how all of these features actually work under the hood, which was super nice. Now here's the issue. All of these articles eventually said we are going to do more articles about this to fully explain these functionalities. Here's the thing. They never did that as far as I know. And actually, if we go to the news section, I can't find these technical articles. So that is also weird. It seems like I guess they had to take more time that they expected to finish up the release, which is fine, which brings me to today. It seems like we are closer to the Alpha version of Dolphin 23 or rather it's released because we can actually download an ISO from August of this deep in 23. And this is because I think they're starting to announce and marketize their new applications that will be in deep in 23, which is interesting. Now they have done three videos so far, I think they will do more. And right now they focus on the music image viewer and also image viewer. Okay, so they've done two videos on the image viewer, but different ones. So I'll go through them. So they'll probably do more. They're posting them at regular regular intervals, and they're very interesting. However, I do feel like they don't provide any kind of information about how we should expect this deep in 23 to actually be. There was a leaked screenshot of an article about deep in 23 that was removed because it didn't get a positive traction. So that is also weird. And this screenshot actually showed dipping to have quick settings in its floating panel, which is interesting. I think actually a step in the right direction today I can speak. Let's see what I'm complaining about about these videos. So this is the first one. And I've actually seen lots of people praise this video. Now here's the thing. So what is this talking to us about? So there is this in application. Now, all of these things is 3d renderings that give us little to no information about the actual look of the application when it's going to be released. I doubt as an example that we will see floating hearts appearing when you actually click on hurt on anything, you know, on that button, like, I guess that was just a 3d rendering. And we also select floating thing is which also won't get in the final UI. So we can try to guess what the UI is like taking all of those elements aside. And when that is done, the result is so, you know, empty. Okay, this one is it. This I think is the best shot we can give at what the application will be like. And my kind of reaction is, okay, like, is this the whole point of the video? I'm kind of not sold on this concept. But, you know, Microsoft does it must must work. The application does look nice. However, that is, I think, really not a point with deep end. I've criticized dipping before for what they have, again, these views, I have no clue whatsoever to be honest, how much these will close resemble the final product. These are 3d renderings. Like, I don't believe this is the final application. How will it actually look like? How close will it be to this? Maybe very much. I don't know. This is what confuses me. This is actually something that we have to be extremely careful about when we are working on a plasma and on spent. Often they are 3d renderings or animation, this kind of things. We always need to be extra careful that they actually resemble the exact look that the user will receive even though they're 3d animations and such. Because otherwise, we're not actually giving much useful information. And as I was saying, deep end, I do have many criticism about the desktop. I've done an interview about that. But the whole point of the deep end is, okay, yeah, looks good, but does it work? Like, can you actually use it day to day? It's the same thing with Maui applications. Yes, they do look nice, but I wouldn't use them because they lack so many functionalities that are still being too heavily developed. And deep end has actually done, they went through this is the third redesign to do actually. And going from the first design to the second, they made things worse. Yes, it was shiny looking and everything, but functionalities went away. This is the image viewer. And again, okay, this is the icon, fine. And then we start seeing 3d stuff like icons floating. Yeah, yeah, like, I don't know. Is this going to be like, is this going to be the UI of the image of your, yeah, I mean, and then there's this. I'm really confused about these videos. What are you trying to tell us? I mean, the message is pretty easy. This is actually a super nice feature. This is something that you can announce just doing like these 3d renderings that won't look like the final product because it's a new feature you're adding being able to select text from a major image. Okay, that is clear, but animating the whole UI in a 3d way. Do you remember when Microsoft did that to the PowerShell and then that the end product was looking nothing like the 3d renderings? I do remember that. So personally, I think that deep end 23 is a very interesting release. I'm actually, you know, looking forward reading news about it. And I'm following the blog post and such. And I'm just confused, genuinely confused about how it's being handled because there we have these articles, and we were supposed to get more, but we didn't. And then there was another article with a screenshot that also got removed. And now we only are left with the 3d renderings of the applications that will be in deep end 23. Okay, okay. However, I do want to end this like on a very positive note because if I saw the last version of deep end, as I said, I didn't like it. If they are, they managed to do all of the designs that they claim they are doing correctly and everything works nicely. This by the way is the Linglong, sorry, the name is the Linglong website to download the apps. If they managed to implement all of that correctly, they do not take off features and everything is still user usable. I mean, I promise that I will do a video saying that they did everything correctly and that they've done a great job. I'll do that. Make sure whatsoever. Right now I'm just what?


The cohort model was shaped to account for psychological data on the perception of language. It assumes that there is a separate active processing element associated with each item in the lexicon. As soon as there is a match between the input and the perceptual specifications of these elements, syntactic and semantic specifications associated with a respective lexical item are brought into operation. The following animation shows the gradual shrinking of the cohort of potential candidates with increasing input information. In an extended version of the cohort model, several cohorts that share the main perceptual specifications of the access unit are activated simultaneously. This extended version accounts for our ability to identify even incomplete input.


Welcome back to Kids Fun Science. My name is Ken. Today's experiment is how to make invisible ink message with no heat needed. What you need for this experiment is a bowl of water, a mirror, a pencil, paper, and scissors. So you're going to start off with two pieces of paper.  So you can see I have exactly the same size two pieces of paper and they have to fit on the mirror.  Make sure there's no wrinkles in it that's completely on top of the mirror then take your identical piece of paper that's dry and put it on top of the wet piece on the mirror and from that point is you're going to write out your message to whatever you want it to be for your secret message. So here I'm going to write to you to YouTube and thanks you guys for all your support for over the years I do really appreciate it and and that you know if you like this video make sure you like and share and I appreciate it kids fun science so and a little happy face there for you and so that's going to be my message then you take off the top piece or you can take off both of them take off the top piece that's your message that's not the secret one and then you take off the bottom piece so you have to be careful because the paper is wet and take it off very slowly off the mirror and you can see I just want to show you it's already starting to be a little bit invisible and so there's your message right there you still can see it but the point where it becomes invisible now is you either have to use a hairdryer I put it out in the sun and you can see it's disappeared and you cannot see the message on the piece of paper to be able to reveal the message you're going to re-dip it back into the water now after it's been dried so if you send it to someone and they get it they're able to put it in water and then once it's in water they'll be able to slowly but surely it'll show the the message overall so I did have to put out the sun to re-dry it to be able to see the whole thing you can see it's starting to come up right here you can start seeing the message up here and over time and after I dried it up you were able to see it a lot better and I'll show you shortly so when it first comes out of the water you can see it's starting to show a little bit more as you go and so you can see my entire message and then as it dries out a little bit and you put a darker background you're able to see the whole message so this is a lot drier here and then this is at the end I put out the sun and you can see the entire message right there so this is a really cool experiment I did one another one a little secret message for yourself so you don't know what I'm going to say here I put it in after I've already dried the paper and now I'm going to reveal it and it says thank you very much so I hope you guys enjoyed this video and this experiment and if you did please like and subscribe and to share and thanks for watching


Borno State Governor Professor Babagana Umara Zulum says Boko Haram fighters layer recruits with as low as 5,000 Naira. The governor also reveals how his government sustained a fight against insurgents in the state in the last two years. He made the revelations in his statewide broadcast to commemorate this year's democracy day and his second anniversary in office stating that of all Nigerians, 36 states none is faced with the level of Borno security and by extension social and economic challenges.


I think it's time to get started. Welcome everybody. I'm Cliff Lynch. I'm the director of the Coalition for Networked Information and I welcome you to this breakout session which is part of CNI's Spring 2020 virtual meeting. Now in the beginning of its second month it will run till the end of May. We'll be hearing from our presenter today. We will take questions at the end. Diane Goldenberg-Hart will materialize and moderate the Q&A. There is a Q&A button down at the bottom of your screen and you can use that to queue up questions at any point during the presentation. I urge you to ask questions as they occur to you and that will save us time at the end when we go to answer them. Topic today is data science support and how to build capacity through graduate fellowship programs. This is a very timely issue certainly in our recent work on emerging technologies that will have high impact on research libraries in the next few years that we've been doing jointly with ARL and EDUCAUSE. Data science has been identified as one of the top priorities. It's really, I'm a little uneasy calling it a technology because it's really a group of related technologies and skills but how to build sufficient capacity for it is a major challenge at all of our institutions and I'm delighted to have Jeffrey Oliver from the University of Arizona who will be presenting on behalf of the team who you can see listed on this slide here who will talk about their experiences and strategies in this area. Thank you so much for doing this Jeff and without further ado over to you. Thanks Cliff thanks for that introduction and thanks to all of you who who are here today. So the first thing I want to start with is to recognize the collaborators that I'm working with on this on this program. So this has largely been a collaboration between myself and Dr. Vignesh Subin in the College of Engineering to create a program for graduate students to support data science at the University of Arizona. It's further supported by the University of Arizona Data Science Institute first with Susan Miller who retired on Friday and now by Malika Oxham. So without these folks this work just would not have been possible. When I usually talk about data science, usually the first thing we have to do is really to define the term data science. So if you look on Google these are the top suggested questions that folks are asking and I think they're pretty telling because they're really asking questions about what this field is and you know how to explain it in terms that a normal person can actually understand and so that's what I want to start with is just what do I mean when I say data science and try to do it without a lot of jargon. So I look at data science and this is one definition not the only definition but one which is really this overlap of three fields and the overlap of computer science really to use advanced mathematics and statistics and apply those technologies to some area of interest some domain such as biology or astronomy or linguistics and really to address questions in those areas and data science also includes really critical skills around communication and ethics that is sometimes overlooked but really data science for the purposes of this talk is going to be the overlap of these three areas. Now I think that as Cliff mentioned in the introduction there's a really a consistent growing interest in data science going back to Google if you look at the searches for the phrase what is data science for the past 10 years you could see a steady climb upward in in that search and just uh I want to take 10 seconds and have you look at that graph and notice that every year there's a spike so what is the spike and although I can't say for sure one of the things that it does correspond with is that's the start of the academic school year so I suspect that when folks are looking for majors when they come to college they type in and what is data science so that's kind of a kind of a fun fun look at the data and when I consider this definition of data science as being the overlap of computer science mathematics and subject matter very frequently that third element is is not discussed much so really the subject matter expertise is super important to the field of data science and to being able to making meaningful inferences using those approaches from mathematics and statistics in some domain very frequently we talk about machine learning or neural networks or some part of data science where we sort of forget the subject matter as expertise so the challenge of course is that that there are a lot of domains across the college campus these are just some of the examples of the way data science is being used across domain we have it being used in uh in the the field of of uh english just looking at actually who wrote texts such as some of english uh some of uh shakespeare's works we also see it playing a critical role in public health and being able to provide sort of uh on-demand or at the moment uh help and then finally we're seeing a lot of data science applications in the field of biology looking at how how organisms are responding to the changes in seasons using data that are just too large to be analyzed through traditional approaches I want to give a shout out at this point too to subject matter expertise uh earlier today the team at UNC gave a really cool talk about using machine learning to identify jim crow laws so really a prime example of how the libraries are engaging in the data science realm so if you didn't get a chance to see their talk live earlier today I would highly recommend going back to watch the recording because they did a really good job so and really showing how libraries are going to make a meaningful contribution in data science so if we think about data science as being a very diverse realm we can't really hire a subject matter uh expert in every domain in the libraries it would be nice if those resources were available but they're not so how can we still support data science across campuses and so if we think about supporting data science what do we need to actually do that so one thing we need is we need experience so we need folks who have experience in applying modern computational and statistical approaches to address these domain level questions to address questions in astronomy questions in biology questions in linguistics and then we also need folks who have an interest in data science education in helping others level up and gain access to the knowledge skills and abilities so that they can use data science approaches and I should say that while pandas is an important python package for data science this panda is actually here to remind us that uh we would normally be in san diego this is from two years ago from the cni meeting in 2018 it's a panda from the san diego zoo so a little a little bit of san diego coming coming to you all even though we couldn't uh be at san diego and so these needs of expertise and interest in data science education there is considerable capacity for both of those in the graduate student population and so there are several graduate students who actually have the in the trenches experience of learning how to do these these new computational approaches and applying it to questions in their own domain and then there's also an interest in actually helping others to acquire similar similar approaches and similar skills to be able to do um the types of data science analyses uh in their own in their own uh field and so what we did is we created a program called the data science ambassadors fellowships and what this does this actually capitalizes on the knowledge that is present in the graduate student population and it provides infrastructure so that they can support researchers in their data sciences needs so what is the program actually what does the program actually do so the first thing we do is we uh provide training to all those who are part of the data science ambassadors program and we start with actually the carpentries instructor training this is a two-day program that happens uh it actually happens online for the most part but it's a two-day program where everyone in the training receives uh received instruction on good pedagogy especially for teaching computational skills on the importance of motivation in creating a positive learning environment and then also recognizing some important parts of the learning environment such as imposter syndrome the stereotype threat and and the idea of a of a growth versus a fixed mindset so this is a really really great training program and I would say that even if you never become a carpentries instructor it's a super useful program and actually all of the materials are available online for anyone to use so if you even if you never teach a carpentries workshop but are doing instruction in the realm of computational literacy I highly recommend this this training so this is the first thing that we ask our instructor our ambassadors to to go through is this training the next thing we do is we work with them to develop a roadmap of expectations so each of the ambassadors creates what we call an engagement plan where they lay out in each of the two semesters in which they'll be an ambassador they lay out plans for how exactly they are going to serve the researchers in their particular domain it's going to be tailored to the constituents that they serve so really the scholars that are in their respective colleges as well as their own expertise what they feel comfortable providing support for and what areas they may may look to collaborators to help out and on these engagement plans it's an iterative process where the ambassador's draft and engagement plan the directors myself and and big Nash provide feedback and we we usually go through a couple of rounds of the engagement plans till we get to a final draft so one of the challenges with with data science resources and you probably see this on on your own respective campuses as well is that there are a lot of data science resources across campus and there's really no one place that has all of the resources and so what we've done is is we started with a with a relatively slim document a data science resource guide and then we asked the ambassadors to curate this document that has all of the resources across campus that they can either use themselves or direct their respective colleges and to find support so this this resource guide includes various service units as well as people who are working in specific data science areas and it includes things like where they can get support for high performance computing for statistical consulting cloud computing resources and the ambassadors have actually done a considerable job of contributing to this guide so it's it sort of removes the burden of everybody going and searching the the university's website to find resource x we now have a single guide that they can use to navigate now the ambassadors aren't doing all of this for free there is a stipend that we provide there's a lot of professional development that we're providing to the to the ambassadors but we also recognize that labor is important and that graded students should be compensated for their their labor and so we provide a small stipend and it's not meant to replace a graduate assistantship or a ta ship really it's just to support the a little bit of the the efforts that they're doing and this is one thing that that you know we're mindful of is that we're really only asking for about 15 to 30 hours of their time each semester so we we are really careful and mindful that grad students have a lot of work to do and that they are compensated for it and so with the support from the the University of Arizona Data Science Institute they receive a a small stipend for for their efforts but this is as I mentioned before like we don't anticipate that this should take up all of their time and it really should be taking up a minority of their time and so how do we do this one of the things that we really want to avoid is exploitation of graduate students so there was one example where a graduate student of one of the Data Science Ambassadors somebody asked for help and really at the end they were asking for the ambassador to do their homework for him and so I provided a little bit of guidance but actually the rest of the Data Science Ambassador cohort did a really good job of how to how to handle this and how to actually you know it's okay to say no and we use slack for communications among the ambassadors and the community did a really good job of supporting the ambassador with sort of guarding their own time and providing an appropriate level of support another thing we've faced not from uh not from the ambassadors and not from students but from uh it's and this is a very minority reaction is uh some of the faculty or some professors are not really uh excited about recommending this to their students so so the question is you know why would I tell my student to do this um and so you know we we reiterate the benefits not only to the students so there's a lot of networking opportunities there are great skills development but there's also benefits to the to the research group so they can bring back best practices and provide training to the research um you know for some people this is uh this is competition with data collection or analysis that their graduate students quote unquote should be doing and there's only so much that we can do um some folks are are not interested in that and that's okay uh we still have enough uh we have enough interest from from the college uh without worrying too much about that and so one of the things that we did uh changes that we've made recently is the first year we actually had a uh a self-nomination process uh in the second year we switched to uh have colleges actually nominate the candidates and so one of the things that this does is is it provides uh sort of buy-in from the colleges it gives them agency because a lot of the colleges the first year were quite sure what the ambassadors were supposed to do or what they were for and so by going through the colleges and asking the colleges to nominate the the students uh that gives them more agency and they have a little bit better idea of what uh role the ambassadors could serve the college because we are asking the nominating units the colleges in this case uh for for a stipend it makes sense that they would have uh the choices to who to nominate and actually we also provide them the opportunity to nominate more than one ambassador if they have the if they have the the support needs to do so if we compare just the first uh just look at the first two years uh there's been growth in the in interest in the in the program we've actually from year one to year two we doubled the number of colleges that there are ambassadors in and uh the interest like I said just seems to go and I just take a quick glance this is not an exhaustive list of the sorts of things that the ambassadors have been doing but they're providing a lot of consultations to scholars in their respective domains they've been either instructors or helpers at four software carpentry workshops here at the University of Arizona and they've also been standing up their own standalone workshops doing workshops in things like common scripting languages such as r and python orange is a really nice uh graphical user interface for for for data science applications especially machine learning as well as work in in geographic image information systems and it's really uh it's really cool one of the things that doesn't show up in this slide but I want to mention is that uh this latest round of cohort we have an one ambassador to the College of Humanities and one ambassador to the College of Education and these are realms that you may not immediately think of for data science but it's really cool to see this ambassadorship program really reaching in and engaging with domains across the campus that are interested in in data science in different areas or at different levels of maturity in data science and that's one of the things that's great about the ambassadors program is that they're able to assess where folks need help at what point in the sort of data science maturity um cycle that they need help these are some of the specific um works that they've done really surveying the landscape of needs for data science uh as I said we had a college we have an ambassador to the College of Humanities and really introducing data science I think the topic of the workshop that they ran was something like what is humanities data and what do we do with it that was really good another standalone workshop was the the introducing machine learning with a great a great python tool called PyTorch and they've also gone beyond just doing individual one-off efforts the first cohort of data science ambassadors actually were instrumental in launching the University of Arizona inaugural women in data science event in 2019 there were over a hundred folks who participated and it was a great event we've done it again this year but it was a data science ambassador to really provide impetus to to get that started the data science ambassadors in the second cohort are currently leading the organizational efforts for our 2020 research bazaar and they've also been in a variety of other involvement in a variety of other efforts including the Our Ladies one of our data science ambassadors actually the local organizers for Our Lady workshops and we also have another ambassador who's working quite a bit with the Code for Venezuela project so that's the first two years and the third cohort actually the deadline for applications was was on Friday and so so it's 2020 and we're in the middle of a pandemic and in the face of the economic crisis that's coming there's concern about providing stipends for for graduate students and what sorts of resources are going to be available so I will be honest I was a bit apprehensive about about a response that we might get this year and and how it might diminish because of the the current situation but as it turns out it was probably not something I needed to worry about I think this is quite telling that despite the challenges that we're facing right now the interest in the program really remains strong is that we had another 13 nominations from five colleges and it's cool because they're some of these colleges college of science the college of ag and life sciences they're clamoring for more data science ambassadors they've actually nominated multiple multiple graduate students to play a role in the in the data science ambassador program so with that I just want to close once more by thanking the folks who I've collaborated with these slides that I have presented here are all available on google drive with the link and and the video is going to be posted later on I'm sure and I want to again thank especially the Gnash Sabine who's the co-director of the the data science ambassador program it was really through through working with him that we really launched this at this point I'll stop and I will address the questions that you have and I'm pretty sure that's going to be moderated by Diane yes it will thank you Jeff thanks thanks for your great talk that was really interesting and fascinating to see I was particularly interested to hear that you have an ambassador in the College of Humanities and I was curious to know if that was a targeted recruit or if that was a spontaneously occurred on its own or is that something that you guys are looking to balance your portfolio how did that happen yeah so so the first so so the it wasn't necessarily targeted we we didn't reach out to we sort of put the call out to all college deans to see to to gauge interest and it really is but but there is a there is a intentional diversification on the part of the directors to engage with lots of colleges so one of the things we we did not design a program to support a bunch of graduate students in the computer science department that that's not the purpose of the data science ambassadors program and so really it's a matter of trying to engage with as many colleges as possible across the campus so yeah good good question interesting all right thank you for answering that and sorry that I jumped in line everybody but I just couldn't resist asking and with that I just want to introduce myself I'm Diane Goldenberg Hart with CNI and welcome to Jeff Oliver and thank you for giving that great talk and welcome to all of our attendees thank you so much for joining us as part of CNI's spring 2020 virtual meeting we're really grateful to you for making time out of your day to join us and with that I will invite our attendees to please go ahead and type in any questions you might have in the q&a and I will read them aloud so Jeff can answer them live or if you prefer type them into chat and I will read those too uh questions comments anything you'd like to say and I see that we actually do have a question already that comes to us from Amanda Henley who was one of the presenters in our last webinar this afternoon uh Amanda writes this looks like an amazing program I wonder about the hours it seems like the need for consultations would easily fill 15 hours have you had trouble with students running out of time we have not um and again part of this is we try to remind students to be mindful of their time and to remember that their primary goal should be to go ahead and get a degree while they're here um but uh I I mean there's only so much I can do to tell students don't spend too much time on this stuff uh and I think they probably all go over and I think to some degree the way I look at it is we really we really make sure that they are not spending too much time on them and really tell them to back off if if they are um but they are I think when they go beyond the 15 30 hours they're getting experience that I think is making them more competitive for whatever comes next in their careers it's something that uh we're trying to assess just the impact one of the things that we do at the end of each cohort is we have a self-assessment and so we're trying to get feedback on how much time are they spending is this something that's that's too much um but it really does seem like they are none of them are none of them feel too pressed for time for the ambassadorship but it's something that I actually want to spend a little bit more time to focus on so that's a great question Amanda thank you for asking that yeah that was a great question thanks thanks Amanda thanks for the answer Jeff and we have another question that came in from Jill Sexton who asks are students largely providing consulting services to their peers to researchers or both and I'll take the liberty of just adding to that that we uh Cliff um ran a series of roundtables in April talking about research continuity and one of the things that we heard in there was that a lot of faculty members are realizing the gaps in their knowledge and how much they've been relying on their students and are seeking training now as a result of the current crisis so I'll sort I'll throw that in there as well to appendage to Jill's question yeah great great question Jill it's great great add on there Diane the answer is both so they are both providing support for their peers and that may be the majority of the the support that they're providing given uh given one the numbers and and two sort of who's doing the work so a lot of times it's graduate students who are who are protest with um data analyses and and and PIs a little bit less so but um I would say that it is mostly peers but uh they are very frequently going beyond uh their own I would say department and extending support uh more towards a college level um because even though a graduate student in linguistics uh may not necessarily know sociologist that much about sociology they still are close enough uh discipline wise that it's easier for them to talk about applications and challenges than it may be for for me who's a biologist to to address those things so I would say they're providing support for both peers uh as well as as PIs um although in the in the case of the PIs it may be sort of an issue of really filling in those gaps that Diane was talking about earlier good question Jill interesting thank you and another question from uh Nancy Hobel Heinrich she asks how are the students deciding what kind of workshops are offered e.g. the carpentries workshop that I think you mentioned are those for specific colleges or cross colleges yeah so the so the answer to that is also probably both uh the carpentries workshops those are organized uh outside of this the data science ambassadors program we have a unit on campus that that organizes and coordinates uh the carpentries workshops software carpentry workshops that we run uh our domain independent so those are those cut across all domains um we have run a couple of data carpentry workshops data carpentry for image processing and data carpentry for uh for GIS uh data and analyses and those uh those the the data science ambassadors who who have expertise in those domains those are the ones that they help out as far as the individual workshops that they are that they are providing that's something that we actually uh work with them to identify appropriate sized audiences so we're we're we're a little bit less keen to have ambassadors run a workshop where the only attendees may be their lab group because then then you don't have quite the reach that you would like to have with the ambassadorship program so what we do is we try to provide uh enough guidance so that they can create a a workshop and a space that will be accessible to uh at least a departmental if not a college level audience so good good question it's it's a little tricky right every situation requires a little bit of different attention but it's um I think it ends up being uh worth the effort to try to identify appropriate audiences yeah okay interesting thank you for the question Nancy thank you for addressing that Jeff and we have another question from Amanda now um Amanda asks are the ambassadors given space in the library to work and where are they located on the org chart oh so uh so that's a good question so the ambassadors are for the most part not provided space in the library um the library the university of Arizona library is is in the middle of towards the end of uh some uh significant construction with the with the library space and so ambassadors are not given explicit uh workspaces they ideally as a graduate student you have that provided by your lab um although the library does provide that for for graduate students who do not have that um but I will say that if ambassadors need space for consultation or they need space to run a workshop that is something that we work with them to provide space in the library the library just opened up a new a new area it's called the catalyst studios it includes both our our sort of our data science area as well as a brand new maker space as well a variety of consultation rooms and the ambassadors have been making quite a bit of use of that area to provide support in data science but one of the things that I think the ambassadors are really good at too is also meeting scholars where they're at for meeting in in whatever college or department uh the folks who who need the support are yeah it would be yeah it's interesting to think more about that it's about how do we provide that space so that they can provide more support that's a good question and I'll have to think more about that one we just heard about the catalyst studios um last week great yeah project briefing and c&i was fascinating and looks like a really exciting space so it's super exciting it's so nice to have that space yep it's terrific okay thanks thanks for that Amanda uh and from Cliff Lynch we have a question Cliff asks what's the duration of an ambassadorship and can they be renewed excellent question so so we're we're um sort of thinking about that right now what that looks like so the duration of an ambassadorship is a one academic year start in the fall and you go through spring but one of the things that we sort of miss out on when we do that is we miss out on continuity to some degree so each cohort is independent and each cohort sort of starts starts anew but I think what we're going to do this fall is we may experiment with a couple of senior ambassadors so we're asking there's a pair of ambassadors um in the current cohort who are not graduating uh next year and so we're going to try to work out something and ask them to be uh senior ambassadors we're not sure exactly what that looks like we're still working through it but I think that that would provide an important level of of continuity and and pardon me uh mentoring from one cohort to the next so thanks for the question Cliff yeah that sounds like a great idea and what a what a great opportunity for the students yep well we had lots of great questions thank you so much everyone for that and Jeff thank you um we're drawing close to the end of our time if you have another question please feel free to type it in but I also just want to let folks know that um we do have the uh capacity to unmute you if you're interested in uh making a comment live asking a question live uh so if you would like to do that now we are recording and if you would like to do that on the recording please feel free to go ahead and raise your hand and I'll call on you um and I'm sorry I will I will unmute you um because I can call on you all I want and nothing will change unless I actually unmute you so um but go ahead and raise your hand or type in your question and while we're waiting to see if there are any other questions or if anyone would like to make a comment I just want to go ahead and share with you in the chat box there a direct link to the schedule for CNI spring 2020 virtual meeting which we'll be continuing on through the end of May so we have lots and lots of webinars yet to come and I hope you'll take a look at that sign up for some and let us know what you what you think so uh looking at our boxes now I see we don't have any more questions so I want to just thank you again Jeff this was such an interesting talk and we really appreciate you coming to CNI to talk about uh your project and the ambassadors at Arizona it was fascinating and please go ahead oh I was going to say thank you it was it was cool to talk and thank you also to all of our attendees it was great to have you here so