He's answering from a defensive perspective. But the thing is, he doesn't say, it wasn't me, I didn't do it. What witnesses were saying, though, was that when they saw the arm stick out the window and do the shooting, it wasn't a skinny arm. It was a bulky, hefty-looking arm. Well, I was in the passenger seat. He says, I was on the passenger side. And that's odd to be confronted with details like this for his involvement in a murder and not saying, hang on, man, I see what you're doing, I didn't do it. It wasn't me, I had nothing to do with it. I know what you're saying, I see where you're going with it. But let's get this straight right now. It wasn't me, I didn't do it. I was there, obviously I was there. Everybody tell you, I was there. Yeah, I said I was there and I'm telling you now I was there. But I didn't do it, it wasn't me. Nothing like that at all. He's being defensive, but he's not being defensive in the right way. So that's, yet again, another classic sign or cue that I would see as deception.


Okay, so my name's Yang, for I can tell I built, or rather I built an Isochrome map setting recently, and then that's what I'm presenting for I can tell. So just as an overview, an Isochrome map is, Isochrome maps is that you draw contours of equal travel time for a single point, but it's kind of like a topological map, but instead of elevation, your contours are travel time. So, I mean something I found is like, it's kind of easy to kind of imagine it, by 3D, so this is the Isochrome maps projected into 3D, starting from Bishan. So, this is for public transport. Folks have done it for driving before, but public transport in Singapore is particularly difficult because it's just hard to find a clean source of public transport feeds, the GTFS feed. So, what you find are things like this, like little islands or little rich lines on the map itself, because it's kind of places that are faster to commute to or more accessible. So, these are essentially your train stations, right? So, I mean a couple other patterns that we have here. I mean, this is taking from Chachukang, or Bukit Panjan, and the equivalent 3D version of it. So, Singapore is particularly peculiar in this case, but we don't really have any natural barriers except for that thing in the middle, which is the central water catchment area. Like the rest of Singapore is completely fine except for this thing, which kind of makes sense.  So, one of the boys in the office actually lives in this place called Floor Drive. So, for Boston. So, yeah, and so not just, you don't get islands just by, just through MRT stations. You also get islands. These are actually buses that travel down the expressway. So, these are actually, this is Selita Camp, this is somewhere else. Yeah, they are actually buses that kind of just run through this expressway here. Yeah, so, and then on Rated, there was these guys that were looking at Sumai Goodong Camp. So, Sumai Goodong Camp is awesome. It's like no man's land. So, okay, generally speaking, if the gradient is steeper, the travel time is, your speed is slower. If the gradient is gentler, your travel time is actually faster. It's kind of counter-intuitive, but that's not what I suppose. It's just an analogy in this case. So, the thing I like about Isochrome Maps is that it leads to other things. So, it leads to things like this one, which is, oh, where we, here we go, yeah. So, based on that, like, just when this, just when, shortly after I made the Isochrome Maps, the new twas line, actually, the new twas line extension actually came up. So, this is before the extension. So, this is how the maps look like before the extension, starting from Jurong East. So, mainly this area here. This is how it looks like after the extension. So, this area here, right? I mean, particularly this kind, this representation, not particularly great, it's kind of like, spot the difference. So, what I did is actually just conclued the deltas. So, these are the four stations that are included in the extension. And, the brighter the colors, the more time savings up to 25 minutes. So, namely around these two stations, if I'm right, is twas west and twas crescent, or something like that. They have it here, actually. So, it kind of makes sense. Like, if you look at LTA's reported time savings, it makes sense why they report only around twas west or twas crescent, because that's where the most time savings is at. If you look at Gao Circle, and twas link is not as impressive a time saving as the other two, right? So, this is one toy. So, I found this other guy's analysis on accessibility in general in Singapore. Absolutely not in Singapore. In general, you compare jobs that are accessible from a point within, say, X number of minutes. 35, 45, whatever. I try to refer from URA and the best data set for that is CPF, but that's classified. So, instead of using jobs as a measure of accessibility, I made this toy version which measures your accessibility to the nearest your de-hocke center accessibility index. So, within 45 minutes, how many orca centers in Singapore can you get to? So, it's kind of, it's very not really, because up here there's actually a lot of jobs in industrial manufacturing, up down here there's a lot of jobs in manufacturing, but it gives you a sense of accessibility in general. That's it. Just for questions, I see a lot of APIs from LTA for traffic fees, but you said it's normally dirty, can you elaborate? Okay, so to build the Isochronic map what I did, what you need beforehand is, you need this thing called the GTFS, general transit fee specification data set which compiles the public transport, which essentially is what LTA would give to Google for them to do their transport routing. That was back in the day, now they have real-time data as well. From my understanding, LTA gives it to them in some XML format that is magical, and then Google actually translates it across to GTFS themselves. So, I've been hunting for this data set for like four years, five years now, like since I've been back, and it is correct that it's actually Google's intellectual property because they did the conversion. So, from the data set, from what is released from LTA, they have the schedules for buses, but not for trains. So, for trains I actually had to scrape the various websites, I mean, consolidate manually the various websites. Yeah, and then all that is part, yeah. So, that is, I mean, it would be interesting to actually, the more accurate way of dealing with this is actually reverse engineer the path arrival and train arrival APIs, and then use that to can calculate the travel times. Like, but you're working backwards for that one. Yeah. So, yeah. Question, sir. Is there a way to visualize that in such a way that it's intuitively, okay, so in this one, I just start at the top and you go down on the mountain side. Yeah, yeah. But, you know, intuitively the further you are, the harder it is to get there. Yeah. It seems like there's some kind of inversion that would need to be done. I think the problem is with the analogy. Maybe it is my problem with my analogy if I use the analogy of equating it to topological maps. So, my question is, if you really leave down the top of the mountain, it would be super easy to go down. You want to do the afters. I think it's a problem with the analogy, not particularly with the representation, because I've thought of this particular representation for, I mean, okay, I take it back. There is, there are the guys over at MIT sensible cities that have done it before. What they did is that instead of drawing it in contours, they deformed the space. They respect time, they deformed space. Problemary part about that is that when you do, they did it with driving data, driving and bike data, which is somewhat continuous in terms of the contours. But if you do with public transport, you have islands and it's kind of harder to map that back into this kind of distortion. And it's also not that particularly easy. My point on this is this one is actually more for planning, you've got more for, I wanted to use it more for analysis, rather than for, I find that that one's a lot prettier. Yeah. How do you draw these contours by estimating the vast tree in the weather pack? Okay, so, okay, I lost it. So, what you actually do is that for every, you cut Singapore up into many grids.  Every point pings every other point. So every point you get to every other point in Singapore and you get a travel time from that. So you get kind of this grid and heat map of Singapore, point to many points kind of travel time matrix.  Essentially you do marching squares and you interpolate between points. So that's how you get the contours. Yeah. So, doesn't make sense, doesn't make sense, yeah. Let's see if I have one more question. What's the thing that actually generates the map? Okay, that's a, which part of the map? Okay, the thing that actually generates the, okay, so this is my pipeline. So from, from digging and scraping from GTF, digging and scraping GTFS, I pipe it into OpenTrip Planner, which does the point to point analysis. And then I take the data out and I have an offline script to draw the contours. Cause what comes out of OpenTrip Planner essentially is just a snack, yeah. And then if I really want the contours, and the reason why I need the contours or why I want the contours is because when they live as proper polygons, you can then perform geospatial analysis on it. Like, what's this? Now, you know what actually has this feature? It's just really far, it's hidden really far inside their interface. You can actually pick a couple of places, set a travel time, and then it will filter for the intersection spatially. So that's why I had to move one step further to actually draw the contours cause I wanted the polygons. Yeah. Thanks. Thank you. Thank you. Thank you.


Suspense and the producer of radio's outstanding theatre of thrills, the master of mystery and adventure, William M. Robson. A man's got to have a good reason to renounce his native land forever. A reason to say like death or worse, life under tyranny. For this reason, thousands of men and women and children who love freedom more than fatherland have made their way across the frontier to the west in the past two months. Of the more than 20,000 who have arrived in the United States, only eight have been sent back. This might have been the story of one of these. Listen then to freedom this way, starring Mr. Hans Conway. Look all the right side of the plane that you are there to stay. You will see the light of your life. But you cannot see them very clearly because your eyes are filled with tears. Look down there on the water. Yes, it is the statue of liberty. The statue of liberty. Mama, is that maybe heaven down there? Yes, my dear. Maybe it is. A midwire repellent there, everybody. New Jersey back. No, it is telling you we are landing at the midwire airport in New Jersey in America.  And that is all right. You can wait a little longer now that you are safe. You can sit and wait and listen to the men outside welcoming you with the music that reminds you of home. Hello, Harjo. You don't hear the officers. The feds are there. You lean back in their feet, wrapped in the warm mantle of security. Hello, Harjo. Oh, yes, sir. You, hello, Harjo. Yes, sir. Come with me. Hello. You understand English, don't you? Yes, sir. I said come with me. Hello. Sit down. Thank you very much, sir.  Yes, sir. And signed them? Yes, sir. Is this one of the forms you filled out? Yes. And this is your signature? Bella Harjo's? Yes, sir. But it's not your name. Is it? Is it? No. Your real name is Bartar, isn't it? Yes, sir. Do you know that the penalty for giving false information to the United States immigration authorities is immediate deportation to the country of your origin? No, sir. No, I can't go back.  I couldn't help it, sir. I had to. Why did you have to? You'll believe me if I tell you this. I'll try to. People are welcome here. We wouldn't have brought you here. But you've got to play the game according to the rules. I know. I know, sir. It was wrong of me, I suppose. But there was nothing else I could do. It was difficult to explain. How shall I put it? We were free, you see. For five days we were free. It was one of the ones who took over Radio Budapest on 23rd October. We renamed it Radio Free Budapest and we broadcast truth instead of lies. But not for long. Two days after the Russians returned, while the Hungarian freedom fighters were selling each three corner with their lives, I made the last drone. And I want to say to what's the radio? I'll give it to you. But as long as you're here now, you haven't got enough guns or enough ammunition. But we will hold on to the last drop of blood. Don't talk like this. Goodbye, friends. God save us all. Thank you, sir. The studio took a direct shelter and that was the end of Radio Free Budapest. Those of us who were not killed were herded into Koparoshihau, headwaters in prison of the dreaded and hated A.B.H., the Security Police. When my eyes became accustomed to the gloom of the cell, I discovered that I was not alone. Another man was lying motionless on the bunk, opposite mine. He was not sleeping, his eyes were open, but he did not seem to see me. He seemed to look straight through me. I smiled, but his face remained motionless. All distant. Hello. Hello, I'm talking to you. Don't you hear me? What's the matter with you? Answer me. Answer me! At first I thought he remained silent because he feared I was informant. And then, as the long night dragged by and the dirty gray light through the grilled window announced another day, I became convinced that it was he who worked for them. I was now convinced he was part of the psychological breakdown. He was the first modest step in a process that would end with my voluntary confession to a dozen crimes that I had never committed implicating a hundred persons I scattered. And he sat there and stared through that long day and the next. And then, sometime during the night, the guards came. Dear Reverend, follow me. Who? Me? Not you, the other one. We are not ready for you yet, but we will be. You, leader, come. Oh, why don't you stop this comedy? You know this man is one of you, a secret police. We do not shoot our own. And him we are going to shoot. It is true, my friend. You can talk. Of course, and here too. At first I thought you were an informant. Me? No, I thought now I know. So I wish you better luck than I had. His eyes were dry, his chin was firm, and he shook my hand. And then he turned and walked through the door. After the barred door had clunked sharp and was doubly locked and the footfalls had died away in the corridor, I unclenched my right fist. When he had shaken my hand, the condemned man had pressed into my palms and pitted for his small, steel file. I crawled around to the window. Yes, the center bars had been filed, almost through. It must have taken weeks of the utmost patience, a labor that my presence had interrupted, a project now devolving upon me. I failed to work with the will, but it was work, tedious work. The fingers aching as they sought to grip the tiny file, the arms bone-reary from the short, small strokes, but work that went ahead, all through the rest of that night and the next, until all was in readiness. I plied the bars apart and started out the window and got stuck halfway through. I struggled and turned, tearing by clothes, tearing by flesh and finally breaking loose from the iron vise. I lost my balance and tumbled into the yard below, full in the blinding circles of the prison staff line. Here, drink this slowly. Thank you. As I drank the chalky fluid, my eyes slowly came into focus and my ears into tune. I was in a bed in a hospital ward. My heart lived and then sank for the sun which streamed through the window fell upon the floor in the pattern of bars. I turned through the young nurse standing over me, impersonal, impervious. My eyes must have expressed the question as she replied impassively. You did not get far. You are still in Koporoshi House. I was not lucky enough to be shot. You will be when you have recovered. Why? Why did they not...? You must be quiet. The doctor will be here in a minute. She nodded toward the door and as I looked in that direction, the doctor entered. My heart stopped for an instant and then raced. I knew him. He was one of us. Or had been back in 1944 in the days when the underground was pushing the Nazis out of Budapest. This is a new patient, doctor. Attempt at escape. Oh, yes. I was told about this one. Doctor. Doctor. One of the freedom fighters, eh? Seems you have lost your freedom and there is no fight left in you. Am I a little man? Doctor. Aren't you, Fakute Damo? Don't you remember me? Don't you remember how we held the market ticket against the Nazis in 1944 when we were both students? Obviously, delirious nurse. Increased sedation. Fakute Damo, what are you doing here? In Koporoshi House.  Our father shouted them in 1919. We shouted them in 44. Our those kids shouted them last week. Mergers, rise!  Meet this hour, what air before you. Yes, obviously delirious. Better move into a private room where you can't disturb the others. Yes, of course. Now then, it's this. It was not long before I learned why the renegade of the circuit had moved me to a private room. Late that evening, when the hospital was most quiet, he paid me a visit. Well, how's the little freedom fighters tonight? I don't need your care nor your insults, Dr. Pernk, old secretary. I was quite assured you put her in the walk in the afternoon, gave her bar talk, but scarcely the time nor the place. Oh, you did remember me then, eh? You voiced down. You didn't expect me to recognize you in that crowded ward, did you? No. No, of course not. It was foolish of me, but to find you, you working for them, I know. No, why? Dr. Fakete, why? Are you a merit-giver? No. Revolutionary cannot afford the luxury of family life. And a family man cannot afford the luxury of revolution.  You will think differently when you become a husband and a father, which is as likely as my ever-escaping from Kapurashi House as I have all with my assistance. Oh, Doctor, forgive me. I did not realize. There are more ways of serving than shouting patriotic verses at the top of your lungs. Yes, yes, of course there are.  Make me ill? Listen, I feel bad enough as it is. Yes, but your brains and confusions aren't enough to keep you in the hospital more than a few days. And we may need more time than that. Four, boss. How will you get me? I'm having the slightest idea at the moment. In matters of this thought, we improvise as we go along. Doctor Fekete was true to his word. The following morning, the nurse Anna gave me an injection. And by that afternoon, I was sicker than I ever remembered. Time stopped. Days and nights ran together in the mercy of the Miriam, marked only by the periodic hypodermic injection. At last came the day when the injection did not throw me into wretched convulsions. Instead, my head seemed to be clearer. I was dimly aware of being wheeled along the corridor by nurse Anna. And then I found myself in a small operating room. Doctor Fekete was there and the nurse and a steel form on the operating table. A form with a sheet drawn over its head. And vaguely I hear Doctor Fekete saying... Make out the gesture of physics at this way, nurse. Name? Bartoguesa. Cause of death? Internal injuries sustained while attempting escape? Doctor. Doctor. Yes, Guesa? Just like quietly. Since you are now quite dead. You can fill in the rest of it down at the most. There is no more room in the most, doctor. They are stacking the bodies in the courtyard now. Good. In that case, there is mostly the corpse of Guesa Bartoguesa. But it's that Guesa Bartoguesa lying there and he says, Who am I? You are now Bela Haydor. And you have a great deal to learn while you're convalescing from your emergency up and back to me. It seemed too good to be true. There must be a flaw somewhere. I worried about it. I wondered about it as the nurse reared me back to a new room. Two. Bela Haydor's room. When the doctor came by that night, my head was buzzing with a dozen unanswered questions. But doctor, if I couldn't hope to get out of Koproshaus, how can you be so sure that Bela Haydor's will be released? Bela Haydor's was picked up along with a hundred other suspects two days before the rebellion began. Security police could prove nothing against him. Then why wasn't he freed and we took over the city? He was in the prison hospital with acute appendicitis.  He was still there when the Russians returned. Certain proof that he had nothing to do with the rebellious. He will be released as soon as his... you're up at deck to me. To assure, I guarantee it. Now take this and learn it tonight. What is it? The facts about Bela Haydor. The answers to the question you will be asked before they release you. You must be able to answer everything on the stage instantly. A single slip will mean death for you. And for me too. But why are you doing this, doctor? Call it patriotism or guilty conscience? In any case, it's the least I can do for a man like you. I spent the rest of the night reading and rereading about the man I had become. Concentrating fiercely to absorb every tiny detail. Then, a few moments before the nurse arrived on her morning ground, I followed the doctor's orders, tore the piece of paper into a hundred pieces and swallowed them. And that night, Dr. Sekati began rehearsing me. Names? Hios Bela. Date of birth? 7 July 19th. Place of birth? Modirova. Military service? And the Lieutenant 14th was ours. Boomed at twice. The war was trying to... Over and over again, hour after hour, night after night. Mother's name? Viterana. Father's name? Janos. Very good. I would say you're ready to be released from the hospital at last. What about my identity paper? Your personal effects were taken from you when you were arrested. The paper will be returned to you when you are released. Passport? It's a lot of Hios pictures in it. And so it has. Your pictures. But how do you think we are not thorough? At least as thorough as the security police? Yes, but how could you make... Geyser Bartok was photographed when he was arrested. Was he not? Yes. A photograph of Geyser Bartok is now fixed to Bela Hios Passport. I don't see how you could manage. If he survives, a slave sometimes has to excel the master at his own game. Be prepared to leave the hospital in the morning. When I appeared next morning before the interrogating officer, all hope left me. He was not of the Hungarian security police. He was a Russian, a captain in the Soviet intelligence service. Apparently, the Russians were taking no chances on another slip-up in this satellite. On the desk before him was spread the doctrine of Bela Hios. And the play for which Dr. Serkipi had so well rehearsed me began. Name? Hios Bela. Born when? 7 July 1920. Where? Modirova. Mother's name? Zita Radna. Mother's name? Arm and arm, question after question and answer after right arm. Finally, the captain seemed satisfied and tore open a brown manila envelope dumping its contents on the desk before me. A few coins, a wallet. Wait. What is this? A passport. Yes, sir. Where are your other papers? Identity card, Russian card. They came for me in the middle of the night. I did not have time. No time? No time to find anything but a passport? Because a passport is what you need to get over the border. Why did you want to leave the country? I didn't want to leave the country. You needed a passport to cross the Danube from Budapest? No, but the passport has always been sufficient. You wanted to leave the country? Why? Why? Why? But I didn't. You lie. All Hungarians are liars. I forced back the compulsion to stick into the face of this tiny slab.  As I picked up the wallet, something fell out of it and fluttered to the desk. A picture of a woman. A woman who was a complete stranger to me. Before I could retrieve it, the captain snatched it out. Who's picture is this? My wife. You do not seem sure. Of course I'm sure. It's my wife. Name? Margie. Age? 25. You love her? Yeah. She loves you? Of course. Then why is she not here to take you home? She didn't know about being released today. Why didn't you inform her? Do you think anyone from here would have taken her the message? Her? Yes. I would have. Not bad. Not bad at all. Undoubtedly one of the heroic women of Budapest.  Why is she here to meet you? I wanted to surprise her. It is a scene I must witness. The surprise of your hero wife. You do not mind if I accompany you home? No. Of course not. I knew the game was off, but I was determined to play it through to the last move. I sat beside this distrustful sadist in the back of this tough car and just picked our way through the rubble of Budapest. I thought time had turned back twelve years to the war. Lime-covered bodies still lay decomposing in the state. Smashed and burned tanks blocked the intersection. In a hole blown from the third floor of an apartment house, a bathtub teetered ridiculously. There was no traffic. Budapest seems uninhabited. For that day, all Hungary had gone on a general strike of process. At last our silent journey ended at 19 Molnarschild, my home. I mean, Bela Hoyo's home. What are you waiting for? I'm afraid. Of what? My wife, when she sees you in that uniform, I'm afraid she will be frightened. A Hungarian woman frightened? I thought nothing frightened, a Hungarian woman. Get out. Please, let me go in alone. Just for time to explain. Go explaining. I will explain. Who's there? It's I, Bela. Bela? My addition, darling. I'm back home, back home. You didn't expect me, I know. Darling, so good to hold you in my arms again. Happy. She does not seem so happy to see you. I told you she'd be frightened by your presence, but she is happy, aren't you, darling? Of course I am, I am happy. It is just I am very lost for words. There, you see, Captain? Would not any of us be happy when her husband returned, even if he does forget to kiss him. Oh, my love, forgive me. Mama, mama, can I go out and play? I am busy here. Oh, a lucky... What? Now run along or he will take you away with him. This is your child? Yes. I asked him, yes, it is your child. I suppose she has a name? Certainly. I asked him, what is her name? Wait, it's... It's her, it's her.  But that is my name. Of course it is, darling. And now she will excuse us, Captain. My husband and I have a lot to talk about, privately. And thank you so much for driving him home. Did you all... I owe you an explanation. No, no, you do not. My old cutie, my thanks for not giving me away. Cutie's father taught her not to ask questions in front of strangers. Then did my husband die? A week ago. I knew he wouldn't be back. It's time I knew he wouldn't be back. You must be hungry. May I get you something to eat? No, please don't bother. It is never a bother to see the hungry man. Great-grand-husband dead. There was nothing to keep Margit in Budapest any longer. And certainly it was no safe place for me. And so Bella Hayosh, his wife and daughter, made the long difficult journey across the frontier to Vienna. Well, that's quite a story, Mr. Hayosh. There's one point that beats me. What is that, please, sir? Once you were safely in Vienna, why did you go on impersonating Bella Hayosh? Why didn't you tell the authorities the truth? Because of Cutie, mostly. During that long trip across the border, hiding in the forest, wading through swamps, walking in the cold rain, she clung to me and called the Papa until it almost seemed as though I really were a Papa. Yes, until it seemed I was really Margit's husband. I was all the head, you see. They needed me. And so you entered the United States as man and wife. That's right, sir. But you're not married. There was no time. That's another section of the immigration law you've broken, Mr. Hayosh. It comes under the heading of moral trepidation. Yes, Mama. You used Papa talking to the man. You must be sure you're not Cutie. You can see if you do. Who was the man, Mama? I thought you said Cutie had been trained not to ask questions in front of strangers. Why? I told her it would not be necessary in America. I told her in America it was safe to talk to anyone. What's your name? Call me Uncle Sam. Are you a good uncle? I try to be. Oh, one last question, Mr. Hayosh. Yes, sir? How much money do you have with you? I'm afraid not very much. I'm too pangor and I'm often shillings. No American money? Oh, no sir, but I hope to find a job quick. I'm sure you will. In the meantime, here's two dollars. But why? Take them. You'll need them. What for? The marriage license. Juan Connery starred in Freedom This Way, produced and directed by William M. Robeson and written by Erno Valabes, Max Colpey, and Mr. Robeson. Heard in the cast were Margie List, Melita Milo, Norma Jean Nielsen, Charles Ravillac, Joda Santos, Jack Krushen, and Fritz Feld.


All right. Hello everybody. My name is Master Chen and you are watching or listening to Twitter word frequency. Welcome to my talk All right, so let's start with who I am or who am I I'm a prior b-side speaker where I spoke about being a con man and working in Vegas surveillance I spoke at Defcon on VoIP security and as well as a DC sky talks on automate your stocking, which we'll kind of cover a little bit about today and and Most recently the recon village in the last few years where we talked about stocker in a haystack URL shortened by any other name which was last year and of course this year and this talk just It's virtual now You could find me at Chen box now that is my handle on on most social media. So so feel free to follow All right, so let's get into this and let's start from where We are at this point in time and and that I think that'll that'll help us understand Where my mindset is when it comes to comes to this talk So of course I started with automate your stocking where you know, I was digging into my Twitter research This is bad and we learned that during the DC sky talks a couple of years ago So the following year I did stalker in a haystack where we Figure out how to not be stalked or at least we can detect cyber stalking And that was that was good And now I've gotten recently into political sports betting or you know market speculation Which is part of the story And profiling I mean profiling like social media profiling on different accounts And of course I do have a degree in psychology. So all this kind of wraps up into where we are at this point So these these five pieces Are what kind of has has you know gotten around this this research here? So about this talk I'm gonna start with the original goal and how I came up with what I was researching at that at that moment Why that failed and why? We move on to what it is currently now as I'm presenting this and what I would like My current research to be in the future So before we get into all of that though, let's talk about caveats and disclaimers and warnings. Oh my I'm bad at that.  I'm gonna add something new to that because I'm very new to the whole data science thing I've only recently gotten into Using pandas and scikit-learn and and numpy and all these different data analytics tools So I've added I've added Inaz. I am not a data scientist I'm not a lawyer. I'm not a stalker and I am definitely not a data scientist, but I'll try my best So this project is a work in progress And I'm hoping that after I explain kind of what we're doing here today That maybe I can get some help from the community to further this project or at least now that I've defined the basics I can continue and make this something very strong This is a neutral tool I'm not I'm not building what I'm building today for Stalking purposes for you know, this is just a tool you use it how you want But of course as always I'm not gonna be held responsible for for what you do with with my research And I did not stand on the shoulders of giants for this research what I mean by that is I Know that there's a lot of research already in the space when it comes to frequency analysis word frequency analysis You know sentiment analysis NLP not neuro linguistic programming, but natural language processing I know that there's all that research out there and I I barely used any of it. So I would like to integrate that later, but I just want to let you know that for this particular talk That was really not used so It is definitely a work in progress All right. So again for those of you who know me. I'm not a sports guy I've only recently gotten into hockey and you know, I've always been a UFC fan But other than that I'm not a sports person So I've never been into the sports book There's one thing I know about being in Vegas for for my entire life is that there's a sports book for every market It doesn't matter what the market or what the speculation is There's a sports book for it or or a betting market for it. And that's kind of where we start our story So if anybody's ever heard of predicted org, it's a market for political sports betting So you can bet on you know, who you think the next president's gonna be not just in America, but globally, you know Pick a country pick a state pick it, you know Impeachment hearings Who will run the White House who's gonna be the VP pick all of these different markets are on predicted org And so you can you can make a fair amount of money if you're if you know what you're doing Or you can just have a casual bet and and just be right with a few dollars and cents and so and specifically we're gonna be talking about President Donald Trump's tweets as that because kind of a famous thing here And and how it it pertains to the political sports betting market Okay And well, let's get into that now because right now we're talking about pi count Com which is a tweet counter that's out there on the internet And it keeps track on a weekly basis of the president's tweets as well as the VP the White House and the POTUS accounts And this is all geared towards the the tweet market that predicted offers or used to offer and we'll get into that in a second but We're talking about Twitter, you know Twitter markets again This is on a weekly basis the question or the market is How many tweets will the president tweet out for this particular week starting from Wednesday of this week and going on to? Wednesday of the next week it could be anywhere from, you know, 50 Which is which is highly unlikely all the way up to you know, 300 400, you know, and and that's that's what I was analyzing the forehead Now I wanted to know if the profits could be based off of analytics and you know, could be Could I anticipate what he would be tweeting based off of current events news drama Anything that's out there in the global space and the goal the goal with this original research was to get the president to pay for my energy bill So if I made enough money on this predicted org market Could I pay the energy my energy bill at the house? With with Donald Trump's tweets. That's that's where I was going with this whole thing. So again prior research is The frequency of the tweets how often he would tweet in that week and and I was capturing as you'll see here In the CSV file on the right side of the spring here. I was capturing On a weekly basis. How many tweets how many tweets did he do in this week? Well, we see 68 in the week of April of 2019 we see 137 140 141 so these are all A rolling tally or running tally of of his tweets and of course you graph it using Using Jupiter a Jupiter notebook, you know, you you graph it and see the frequency here and then you ask yourself, you know was this peak here due to impeachment drama was this due to some sort of scandal or emergency in the Middle East What caused these peaks of tweets? Was it just somebody getting on the president's nerves? These were all the questions that I was asking at the time, but there's a problem Predict it org actually stopped their their tweet markets. So while well predicted is still around They no longer offer You the ability to to bet on tweets and so all of this research has kind of just stopped You know, so they changed their offerings They they started to offer other markets that just weren't working fast enough You know, these other markets aren't resolving on a weekly basis and so my profits slowed to a halt And so because of that this whole project that I was working on as far as tweet frequency It it kind of took a pack a back burner and I kind of forgot about it for a couple of months But it got resurrected and so the project lives and I'll tell you why so I Tweet on a regular basis and I tweet very vague vague things And that's on purpose. I would say it could be a zen of the day quote. It could be Something obscure or just something that's on my mind, right? Because that's exactly what Twitter is used for you You post something just because it's something that you're thinking about and then you just let it out there It's not always political. It's not always socially driven. It's just a thought that's on your mind. Well, I Had one of my followers Kind of get a little bit offended or had a little bit of ruffled feathers here with one of my tweets and So he kind of got mad at me and you know, what? I Wasn't being political but the vagueness of my tweet allowed this particular person to Project their political ideals on on my tweet. So I thought about that for a while and I could have gotten mad and you know gotten back and forth with him But I didn't and instead like I don't get mad, but I will turn you into research and and that's what's bringing us here today so again the target projected their beliefs on me and the meaning of my tweet even though There was no correlation there. There was nothing to draw conclusions from okay, and so Blindsided by rage meaning that I had no idea that I that this was going to be happening But I asked myself could I have seen this coming? Could I have predicted that maybe what I tweeted would result in a certain outrage from not just a certain demographic but for maybe specific people and This is still the work in progress So Who are we targeting with with what we're working with today? Well as as stayed in the last slide we're working with political opponents or we're talking about political opponents and not because we're trying to be political but just because This is a use case for what we're doing. This is a scenario Corporate marks we could use what we're going to do today for you know spear fishing or maybe password lists or some sort of targeted Execution of of an attack Cyber bullies, you know there are plenty out there and wouldn't you want a leg up if you knew the type of vocabulary that they were using the Way in which they tweet the sentiment behind their tweets and maybe you could You know work for a better outcome Against your cyber bullies because yes, they are definitely out there Now sadly I have to address this This also has some stalker interests But remember what I said before and in my previous research Stocker interest. This is bad while it can be used for stalking. I do not condone it I I think we've we've crossed that already. Yes Okay, so what are we talking about? Well, everybody knows Twitter is a goldmine for oscent and recon. Okay, and and it's not a secret It's it's very well known and it's it's that way by design Not everybody has a private account and and it kind of ruins the fun if you are on a private account So Twitter we know as a publicly shared sentiment if you're gonna put it on Twitter, you have to expect that It can be analyzed. It can be scraped. It could be mined. It could be Used for research such as today's research So what we're doing though is we're making an at-a-glance picture of what this profile a target profile Is about what it's all about. So You know the term at-a-glance what I'm talking about here is instead of Instead of having to scroll through an entire timeline to understand what this particular profile is all about What if we could just take a look at a dashboard or or just one screen and understand the sentiment of that? Twitter profile that's that's something that I think would be very valuable Why why are we doing this? Well? Because I can because we can we're hackers and this is what we do We look at something we look at a problem We look at maybe a scenario that has recently happened to us and we say okay I know how to fix that or I know what I can do about that. So yes, because I can because we can remember we're hackers All right, and we also want to do this because this gives us an insight into tendency of the profile Okay, again, and the goal is here to to find maybe quicker red flags. Maybe catch that outrage Before it bubbles up and blindsides us Okay, and of course as with anything we can use this for later weaponization We could turn this into something that could be an offensive tool if needed, of course We're talking about password lists further social profiling Maybe psychological profiling and troll bots, you know, maybe they could have a conversation with themselves Now how are we going to do this? Well, we're going to look at a couple of things We're going to track a small sample size of the Recent tweets in the timeline and an ongoing sample of course as we add that programmatically And we're going to be doing our analysis on word frequency word choice retweet frequency And hashtag usage. That's actually of course as we know it's pretty important Okay All right, so let's take a look at the code. But before we do a couple of notes here And you can play the game at home actually so now by the time that you're watching this This should be available and public for you and your consumption so you can follow along with what I'm doing here In the next few slides, so I'll go ahead and give you a minute to to take that link down And we'll go from there Actually, there's a couple more points here. So It's just basically my github handle and you know the name of the project twitter word frequency Now we scraped I scraped this Information with python and it's all python all this is python Um, but I scraped with an actual python file And then I use a jupiter notebook for more analysis and there's a reason for that as well And we'll see that in the next couple of slides In the background here, you'll see your code snippet of the actual script, which pulls the timeline Now there's a couple of things here. It either Checks to see if the timeline has already been saved on your machine And if it hasn't been saved on your machine, it then goes out using the twitter api To grab the latest Timeline of your subject or of your target Okay, now in the foreground here, you're going to be seeing A snippet from the jupiter notebook and I used the jupiter notebook because Maybe I wanted to run a little snippet of the code without running the entire script So a lot of the code is going to be the same but with With jupiter notebook, you know, and I'm sure everybody who's in data science already remember. I'm not Um, you you already understand that you can take these pieces of or snippets of code and just run those individually and change things as new data becomes available to you All right, so let's talk now about the analysis. Okay, so this first analysis is actually Myself. This is my own analysis on on my handle at chinbox Um, so on the left side, uh, you'll see a couple of the words here that I've used that on a regular basis, of course with with the most current recent events you see Mask is used there six times a twitter, okay, because I've I've had Opinions about twitter on twitter. Okay, so that's that's there. Um, now you'll notice that these red blotched out Pieces are actually These are twitter accounts. Okay, and and how often I've referenced these twitter accounts So this can be a way that we can again we're talking about at a glance We can see who we're looking at who We're associating with Quite quickly and and right right up front. Okay On the In the middle on the on the top side, you'll see I have a red dot right next to Rt Rt medium course retweet and you'll see that my retweet frequency is about 54 times in a 200 tweet sample That's what that means remember. This is out of out of 200 tweets 200 tweets 54 of those were retweets of other people and of course All these twitter accounts that are blotched out Um, I think it would be safe to assume that if I'm not mentioning somebody I'm definitely retweeting then At the bottom, you'll see 26 38, which is the word count associated with the last 200 tweet sample of my own personal account I'm using mine as a base as a baseline And on the right side You'll see my use of hashtags and of course its frequency and at the bottom is the Um association with the histograms. It's a histogram associated with With the hashtags there at the top At that and there's there's my handle. So, you know that this particular slide was for for my own profile analysis Okay, so, um, remember that person that I said got kind of angry with my vague tweet Well, this is uh, this is the analysis slide of of his account. So You'll see that there's a couple of differences, obviously Because we're not exactly the same On the left side, we'll see a couple he's he's mentioning a couple of people who are blotched out Not as frequently as maybe I do but you know, these these profiles are in in the scan that I've seen You'll see his retweet frequency is 178. So so out of 200 out of 200 tweet sample We're talking about 178 of those being retweets retweets and I also hit the A red dot on the word I because I was just kind of curious as to see How often somebody is Um is using I in a sentence. I'm sure that there's a psychological profile Based off of The use of that word, right? and at the bottom we see The word frequency 37 88. I know that there's math that we can do on this word prop or on this On this word count as far as Calculating, you know, the types of words that we're using How big they are how small they are etc. And and another interesting thing about this particular analysis is The histogram on the right side Indicates that this particular individual only Tweet or only uses a hashtag once like One and done. So I found that to be interesting Again, this is for the at my target. This is not The actual twitter account obviously But I thought I had to identify it somehow Now lastly, I'd like to you know, I use myself as a baseline. This is the targets um dashboard analysis and This next one is Actually, uh president donald trump and we'll see of course a couple of uh, of of key features here on the left We don't see the word I actually we do but it's no more than 20 times now For those of us who might think that uh, president trump is a little bit of a narcissist We might be kind of surprised To see that he's only tweeted the word I about 20 times in a in a 200 tweet sample at the bottom there. We see 3400 words. So these these are all, you know, kind of interesting the same stats He's retweeted only 96 times In a past 200 tweet sample, of course This piece is not so Surprising because we know that he uses a lot of his own words In his tweets, um, but uh, back to the left side really quick. Um, the only blotched out account there Um, I don't know if anybody wants to take a quick guess at what that is. I know I can't Wait necessarily for your answer as as uh, this is the closest that we can get to um audience participation at the moment But uh, yes, if uh, if you guessed that that was his own account you are correct So he's what i'm saying here is he's mentioned himself in his own tweets about 46 times So that might be a an indicator of narcissism. Maybe tweeting in the third person will have to analyze further for that And on the right side, we'll see um, again our histogram and and hashtag matching so Um, uh, president trump has maybe tweeted a couple of things with hashtags But of course the recurring one is maga. Is anybody surprised? I don't think anybody is I'm not And actually that would have been three if he didn't add emojis to that Third maga there at the bottom so again, my point is All of this was programmatically programmatically excuse me. Um, all this was programmatically scraped and and put together so that we can at a glance take a look at what A target is talking about And and this is done. I understand that you know, this could be easily done through apis and other research This is my own Basic whiteboard. This is my own started from scratch analysis of these targets myself President trump because of the sports, uh, bedding And of course somebody who got really mad at me for something that Was really vague Okay, so now that that's uh an overview of the data really quickly. Let's take a look at the insights here So some of the insights um It seems like of course Retweets indicate shared sentiment. Well, uh, but the question is From who who are we sharing a sentiment with? This might give us insights, of course into Who a person is associating with or how frequently or How how closely related these ideals may be that they share Depending on the retweet, of course And of course we see narcissism in hashtags. So you may see a lot of A lot of your your own actually, okay, so there's a couple things here. I did forget to include Uh a screenshot that I have of my target tweeting himself like his own handle in In the hashtag so his hashtag his own handle And I I found that to be very narcissistic Kind of interesting, but that's something that I wanted to Piece in there. So I do apologize for not having that screen cap in there But I found that to be interesting And that's why I put that in in here in the insights um and Repeating hashtags to me, of course, again, this is this is kind of obvious when it comes to somebody who's a regular twitter user Um, it depicts brand or focus, you know, and of course we see that with with the repeating hashtags um Now I've noticed that word frequency um the word frequency count significantly drops off after stop words so, you know, I have a rudimentary introduction to uh natural language processing so I understand a little bit about tokenization and What stop words are stop words being like uh in the very small Words that kind of glue the english-led language together right And so again after after those words are scraped off the top the the frequency of those words of other words Really drop and of course for those who are linguists May already know that Now, um, obviously with what we've uh with what I've presented today We know that descriptive statistics are as far as we can get Without any sort of further, um analysis with better tools better tools being of course, uh, neurolinguistic Not natural language processing. Maybe some other types of data science tools and Techniques and so that is where this work in progress is going to be heading next Okay, and so speaking of which, uh, where do we go from here? Okay, well, uh, of course I want to clean up the data collection data collection methods right now It is pretty rough and I'd like to turn that into something that is uh easy to read and and followed very Uh very easily Now better data visualization. Um, I quickly grabbed screenshots together Um, but of course I'd like to incorporate word clouds and other charting. Maybe better charting, right? Um dashboard of data, I'd like to clean that up so that again the the whole goal is an at a glance for For a twitter analysis Okay Now what can we do with this? Well, we could talk about a profile scoring. So for instance, um Leaning's whether it's a sentimental leaning a political leaning a corporate leaning. I'd like to see if we can we can understand that At a quick look The potential for extremism If if somebody's getting mad at you for a tweet that was vague enough for them to project Meaning onto it Then then what is the potential for somebody to go kind of a little bit more off the rails? That's something else that I'd like to look at Um, and of course, um ongoing me being a psychology buff You know ongoing psychological profiles and red flag notifications If there's a red flag with anything that we see here in in their timeline Can we detect that and of course? Um, I am I'm almost certain that there's already research out there I'd like to continue looking at that myself and and building from there So features to incorporate I've said it a lot already Um natural language processing. I think that'll be a very uh a very good thing to add in here sentiment analysis also part of part of that space a mirror but Really quickly what I want to talk about there is is um If we know how our target speaks can we make a bot that kind of Talks to themselves. I think that would kind of funny to watch. Um Hopefully doesn't get anybody banned, but I think it'll be again. It'll be Funny to see just as a funny project. This is all just it's just jokes folks. It's just jokes um Now I want to build off of the prior research that I myself and the community has done Including my my stalker research and and anti-stalking research and anything else that the community has done I'd like to incorporate in what I'm doing now um And even though we've even though today I've only shown three profiles. I'd like to do a quick Mass script a mass scripted analysis of maybe everybody that is following me or everybody that I'm following and just see What kind of results are in their timeline? These are public timelines and of course, um, I don't want to Hit any rate limits. So we'll we'll do it slowly some future some future questions that are on my mind when it comes to this is Can I get a target to talk to themselves? Uh and agree or disagree? I think that'll be funny That's what I was mentioning with the the mirror bot Can a person have a conversation with themselves and disagree on their own? Maybe extremist points or non extremist points, you know Next question is, you know, can outrage be predicted, you know, that's an opinion that I that's something that I've brought up Prior or earlier in in this talk as well Could that be predicted based off of what is in the current events in the news and what's going on globally? at the moment Next one, of course any questions that the audience may have for me. I would definitely want to put that into this project So to summarize Who said nothing came nothing good came out of sports betting? I think I think there's some benefit here. I'm glad that I went to Tom's rabbit hole Uh now sharing vague sentiments can can still make frenemies, you know, apparently I've I was Not expecting that even with today's climate, but hey, it is what it is Um now remember don't get mad Uh, you know, don't get mad. Don't feed the outrage. Just don't get Don't you know, don't send the rage back just get productive Take what you have and turn it into research. That's been that's been my guiding light for the past five years Maybe longer. Um start somewhere. Like I said, this project is definitely a work in progress But I'm going to start somewhere and of course we build Uh, okay, so fork me There's the link again to get hub link if you didn't get it before. Um, twitter word frequency and oh, sorry I'll give you a couple seconds on that one A couple more And resources so the top link is actually another, uh, uh, it's college speech on, uh, Natural English processing and and and how that goes And then of course, um, oh these next two, uh These next two links are very good. I'll let you check that one out Because uh, those are actually a kind of in line with what I'm trying to do But on a massive scale for myself like I'm trying to do this on a massive scale What these last two links are doing specifically for Donald Trump's, uh, tweet account Uh, thank you very much and and that concludes my talk


Welcome to ITU Telecom World 2017 here in Busan in the Republic of Korea. I'm very pleased to be joining the studio today by Chi-Hung Lee, who is president and CEO of the Seoul Digital Foundation. So Lee, thank you very much for being with us today. It's my pleasure. Now I'd like to start off by talking about smart digital transformation. It's a question I've been asking most people who've been coming into the studio here. It's the key word, the theme here for ITU Telecom World. Perhaps you could tell us, what does it mean to you? Okay, so let me make it very simple. So digital technology is connecting people and things and space within a city. And cities are generating huge amount of data. Those data are collected and online to make a city smarter. In short, digital transformation is city becoming smarter using digital technology. Okay, fantastic. Now tell us a little bit about the Seoul Digital Foundation. What do you focus on mainly? Okay, so Seoul Digital Foundation is under Seoul Metropolitan Government. We work for a city of Seoul. We developed a strategy for the smart city. And also we are offering digital education for the city. And what are the key smart opportunities and challenges for Seoul in the next five years, let's say? We are investing lots of money to build a data network. We believe that the data network is the basis to make the city smarter. And also we are building up the capability to analyze data systems. So we much focus on data network and data analytics capability in the next five years. I mean, Seoul is a big city so there must be a lot of data coming in. Right. We are trying to combine the different source of the data into the one single platform. That is the most challenging but the most important thing. Sure. And how is Seoul managing public data for citizens? Okay, so we believe that opening public data is very important for the city. So we published important data on the website and mobile. And also we published very important but private sensitive information at a very close area. Where citizens are allowed to get into that place. They have access to private information. Then they can process them for their purpose. They can take the results to the outside. They are not allowed to bring raw data to the outside. And what kind of data are people most interested in? People and business are interested in the data such as personal transaction information. So the business can make a decision based on that information. Then they can forecast the sales also. Right. So in other words, people taking public transport, people using their mobile telephones, people using electricity I would imagine, all of these kind of elements as well. It's okay. Great. And how do you measure the smartness of Seoul? Can we talk a little bit about how is this all this data collected? Actually, we still don't have a specific guideline for the KPI for smart city at this moment. We are working on to have our own KPI. We believe that KPI shouldn't be the same to most cities because the city has their own priority. So we now much focus on the digital business side as well as the innovative public services. So we try to combine both into the one KPI at this moment. Okay. Great. And now you're here at ITU Telecom World. This is a key event in the ITU calendar. Why is it important to you to be here? And do you have perhaps a message to the participants here? Why? So the ITU, this event is very famous for the smart city readers. So I saw lots of people at this place. So it will be great for me to expand our network and share the experience with the readers. That is a great value for me. And also I like to communicate excellent in digital capability of the server to the world. Fantastic. Well, that's great. You certainly have here. And many thanks for being with us in the studio. And we look forward hopefully to catching up with you again in the future. Yeah, it will be great. Thank you so much. Thank you. Thank you.


Minister Hlangonani Gumbai, cooking with Zomiza was a waste of money. Deshado Minister of Tourism, Hlangonani Gumbai, said the cooking date between Zomiza might longo and the Minister of Tourism was a waste of money. Minister of Tourism Mamaloko Kyubei and Gubain hosted a celebrity cook-off event, which cost R150000, ahead of budget-debate vote last month. This expenditure was completely unnecessary, wasteful, and does nothing to help the tourism industry get back on its feet after the government-led lockdown. Instead, what it does is promote the Minister and her public profile at the taxpayer's cost, said Gumbai. He questioned the Minister in Parliament last week where he demanded to know how much was used and the reasons why the event was hosted in the first place. Kyubei and Gubain said the R150000 was used to cover the venue and mobile kitchen hire as well as event staffing, safety, event compliance requirements, the stage, sound system, food supplies, exhibition set up, and publicity, including live streaming of activities. She said the event was meant for departmental awareness activities, including giving graduate chefs from their training program the platform to show what they had learned. It is also important to state there was no payment made to Mr. Somaizu Maite Longo and the department notes with concern the general public perception that he benefited from the event, which is not the case, she said. Gumbai said instead of spending money cooking with Somaizu, the Minister should have helped more than 100 accommodation businesses benefit from free grading or even helped clear the rates charges. Gumbai said Kyubei and Gubain should focus on rebuilding the tourism industry which has been battered by COVID-19. He said he was also disappointed the Minister accepted the appointment by President Cyril Ramaphosa to act as Health Minister after Dr. Zuleen Geys was placed on special leave last week. Tourism cannot afford both a part-time minister as well as one with four judgment regarding spending priorities. The Minister was serious about the tourism sector and its recovery. She would have declined the President's request to step in as Acting Health Minister and focused on actually getting the tourism industry going again. Gumbai said.


Morning Traders, Patrick Munley here with another Tick Mail Charter. I'm going to draw your attention today to a developing opportunity in the Kiwi Yen on the daily time frame. Price is trading above the prior 2020 highs at the 7350 level. We have a potential breakout play here through the 74 handle. We should see prices extend to test the weekly R3 at the 75 level. Through there we looked for predicted monthly range resistance 77 58 and above there we trade for the topside projected trend channel towards the 79 level. I'll be using a protective stock just below the five-period B WAP coming in at 73.30. As always Traders, plan the trade, trade the plan and most importantly manage your risk. Until next time, thanks very much.


Abstract mesenchymal stem cells, MSCs, have been used in regenerative medicine for their ability to differentiate, immunomodulate, and be cultured and manipulated. Recent studies suggest that the therapeutic effects of MSCs are mediated by paracrine factors, specifically exosomes. Exosomes transfer functional cargos like Myrna and Myna molecules, peptids, proteins, cytokines, and lipids to recipient cells. They participate in intercellular communication events and contribute to tissue healing. MSC-derived exosomes can be manipulated and applied as a cell-free therapeutic approach for treating various diseases. Exosome isolation methods have been developed for clinical use, and current research is focused on translational medicine. This article was authored by Sepeda Nikfajem, Jaffa Rizay, named Majidhi Zolbanin and others.


Now, we will talk about the importance of cell division. Why cell division occur? There are three major objectives, development and growth, regeneration and asexual reproduction. Cells need to divide. There are few parts of our bodies or animals bodies which do not grow. They do not require a cell division as we previously talked about the neurons and nerve cells. They do not divide. They remain in G0 phase throughout their lives, so they do not divide, they do not make division. But many other cells of the body, they require a continuous growth, for example our skin cells, they need continuous growth, our skin cells are continuously falling down and new cells are forming, cells in our stomach, they are also very important cells and they are exposed to different pHs due to entrance of the food, its digestion and other processes. So the cells of stomach need to be replaced again and again in all of these tissues like the stomach or in our mouth or cheek cells on our skin and many other cell types they need to grow and for growth they need to divide and this is very important that they divide in same type of cells with same number of chromosomes. So mitosis is a very, very important process which is required for the tissue and the organ growth. For the tissue growth, for the growth of the organism as a whole, there is another requirement if sometimes organisms body is wounded, it is injured. For example we hit our hand on some hard surface and our finger is injured and animal has injured, when it is injured its skin cells are cut off, its muscles they are broken down or something and they have to be replaced. For wound healing we also need cell division, just like that many times the plants they are also wounded, eaten up by for example an animal cut down by a bio kit or otherwise they also need to replace their parts. So mitosis is very important in the growth of the tissues and in the wound healing. There is another very important process in which mitosis helps, few organisms can replace or remake their lost parts. For example starfish which have usually 5 arms, if its one arm is broken or cut off or we can say amputated by a predator it can remake its whole arm by the process of we call regeneration. It can regenerate its whole arm, it is able to regenerate the arm with the help of the cell division or the mitosis because we know that mitosis is the cell division in the somatic cells the cells other than the germline cells. In some other organisms the regeneration also takes place for example the lizards they also can replace their lost tail. Many times what happened that a lizard is escaping from its predator it is successful to escape but the predator somehow breaks down its tail. Lizards also replace their tail with the help of mitosis the cell division. So it means that organisms can divide their cells to produce new cells for the tissue growth, for the wound healing and for the regeneration of their lost parts. Lizards also use mitosis, few organisms also use mitosis for the asexual reproduction. There are few unicellular organisms which asexually reproduce by the help of this simple cell division the mitosis. So mitosis or cell division is a very important process. Now we see that what happen if there are errors in mitosis. There may be different types of errors in the mitosis cell division like particularly mostly what could happen that when the chromosomes divide at the centromere during the NFA's. When the chromosomes of course we know that each chromosome at that time consist of sister chromatids and for going towards the poles it have to be broken apart or it have to be cut off from the centromere into two sister chromatids and each sister chromatid have to go towards one pole. If sometimes or somehow by a mistake they are not cut off they are not broken at centromere and the whole duplicated chromosome goes towards one side then in one cell there will be more chromosome in one daughter cell there will be more chromosome and in the other daughter cell there will be less. Most probably these cells will not be able to survive. Now this process of cell division is highly regulated as we have seen in the process of mitosis and in the process of cell cycle particularly that there are different check points controlling mechanisms which always check that whether the cell is cell has completely or correctly completed the process as required for example during the G1 checkpoint which checks that whether all the materials required for DNA synthesis are complete or before the M phase or the division phase in the G2 phase are all the materials which are required for the mitosis the karyokinesis are they complete but sometimes what happen and in the M checkpoint the mitosis checkpoint itself which checks that whether the nuclear division is correctly completed but sometimes what happen that this regulation fails and if somehow at some place this regulation is not correct then the result will may be uncontrolled growth of cells the worst sequence is the uncontrolled growth of cells. If the cell cannot stop dividing after M phase it do not enter into a proper G0 phase and rest for sometime and then go to the interface in as normal but it grows randomly. It happens due to mutations there are certain types of mutations due to which mitosis the process of mitosis continues uncontrolled and the check points they are not properly checking their places where they have to check that whether everything is correct the result is this is the uncontrolled growth of cells not in the form of normal layers of cell but in the form of heaps the result of this is tumors we call these heaps of cells tumors if these tumors are just present but but they are they are not like growing further or they are damaging start damaging other tissues and second thing they do not break off from their places. These tumors are called benign tumors but sometimes what happens that these tumors they become we call malignant they become cancerous they start growing very fast their size increases a lot and the cells from these tumors they break off and go to the blood circulation and through blood circulation they reaches other tissues and make tumors there as well so when these these cells which are broken off from the original tumor they go to different tissues and they can make secondary tumors at these places we call them we call this state or situation metastasis which is the spread of the cancerous cells or the cancer which is the very dangerous stage at which our treatment of this cancer become very very difficult so uncontrolled growth of cell may result in very serious consequences.


Welcome back, and as promised in the studio with me tonight, I think I'll see you in the next video. I've got Tina Garry and Louise Flanagan, and we're going to be looking at the latest installment in the Thursday Murder Club, The Last Devil to Die by Richard Osman. Tina and Louise, you're very welcome. Thank you for having me. So, Tina, this is not your first time, and I know you love the Thursday Murder Club, and Louise, you're very welcome to the Book Club Reviews, and I'm sure it'll not be your last time. You'll be asked anyway, I know it's once you're in, it's very hard. Like the Thursday Murder Club, I would say. So, Tina, just maybe a recap of, I'm sure 99% of people out there know about the Thursday Murder Club, but just to recap very briefly who they are and what they're about. Well, this is the fourth book in the series, written by Richard Osman that people might know from TV's House of Games or formerly of Pointless as well. It's set in Cooper's Chase, a retirement village in Kent, and it's far from sleepy. It's full of very interesting characters. And the Thursday Murder Club is people that look into murder cases instead of doing jigsaws in Cooper's Chase puzzle room, and the four key members are Elizabeth, Joyce, Abraham, and Ron. His name almost just... And they're very fully formed, warm characters, and they represent a little slice, maybe a little different slice of British society. You know, Ron is a tattooed West Ham supporting Union man. He's a bit rough and ratty. He's a bit of a white boy. Abraham is an Egyptian psychotherapist, so he brings a lot of medical background and experience. He's very wise and very reasonable. Elizabeth is kind of the head honcho of the group. She's a former MA5 agent, and she's very cool and very aloof, and she's a really interesting character. And then, by far my favourite is Joyce, who is a widowed nurse, and she acts as a bit of a comic foil to the others because she has a lovely innocence, and she can be wee bit gullible and funny. You know, she can introduce some comedy into it as well. So between the four of them over the past four weeks have gotten into all kinds of capers. I think people who are fans of very gritty or serious crime novels would be a bit disappointed even. These are capers. They have great plots and mysterious subplots and complex and convincing backstories, but they are a bit of a caper at the same time. They're a really enjoyable read.  Absolutely. When Tina approached me anyway about the book, I said, Oh God, well, I'm not really sure I could come on and speak about it because I haven't actually read any of the others. And I know, of course, that there are three other books in the series, but Tina assured me that, you know, they're individual stories and that, you know, it's a standalone investigation, so to speak.  And I must say I really, really did. And something, you know, really to its credit, I'm actually a very reluctant reader and it takes a lot for me to sit down and read a book. And then any time I do when I enjoy a book, I'm like, gosh, I really should do this more often, but it does take a lot of busy life and all the rest. And I thoroughly enjoyed it and I would definitely, I want to go back and I want to read the other books now and learn more about the characters. Like, as you mentioned, like the characters, they're so complete. They're so real. Like they seem to me like they're actually real people. And that they're not just these fictional characters. And I want to learn more about them and know more about them, you know, which is an indication that it's a very good story and a very good series. And I think the way that Richard Osman writes the book, it's written and it's very easy to connect with the characters. You say, you think you know them as real people. And did you find a disadvantage that you hadn't read the other books or were you able to assure you to get into it? Well, I thoroughly enjoyed it. So you certainly can, you know, read them independently. But I found at the start, there were quite a lot of characters introduced. They have a dinner party near the start. And I found it kind of difficult to figure out, you know, who is who. There was reference, for instance, to Alan. And I was like, who is Alan? Oh, Alan's the dog, you know. And I'm sure, of course, people who are familiar with the series, you know, would obviously know that. So it probably would make sense to be honest, you know, to read them in order. But certainly I enjoyed it. And I found very quickly that I was able to kind of establish, as you mentioned, you know, the warmth of Joyce and the authority of Elizabeth, etc. And that did become apparent to me very, very quickly. So, yeah, I really enjoyed it. I was interested in finding out what Louise's take was going to be. You know, having read the first three and having invested heavily in the first three. And there are recurring characters. I was really interested to see, you know, could you jump in into the fourth one and not be lost. So I'm kind of relieved that you are. Yeah, no, I definitely could.  But again, that has kind of whetted my thirst, my interest, you know, in terms of going back and reading them. And I'm like, I want to find out about those Diamonds and the Kettle, you know. So, yeah, I really, really enjoyed it nevertheless.  And one of the things that I noticed again, I haven't read the other stories, but just her relationship with her daughter, Joanne, like I would love to know more about how Joanne has interacted with her mother in the past because we have such love and affection for Joyce as a character, but her own daughter doesn't seem to have that same love and affection for her. And that was something that I just, I picked up on and I was like, I wonder what other interactions they've had, you know, in the other books because I just felt so sad and disappointed for Joyce that she was sending text messages that weren't being returned. And it was a bit of a heads up too, as well, I suppose, for us all to appreciate our own parents. And, you know, sometimes other people can see the good and the worse, but we can't see the wood for the trees ourselves with people in our lives that we perhaps take for granted. So I found that interesting and I'd like to know more about that. Osman's clever on that. He structures it in a way that a lot of the chapters are from different points of view, different narrative perspectives. But Joyce's are her own personal diary entries that she uses as therapy after losing her husband. And they are particularly warm and because it's a diary entry and it's private and it's her own thoughts. Do you really get into her as a character in a way that you maybe don't with the others and she just is so warm and those little simple things like those text messages, they're very real, they're very easy to relate to. Osman had said that he wanted it, like his mother is in a retirement village and the characters in the novel are not loosely based on her friends but maybe inspired by her life and her friends. But he... I can't remember what I was going to say now. It's gone, it's gone. And no, whenever he writes from her perspective, it is very real but he had said that he had felt that that generation were an invisible generation and we had spoken about the representation of old people whenever we reviewed. I think it was the second one we had done together, Jane. But he had said because they are an invisible generation it made them ideal for a detective story and the ones looking at Elizabeth thinking, does she have a gun on her handbag? Because she's an octogenarian and she does have a gun around. So he's doing something really interesting with characters that I don't think anyone else has really tapped into. And of course it wouldn't be the Thursday murder club without a murder and the last devil to die there's a few murders for them to investigate but it starts off with a friend of theirs being murdered, Tina. Yes, an antique dealer that we are introduced to in the third book who is a friend of Elizabeth's husband has a very small bit part at the start. He's not on it for very long. The opening chapter of the novel explains how he has been told to take a donation of an antique box into his antique store and that someone else will come and buy it tomorrow so there's something criminal going on and that first chapter it's him deciding what to do with it and then the last line of the chapter is he notices the flash of a shotgun or a flash of a bullet or whatever it is and then he dies. So we're sucked right into the narrative very, very quickly and there's quite a high body count on this one as well. The reference of the last devil to die then is there are so many villains in it. Basically the last one left is the one that's hitting the trigger or the one that's the mastermind of a lot of the crimes here going on. So it's very, very cleverly structured. That non-linear narrative as well where you're kind of going backwards and forwards in time. But yeah, Per Kaldes, he's not in the novel for very long. And also there are so many subplots, Louise, going on as well. There's the plot about romance frauds, that's what it's called, with Merevin and Tatiana and then there's the other one too about a very sensitive subject about assisted suicide or assisted death, I shouldn't say so. And he brings them all together in a nice way. As you say Tina, he's humorous and you're laughing and then when he deals with Stephen's dementia it's very, very sensitive and very caring. Yeah, definitely. I found with this book that as I was reading it sometimes when I literally laughed out loud, or just kind of make you just do a little kind of, when you're reading it, you know, that it's just the wee turns of phrase are just so funny that they wouldn't literally make you make a sound like that. And then I also was literally reduced to tears as well. And I haven't read very many books that have made me both laugh out loud and literally have tears rolled down my cheeks. And in this case, both of those things happened. And in reference to the subplot with the Tatiana, Mervyn and Tatiana, I thought that was dealt with really well. And I suppose, you know, it was a bit of an insight into, you know, how vulnerable people can be and how naive people can be. And I thought it was lovely the way the members of the Thursday Murder Club kind of took Mervyn under their wing and just realized that this was an injustice and it was something that they couldn't turn a blind eye to. Even though they're not particularly fond of Mervyn yet, NOA is a person. They kind of don't really explain too much why, but he just seems a bit kind of drool or a bit distant and they haven't quite made their mind up about him. But nevertheless, they just think, you know, we need to help him out here. We can't let this happen. And he is very, very naive and he is convinced that Tatiana is a real person and that they're just fools and that they'll be sorry when she comes over on the plane and, you know, after he has sent her a few thousand euros or pounds to get her to come. So I thought that was a very, very good subplot and it's probably something that, like, a lot of readers of the book, it might kind of help to create a sense of awareness about, you know, situations like that. And then the other one that you mentioned as well, like the subplot about Stephen, because I haven't read the other books, I feel I haven't seen Stephen at his best. And again, I can't wait to go back and read the other books and learn more about him and learn more about the man. So I thought it was just dealt with in such a realistic and respectful way. Yeah, I just literally cried. I thought it was beautiful. There was an episode at the beginning of the book where Stephen reads out a letter. Excuse me to Elizabeth. And by just dementia. And she realizes that he wrote it himself. I thought that was very touching, Tina. Yeah, certainly the whole issue of Stephen's dementia has been dealt with in the other books and we can see that gradual degeneration as the books progress as well. But it's really dealt with, with, with dignity and humanity. And, you know, there is a plot where it is there's a euthanasia element and he's, Osmond's not trite about it. He's not preachy, you know. And he's very respectful of the fact that, you know, that has been their choice. And it's lovely that Elizabeth's friends don't judge either because, you know, the book really explores, you know, the reality of aging and loneliness and loss and of life and death. And Osmond kind of puts the situation out there, but there's no judgment. And it's basically, you know, what would any of us do in that situation? So it's really dealt with with all that pathos and humanity has really dealt with, with dignity. And it is a lovely subplot. I mean, because of it, Elizabeth, Elizabeth as a character kind of takes a backseat because she's not as present or as available because, you know, she has more pressing issues to deal with at home than these murders. But it's certainly very interesting subplot. But then again, he'll, you know, interchange it then with humorous episodes even at Kuldash's funeral.   So the vicar is trying to put some kind of sermon together for Kuldash who he has never met and, you know, surmises, oh well, he lived in Brighton so he must have lived the sea, must have loved the sea. And he lived in the bungalow so he mustn't have been a man who liked stairs.  So even the darkest of subject matters are treated in a way that really tickle you with this book, you know, and I have to say I totally agree with Louise. There are laugh out loud moments, you know, it's not, you're not holding your sides in, stitches laughing, but there are really touching pieces of humor, definitely in it, you know. There's one part to remember whenever Dom Holt came, Abram and Ron and George were spying, and he comes with the golf club and slashes their tires.  It's so funny. What I liked about it as well, I suppose it was just because my eyesight is deteriorating and the prints big and the chapters are small or short, so you can read, you know, maybe four or five pages and you'll say, I'll do another one. Like, you know, it's very well structured that way. It's difficult to put down, Jane. Yeah, it is, definitely. And is there one, any part in particular, that you really, really liked or that stands out for you? I think the whole issue with Stephen's death, I thought that was really touching. I shed a tear or two at that as well, and it kind of came as a bit of a surprise because I didn't think that was the direction they were going in. Before the book was released in the middle of September, they had said, you know, there was a big body count in this book, and they had said, you know, that there might be someone we know and love who's part of the body count, too. I was dreading it that it would be one of the four. I know that's terrible, or dreading that it would be Joyce, which is by far my favourite. And then, as it became more apparent that it was going to be Stephen, and it builds quite gradually up to that. And it doesn't take over the main plot at all, but it's this little, you know, sad undercurrent that they revisit, and then, you know, it comes to a head then, and again, it dealt with really sensitively. Like, right before, he does pass, like he says, tell me the story of when we first met because he keeps forgetting it and she keeps reminding it. And I just think it's just done in such a lovely, respectful way. And then, you know, as you said, the fact that Richard Osmond doesn't make any judgement in terms of whether they have done what we should all do or what we should all think, it's just what was right for them, it was their decision. And then the fact that some of the other characters in the book don't necessarily agree with the decision, they completely support Elizabeth, you know, following his death. But they think, God, I wouldn't have opted for that. That's not what I would do, you know. To kind of, I suppose, allow the reader to kind of experience that as well. Like, we don't need to agree with everything that happens necessarily, but we just need to understand that people are entitled to make their own decisions and everyone's experience is different and everyone comes at situations, you know, from a different angle. So I just thought it was just dealt with in a really, really respectful way. It doesn't matter what your own personal belief is in relation to it. You can still empathise with the characters and you can still kind of see where they're coming from from their perspective, even if it's not something that you agree with yourself. And I heard Richard, I've been interviewed and he said he's taken a break from the Thirsty Murder Club, but there will be another installment and that Steven Spielberg has bought the rights to make a film. What's your views on that, Tina? I won't lie, Jean, this is something I'm struggling with. I would love to see it serialised rather than made into a movie and I'd love to see it in the hands of a British director. I would worry that some of the cultural norms or even we nuances might be lost and I don't know if it would translate well to an American audience or I don't know... It's so British. It is, it's very, very British and I would hate to kind of lose that. So look, I mean, hopefully Spielberg will make a lovely job of it maybe A-TV or BBC, maybe someone like Leslie Mann involved or, you know, when I had first heard that there was a chance of it maybe going to TV I was trying to cast it in my head and, you know, who I would like in a role. So it'll be interesting to see. I would love a series out of it. I think it really has the legs for a series, but... I just think Maggie Smith would... I can see her as part of the Murder Club as one actor anyway, actress. She would be wonderful and she really would. So out of ten, what would you give the book, Tina? Oh, I'm going for a nine. I would nearly give it a ten. I'm a massive fan. I think they're just really pleasant rates. They're not taxing. They're not challenging. They are just a caper. I think it feels like the secret seven for adults. You know, they're not overly serious. I just think it's a really nice rate. I have to say I really enjoyed it. There has been a little bit of criticism that maybe it's a bit unrealistic that even though these four people take on such dangerous feats, they're never really in proper danger themselves. But I don't want to read that. I prefer the caper element of it. I think that that's kind of explained or justified by how so many people undermine them because of their age. Absolutely. And don't kind of view them as a threat because they're just old people in inverted commas. So I actually wouldn't agree with that criticism. So when I was trying to think of what I would give it out of 10, I had kind of thought nine as well and then I thought, what would I take the point away for? And I literally couldn't think of any reason why it deserves to be Dr. Mark. I just enjoyed it so much. So I actually would give it 10 out of 10. I just think it's beautiful. It's so accessible, but it's also beautifully written. It's not pretentious, but it's just breath-taking and I really enjoyed it. Thank you so much for taking time out tonight and as I said, we'll have you back again in a few months to do another one. Thank you.


Well finally the sport itself is not well known. The Brainerd Adaptive Floor Hockey team is off to a solid start this season. They're undefeated and the defending state champs hungry for a repeat. Clayton Castle has more. Just a year removed from winning a state title, the Brainerd Warriors Adaptive Floor Hockey team is rolling in 2017-18 with an undefeated record. While you will find packed stands at the team's games, not many people know what Adaptive Floor Hockey is. It's a state high school league sport that's created for student athletes that have some type of physical impairment whether that be a heart condition or spinal issue or you know just a variety of other things to give them a place to compete. The current team boasts so many strengths that it's easy to rattle off just some of them. I think the communication and the different skill levels and the grade levels are all strengths on this team. In Adaptive Floor Hockey student athletes can begin playing as early as seventh grade so the chemistry among this group of seniors is undeniable. We have three seniors on the team that have been on the team for at least five years and we just work really well together. For the players playing on the team goes beyond the wins and losses. It's about the opportunity they might not otherwise have and for that it means a lot. It creates an atmosphere that would otherwise kids that are adapted wouldn't be able to be a part of. It creates a sport that everyone can get along with. The Warriors face a tough Robbinsdale Hopkins Mound West team next Monday at home. Reporting in Brainerd Clayton Castle, Lakeland News. If you enjoyed this segment of Lakeland News please consider making a tax-deductible contribution to Lakeland PBS.


June is National Dairy Month and everything dairy was celebrated today at the Culver's location in Baxter. Clayton Castle has a story. It's June Dairy Month, which means it's time to move on over to the annual June Dairy Days event put on every year by the Crowing County Dairy Association at the Culver's location in Baxter. We've been doing this for seven years now. We've had Jersey Collier one year and we've had Holstein College here. The crowd keeps getting bigger. We get dignitaries to come. Like Senator Kerry Rood was here today and Josh Heinz has been here before, but he had another commitment so his wife was here. Senator Rood has participated in the event all seven years and keeps coming back for more as the event is more than just a competition. It's an educational experience for children. But it's really fun and the focus is on, you know, all these young people come and they learn about dairies and they pet the cows and they learn about what they look like and they're not afraid of them. My granddaughter actually got the milk, the cow. So it's really all about letting the kids know about farming and how important it is to us and where the milk comes from. So it's really fun. The event is also put on for the general public to see a cow firsthand and learn more about why we need dairy. We're celebrating June Dairy Month, a chance to get the dairy farmers to bring a cow into town so the public can meet the cow and celebrate why we should consume dairy products for strong bones and teeth. Senator Rood wasn't the only one participating in the event. Local celebrities, dignitaries and yes, even. We get Lakeland News to come out and do a little try to milk the cow and have a custard eating contest. The key word there was try. Coming from Cincinnati, I had never milked a cow before, which showed on the scoreboard as I finished in last in the cow milking competition. Other events include a straw bale toss and a frozen custard eating contest, none of which were won by yours truly. Now the event is sponsored by Culver's, which gives a thousand dollars every year to the future farmers of America. Reporting in Baxter, Clayton Castle, Lakeland News. Good to see Clayton getting involved there. As they say, Clayton practice makes perfect as far as the cow milking goes. If you've enjoyed this segment of Lakeland News, please consider making a tax deductible contribution to Lakeland Public Television.


Spring Cleaning is here and Appalachian Wireless has the deal to get you started. Get a Samsung Galaxy S8 for a penny or a Galaxy S8 Plus for only $89.99 on the region's best network. Better service, bigger savings, that's today's Appalachian Wireless. So your agreement requires you to store for details. After three decades of serving as community, Pockville Fire Chief Ronald Kahn is calling it a career. I wish it could go a little longer, but it's this time. The city of Pockville and Pockville's first responders commemorated Fire Chief Ronald Kahn's last day on the job Thursday. Kahn served on the Pockville Fire Department for 30 years, serving as chief for the last 11. He said the decision to retire was difficult, but necessary. A bittersweet right now. It's been a journey, but it's been a journey that I have no regrets on taking. I've had the privilege to work with so many great men in this city of women. The city has been so kind to me. I have no regrets whatsoever. At a dinner Thursday in his honor, those close to Kahn shared memories and thoughts about the chief's career. Having Ronald here with all his experience is tremendous. You don't have to worry about a lot of things. You know that it's being taken care of and the training is happening and you can sleep better than Appalachian. A lot of people look at this as being a sad day, but I know what chiefs go through and I know he's been through it for a long time. And I know how he loves these men and how he loves everybody he works with. It's a happy day for me just because I know my brother's going to be a lot less stress-free than what he's been for a long time. He's always been at the other line for me when I've called or needed something. He'll never know where he's at in my heart because he has a place in my heart. I appreciate him and it's one of the things I love about him today. Kahn said his main focus throughout his career has always been the good of the department and its personnel. It's always been about this department. Even when I took chief everybody was talking to me about what are you going to do. I said I'm going to do what these men deserve. It's all about the men. It's not about me as a chief. It's about these guys that work under me. I've had the privilege of working with a lot of good men. The camaraderie is what I'm going to miss the most. The job, the people I'm going to miss. Kahn said he doesn't have any solid plans after he rolls into retirement, but... His wife has a big honey-do list and then we'll see after we get that done. Honoring a fire chief service in downtown Pikeville, I'm Chris Anderson for EKB News.


The fifth secret I will leave this day as it is my love. Yesterday is gone. Love season is gone. January is gone. February 17th is gone. February 18th is also almost gone. Yesterday is gone. And tomorrow, no one knows what's going to happen. Every day when I get up from bed, I'll say that today is in my hand. Thank you God. Thank you for another day. And I'll leave my best. Every single day. Every single day I'll leave my best. Because tomorrow for coffee you tell sir, tomorrow at 5 o'clock, I'm going to be 100% this. Can anybody say? No, we don't know. We may say but we don't really know. So best. I'll leave my best every day for 7 days. I'll leave my week very well. If I leave like this 4 weeks, I'll leave my month very well. If I leave 12 months like that, I'll leave my year very well. And if I leave many of those years very well, I'll leave my life very well. But it begins from living that day, that every single day, the best of my potential. Sir, not this season, sir. Next season. I wish you next season, sir. Next season, I don't know. This season is important. Now, today is important. Every single day, when I come back from a market place, what have I done? Did I do my best? Did I do good prospecting? Did I take the point in the best way? When I went to customer, did I open the call in the best way? Did I close it properly? Did I do my presentation with farbing correctly? Did I do the best for? Have a salesman. What are the things I have to do? Did I do those things in the best possible way? Sir, do what I will do. No. Why tomorrow? Today. Today.