Now, the Mole Mystery Theater, presented by M-O-L-L-E. Mole, the heavier brushless shaving cream for top whiskers or a tender skin. Welcoming you to the Mole Mystery Theater, the program that presents the best in mystery and detective fiction. Tonight's mystery, entitled, Where's a Mask, was written by Robert Mitchell and Dean Levitt and stars Bill Quinn. The story of Joseph Talbot, who escapes from prison and tries to claim the woman he loves. To do so, he finds himself forced to assume two aliases. One is a common and up-name John Mason, but the other is Humpty Dumpty. And his short career follows that of the mother goose character rather closely as he finds that death wears a mask. Well, so Mr. Barnes, you sure have me curious about this Humpty Dumpty character I can hardly wait. But first, there's one thing I just can't help saying. It's this. Man, if shaving top whiskers or a tender skin has you hollering for help, then call for Mole. The heavier brushless shaving cream. Yes, sir, it's smooth. So smooth. It's slick. So slick. It's a smooth, smooth, slick, slick shave you get with M-O-L-L-E. The heavier brushless shaving cream for top whiskers or a tender skin. Try it. Mole. Now for the nice Mole mystery. Death wears a mask. That's when my insides turn to ice water. I clamp the rigid grip and my courage up to then held onto my pores and my feelings until I unfolded that black mask. Then I got scared. Really scared. That's when the whole awful business boils from my mind like a churning torrent. The torrent of grinning, gaudy faces of laughs and shrieks on the mountains. Garage distorted faces that bobbed and waggled as the fantastic convincing figures reached out crying for me. The evil Duke of Gloucester, Captain Kibb, Clear Pottsley, George Washington, Napoleon Lucifer, The Black Prince, All of them and more, comforting in a mad circle around me. Kidding and taunting and gassing for me. Joan of Arc. Joan of Arc. More beautiful than I'd remember. A mask gone. Staring up the sky. As the silent ripples, dancing over her face, slowly darkened. In the instant it was left, my mind plunged back through these memories to the point where it all started. Back to the night I walked in the shadows of a flagstone path. And stopped a moment to look at the name on the door before I pressed the bell. Joseph! Surprise, Brother John. Come inside quick. Is that wise? Perhaps you're cooked. Or your wife alone can be before someone sees you. This is if you've done pretty well for yourself in the last four years. New city, new business, even a new name. Mason now. Talbot was a little carnage, say, John. Never mind all that. How did you get out? What do you mean, coming here? Take it easy, John. One thing at a time. I broke out. I shot a guard. Joseph! You may have died, I don't know. That tough time last night, a tougher time today. Getting down here and finding you wasn't even. Do the police. No, they think I went east. I'm okay for a while. Now see here, Joseph, I can't afford to... Besides, John, where else would I come for help? Except to my big brother. Well, of course I want to help you, but you must realize... Why don't I pour a drink? Oh, help yourself. Been four years since I've tasted whiskey. You have to be a hunter to know what it's like to really relax. Now, little music on the radio. Joseph, you've got to get out of here. Some friends of mine will arrive in a few minutes. I'm expected to go out with them to the annual masquerade ball. That's all. That's too bad. I'd hope for a chance to talk to you. By the way, where's Cliff? He's gone ahead to the ball she was on the committee. Oh? Since I'm a traveling man, I'll need cash and some clothes. It might be a long trip, so... Make it heavy on the cash. No, wait a minute. No, Juan, get the money, John. Bring it off. Well, I'll bring what there is in the safe upstairs. My clothes will be a little large for you. You'd better take sports stuff. Wait here a minute, Joseph. I won't be long. You better not be. Well, so far so good. The whiskey was warm inside me. And the music was low and sweet. I dropped my head back into the soft, smooth cushion of the chair. It closed my eyes. The gentle music flowed from the radio and smoothed me. Almost subconsciously, I became aware of the clicking that had intruded into the melody. Absently, I remembered it was like... like a telephone being dialed. The extension upstairs. I sprang out of the chair and dashed across the room. The downstairs telephone sat on a small table in the hall. Mr. Sergeant, never mind who this is. I just thought the police on and all that, Joseph, told that the escape comes into the town. You're jumpy, John. I think you're playing with me with you in the house. I'm just 1200, that's all there is. Okay. I got restless downstairs. You were taking so long. I had trouble with the combination, huh? Where are the clothes? Hey, the devil is this stuff. It's egg business and these striped pants. That's my costume for the night.  I told you, it's a costume ball, masquerade. Oh. It's a little flashy for me. Here, I'll take that suit, some shirts, a couple of ties, some socks. All right, put them in this bag. Take anything you want on me.  My friends... Yes, yes, I know. They'll be here any minute. Quit worrying. You have more important things to do. What do you mean? John, did you ever stop to figure how long four years are? A man can figure a lot of angles in four years. I've been thinking all that time. How helpful you've been, John. Well, I've always tried to do what I could, and you've done so much, John. Like when Claire was my wife, and we were flat broke. You took us in to live at your house, remember? Well, I... You found me a job, that bookkeeping job, remember? To help me learn it, taught me the tricks. We had a nice little penny-ante deal going. And all of a sudden, I got arrested and tried for grand loss, and you remember that? No, look, Joseph, but I got the axe. Ten years, they said. But even then, you helped me. You promised to look after Claire for me, to take care of her. And you did. You married her. Oh, no. Now, wait a minute, Joseph. Claire and I, we... Well, I fell in love with her, and you were gone. If it wasn't fair for her to wait, you can't expect. Maybe you're right. Maybe we're square. Joseph, you know I'll do anything I can. Right to me, anytime. I'll send you more money, Joseph. After I leave, you won't call the cops and tip them off, John. Of course not, Joseph. Good heavens, you're my own. Wait a minute. That was a statement. Not a question. Right. Much I hated, John. Until I found myself presenting the neatness of the little round hole in this forest. But now I had to move fast. I snapped the suitcase shut on friends. They were at the door. It seemed to be John. Our forces weren't alike. Hi, you two. Sorry, I'm a little behind schedule. Make yourself a drink. Into this rig. I'd go to that dance and John's outfit would be clear now tonight. Maybe she'd come with me. We could leave the country together. The costume was big and baggy. I slipped it on over my clothes except for the long point of shoes. Then the headpiece. The egg with a painted grinning face. I looked at myself in the mirror. It was funny. Really funny. All I had to remember now was to play the part. Played John out for a good time. Part of you, John. You look pretty good yourself. Clear parts, all right? And cats and kids.  Running through the type, aren't you? Okay, I get it. You're going to be nasty. Hey, your voice sounds different. You sound like you have a mouthful of moisture with that thing over your noggin. Oh, my goodness. Well done tonight. Come on. Certainly with hands.  What's this up ahead? Huh? What? Looks like a barricade at some time. Oh. Huh? It's a roadblock. Here's a tabletop that looks as though Humpty Dumpty is set for a fall. Now, we shall see in just a moment when we bring you at two of tonight's Mole Mystery. meantime, here's James Seymour with a message for a certain group of our men, listeners. For the same end, for a long time now, we've been having a lot of fun reminding you about Mole. Even singing a little song about it. Well, we hope you've had some fun out of it, too. Especially learning about those smooth, slick Mole shades. And to those of you who just never got around to trying it, all we say is, next time, ask for Mole. You know, many of us miss out on a lot of good things by not trying them. Try Mole. The heavier brush reshading cream. Notice what close, comfortable shades you get, no matter how tough your whiskers or how tender your skin. Yes, as plenty of men have discovered, because Mole is a heavier cream, it not only softens your whiskers, it stands them up straight and lets your razor shave them all faster. Closer, easier, and painlessly. So how about it? Tomorrow, get a cube of Mole. The heavier brush reshading cream for tough whiskers or a tender skin. And now this is Jeffrey Barnes returning you to act two of Death, War, and Mass. We're stopping all traffic. I strength back at least to see that the cops stepped out in the road. I'm finding a hope. Welcome aboard, Tim. It's me, Bill Brady. Oh, it's the Brady. Well done, Tim. He traced an escaped convict to this neighborhood, killed a guard at the prison last night, armed and dangerous, protecting everything that looks suspicious. That's us, Tim. Captain, Tim here is wanted for piracy. I'm wanted by Mark Anthony.  It's the only innocent aboard. Well, let's see about that. Hey, that sure is some get-up estimation. Sure you're not a bad egg? Ho, ho, ho. I'm pretty bad, Tim. You might say that the yoke is on you for letting him go. Ho, ho, ho. Brother, how corny can you be? Okay, folks, on your way. Have a good time. There's an old mother hub at the Tandaleo. They were all here. As I moved through the crowd, I made quite a hit in John's costume. No idea where to start looking. Claire would recognize this Humpty Dumpty Rig. Maybe she'd spot me. Once, a girl alone walked up to me and I stopped. Hello. Oh, you look marvelous. Smile.  Claire? No, wrong number with her. I met Anna Fogg. Can't you tell? These confounded masks. I moved toward the back of the room and then I noticed Joan of Arc standing alone in the corner. She was waving. I looked around but no one seemed to be paying any attention. She waved again so I walked toward her. Hello there. Wonderful. Your costume is the best in the place. You really think so? Yes, I told you, I would do it. I'll give you that now and then we'll pick you up on time. Oh, sure, sure, plenty of time. Although, that thing might be late. Oh, we had an awful mess here. Never again will I feel like a man's coming here. Would you like a drink, Joan? What? What'd you say? It's a matter of your day. Oh, I'm sorry. I was thinking. Is something wrong? Wrong? Oh, no, no. There's nothing wrong. What? I'm sorry. He's sort of worried. It's not like he's feeling it. Oh, you're... Tom, look, you wouldn't sound the samey. Shall we have a drink? I'd much rather dance with you, Claire. All right, darling. Everything else faded away. Crowd, the color, the noise. Leaving just Claire and the music. I'd waited so long for this. I wanted to forget everything else. I love dancing with you, Joan. Does it stop there? Does what stop? Your love. Oh, you silly. Oh, John, before I forget, here are the car keys. I've almost lost them a dozen times. I guess Joan of art had no use for pocket. The keys to the car? Oh, okay, sure, sure. I've kept the moose over the handle of my poignette all evening. Happy with your what? The staggers. The real 15th century poignette I just found out. Oh, that's so. Well, by the way, where did you park? We're going at the end of the center lane. I thought we could get out faster. That's fine. Fine, darling. I'll, uh, I'll keep the keys. But, uh, we were talking of love there. Remember? Nice, that's it. Just where does your love stop? It's not with dance. I know. How? Good morning. I really want to know. I mean it. Something's come up and I must know for sure about you, Claire. You're looking. I've been more curious in my life. I've been more curious in my life. I've been more curious in my life. I've been more curious in my life. I probably suspect a scandal when Mother Goose dances with Humsy Dumsy. But, uh, this is our dance, isn't it? Shall we resist? Why, uh, I think... You know what you ought to declare. You held up over there. I think we can trust them. Hardly wait for the unmasking of midnight.  Unmasking? Admit that? Yes. We'll see who or what. But it's... it's 1130 already. Oh, well then, it won't be long now. There's Orson and Claire and they're not listening to us. I wonder what's wrong. Excuse me, will you? Well, yes, yes, of course. John, there was trouble in the headboard. Chief Denny just got a call. The police... What about the police? John, don't know this, didn't you? That's what you mean. Let's get out of here. We've got to talk. I'll go to the room, dance briefly on the quiet border of the fish pond. We were alone. Claire looked at me for a long moment and then... What are we going to do now? Claire, before you say anything more, please. Please answer my question. Do you love him? John, John, how can you even ask that? You know I do, darling. Say it. Say it, Claire. I want to hear it. John, I... I love you, John. I love you. Something I always loved you. Don't worry about him, Claire. You'll go away. I promise you that. John, well, he wasn't to get us, John. Why else would he come here at all? He knows he was pregnant and he must realize that we did it to get rid of him so we could be together. The meaning of a word jammed in my brain. I felt a terrible pressure swelling up inside me. Maybe we should tell the police to ease your body. We'll be waiting for us at home and ready. He became alive. We'll be talking again if I reach out and see the mask he wore. She stopped short when I ripped it from her face. Her eyes grew wide as I moved toward her in her mouth, a look. I was afraid she might scream so I can't put her hand over her mouth. I... I... I bent her head back and I told the little beggar she wore from its scabbard. She drove its point deep into her throat.  Lord Putnam, thousands of people who suffer the social and business handicap of Dandruff are discovering that the way to combat effectively is with double vanderings. Outstanding authorities explain that the most common kind of Dandruff is caused by a germ called Pityrospalmo Valley.  If you want real relief, the germ must be destroyed. And double dandering does just that. It kills this germ on contact. Even in many stubborn cases, results with double dandering have been amazing. Now, a special ingredient is the reason for double dandering's astonishing effectiveness. An active antiseptic, so remarkably efficient, many hospitals use it. In double dandering, we call it Alzan. So try double dandering and see if you don't agree that it really works. That it really does more than many dandruff fighting methods that actually are no better than plain water. Get double dandering tomorrow. It carries a money-back guarantee. I could make it if I could leave without being seen. I leaped up to the wall, clambered up on top of it and swung my legs over. I was about to jump when... Hey! You're up on the wall! Where do you think you're going? I... I... What's the matter, officer? At the same time, sir, there's an escaped convict in the neighborhood. Wouldn't be safe to go through these trees now. Oh, I... I'm not leaving. It's just a gag, officer. You know, Humpty Dumpty on the wall? Well, what does Humpty Dumpty usually do on a wall? It falls off.  Hey, where's Claire? Oh, didn't you see her? She just went up that path. I jumped down off the wall and led them away from the terrible thing in the fish pond. I left them near the ballroom and said I was going to find Claire. I thought about a side entrance, but back back when I saw a cop standing there, too. I cut across the dance floor, pushing my way through the people that kneeled around the edges. I was about half way across when... I tried to get far, but I was swept up with them as they pushed in close. Yes, this is my father. The most successful party ever sponsored by the Oak Bridge Terrace Country Club. I had to. I began to shoulder through the mob, forcing my way between the tightly packed bodies. Yes, oh, but that man's big! People began shoving me back towards the stage. They were all laughing and shouting. It gives me great pleasure to announce that the judges were unanimous in their selection of the masquerader, who played best the part portrayed by his costume. As the best clown of the evening, the grand cry is good. He was silver cup. I still thought I could clown my way out. I bowed foolishly and then... I turned headlong into the milling, laughing ring of Preston on me. I struggled to break two of them as they sweated and sang and clawed at my costume. They closed over me. They didn't know what they were doing. They were laughing and shouting. I felt the shell of my headpiece crack and they ripped it off. Then, hands were helping me to my feet. The deadly silence suddenly swept out through the crowd in a never-increasing circle. With me as the center. That's not John Mason. At my feet, twisted and grotesque and grinning, lay the hunky-dumpty mask.  Joseph Talbot, executed in accordance with the laws of this state and the sentence pronounced. Have you anything to say? Holding the mask, warped toward me. He slipped it over my head and tied it on. Then they adjusted the rope around my neck. And in the blackness of the black hood, and the expectant hushed beyond, my mind screamed for something to hang on to. The presentation of this wears a mask. The original music for the Mystery Theater is composed and conducted by Alexander Semmler. Billy Quinn was starred and Mitzi Gould and Gregory Morton featured in tonight's play. Any resemblance between the names and characters used on Mystery Theater and any actual person living or dead is purely coincidental.


When I was first working on changing all the parts of my life, really at the same time in my 20s back then the thing that inspired me the most was really seeing the stories of other people's transformations. You know, it's a lot like if you have to lose 50 or 100 pounds. It seems impossible. Like it's never going to happen. But if you see one of those success stories on the internet, now you know it's possible. So I thought in this video today, I would share a little bit about the story of my 20s and three of the most important lessons that I learned. What's up, you guys? Alex Hein, author of Milk the Pigeon, a field guide for anyone lost in their 20s. Subtle product placement there, right? Now I've included a free worksheet below this video to try and figure out what to do with your life and plot the path forward. The free journaling worksheet right below in the link there is going to help you figure out exactly what to do, at least to plan out your next steps. You're also going to get a weekly email on how to use journaling to direct the future of your life. So if I'm being brutally honest, you know, in my 20s there were three main things, three questions I was obsessed with. I mean, those questions made up this book, Milk the Pigeon. Those three fundamental questions are the three fundamental chapters, each with the lessons inside. But the first fundamental question is really what the hell should I do with my life? And I want to tell a little bit of a story for each of these lessons, because I think in some way it's going to help you as well as my takeaway from that specific lesson and how I answered that question.  And I've talked about it here before, but I want to share it in sequence because some of those things I think will help you. So I got a job at a college. It wasn't in the field I studied, which was biology and environmental science. And it wasn't even really a job that I specifically wanted that much. But I had been at home with my parents looking for a job for a while. And my dad got me an introduction to the principal at this school in New York. And she said, you know, did you want to teach and help in the two drink center in our high school? So I got the job. It was a great job. I knew it wasn't what I wanted to do forever, even though I do love teaching. And so near the end of the year, I was like, well, what have I always wanted to do?  So I should probably just do something that I really, really, really feel excited about. So I was like, well, since I was a kid, I'd always been into kung fu and meditation. I thought I'd become a monk. Like even since my early teens, I joked about potentially becoming a monk. And I always felt this dichotomy between living a human life as well as the split between do I just retire to some mountaintop and do some esoteric practices every day. So I always felt that pull, you know, that tug since I was a little kid. So I was like, well, guess what? I mean, if this is the last chance in my life, I have to potentially be totally free to do that. Then I should go do that. So I get this one way ticket to China. And the whole all the while I'm thinking like, what the hell do I do with my life? I know it's not being a teacher. I know it's not that. What do I do with my life? So the whole year I'm living in China, I'm learning from kung fu teachers in the park in the middle of February freezing in Beijing. I'm studying Chinese four or five, six hours a day. But still this nagging feeling of this is a great adventure. But this is not what I'm going to do for the rest of my life. You know, this just feels like the next step. So where do I go from here?  Because all it answered for me was that I did not want to continue living in China forever, certainly not as an English teacher. Kung fu probably was not the passion of mine that I wanted to do every day for the rest of my life. And what it really did was it opened up this kind of massive, deeper existential crisis when I came home. Because now basically as being, you know, an expat who's repatriated, I felt even more lost than the first time. Because now I did the thing that suddenly I thought I was going to do forever. You know, I told my parents I'm planning to be there for a decade. And now I'm 24 and I'm back home. So it taught me a very important lesson.  There is no map. Once you leave conventional grade school, school gives a structure. So even though you may hate school or you don't want to show up to school, school gives you a structure that also gives your life meaning.  You have a mission to do. You have things to get done every day. Now, even if you don't like that, at the very least, having a clear purpose in the moment gives your life direction. So if you're outside of the structure, you've graduated, you're in the real world, whatever that means. Now you have to create the treasure map. You are now the captain of the ship. You just have to figure out where the ship is going. And that is a very difficult thing. And it doesn't solve itself in one year or three years, five years, seven years. In reality, the ship is always sailing. That's the point of a ship. It has to always be sailing somewhere because that's what it was designed for, not to be docked in a bay somewhere, but to be going in a certain direction. And the other big lesson for this from me was that you may not know where you're going for a long time. But at the very least, you need to pick a direction and go in that direction. Whatever is the best opportunity at the moment that may last a month, that may last six months, that may last 10 years. But you have to be sailing in some kind of direction if you're not even sure where the treasure map is and where you want to go. So just pick the best direction that excites you the most and has the best potential for your future right now. So my action step for this question that plagued me was to really be obsessive about being very deliberate with where you want to go. And if you really aren't sure where you want to go and I know so many of you have told me that and I thought that for years, pick just the next best decision and just commit to that. But whatever you do, be deliberate. Question number two was really all about how do I find the work I love? Because I learned very quickly, I am not the guy you want to hire to just pay a lot of money to do something I don't like. Or worse, something that pays me a lot of money that I don't feel like delivers any value to the world. The problem for me was that I had spent all these years building this entrepreneurial venture. Actually, I had tried multiple, but Modern Health Monk was the first one that worked out to the point where I made enough money to quit my job. So I'm in this phase of my life where I'm hustling. I'm back from China now. It's 24, 25, 26. I'm feeling very lost. I'm trying dozens of careers. None of them excite me. None of them I'm passionate about. I don't want to be doing any of them three months from now, let alone 20 years from now.  I don't know where to go next. I don't know what I want to do. I'm thinking about just moving back to China and just making the best of it. I'm working multiple jobs. I'm freelancing. I'm also going back to do night classes for physics and some other stuff, considering maybe a conventional medical program to follow up. I do what every lost 20-something does, which is you think about grad school, even though it's not clearly really related to a next step, but at least you're doing something and buying some time. I thought about fleeing back to the last place I came from, China. I think about all these entrepreneurial ventures, but then an interesting thing happened, which is that I had been committed every single night and every single weekend to building this entrepreneurial venture to try my best to earn my freedom. You know, if I could just make 3,000 US a month, that would be enough to reclaim my time and begin doing what I wanted to do with it. So I'm working every single night, every single weekend, every single Sunday. My girlfriend and I at the time, who dated for like five years, only saw each other on the weekend for three years, right? Nothing Monday through Thursday. And eventually, after over 1,195 days, I counted. I was able to make enough money to quit my job. Wasn't a lot of money. It was barely enough to live. It was like $2,500 US a month. But I figured I could at least pay my rent and eat. And now I would have 40 hours a week to decide how I wanted to live my life. But a crazy thing happened next. This goal that I'd been just destroying myself, crushing myself, trying to make happen. Now all of a sudden I find myself with all the time in the world to work on what I want and I'm building a business that I don't even like. Because now as an entrepreneur, my job is to do sales and marketing and business growth all day, which were not things I naturally enjoyed anyway. They weren't things I wanted to be spending my time doing. So I learned my next very important lesson about how to find work you love. The big lesson in a realization here was that your excitement about what you like is always changing. It's always evolving.  I mean, look at professional athletes. They do the crazy grind. They have sickening discipline and work ethic, even those that love the game. You know, by the end of their career, they just don't even want to play anymore. They're just done. And so there's two really important things about finding work you love. Number one, it's kind of a journey of exciting projects. I think of it as almost phases of your work life, where this phase you're working on, this thing that excites you, but in a year or three or five or two months, that's completely different. It's a totally different game. And the second thing is that what is eternal is the valuable skills you acquire in the process. Because you never really know what your next exciting project is going to be, that then it's going to tie in all those prior skills that you developed that are now super useful for being successful. You know, for example, I had no idea that I was going to ever write any books, but two of those skills I acquired before I wrote my books were audience building and learning a bit about marketing, which is just helping people find out about you. So when it came to doing my best to write these two books that I talk about here, I not only had an audience that was willing and interested in buying them, but I knew how to like generate buzz and interest about these books and how to regularly get the word out about the books because I don't have a publisher. I don't have a huge marketing publishing house that can get the word out to millions. And as a result, those prior skills I acquired that didn't seem that relevant to anything else resulted in my books all being Amazon bestsellers and I've made almost six figures in royalties from them. So these skills you acquire that are super valuable are closely tied into these exciting projects after exciting projects. So my action step and my formula for this phase became chase what is always exciting you and in the process continue to acquire valuable skills. Now my third and final question, which is one that kind of always plagued me since I was young was how do I build an awesome meaningful life worth living? Like how do I build a life that I feel inspired by? That end of the day, I feel like it's just such a good full life. You know something that just excites me and makes me feel alive. Now around this time of me reinventing myself and coming back from China and trying to work on all the pieces of my life. I went to this business conference and met a guy named Clint.  Just one of those friends you instantly connect with. You know you're going to be friends forever. You're immediately hanging out all the time talking on the phone. I mean, I'd never I've never had that kind of friendship as a guy with another straight guy basically is what I'm saying. You know, I've had that that weird connection with a girl in dating that then progressed to a relationship but never with friendship. So I thought this was awesome. It was like the best thing ever. I'd never had like a best friend maybe outside of being eight years old. So to be an adult and to find that was pretty cool actually. So this friendship just evolved quickly. We were always talking about business. We were planning like cool business mastermind trips together. You know, we met each other's friends and we were in these entrepreneurial circles.  And it really got me thinking about what makes life meaningful. Whether you achieve things but you don't achieve things. What makes it meaningful? Now the dark turn of the story is that, you know, about six or nine months into us hanging out all the time. He gave me a call left a voicemail and said, you know, could you help me move in a couple days? I'm going to be moving into my fiance's with her. So, you know, around closer to the time of him calling me, I called him back and I was like, yeah, where do you want to meet? Where do you want to go first? And no response, which was very unlike him. Next day, I called him again. I texted him also no response, which was definitely not like him. So that's kind of where I got the hunch that maybe something was wrong. And I found that he committed suicide, you know, the night before I was supposed to help him move. You know, a piece of that experience was besides just feeling like, like something went wrong in the matrix. Like it was actually an error in the universe. Like, you know, someone didn't carry a decimal or, you know, a number or two. And then this person randomly died in the cosmic order. Besides that feeling kind of unsettling me. It also made me just feel a little confused about what I found meaningful in life. And I thought a lot about the experiences that I had and whether success and just even working hard was tied to meaning for me. And I came to the realization of two very important things being important. The first was meaningful relationships, because here I am, you know, five years later talking about how meaningful that relationship was to me.  So the first was that an inherent piece of a meaningful life is not related to anything you achieve at all. It's just being with great people that you want to just sit and drink a beer with and just reminisce. And the second piece was that meaning is closely tied to whatever makes you feel alive. And usually it overlaps with contribution. So things that you do that then impact and help other people usually are higher on the meaning spectrum than things that you just do that don't affect anybody else. But the most important thing about meaning is that, you know, when you're a millennial, you compare yourself to the factory farm lifestyle. The status quo is you get a job, you get the nine to five, you get the white picket fence, the 2.5 kids, that's life. That's the status quo. So the juxtaposition, the opposite, the contrary is a bucket list life, right? YOLO. Create a list of all these crazy experiences, do all those crazy things. That is a full life. But that's often not a meaningful life. Contrary to that, a meaningful life is usually not a bucket list life. And that's my big point here. Meaning is usually a lot more subtle. And it usually is related to relationships, to key core emotional experiences, and just projects you work on that are helping other people, you know, as well as are personally fulfilling. So my formula for this question became, you know, meaningful work and meaningful relationships. That was the secret to me, having a meaningful, really full, alive life. So I realized that's a pretty long video, you guys, but I hope those stories help answer kind of some of these existential questions, which were not so easy for me. And some of those I'm still working on. But I do feel like that restlessness I had is very much not there anymore. And I think because I really thought about these questions a lot. Now, if you want to work on those, try to get your stuff together. Check out the free journaling worksheet below the video, because you're also going to get any journaling series on how I use journaling to plot the path forward in my life. Now you can do that as well. All right, you guys, before you go, I have two related videos right over here. I'll catch you in the next video.


everybody to this second week of the school. Thank you very much for being here. So today we are going to have a different format compared to the ones we are used to from last week. So today is my pleasure to introduce the lecturer of today who is Jordy Vasconte. Jordy is a professor of ecology and evolutionary biology at the University of Zurich. in Switzerland and his research is mostly focused on ecological network and in particular on mutualistic networks. So as you know, Jordy Vasconte has uploaded two pre-recorded lectures that were available on the website starting last week and this session of today is a Q&A session. So it's an opportunity to discuss with Jordy the material presented in the lectures and I think it goes also a little bit beyond that. So thank you very much, Jordy, for recording the lectures and for being with us. Thanks to you, Ciacopo. It's really a pleasure and welcome everybody. And so now we are open to questions. So if you have any question on either of the two lectures, please use the raise and button of Zoom or write it in the chat or if you're following from YouTube, you can write it in the chat of YouTube. So we have a hand raised by Sylvia. So Sylvia, if you want to ask the question, please unmute and ask. Yeah, can you hear me? Yes. So I have a question on the first lecture concerning how the nested structure emerges. In fact, like in general, one could hypothesize that the structure could emerge either from the ecological dynamics or from the evolutionary dynamics, right? And on Friday, we heard a lecture by Stefano Alesina that was talking about community assembly and we learned that there will be a structure in the interactions only if there was a structure in the original pool of species. So this would suggest that the nested structure can only emerge from the evolutionary dynamics. So could you comment on this? And is there any of your works where you dealt with how the nested structure can emerge? Yes, that's a great question. Thanks for posing that. I think that as we've learned more about these ecological networks and the suite of mechanisms that are compatible with the structure, we tend to move from an initial focus where people were picking up a particular mechanism to considering like simultaneous mechanisms that can potentially be at war here. So early on, right after the first wave of a study describing the structure of these networks, people start focusing on particular mechanisms. For example, one of those is species abundance. So people realize that if most abundant species tend to be more available by chance, it's more likely that species would tend to interact with these more abundant than less abundant species. So this kind of neutral approach become one important mechanism in generating networks. At the same time, other people were focusing on other aspects. For example, a phylogenetic signal is well known that there is a phylogenetic signal, meaning that species close in the phylogeny tend to play similar roles in the network of interactions. What this is suggesting is that past evolutionary history may be important in understanding contemporary patterns of network built up. So for a while, as it tends to happen in science, it seemed like there was a little bit of a competition between specific mechanisms. I think where we are standing today is in a place where we recognize that there's a suite of mechanisms. There's not only one mechanism. So ecology certainly plays a role because species abundance, it's important in order to explain these patterns, but most likely it's not enough. And it's true that this coexist with this evolutionary signal with trade matching, for example, which is another set of explanations that emphasize that trades are the currency that explains interactions. And therefore, for example, one trade would be the length of pollinator stone, another trade could be the length of plants corolla, flowers corolla, and therefore whether or not there's a matching between trades may be key in order to explain those interactions. So what I think it's now the state where we are is in trying to understand, not proving that this is the mechanism or that's the mechanism, but in trying to weigh the relative importance of a series of mechanisms, always taking into account the phylogenetic structure. Because in these comparative studies, one cannot forget that species are not independent units, but they form part of this process of related species coming from an ancestor origin. So that's where I think we are right now. I think that evolutionary mechanisms certainly are important, what you were emphasizing, but there are other set of mechanisms like ecological ones. And I don't think there's nothing wrong on that. I think that as with many other things in science, a pluralistic view is most likely going to be at worst. So yes, I would highlight evolutionary mechanisms, trade mechanisms, and neutral or species abundance mechanisms. If I can ask just a little verification on this, like when you mentioned the importance of abundance, so are the species that are most generalist, typically the more abundant ones? Yes, that's something that people realize from an early stage. And if something, the debate was, I mean, are species more abundant because they are more generalist or the other way around? So that's really a bit where the discussion was. But from very much the early stage of these studies on ecological networks, and in particular these mutualistic networks, it was clear, and particularly, I'm thinking about the Great War by Diego Pazquez in Argentina and colleagues, that abundance was really important. The thing though is that, for example, going back to our own work, we had a paper laid by a former student, Abe Krishna, that proved with a simple model that while abundance is important, when you combine abundance with trade matching, the fit to the data is even higher. Great. So Silvia, you wanted to follow up? No, I'm fine. Thank you very much for the answer. So there is a question from Washington, Taylor. Yeah, hi, thanks. I thought your lecture was very interesting. You found some, there's some nice clear and simple ways of starting to address some really interesting and deep questions. I had actually two somewhat unrelated questions. Maybe I'll throw both of them at you and you can choose which one or address them whichever you want. So one is, you focused on climate as a driver of extinction events and as kind of a primary thing throughout your lecture. But as I'm sure you're very well aware, most of the things currently driving species extinction are other things like habitat loss, human use of the ecosystem, pollution, invasive species and things like that. So the first question is whether those would have a similar impact or whether there are some climate specific signatures in what you were describing. And then the second question is, when you describe these essentially two level networks, I mean, of course, in a real ecosystem, there's all kinds of very subtle other species playing niche roles that are mediating interactions and maybe playing key roles as, you know, in all kinds of places in the system. So I'm wondering whether that you've explored whether there's any sense in which these networks you have are robust against intermediate species that are involved in the system going extinct or, you know, how that plays in the missing pieces that you don't have in the network. So those are sort of two questions. Yes, these are very great questions. Going back to the first one, you're totally right. I mean, climate change is just one driver of global environmental change, the other being habitat fragmentation or nitrogen deposition and so on. While our focus was here, probably the reason we're focusing on climate change is for historical reasons, because from early on there was this attempt of bridging between these somehow distant approaches, one the network approach and the other the climate change ecology, right? So to some extent, focusing on climate was a consequence of these two different approaches. But there's been a previous work by other people who focus on habitat transformation. Some of these work is theoretical using models of habitat loss, habitat fragmentation and looking at, what's the rate and shape of network collapse. And I would say, I would expect finding the same type of qualitative results. I don't think those results were quite specific about climate in terms of the rate and shape of collapse, in terms of like finding this phylogenetic signal or having a moment where the rules of the game, so to speak, change and then we're focusing different species from the phylogenetic tree. So I would say those are quite general results, although to be totally honest, only a subset of these questions have been addressed using other drivers of climate change. So here I'm kind of telling a little bit my gut feeling. For example, the one is for sure similar is this kind of abrupt collapse, this idea that the consequence, as we are moving through this axis of global environmental change, the thing that early on, nothing seems to change too much up to a point where suddenly there's a collapse. That's the kind of result that different people have seen when looking at different drivers. The other ones, I'm not so well aware of the studies, the ones looking, for example, at how functional diversity is eroded or evolutionary history is eroded. But my gut feeling would be that these are quite, have to be quite general consequences. So I would expect a similar kind of signal. In relation to the other question, that's very interesting. It's true that one should expect having this kind of, if you want, gist on a species, species that play a major role in bringing the network together. And that's a piece of research that has focus on that. But in my view, it's more a static one. For example, research looking at the modularity or compartmentalization of these networks. This research tends to look not only at this tendency to be organized in modules, but also at the role that different species play. And in particular, this role by a few species in bridging across different modules in being the sort of the glue that keeps this module together. Now, if I understood your question correctly, you were asking whether some studies have focused on what happens when these species disappear. And I can think of a study that was looking at a genetic diversity of some of these species that emphasized this thing that once you remove one of these species, you can have a major change because suddenly you can have a network that previously was more or less cohesive. And now you have like a collection of different networks. Great. Thanks. Those are great answers to both questions. And on the second question, I guess one, if I could just go a little further on that. So I guess one of the things I was also asking about there was you have this database of interactions between different species in these different habitats. And I guess I'm wondering, you know, probably there are important species that were missed in each of those databases. So for instance, you may have 73 species in the given area, but there may be another 30 species that really play a keystone role. So part of the question is, even if you missed some of those key species, and those were somehow just encoded secretly in the interactions, are the results that you're getting robust against, say, replacing the network with one where you imagine that you only know about a subset of the species and then test the same hypothesis? Yes, you're totally right. And that's the kind of, I would say that encapsulates a series of criticism that was about using these large database studies where, you know, I mean, it was a nice attempt in the sense of looking at generality, but there are trade-offs and part of the consequence of that. And I think it's a fair point, part of the consequence of people who were more critical about our work and the work by many others for the same sake, was that each of these networks has been compiled by a different author or a different team spending different time or using slightly different methodologies. And therefore, in the same way that when looking at studies on species diversity, it's very clear now, pretty much everybody knows and understands that we should use rarefaction cubes, we were not at this stage. And that arise some questions about the value of this generality. Now there's been, as they feel mature, and these kind of studies become a little bit more mature, there's been already a subset of those that started using similar methodologies, and in particular use these rarefaction cubes. And this allows to think, first it allows to focus on the smaller subset of networks that have been sampled enough, so have a similar level of sampling, and then focusing on those, but also like looking at how these properties may change across a gradient in sampling, and there are properties that may vary quite a lot, but some of these properties do not vary that much, like in particular that nested structure I was emphasizing during that particular first talk, each one that is a little bit like the different builds of an onion, right? Essentially you have this, this core of generally species and then these few generalists, the thing is that if you sample more, you start having a longer tail of a species, and normally those species tend to be specialist and to be less common species, but also they tend to attach to the most generality, so depending on the type of dimension of a structure if you want or perspective, these may not depend that much on on the level of sampling, but in general I think that's a poor answer, and I think that now what we should try to do is every new study try to have a sort of rarefaction cubes, and people can do that in the same way that we look at how many different species we have when we sample 100, 500, 1000 individuals, we can do the same for example with a number of interactions, and oftentimes we have enough of a sample that people consider a little bit of an assing to it. Great, thanks a lot. My pleasure. Great, so the next one in line is Alfonso, so Alfonso please unmute yourself. Hello everybody, thank you for your great lecture, and my first question is, can the mutualistic networks account for weighted interaction between plants and insects, and in that case how much the distribution of these weights might change the results of the number of species, the maximum number of species supported by the network, or the change of extinction in case that, in the case of non-random extinction, like the extinction that you talked about in the lecture, and my second question, I just come up with that question recently, is that, is there a relation of in like generalist species tend to be more abundant? My question is related with the species abundance distribution, if there are a relation between the species abundance distribution of a community and the network structure. Very good, very good set of questions. Let me start by the second one. The answer is yes, and some of these approaches we were referring to a few minutes ago in terms of like checking the relative role of a different mechanisms in explaining network structure, one of those, this kind of a neutral approach, was using these observed skew species abundance relationships, and then for the plants on one hand, for the animals on the other, and then assuming that the probability of drawing an interaction is going to be proportional to the to the product of these species abundance, so it's kind of simultaneously taking into account both the skew distribution for both sets, right? And when one does something like that, you come up with a network of interactions that tends to be similar than the one we observe in nature. So people would tend to think, okay, that's that kind of supports the idea that neutral processes, species abundance is certainly important. Again, as I said, when you have a model that takes into account these and other factors, you can get an even better fit, which tends to support the idea that there's not only one mechanism, but most likely a suite of mechanisms. So you are totally right, species abundance and the particular empirical distributions is something that may be very important and has been empirically used in order to come up with the expectation of these network of interactions and then matching that expectation with them, with the observed one. I don't know if that answered your question. Yes, I think that answered my question. Lovely. Then in regards to the first one, you are totally right. I think my talk, you probably realize that I mean, when I give this talk on mutualistic networks, now it's a talk that spans now 20 years. So early on, when we were mainly looking at the structure, I was going through different levels of the structure and focusing on interaction strength. As more results were packed, I tend to reduce the focus on structure and just focus on that particular dimension, the nested one, but you are totally right. And although early on, the first set of papers were looking at binary data, and that refers to, for example, this nested pattern I was talking about, but also these connectivity distributions, whether they are, they follow overlaw or a truncated power law or an exponential that was like the kind of things people in natural research were doing at the same, at the time. I mean, a few people again were critical about that and they would say that, okay, all these results may be meaningful without like considering embracing the fact that there may be a huge variability in the wave in the strength of those interactions. And actually, there was a few studies that were looking at the structure, but using weighted data. In that big repository, I mentioned during my talk, right now there's almost half of these networks that contain information not only on who interacts with whom, but on the relative ways of this interaction. Oftentimes, this is the surrogate of frequency of interactions is used or number of fruits removed, for example, things among those lines. So there's this kind of information and some of these studies describing network structure were focusing on that component. For example, they were looking at the dependence of an animal in a plant. And they were focusing or they were highlighting this idea of asymmetry in the interaction, which can be also observed in binary data. One of the results of an instead pattern is this asymmetry in the sense that specialists tend to interact with the most generalist. Now, when you look at weighted network, you can see that this also happens in a pairwise scale. So like, for example, a plant that depends very much on an animal for its pollination. Normally, you encounter that the animal depends very little on that particular plant. So some of these results you can still see when you move from binary to weighted networks. And other results only make sense or only kind of tools or approaches when you have a weighted network. So overall, yes, you have this kind of information, you can address new questions that you could not with a binary data. And a few questions you can check with both. And I would say you tend to find similar patterns. Great, Alfonso, you have a follow up? No, I think that that answers were really nice. So thank you very much. Thanks to you for the question. Great. So next in line is Violeta. Yes. Hi. Hello. Thank you, Jordi. Yes, my question is about structural stability. More trade off there. Okay. For me, crystal clear, how do you firm the nested net of the network? You just measure it with some algorithm. But what about the mutualistic trade off? I mean, how have you inferred this mutualistic trade off? Because then if you see the equations that generalize a couple of the right questions there, the parameter space is multidimensional and very, very wide. So I suppose that you just chose certain parameters. But can we be sure that about the general generality of the results when doing that? Yes. In terms of how one does this, on one hand, you have for these weighted networks, you have empirical information. Essentially, that's information that relates the degree, how many species, a focal species interact with, that may be two, five or ten species, but you also have information on the weight of each one of these interactions. So this is information that you have empirically from the network. So that means that you can determine where the point is in that figure. In terms of how to explore, it's very much similar than with nestedness. I mean, with nestedness, you take the network as it is, and then you randomize that with a series of assumptions. Normally, you tend to preserve total number of plants, the number of animals, total number of interactions, and approximately how many interactions each species has. With the trade, obviously the same, you could have like a randomization where you maintain the degree of each species. You maintain like the number of interactions they have, but you can shuffle the weights of each one of those interactions. So that would allow you to explore the taxes in parameter space. But anyway, that axis is also related with the intrinsic weight of the species and also the competition parameters. So all of those. That axis, it's not related to anything else, because it's the way you define it. You define an axis like being only a value of nestedness, and then it's only structural, and you can change it. What it's related to these other parameters, and in particular to growth rates, which this was the variable we're looking at, is in terms of the measure of structural stability. So on one hand, you have parameters that define the structure of the network, and then you use growth rates as a way to quantify how much variability in those growth rates the model can cope with before one or more species is driven extinct. There's a little bit of an uncoupling. Some of these variables of network structure are just used to show how much variability you could have. And then for each level of variability, the demographic parameters are used in order to explain the range in growth rates in this case in particular. So you choose like the center of this domain, the center where this domain of feasibility, where all the species can coexist, there's ways by which you can focus on that center, and then you start perturbing growth rates, changing growth rates, increasing, increasing, increasing up to the point where one or more species disappears. So there's a little bit of a decoupling on how you treat these different different parameters. Okay, sorry, last question. When you are varying the range of the intrinsic growth rate during your equations, you must fix the other betas and gammas. So maybe it happens that for those 13 parameters of gamma and betas, your intrinsic growth rate behaves in some way, but maybe there's a tiny region where they don't. So is that actually important or not? Yes, you are totally right. And to make a long story short, essentially that's for a specific values of the other parameters. What one can do is then repeat the analysis for another value for each one of these parameters. So this gives you an idea of how robust results are for variation in the other parameters. But to be honest with you, essentially that's more like, okay, you fix the other parameters and then you focus on variability on growth rates. And yes, you cannot rule out the possibility that there may be some combination of parameters where now you could have a slightly larger or a smaller range of conditions compatible with feasibility. You are right. It's a very complex problem just because of the dimensionality in parameters. So to some extent, you fix some of the parameters and then you focus on growth rates. So if you want, it's a partial account of the much more complex variability in parameter space. Okay. No, but thank you. Thank you very much. Very interesting. Great. Thanks a lot for the questions. So the next in line is Martina. Hi. Hello. And thank you for your lectures. So I have two questions. One is a clarification. The other one is more general. So maybe I'll start with clarification. So when you were talking about extinctions that were driven by climate compared to the secondary extinctions that are driven by interactions, you had those phylogenetic trees and with the circles. And you were saying that you can predict the direct extinctions with the geographic location, whether you predict the others with the traits. And I was wondering, maybe it's completely wrong. Sorry. Just to be precise, the single most important variable in explaining extinction is what we call network ID. So a property of the network. Yes. Okay. And I was wondering whether, okay, if you have interactions, you're supposed to, you have them in the same location. So I was wondering, how can you get these, say, switching the first predictor? Essentially, the way is by using these generalized linear models where you can have different factors. One is geographic location. The other, it's a factor called network ID. So a property of the network, which it's unique and it's not affected by the others. And then through this kind of a statistical approach, you can wave the relative contribution of one of these variables accounting for the other ones. So it's a way by which you can focus on the relative role of geographic location while keeping into account, if you want, keeping fixed the role of network ID. That's one component. And the other one is, or the complement to that, it's by using what's called a Caikis information criteria because other things being equal, I mean, the more variables you have in the model, the better it gets. But you have to penalize it. To some extent, it's an artifact or just a corollary of having more variables. So the idea is to really focus on the variables that explain the variability in a model, taking into account the number of variables or the dimensionality of the model itself. So that's a kind of statistical approach to come up with this kind of result. So essentially, it's statistically, you can do that. Even when you have several variables, these kind of models allow you to focus on one variable at the time and kind of give you the relative relevance of that variable while keeping the others constant. And also the interaction because sometimes the interaction between factors or variables. Oftentimes, it's not just that variable x or variable y are important, but sometimes you can also find a significant interaction between these two variables. And so given these models, so the network ID is in the fixed part or in the random part? That's a good point. To be honest, now I don't remember if we treat it as a random factor. This I cannot remember now. It's fine. I can read the paper, probably. Yes. I mean, I'm sure the details are there. Because that's a very interesting thing, and it's not trivial. The way people who are really knowledgeable about these models, the way they treat these factors as either a random or a fix, that depends very much on the structure of the question, but also a little bit the constraints or the limitations of the data. So again, if you are interested, details are there. I just do not remember now. Okay. And the other one is more general. So you find these very nice relationships between nestedness and biodiversity. And do you know what happens if you have modularity on the x-axis? That's a very good point. We've not really checked that in the context of that framework. So I cannot give you a solid answer to that question just because we did not check. Obviously, one could think about these two dimensions of network structure not being totally independent, but somehow related. And although it's not perfect relationship, people tend to assume that the higher the nestedness, the lower modularity, that's not necessarily the case because that depends on a level of connectivity. So below that threshold of connectivity for low-connectivity, you actually find a positive relationship. You find the networks which are more nested. They are also more modular. But when the network is well connected, you find this kind of in their relationship. So one could conclude that because of that, you would find the opposite sort of trend. Okay. Thank you. My pleasure. Okay. So we can move on with Sree Rama. Thank you for your talk. Am I audible? Hello. Hi. Yes, I couldn't hear you very well. Sorry, am I audible? Okay. So actually, I have a general question. Suppose if you take a general predator or anything, they have some referential structure. So there's something like optimal forages. So what happens is every time the network structure changes because they can prefer one prey or another prey, so the network becomes a dynamics. So how this dynamic network can be modelled generally? That's an excellent point. You are totally right. And one of the limitations of the last part of my talk, talking about these models of climate change, is that we were not taking into account that. So essentially in this kind of approach and also the approach by many others, the thing is that once a species runs out of resources or the fraction of resources disappear, those species have a higher probability of being driven coextine. And we know that things are a little bit more complicated because as you already point out, there is a trophic flexibility, the fact that some species, whenever their favourite prey items are not abandoned enough, they can shift to another one. So I mean, to my knowledge, the very first person who brought this forward was Mikio Kondo, a theoretical ecologist based in Japan that in a paper in science, that's probably now about 15 years ago, proved that this flexibility can certainly shift. He was focusing on the relationship between stability and complexity. It can be shifted. So when you have trophic flexibility, you can see that more complex food webs tend to be more stable. Also in the context of mutualistic neighbors, people in Fernanda Valdobinos, it's a good example, have shown that this relationship between stability and complexity can largely change through that trophic flexibility. So I would say that the sort of models that we and others have used, ignoring trophic flexibility would be a sort of worst-case scenario. Whenever you have a trophic flexibility, things become a little bit better. But I would say that some of the qualitative results, for example, the existence of these tipping points are still there, only that you can shift the tipping point to higher values of habitat laws or species extinctions and things like that. I think now the question, though, is how to really bring a biological informed model of network rewiring. This is what we're trying to do now in the lab with Marilia Gallarsa. And I think that, again, that phylogenetic signal can be key here. The fact that, okay, although there's a potential for rewiring, oftentimes this is not going to be random. So any species will most likely not have the possibility to shift to any other item. But we think that it may be a good starting point to consider phylogenetic signal, meaning that if one species runs out of resources, most likely may shift towards resources that a species close in the phylogeny depends on. So I think that would be a good way to start introducing these rewiring a little bit in a more biological informed way than just assuming every species has a probability to rewire with any other species randomly picking the community. Can I add one thing? Generally, most of this optimum phrasing is something, suppose they are not able to see that they are not referring, they are not, the feeding may not be giving the required growth or anything, they will divert to another species. So that means something like, suppose if they are seeing that we are having a lot of energy we are spending in time of predation, but we are not getting required energy to our growth. Then we have to shift for another species. So how can you do this? That is what my question, I mean, I don't know, I'm able to properly convey that or not because I'm not a biologist, I'm a mathematician, I'm working in this area. So yeah, I think it's a very good point. I mean, to be honest, we know very little about that. And the reason is again, because these kind of studies have gone quite independent from each other. A little bit I was emphasizing that independence between network research and climate change research, and that was a little bit of the rationale for us trying to bridge them. Another big gap exists between these models or this approach of ecological networks that tend to be quite static and this optimal foraging, which obviously emphasized a dynamic component. I think it would be a very interesting direction to try to bridge those. And for example, try to see what would be the predictions, what would come up out of these basic ideas of optimal foraging. So for example, allowing like a few species of animals to forage in a given landscape and then trying to see how out of these basic rules of optimal foraging, what kind of network structure would arise. I think there's a little bit of that. I seem to recall a paper probably by Morales and perhaps Diego Vázquez as well. I may be wrong, but I think these are the authors who tried to do that. And that was certainly very, very interesting. But I think there's lots of room to kind of expand this kind of bridging between optimal foraging and network structure. My pleasure. Great. So we are going at very high pace here. So there is another question by Ankit. Hi. Hello. Thank you for this very broad survey of mutualistic networks. So I had a question regarding like which is somewhat related to May's result of stability in large complex ecosystems. So there obviously he looks at like entirely random networks. But let's say if you talk about large mutualistic networks, where you have some asymmetry between the number of plants and the animals, like let's say there are very few plants, but many animals which like depend on these plants. So in that case like is there a theoretical result of like stability in the same sense as May or like yeah, or like is it difficult to like define that because I guess in such a setting you would have a lot of negative interactions instead of like just totally random interactions. What do you mean by negative interactions? Non random? Just non random? Yeah, random negative interactions, but they don't sum up to zero. I mean like the interactions of the entire matrix. Yes, that's a very good point. You are totally right. I mean, Bob's May great paper has to be seen as like a baseline expectation. So some of the criticism the paper had actually did not arise because of the paper itself, but our faulty way of interpreting that paper. So we could not interpret that May said that most complex communities have to be unstable. Rather, what he said is that our baseline expectation, if communities were randomly organized is that there's a limit to complexity. And therefore, I think that paper was extremely influential in shaping the field in many directions. One of those was just asking ourselves what may be those mechanisms or these dimensions of structure that can help reconcile being complex and being stable. So yeah, our original work on trying to bridge between this network structure and stability that was our science paper in 2006. We tried to do that in following a very similar approach than Bob May with lots of limitations. I mean, that was our first attempt and therefore we had to simplify a lot of things. But what I want to emphasize in the context of your question is that yes, you come up with an equation for the linear stability and feasibility condition for both being feasible and linearly stable that very much resembles Bob May. Essentially, you have in Bob May, you have that the average strength of interactions has to be lower than an amount, amount that involves number of species and connectivity. So what you have here is a similar thing, but instead of having like the average strength of interactions, you have the average product of the strength of interaction of the animal and the strength of interaction of the plan. And this is what has to be less than an amount. And that allow us to predict that what's relevant in these motoristic networks is that either you have species that depend very little on others or when one species depends a lot on a second, that second depends very little in the one. So even when one term is large, if the other is very, very small, the product still remains small. So that would be an example of a very similar kind of criteria than Bob May, but it had some interesting variability and that variability allow us to start thinking about how these dependencies of a plan and an animal and the animal on that plan have to be rearranged to keep stable communities. Yeah, thanks. I'll also look at your paper. Thank you. Great. So is there any other question? I don't see anyone with the raise hand in the participant list. No question in the chat, but we had a 50 minute, very intense question session. So I think that if no one has a question, we can move forward. Great. Well, I think this was a sort of experiment for us to have this pre-record sessions plus question, but I personally think it worked very, very well. And I'd like to thank Jordy for being with us and for answering all the questions, as well as pre-recording the lectures. Thanks Jacopo and thanks every one of you. I think you come up with extremely good questions. And I think a proof of that is that these are the questions that we are encounter when trying to publish papers. So in that regard, I think that you are thinking very well. So I've really enjoyed and had a great time. So I'd like just to add that feel free to email if some of these ideas start developing or you have further questions. So just drop an email and it would be my pleasure to keep discussing some of these ideas. And best luck to every one of you. Hopefully you have a nice school and a great career. Thank you. Thanks, Jordy, also for your availability. So what we're going to do now before the next lecture, which will start in about 20 minutes, is that we're going to split again in breakout rooms. So feel free to chat


fifth point you see reaction of carbon with O2 reaction of carbon and O2 two reactions possible we know already like C plus O2 gives CO2 this is first reaction and C plus half O2 gives CO this is second reaction in this reaction you see in the first reaction the volume of CO2 obtained volume of CO2 obtained it is same as the volume of O2 used volume of O2 used okay one volume in one volume hence what happens hence delta S delta S is very small almost zero and delta G hardly changes with temperature right one volume of this gas gives one volume of CO2 gas so number of gases particles same both side so entropy won't change that much delta S is almost zero hence delta G won't change with temperature that's why you see the line of C and carbon well a line is all almost parallel to the x axis like this we have in the Ellingham diagram I'll show you just let me write down this first same logic if you apply here right in the second reaction we can say the volume ratio I'll write down like this the volume of O2 divided by the volume of CO is half right to get one volume of CO we'll use half volume of O2 or we can say to get two volume of CO we'll get one volume of O2 right so half of the volume of O2 required to get one volume of CO right hence if you calculate delta NG here so delta S will be positive greater than zero and we can say delta G becomes more negative delta G becomes more negative as temperature increases as temperature increases and that is why the line goes like this this kind of line we have in the graph so what we can say here to conclude this below 710 degrees Celsius reaction gives CO2 above 710 degrees Celsius the reaction gives CO this is what the overall thing is okay now when you see this Ellingham diagram you see here at 710 there is almost no change in delta G till 710 right and as I discussed that when the temperature increases this line gives you what this line gives you C plus half O2 gives CO so delta G for this reaction just now I have discussed delta G becomes more negative and hence the line has to go down that's why it goes like this so after the 710 this line represents the formation of carbon monoxide and below this 710 the line represents the formation of carbon dioxide okay so these are the key features of Ellingham diagram aluminium with carbon right aluminium with carbon you see this diagram Ellingham diagram what we have you see here aluminium and carbon aluminium is here where is aluminium here and carbon is this right see this thing first of all you understand one thing the logic is the one which is down will oxidize the one which is up right or in other word what we can say the one which is up can reduce the one which is down right this diagram is a rough diagram Krishna I'm telling you this diagram is a rough diagram so maybe some temperatures maybe here and there that precise thing we cannot draw right but actual diagram if you see in the book with respect to that you can say like here you see suppose if this diagram is exactly correct we are assuming right if this we are assuming it it has exactly correct so what you do you just um compare this point at this temperature suppose this is exactly correct diagram we have so at this temperature whatever the temperature it is suppose we have 13 degree Celsius somewhere here we have so what we can say this line represents carbon and CO O2 gives CO right so we can say below this temperature around 13 degree Celsius right carbon can reduce chromium right and chromium will oxidize carbon so it forms CO and chromium will get reduced but above this temperature what we can say chromium reduce carbon but carbon and carbon oxidizes chromium that's what we can say if this diagram is exactly correct again I'm telling you this is the rough diagram here maybe some temperature here and there we'll have you over here so exact thing is what what you need to keep in mind at a given temperature if metal A is above then metal B then we can say A can reduce B right at a given temperature so exact diagram you can go through in the book and see how it is given and from that you can say anyways whatever metal is the concept is this only understood did you copy down this can you move on okay now in this chapter we are left only with the extraction of some metals okay so that we are going to start Ellingham we have done we have also done the what is the various processes by which we can extract a metal now for specific metal what is the process we use so first you write down extraction of copper extraction of copper the ore that we use to extract copper is copper pyrite copper pyrite and we use in this the process that we use is smelting all these things you need to memorize you can read this in ncrt whatever ncrt given in ncrt that is more than enough okay the process is the same that we have discussed okay but here also we'll see I'll just draw the flow sheet here okay so what we do first of all we'll take copper pyrite copper pyrite what we do this copper pyrite we'll take must be crushed and sieved right crushed and sieved we crushed it and we'll sieve it right we'll take the all the major impurities the larger size impurities out from this okay in this ore now we'll do the concentration of this that's what we did okay we've discussed the general process that we discussed that is what we are following here then we'll do the concentration concentration of this ore and concentration will do here by froth floatation process what is froth floatation process again we have discussed okay so what we do here we'll write we'll take the ore that is powdered ore and we add h2o into this we'll add pine oil what is the use of this I'll tell you pine oil and air will allow to pass through this basic thing we have already discussed we'll get sulphide ore in the froth why we use pine oil pine oil that we use here pine oil we add and we also add potassium xanthate potassium xanthate you know this potassium xanthate act as a collector that we have discussed pine oil and potassium xanthate act as a collector and then what we do we'll do the agitation with this what happens impurities settles down into the bottom in the froth you have sulphide or we'll take this out okay second process is concentration by flow floatation process and we add pine oil and potassium xanthate into it okay as a collective that's what the thing is now the next step is what after concentration we'll get concentrated ore then we do the roasting of it roasting and roasting takes place in presence of air that we already discussed right in this process what happens the concentrated ore here that we get in this process the concentrated ore is heated strongly at very high temperature that should be less than the fusion temperature heated strongly right and the impurity that is present here suppose we have sulphur combines with O2 forms SO2 we'll remove this sulphur dioxide arsenic is one of the impurity combines with again O2 it gives arsenic oxide right Sb attached with O2 and forms again the oxide of it these two oxides are volatile in nature and hence escape right overall if you see the reaction in this the copper pyride which is 2 Cu FeS2 with oxygen it converts into Cu2S plus FeS plus O2 which further converts into the oxides of iron and the oxides of copper Cu2 this is what we get in this process okay this is the process roasting we have all these reactions takes place okay finish this one you'll hear okay now the third step is third step is smelting smelting that we do in blast furnace in presence of air blast furnace in presence of air the reactions we have here is this FeS plus Cu2 whatever iron oxide iron sulphides are left that will also oxidize into its oxides plus Cu2S FeO further combines with SiO2 and forms FeSiO3 right so most of the iron here removed in the form of this slag most of Fe removed in the form of slag okay in this process what happens the roasted ore that we get in the last step is mixed with in smelting the roasted ore mixed with coke and silica coke and silica right we add silica over here after this the next process we have here is Bessemerization and this takes place in Bessemer converter again in presence of air here also in this step also we add silica here also we add silica why we add silica that also we'll understand here but we see this first the reaction over here whatever iron sulphide is left here in the previous step it gets oxidized into its oxidized into its oxides FeO plus SO2 sulphur dioxide FeO again combines with this silica SiO2 and forms slag which is FeSiO3 copper sulphide 2 Cu2S also combines with oxygen and forms oxides of copper with sulphur dioxide in this Cu2 and Cu2S there is auto reduction okay they get reduced right auto reduction Cu2O and Cu2S combines goes under also auto reduction and forms copper plus SO2 okay two molecules of this we take it will be 6 and SO2 this copper we call it as blister copper blister copper which is 98% pure 98% pure blister copper okay and further in the last step we'll do the refining of it and for that we use electrolytic refining the last step is electrolytic refining so in electrolytic refining what is the anode we use anode is impure right so we use impure copper plate impure Cu plate large one cathode is what pure Cu plate because we have to take the same metal right electrolyte what we use we can use ions solution of copper CuS4 with S2S4 also we can use by S2S4 we are using because we won't want this sulphur to get reduced right that's why we are using S2S4 in this what happens the pure copper deposited at cathode pure copper deposited at cathode this is the overall process we have


question like how how do I get out of the linear to the vertical in the back of the text of the Course in Miracles he's got rules for decision and basically the first two rules you know are you know if I will make if I make no decision there's first the first one decide the kind of day that you want very very practical decide the kind of day that you want and then the second one rules for decision is if I make no decisions by myself this is the day that will be given me if I stay with the Lord if I want a happy day and I stay with the Lord I'll get a happy day guaranteed but if I rebel and want to have autonomous decisions and make all kinds of egoic decisions by myself you're heading for trouble emotionally you're not going to have a happy day it's going in the other direction he's got three four five six seven he's got other ways to come back after you've gone off the beam so to speak he's like saying stay on the beam in fact you know Jesus always emphasized in the Bible the first two commandments you know he was really emphasizing the first two commandments you don't hear him talking a lot about the rest of the ten commandments you know love the Lord I got all your heart soul might love thy neighbor as they self that's why he was focusing on was love and he focuses on his first two rules for decision he even says you know it's easier to have a happy day it's easier to be in the flow if you just can stay with the first two the others three four five six and seven or is your if you're off the beam he says it's much harder to get back you know so he's telling us right away you gotta really be focused and tuned in so you know you really have to desire this if you have a desire for the vertical if you have a desire for that alignment that desire is so powerful in the mind that you'll start to draw people to you relationships books movies music all kinds of things that will help you that will be they'll be like angels coming at you from every angle because you desire it and and one of the most difficult things is just things are so accustomed we're used to just following our past learning we get into ruts of just you know just like that people song of Paul McCartney it's just another day it's just another day you know the whole song is about just the repetitive monotonous kind of daily life that we go through or we're just marching along based on our past conditioning recently we had an experience where we did a retreat in Brussels and then we were on the way to the airport in the morning and they told us you know the traffic as you go towards that south towards that part of town can be very very heavy so we leave hours in advance so we left hours in advance we got on the highway the traffic got we were in the inside lane you know right over what the guardrail and the traffic got slower and slower and slower and then it turned from slow traffic into a parking lot we just sat there and the clock as we were just watching nothing was moving it was just sit there sit there sit there and then we're getting closer and closer to the time the plane supposed to take off and we're just sitting there the traffic is not moving people are getting out of their cars going like this is you know we're just sitting in the people getting out of their cars and then finally I was just sitting there in the front seat just kind of looking around I really had no investment but I get on the plane or not you know it's the moment it's the moment it's always perfect you know it's just this is what the script is I'm just but I'm looking over three lanes of traffic and I'm seeing that people are getting off the highway and driving on the grass leaving the pavement parking lot central lane parking lot and then another one over there and then I'm looking over there and I can see between these giant semi trucks this is huge trucks two people are driving on the grass I said look at that they're they're flying by at high speeds over there on the grass so the woman or Mel who's driving she was sitting next to me I said yeah I said all we have to do is get out on the grass because we're looking at all but she said I'd like to go between those two trucks and this I really would and then within like a few minutes the parking lot creeped ever just ever so slightly the big semi trucks opened up and a gap a crack appeared to and she went and she got us all the way on the outside and it started to move a little bit and off we went on to the exit now we had to continue going this way and then we could see the highway where we had to go to the airport it was all a parking lot it was just all no movement whatsoever so we got there to the ramp and she says this is we go from this ramp this is going the opposite direction of the airport they say yes go for it so we go zipping off with parking lot with highways jammed and everything completely opposite of the direction of the airport it's my glee leading the way go for it just go drive and the French GPS was you know I don't know French but I was telling us quite a lot are you making a wrong turn or you turn around at the next turn you know as polite as it can be it's that the GPS was one really a lot of French coming at us because I'm I'm directing now I'm the GPS I'm the God trans you know system positioning system God positioning system we're now we've gone because you know it's just a mode it's based on the past it's based on the you know on the maps and everything we're driving the exact opposite of the airport at high speeds and then we're looking and I said look there's then it says downtown Brussels said yes she's like yes so she takes us into downtown Brussels all these little narrow streets we're moving we're moving I guess I've been getting a little sightseeing tour of Brussels I had never seen Brussels so we go through all these different angles little teeny streets we're moving moving around here and the GPS was still all around us and we go around and go around and then this starts it the GPS always was trying to draw us back to the major highways you know that's what it does so we go like this we go come across we go back and it's still growing us so finally it starts to bring us back to the major highway and as we were approaching the highway I was saying this is the time I said everybody in the car this is the time to forgive just let go of everything that you think you saw think you know everything this and this so we got up to the highway which is the highway that's going to go over to the airport and the cars are slipping along at high speeds we hopped on the highway whoo we zipped along we zoomed over there we got there just just on time we were there on time because yes we had to go the opposite way and go for a tour through downtown Brussels and then come out and however it's that's what that's quantum the egos one I don't like that story at all it's like the place was a parking lot there was no way out I had you you were trapped you're gonna miss the plane you're supposed to stress out about future thoughts okay we're gonna miss the plane what are we gonna do how are we gonna handle missing the plane and all these different you know always wants to scare us with tragedy in the future based on our memories of tragedy in the past and it's a closed system and yet when we start to follow the spirit that's where we get inspired but it could take the form of going in the other direction of what you logically would think which we did we went flying in the opposite direction of the airport and it worked out perfectly