All right, welcome to Off Topic Tuesday. It's time to go off topic, ladies and gentlemen. Way off topic today. We're going to start with Pornhub. Why not? We're at Wacky, we're going to start with machine learning, AI systems and they took our jobs. Sure did. There's someone saying that right now. So Pornhub is using machine learning to automatically tag it's 15 million or five million, five million videos. That's an amazing number. I bet it's more now because this is actually, this is not this article from today, it's from a little bit ago. That means there's more than five million videos. Now they're using artificial intelligence to dab hand at recognizing what's going on in photos and videos. But data sets that's usually trained on are pretty genteel. Not so for Pornhub, which announced today it was using machine learning to automatically catalog on videos. The site starting small deploying facial recognition software that will detect 10,000 individual porn stars tech and footage. Usually some friends provided by uploaded by viewers who will still play a part in verifying the software choices. It plans to scan all five million videos within the next year and then move on to more complicated territory using the software identify specific categories. We belong to like public and blonde and more categories that we probably can't say. Definitely can't say. So it's going to know what we're doing. Now here's the thoughts. So we have lots of these listening and watching devices and things like that. So once it figures out what the humans are doing, then we correlate all that data that Google and other places have of all those private photos are up to the cloud. And then we can make other assessments on the humans, like where certain positions are popular based on zip code. I mean think about the, think about the implementations, when the AI systems figure out our breeding habits. Wow. They're big fans of missionary in southeast Michigan. I don't know. I'm guessing. I don't know. We've always, this is actually a problem. We've always relied on people to tell us and expect them to be honest about what this is. Yeah. And if we know it was one thing that people lie about, it's probably this. So now if we actually just go ahead and hide all together, surrender all of our privacy not to the government, but to the AI system that watches porn. This is, this is great. I mean, it's the, it's the ultimate and they took our jobs, but there's someone going, Hey, you could have paid me to do, I would have been honest. They were paying somebody. I mean, it used to be somebody's job to sit and watch this and go, Oh, that is such and such. So and so, right?  So and so she's blonde. She's doing this. Yeah. So, I mean, you want to upgrade, it's going to be able to identify the act in there. I remember reading that in another report related to this. So they want to know exactly what, I mean it's just, is this going to turn AI systems into perverts? Well, here's the thing. Like, will the AI begin to develop a proclivity towards certain things? What, there's a what's, what's the AI Spanish? Exactly, right? So one of the interesting things is the way you train AI, normally in a computer program world, you design a program with a set of parameters. So you're always just trying to predict all the variables to get the parameters correct to get it right. AI is trained with data sets. This is actually why it's so hard to, or data sex. I know. I know. That's a great pun.  Your choice. Sex data, data sets. Data sets, oh, okay. But you know, it's really close. Data sets of sex. So when you train AI systems with data sets, this is why the actual behind the scenes learning is so hard for us to figure out because we say this is this and that is that. And we repeat those images over and over again until it understands what it is and we let it make all the inferences to understand, you know, to identify an object. This is how just AI works in general. Now the good thing is there is absolutely a lot of foreign. So we have lots of image sets. There's plenty of data sets. So will this make though a better hot dog, not hot dog app? Oh, it's going to see a lot of hot dog. That's for sure. Will it be able to identify it? Yeah, yeah, a lot of hot dog. Definitely a lot of buns. Yeah. Definitely be there. And in one comment we'll have before we jump off this topic, before we just make childless jokes, which is like we haven't already. Yeah, we could do another 30 minutes of this alone. Yeah, we could for this get stale. Pornhub also released in its, and you guys tweeted it out. I don't have it pulled up, but you can find it, a chart to show that with the Hawaiian missile crisis relating back to last week. Yeah. Yeah, I've got to bring up the Hawaiian missile crisis. The sudden drop in viewership in Hawaii. But about midway through, people started getting back to normal. And it, well, I believe it spiked up and over, didn't it? Oh yeah, after they, yeah. Well, once they said, once they declared it was over, then it actually went up above and beyond. Yeah. People celebrated.  Thank God it didn't happen. But if it had happened, there was really a missing. All people coming to the disaster area and be like, oh, he was looking at porn when this happened.  So it looks like they were doing something intellectual. Yeah. But as soon as it was clear, they were like, well, back at it. Here we go. We may be revisiting the Hawaiian missile crisis in roughly nine months as well. For another, no kidding.  That's going to happen. Hawaii's going to see a huge spike in population and baby birth. And speaking of baby birth. Contraceptive app Natural Cycles is on investigation for unwanted pregnancies. Natural Cycles is a popular contraceptive app, which tells women which days they can have unprotected sex by tracking their temperature. The app is under fire in Sweden after House reported 37 women who had been using the app to avoid pregnancy to became pregnant according to local news agency SVT. The hospital reported its findings in Sweden medical devices regulator, which has reportedly launched a probe. Oh, that was a terrible choice of words. It's a temperature probe. I'm sure. I'm sure. Yeah. I'm sure that's what it is. If you're using an app to not get pregnant. There are, I did not know this app existed until they got sued. Okay. I'm not thinking that it's the, I mean, they, it based on the rhythm method. So there's some theoretical science behind, there's science behind it. I don't know how much of it's actually in the app, but, or how well these people followed the app. Right. But I'm going to probably say there's other, like use the app along with some other methods like that. Well, so apps like this, I think they were, they were designed for like people doing like fertility treatment and stuff so that like, it would tell you when was a good time. Yes. To have to do a thing to do, to do what you got to do. So they're just, they're just kind of reversing it and saying like, Oh, this is a time not to do it. But like anybody who had gone through any kind of fertility treatment knows that like it doesn't, like it's not always accurate. The thing the app may say now's a good time and then you do the thing and then it still doesn't happen. But this is where their, their own description. Natural Cycles describes its app as effective method of contraception. I don't know about that.  But this, this seems a bit excessive. Now, could you, could they take this app and combine it with the learning that the Pornhub AI is doing and say, so that your phone could be like, hold on a second. It looks like you're about to do this thing. And that has a statistically likelihood of getting pregnant. We could combine all this. Yeah, that's right. Like, uh-oh, you're about to do a thing. I don't know if you're aware, but now would be the use of protection time. There's a theme of this show where the AI systems now can control our breeding. They know how we do it and they know when we do it. And they tell us when to do it. That's what, yeah. No, you're right. This is, this is how the human race dies. Yeah. The app said it wasn't breeding time. Well, this app's failing. So this is another science experiment because these people got pregnant with an app that was supposed to copy from getting pregnant. Thank you, internet. Thank you, internet. So, um, all right. So let's talk about getting in shape. Well, because you want to get in shape so that you have a reason to use the app. So lifetime fitness, which has 120 locations, set a statement on its Twitter account, the decision to remove the national cable news network stations resulted in significant member feedback over time and our commitment to provide family oriented environments free of consistently negative or politically charged content. So in short, they turned the news off. That's great. It's always a good idea. It's got positive feedback from people and I am, they didn't say, but I wish you would just put the food network on because that's... Right, yeah. That's it. That's genius marketing right there. It's like putting a bulk foods next to a weight watchers. Part of the reason I like that article so much and as laughing is because me and Marvin, we have a gym as a client and one of our service calls there was someone got aggravated with that and they locked out. Someone took the remote, so we're brought a remote in. We don't know. Those remotes are locked up. You know, TVs, redores remote. They went around and locked out all the news channels and the guy who runs a place isn't tech savvy enough to figure out how to reset the TVs and we had to look it up ourselves.  They locked it out and locked it, they locked it down to a camera-watch channel but it was not news, which made me laugh. Well, that's the question. I think it was locked on sports. So a lot of people do their work out in the morning, right? Well, what else is on besides news in the morning? It's like Sesame Street. Sorry, is it just going to be a bunch of kids programming at the gym? Maybe. Like what else is on? It's infomercials. They could sell you a George Foreman grill or something like that maybe. I don't know what else you're going to watch that early in the morning. You know, I just put, I thought I'd go to the gym very often. When I go, I put headphones in and listen to my own thing. Whatever's on there, generally some BS stuff. But yeah, I don't know. It's kind of funny. I think it's a great idea. See, I cut the cord in like 2011, but this is something you go and see. Just this constant feed of news cycle.  And like we had talked about this before, they're all bad because they're just trying to find something to keep you glued to the TV for some unimaginable amount of time. It's stopped being important to be correct and it's more important to be first. Yes. So they report it and I can always recant, change it later. So yeah, I'm happy to see it on there. And not really on our list, but we'll talk a little bit about this because even Zuckerberg realized this is a problem. Yes. And so the whole Facebook thing has changed. This is off topic on topic here because a lot of people have tuned out Facebook with good reason. And I find myself, I have some more time in certain forums. Facebook is going to start supporting interaction between people as opposed to they're going to cutting back on the videos. They're cutting back on, which is a shame because we love our videos, but they want to go with engagement and they want more than one word answers. They want people to have discussion so they're looking for sentences, complete ones, which is going to rule out a whole lot of people. Yeah, I mean if you can't put together a full sentence. Yeah. Actually they want paragraphs, like the longer they're going to give. They want long form responses. And this is interesting because it reminds me of this and I think they're realizing when you start gaming the people, they will just kind of zone out and do it, but they're also seeing that the, probably the more intelligent people check out of it. Because I admit when you go, there's nothing of value in here. It's a bunch of people going, I agree with this random post that I didn't read and I'm saying, yeah, I am outraged by it too. And I have to admit, I love the Gotcha Posts where like they take like a picture of like Obi-Wan Kenobi and say that like this is somebody and he did this, this and this and then people just start sharing it, ever going, I am outraged that this happened to this man. And it's like it's, It's completely made up and fake. It's completely made up and fake. The Huffington Post actually ended their contributor program. Yup. So like people used to like, you know, write new stories and blog and whatever doving it post. They stop that now. So I think this is a good trend. We see the people at the gym, which are probably, the category of people that go to the gym are generally going to be more motivated people. So I'm going to not say that it's bad at all. Like this is good. And maybe we see more of this on there. Like if some people just turned it off, I think things like social media, they offer a great way to people engage and that's how I've always looked at the internet and even in the early BBS days in the 90s when I started doing all this, I love the deeper engagement, but that's why I've kind of moved over to some of the tech groups and things like that. By the way, we have a group of our own. Yes, we do. Yes, we do. I moved there because I can have a long-form discussion. Someone had a question about some of the technology products. That's better. So I actually see this as a great move for Facebook and hopefully less crap.    Yeah, really. What you need to do is you need to make us a C-first option, which we can cover. Click the bell, like, subscribe. And we are bringing to the show because the same reason I haven't posted a video in two days before I did this one, there's actually been work to do. I know. Man. So until I can make more money off this so I can spend more time making videos, I have to go do work things. I have to go do work things. So we will see you. Vlog Thursday for sure. I may have a video coming out tomorrow. It depends on how fast I get these next two jobs done that I'm working on finishing. So, woohoo. Yay, jobs. Yay, jobs. Like, subscribe. We did. I am including a link to our Patreon. We're working on what to do for our amazing, I think we're two people. Thank you very much for donating to us on Patreon. But we're... You're the best. You're true MVPs. Yeah. And I think we might offer like where the Patreon people can provide it.  We can contribute some articles for us to just read. Yeah. We're trying to figure out what to do and encourage it because I'm not... I'm not sure. Like, I'm very new to all this because myself, I have donated to a lot of projects but I've never even asked for anything in return. Right. Because mostly it's the open source community. So help me learn what is good. I've been looking with other people when doing someone release videos early, which is cool. Maybe we'll do some of that. Yeah, a lot of that. There's a lot of that. Yeah, which is cool. Priority access to stuff. Does someone want to see us sooner? The biggest problem is the way the production schedule works. I'm going to take this card out and put it in the machine and upload it. So in a half hour after shooting, it's generally online. Yeah. So... Usually. Something in. We've done it real fast. Anyways, thanks again for watching. Thank you for all of you that are here watching us do stuff. We really do appreciate it. Yeah. We really do appreciate it because it feels good. We talked to Dead Air for a long time. We get like, Marvin, we got like 10 views. Holy cow, that's great! So you keep watching. We'll keep putting them out. Yep. And here's a tip. We're going to put a link to the stories that we talked about. Use the link for the Pornhub story. Do not go searching it. At least not at work. Yeah. Or do it in an incognito window. Yes, that too. Yes. See ya. See you guys.


I'm Charlotte Brand. I trained at Kent Midway Training and I did a PGCE in straight physics and it was a school-centred initial teach training scheme where I got a PGCE out then. Hi, I'm Rachel. I trained at Barsapar University, so the University Week. Highlights of my year were teaching Year 7s about why a newton's called a newton and having them say things like, oh, I'm going to invent the ins one day and we're going to measure the James's. Hi, I'm Jake. I'm in NKT Plus 1. My route into teaching was a PGCE and last year I taught from Year 7 to Year 13 and that was mainly physics, but I did teach Chemistry and Biology to Year 7. The scholarship really helped me this year because it meant I could completely focus on my training and planning and being in the classroom and just growing and developing into the teacher that I am today. I've been a profiled scholar for the IOP, which means that I get to do things like this and talk to people about what it's like being a physics teacher and training to be a physics teacher. This is quite important for me because being in schools, I've seen that there isn't enough physics teachers out there and they really need some more physics teachers to kind of inspire that next generation and infuse that next generation. I received the IOP scholarship for my PGCE, but apart from that I've been to several events at the Institute of Physics. Events where I've just been a mentor, been assigned a physics mentor and we had group meetings where we were discussing different teaching techniques. I was shown different techniques given lots of great resources, which were appreciated. The mentors were really useful. Having someone to call on outside of your school and away from your university was really, really useful. Having someone that's been there before and knows what you're going through. My main advice for someone starting a training year is that it's a training year for a reason. You're not meant to be this polished article and sort of approach it like that. Take risks, look at the different challenges and really try and improve on your teaching repertoire. There will be lots of different techniques, lots of different things you'll learn. Really look at that as an opportunity to learn rather than an opportunity to tick things off a list. Go into it with an open mind and enjoy building up your toolkit, all the things you can use as a teacher. Make sure you make time for yourself. Have your teaching time being that amazing teacher and being in school. Come home and be yourself. Make sure you keep your interests going. I'd say use your mentors, use people who've been through your training route to find out what you should be doing at that moment in time. What's the most important thing for you to focus on? Probably going to be your lesson planning and making sure that they're really good but you're going to want to be collecting some evidence as well. But then know when you need to be doing what and what you should concentrate your time on so that you can have a bit of a break as well and make sure you get all of the sleep you need, etc. Hi, I'm Chris Shepherd, teacher support manager at Institute of Physics. I hope what you just heard inspires you in terms of your year to come. We've tried to put together a selection of the real experiences of previous scholars. What we really want for you is to enjoy this next year for the challenges but also tremendous opportunities. You are to be congratulated. You've got an IAP scholarship but please make the most of it. Take all the opportunities from the e-shots you'll be sent with the various suggestions, through to the local meetings and other opportunities to get together. So well done, fantastic. Please use everything that's on offer for you and all the very best from the team here at the IAP.


Welcome back in the last class we introduced semantic tableaux method and using semantic tableaux method we have seen how to show a given well form formula in the preposition logic is valid or can even show when two groups of statements are consistent to each other or you can even show when two well form formulas in preposition logic are said to be logically equivalent to each other and these are the things which we have seen. So in continuation to the last class where we were studying some of the puzzles in particular so we are trying to solve some of the puzzles using semantic tableaux method. So in this class we will focus our attention mainly on solving some of the puzzles which includes Nights and Naves puzzles which are cooked up by a famous logician Raymond Smoller. So in continuation to the last lecture we have left at this particular stage that here is the problem which we were trying to solve. So the Nights and Naves puzzles are like this. So imagine a situation where you went to a kind of an island where there are only two kinds of inhabitants. So they either they only speak truths they only tells lies for example if you ask them is 2 plus 2 is equal to 4 the Naves will tell that it is false. If you ask if it so happens that the inhabitants is a night then if you ask them is 2 plus 2 is equal to 4 the answer would be yes because they always tell truths. So these are the only two kinds of inhabitants and the rules of the game is like this that a Nave can never tell truths for example if I am a liar I cannot tell truths if I tell truths then I am no longer considered to be a liar and all it goes against the definition of what we mean by lying. So that is one thing a liars cannot tell truths so liars can only tell lies and the other thing is that Nights always speaks truth and Naves always tells lies.  So now you came across assume that there are two inhabitants A B C and the problem goes like this. So now you asked A then A said B is a name and you asked B then he said he is talking about A and C A B C are three kinds of people and so B saying about A and C like this B says A and C are of the same type that means either they are Naves either they might be nights. So now given this piece of information how do we know what type C is. So this problem can be solved by using truth table method you can solve it by using some other kind of reasoning that reasoning goes like this. So in all these nights and Naves problems usually the ordinary way of solving this problem is simply like this first you will assume these are the A B C is in all and then what you will do is you have to assume something or other in the beginning suppose if you assume A is night and all. So the representation remains the same and all if I write simply A that means A is night suppose if I write not A that means A is considered to be Nave. So there are no other kinds of inhabitants exist in this world either they only tell truth only tell lies in all it is not the case that somebody tells you neither true nor false and all the third value does not exist at this moment. So in all these problems that we are going to study in this class. So now one way of solving this problem is assuming a kind of reduction of add absurdum method which we will use assuming that A is a night and then you take all the piece of information that is there in the puzzle and then ultimately you will show that there is a contradiction and all you will arrive at some kind of contradiction. So by taking the information in the puzzle then what you will say is since assuming that A leads to contradiction this symbol stands for contradiction then what you will do is it is not the case that your assumption is correct that means it has to be not here rather than A. So in that sense you will show that A is a name by assuming something A is a night if you can come across the contradiction you will show that it is not so once you find out one particular kind of inhabitant what he is then you will substitute into the piece of information and then you will try to figure out what are the other kinds of people what type of what type the other belongs to whether their names are nights etc. So there is another way with which you can solve this problem that is the truth table method so which we do not go into the details of this one but we have studied semantic tablux method in greater detail so we will be solving this problem using semantic tablux method so now the problem is like this A says B is a name and then B says this particular kind of thing A and C are of same type so now based on this particular kind of information how do we know that what are A B and C so the one of the ways to solve this problem is like this so suppose if A says that he is a night then usually you represent it as this one A says that A is a night that means A if and only if A so that is a way to represent this particular kind of problem so now this problem can be represented as this A the first one B is a new that means it has to be negation of B that stands for the first statement now the second statement is represented as this thing B says that that means B if and only if then this is the one A and C are of same type here there are two cases which you need to take into consideration so A and C are of same type means either they can be both nights or they can be both names also so that means you need to take into consideration this possibility either both are nights or both can be names so names are represented with negation so the brackets needs to be closed properly now this is the second formula so now we need to figure out under what conditions these two are simultaneously true or what are what makes this thing satisfiable or what makes this true two statements true you can solve it with the help of truth table method by constructing you take this as X and this as Y and then you construct a truth table X and Y and then you will see wherever you find T is in all that row you need to inspect and then that means that is a row that is going to satisfy these two formulas and that row you need to inspect and then you can find out you can go back and find out what are A's and B's in that particular kind of row so that is one way of solving the problem but we are trying to solve it with the help of semantic tab looks method so now this is the first one which we have represented A if and only if B not B and B says that both are of same type that is A and C or it should be not A and not C so now we will be using some kind of alpha and beta rules to X to construct a tree for these two things so now we are opening this formula first so that is for example if you have a formula X implies why then what you do is you expand the tree in this way either X and Y is the case or not X and not Y so that is one of the possibilities so now you have listed out B as it is B A and C or not A and C as it is so now this is the one first one and you negate this literal and then you have to negate the other one also not X and not Y not of all these things so now you further expand this tree and all so this is A and C and not A and C so A and C actually this should be like this A and C now this further expands to is so now you have not A and not C here this expands to not A not so now there is no way in which you can close the branch and all because we do not have a literal and its negation at this moment so now you further expand it with this thing so on the other hand we have not of this one first negation of disjunction is a conjunction that is why we have written one after the other one so it is not of this particular kind of thing and not of this one so this is the one so now you expand this particular kind of thing negation of conjunction is a disjunction that is why we have a branch here you will see branch here it is not a first one not A or not C this is the one which we have written for this so now you further expand it with the help of this one not of not A and not C that is negation of disjunction conjunction is a disjunction that is why we have a branch here negation of negation of A is A negation of negation of C is C and in the same way the same information which you put it in the other branch which is open again A and C at this moment you need to see whether you have a literal and its negation that means if there is any conflicting information present or not so now you have A here and not A here this branch closes here and then this branch is still open now you have A here and of course this branch is also open you have C here and not C here so that means this branch closes here itself you need not have to expand this particular kind of branch so now these both these formulas are checked and all we are simplifying this formula and all so now you write for this one so this is x implies y means x y and not x not y so that means this is simply A and not B and then negation of this one is not A and negation of B is B so that is what we have written again the same thing needs to be written for the open branch here this branch is open so that is why we need to write the same information for this one A not B the same information not A and B we finish the branch and all because we ended up with only atomic propositions so there is no rules can be no further rules can be applied here it stops here itself because the end of the branch is considered to be here an atomic sentence no further rule can be applied so this branch ends here now we need to inspect whether a literal and it is negation is present in its branch that means the conflicting information is present or not in the given branch so now here I have not be here and so this branch closes here itself need not have to worry much this is the one which we need to inspect a and not be and all the way up here you have not a here and a here so that means this branch closes so now in the same way you have B here down the tree and all the way up here you have not be so that means this branch also closes so now this branch remains open because there is no conflicting information so now this is the open branch which you need to inspect now here also you have B here and not be here the branch closes so this is about the right hand side now we need to see about the left hand side in the left hand side we have here you will see clearly here you have B here and not be here that is why this branch closes this mark represents the closure of the branch you can represent it with any other mark and all it does not matter but you put cross and also that you cannot further extend the extent further it is like you are sitting on a branch of a tree and you are cutting that branch and all if you cut the tree then there is no way in which you can move forward if you move forward you are going to fall into ditch or something or in logistic terms you will be falling into some kind of hell hell because there is an inconsistent information in all inconsistency is considered to be a kind of hell for the logistic why because if you have an inconsistent statement you can derive anything any strange kind of thing using the principles of logic so all principles of logics are true preserving and you use the same kind of modus ponens etc and all you can derive any strange kind of preposition that is the reason why logicians will hate to have this inconsistency you know. So now we have only two open branches in all and open branches are the ones which makes this formula true I mean these two formulas simultaneously true that means satisfiable so this is the interpretation under which this two formulas are going to be true that means satisfiable so on the one hand you need to inspect here you have not here that is what we have listed here and then B is the one which we have listed here then whatever is there not C is the one which we listed out here so this is one particular kind of solution so that means if A says B is a name and B says A and C are of the same time now A and C now they are of the same time so that means A has to be a has to be a name and C has to be name that means they are of the same time so that is what B is saying so now this is one possibility and another possibility is this that either A has to be night and then both B and C have to be of same type not B and not C so the solution of this problem is this thing when B says that A and C are of same type and that seems to be satisfying this particular kind of solution so that means A and C has to be names and B has to be a night so this is the way in which we can solve this particular kind of problems we will consider some more problems in little bit in greater detail little bit later but before that we will consider some of the interesting problems which we began within the beginning of this course beginning of this lecture on propositional logic so we will go back to that particular kind of thing and we will see how to solve this particular kind of problem so this is the one which we will be looking into he began with a very interesting problem that is this thing so instead of doing this logic course in with all theorems etc and on it is also interesting in certain way but we are trying to include as many as much as possible some of the interesting problems that you come across in day-to-day discourse so here is the it is an interesting problem which we began with and then a detective is trying to find out who has committed this particular kind of crime so the problem goes like this there was a robbery in which some goods are stolen means lots of goods are stolen that is why you are worried about it so now the robber let us say is left the truck left in a truck and all after stealing all the stuff and all they flew in a truck with the help of truck they flew away so the information that we have at least we have this piece of information and from this piece of information you need to find out who has committed this crime or who is innocent or who is guilty in so the first statement says that no one else could have been involved other than ABC somehow you could figure out that only ABC are involved in this particular kind of theft or robbery no one else is involved in that one you have seen three people flowing flying the three people are leaving in a truck so now the second statement is this C never commits a crime without Ace participation that means wherever wherever C goes you will take a in particular so C has a lot of faith and A may be C A is considered to be best friend of him or C is sure that whenever A is there and you might commit the crime effectively I mean theft effectively etc that means C never commits any crime without the help of Ace participation that means wherever C is there A will always be there so now the third bit of information that we have is this thing B does not know how to drive that means B cannot drive the truck and all so we doesn't know how to drive so that information also we somehow have so now given this piece of information we need to find out who is guilty when that means whether A is innocent or guilty so now again this problem can be solved in N number of ways so one is this that you can assume something someone is guilty and then you show that using reduxio add absurdum method somehow you came to this conclusion that a contradiction A leads to contradiction then obviously you will say that not A is the case that is one way of solving it or you can process this information in your mind and then ultimately you can come up with your lucky you can come up with an answer but things would be relatively easier once you represent this piece of information into some kind of language where you can some kind of language is called a symbolic logic or symbol or propositional logic so now this piece of information if you can represent it in this way then we can find out who is considered to be guilty so now the first one first statement is that no one else could have involved other than ABC so this can simply be translated as A or B or C so you have to note that this is the problem that we began with when before entering into the propositional logic this is one of the motivation motivating examples which we have taken into consideration but at that time we don't have we didn't have the semantic tableaux method or truth that is why we left it there so now we are taking it up and then we are trying to solve this problem using semantic tableaux method so now the first statement is translated into A or B or C because no other person is involved in it D is not there so that is why ARB or C so now the second one is this thing C never commits a claim without a spot is patient so that means presence of C is important for sufficient for is involvement in the crime in all that means it is C implies A so and the third one is B does not know how to drive that means if B is a person then obviously it has to be accompanied with either A or it has to be accompanied with C then only you can flew and you can escape from the scene the robbery scene otherwise you will be caught in all so either he has to take the help of A or he has to take the help of C so now given this piece of information again we will draw a kind of semantic tableaux tree for this one and then we will see whether we can solve this problem or not so now the first information is ARB or C first we will list out all these things then we will see whether we can solve this particular problem or not so now the third one is B implies B and A or B and C B always has to be accompanied with C then only he can run away otherwise there is no way in which you can you cannot drive the car you cannot drive the truck that's why you will be caught in so this is the piece of information that we have so now the question is whether A is guilty or not so now before solving this problem we need to come up with some kind of representation so in this problem I am taking into consideration A means A is guilty and B means B is guilty etc. Guilty means he has committed crime and that's the reason C is guilty so now exactly opposite of that one is what we mean by this A is innocent so not B is B is innocent and not C stands for C is innocent suppose if you are not comfortable with this negation etc and all usually we will say guilty means not a that is innocent means a clean so that's I says a so in that sense what you need to do is you can interchange these two things and ask and represent it first suppose if you represent a as innocent now this formula will become not a or not B or not C so that is only difference here and instead of C you will have not C and not because what you mean by innocent a is innocent here for you is this one rather than this particular kind of negation so I am taking into consideration a means a is guilty B means B is guilty and of course not a means a is innocent so now once you represent this formula in terms of appropriate language of propositional logic then you will come to know a detective let us say is trying to find out is trying to club up this information and he is trying to find out who is guilty and who is not guilty so you can process this information in your mind and then you have to work a lot and all for coming of this kind of solution for this particular kind of problem but once you represent it in terms of some symbolic language like this and if your information is correct then obviously you can come up with your solution so now forget about what a B C C et cetera and all now now we will process this information using the semantic tableaux method so now this is the piece of information now we need to figure out under what condition this is going to be satisfiable you construct a tree and you will come to know when these three kinds of statements are true so now you will open up this branches and all so first any formula you can use we will open up this particular kind of formula that is it is not C and E because x in plus y is not x and y so now this is over you check this formula so that is done taken care of now the second thing which we will do is this one this is not B and then the same formula which be right B and a or B and C so now the same information you write it in the other branch which is open so now this is again the same thing now this is B and a R B and C you might ask why I need to do all these things to figure out who has guilty and who is not guilty you might say that I will assume that I will begin with a is guilty and then I will substitute into this information I will find out what C is and then from we can find out way what a C and all about and then you can find out all other things you can do it in that way also but we are trying to solve this problem in a much more rigorous way semantic tableaux method is very simple to use so and very effective kind of method it will list out all the possibilities under which this formula is going to be true it will not leave out any possible so now so this is over so now we tick mark this one so we will further simplify this one so now this becomes B and a because B and a is written in this way and this is B and C so now in the same way it leads to a branch and all because of this current you are this is BA and B and C little bit of effort is needed to see under what condition this becomes true so now what is left is this particular kind of thing now you have to see here you will observe you can observe that you have C here and not C here so obviously the branch closes now you have to find out whether any way in which you can close the branch so this branch is open and this is also open and all the branches are open so now we what what is left is this particular kind of thing now we will check this formulas each open branch that you have you need to add this information so it is A or B or C so this is a branch which goes like this now this is also again an open branch so we write ABC now this is a close branch we need we not have to worry much about it so now not be and you have ABC and this is also an open branch so again you add this piece of information under this branch ABC again you add the same information here so there ends the we have applied all the rules of all the beta etc and all no we ended up with only atomic statements atomic prepositions there are no rules can be applied on this one that means there ends the tree now you need to observe whether there is any conflicting information in any one of these branches so now here a not B not C so this branch is open now you have B here and not be here this closes and see here and all the way up here so you have not see here C and not see so conflicting information that closes so now A B and C this branch is open now this B AC this branch is also open now you have C here and not see this branch closes the branch means the path of the tree is like this not see all the way down here and all the way like this and then it is going all the way down here so now here the next branch is also open now you have B and not be here is closes and this remains open and all the open branches are the ones which you need to take into consideration for solving this particular kind of problem so now this branch is also open this is also open this is also open all the other branches are open so now what is that we are trying to figure out we are trying to figure out whether or not a is guilty or a is innocent a is guilty means you need to get a this formula a is innocent means we need to get this particular kind of thing so now we need to observe all the open branches this which satisfies this particular kind of formula so now so in this open branch you have one particular kind of solution is a not be this is the one which you need to observe not see what does it mean a is guilty B is innocent and C is C is innocent this is C is innocent now this is guilty that is the first one which we got the open branch here now other open branch is a B and and not see a B and not see so that means again a is considered to be guilty here so that is one way of doing it another possibility is this one this open branch B a and not see the same thing which we have so a B and not see and you have B and not see B a and not see this is one form another one is a not be a and not be we do not know about C using this particular kind of information so now the other possibility is a B the same thing which we have now the other possibility is a B a B and C a B and C so now the other open branch is this thing a B C the same thing which we have written the same way you have a B and C here so the same information which we have even here also your a B C in all the possibilities here we have only one particular bit of information which cleverly clearly indicates that a is considered to be guilty but if you are asked to find out whether B is guilty or C is guilty the problem comes to us is very difficult to determine because in some cases B is considered to be innocent C is considered to be innocent here but now in this case B is considered to be guilty and not C is considered to be a C is considered to be innocent here in the same way this two in this information is one of the same now in this case we cannot determine anything in the case of this thing is definitely guilty here but B we can say that is again guilty but C you cannot determine anything so this problem at least you know with this particular kind of formula we can achieve this particular kind of thing that in all the cases that we have studied all the open branches are suggesting us that it is only a is guilty but the problem is is that until we have some more information we will not be in a position to determine whether B and C are guilty so you need to add some more information to this one so the detective has to find out what information one needs to add so that even you will come across with some kind of evidence that B and C are also going to be whether they are innocent or guilty and all for that you need some more bit of more information to solve that particular kind of problem but as far as a is concerned we are trying to find out that is the reason why we asked in the question whether a is guilty or a is innocent in all the open branches it clearly suggests clearly suggesting us that it is pointing finger towards a that means a has to be guilty so whenever you come across the information a that means the original translation is like a is guilty whenever you have this information not be and that means so this is the thing B has to be innocent but in some cases B is innocent some cases it is not we do not know what it is so that is the reason why we cannot specifically tell about whether or not B is involved B is guilty or not so now this also satisfies the other condition that whenever C is there a is also accompanied with that particular kind of thing so wherever C is there then that has to satisfy this particular kind of thing wherever a is there C also has to be there when a is guilty C also has to be guilty that means with that particular kind of information you can even talk about whether or not P is guilty or not this particular kind of solution we take into consideration where we have all a, b, c and all that means all a, b, c are said to be guilty so in that way we can solve this robbery is case in all so here in this problem we can clearly say that a is considered to be guilty so there are some other problems which we can solve so we look into some other issues related to the semantic tableaux method so what is important here is this that given a problem we need to translate it in appropriately into the language of prepositional logic and then once you translate into the prepositional logic things will become simple so we are trying to look into some other kind of problem what we will do is translate the English language sentence into the appropriate language of prepositional logic and then we will see whether that argument follows or not so here is a simple example which is there in the natural language that is English so it says like this unless food prices continue to rise or building costs sold the general living index will not remain in an inflation rate trend so that is the first sentence so the second sentence is we read in the papers that food prices continues to rise inflation is rising food prices vegetable prices are increasing you know so the conclusion is this that so we must conclude that the general living index will remain inflationary so now once you are given this particular kind of problem the first thing you need to do is you represent these sentences in terms of some kind of sentential letters here F stands for food prices continues to rise and B stands for building costs so and see I stands for the general living index will not remain in an inflation rate trend so now the first sentence is FRB implies I and the second sentence is F therefore I now we need to see whether this particular kind of conclusion follows from the premises are not the premises are the first one is unless the food prices continue to rise the building or building costs so there is one premise and the second premise is the general living index will not remain an inflationary trend there is a second premise etc so now once we translate into this particular kind of thing we have FRB implies I this is the first one and the second one is F and then the conclusion here is this one I so now how do we know that this conclusion follows from these two premises here is a decision procedure method which we have been discussing so we are trying to solve these puzzles these problems with the help of semantic tablux method so now in semantic tablux method the essence of the semantic tablux method as we have discussed in greater detail is this that we need to construct a counter example so now what we do here is thing we list out all the premises in all now we need to write like this so what we will do is we negate the conclusion we start with the negation of the conclusion that is denial of conclusion so the idea here is that you began with some assumptions X and you ended up with the contradiction that means X implies the contradiction and that implies that it should be not X rather than X so this is what is another version of deduction and absurd kind of method now negation of the conclusion we construct a tree for this particular kind of thing so now the fourth one is this now these are two atomic sentence and all is nothing known in nothing needs to be done here I mean no rule will apply on this particular kind of thing so now the only the rules apply on this particular kind of thing the first formula so now this is a branch so that is not of X and Y is here I so now this further simplifies to is not F for B that means it is in the negation of F negation of this junction is conjunction that is why you list it out just below this one and this is the one so now there ends the tree so now we need to see whether there is any conflicting information in any one of the branches here you have F here and you are not F here this branch closes and you are not I here and I here this branch closes so that means negation of the conclusion that is what we assumed all the beginning leads to branch closure that means it is a contradiction that means negation of X is unsatisfiable the other way of round of saying the same thing is is that negation of X is unsatisfiable so now X has to be true and it assures us that X has to be the conclusion that means X is what here this is the one actual and not X is this one not of I but the actual conclusion is X that means I is considered to be the conclusion of this one suppose if you take the denial of the conclusion it leads to branch closure it makes unsatisfiable so that means this particular kind of for this conclusion follows from these two premises and all so this is the way in which you can establish that a given formula is considered to be valid or not is considered this argument is considered to be valid or not we can establish so what we have done here you have translated the English language sentences appropriately into the language of prepositional logic and just we simply forget about what they mean and all and now then we apply a semantic tableau rules and with which you can find out whether or not that particular kind of conclusion follows are not there are other kinds of examples this class is all about solving some problems the best way of learning logic is to solve the problems so now here is another kind of problem again it is written it is it is in the form of English language sentence now we need to find out there are three or four sentences which are given now we need to find out whether they are consistent to each other again using the same method that is the semantic tableaux method so now the first one is translated in this way it is in true that the litmus paper is put into an acid solution but at the same time it does not turn red you put it in the litmus paper is put into the acid it will become red so it is it is not the case that you have put it into s and then it is not r and all it is translated into not of SNR so that means SNR has to be the case I mean so not of SNR is the first sentence so now the second statement is had the litmus paper turned red the experiment would not have been a failure so that means would not have been a failure is not f so that means r in place not f is the second sentence now the third sentence either this litmus paper is put into an acid solution or it does not turn red it should be as red or the experiment is a failure that means SNR or f so now the conclusion is this thing therefore it does not turn red and the experiment is a failure so there are three things which you can you can talk about consistency by taking out all the four sentences and all or since it is explicitly given that the last sentence is considered to be a conclusion now again we can see with the help of semantic tableau method whether this particular kind of conclusion follows or not the first thing which you need to do is you need to represent these sentences in terms of some kind of variables SRF usually it is written in the capital letters so now once you transform this sentence into the language of prepositioning logic and things will become easy so now here is the one in which you can solve this particular kind of problem so we know that sometimes we might know without using this semantic tableau method that this conclusion follows and on but they should be a procedure for knowing that this is the only conclusion that follows from the given information so the first one is not of SNR we have translated it properly and that is the one and the second one is R implies not F and the third one is SNRF so now the conclusion needs to be separated and this is the conclusion not R and F so now again how to solve this particular kind of problem is simply this thing first you take the negation of the conclusion this is denial of the conclusion if you deny the conclusion whether or not it leads to branch closer or not is the one which you are trying to look into so what we have done here once you translate the English language sentence into appropriate language of prepositioning logic we do not bother about what we mean by SR etc and all but we just use the method here and then once we get the branch closer and all we will look back and then again we look into our translation so now the one of the important methods that we have seen is that first we need to apply non branching rules over the branching rules but here it does not seem to be any non branching kind of rule here so that is why you can use any rule here you can open up any statement so first we will start with this particular kind of thing not R and not F so this is the first one which we have used we applied X implies Y that is not X or Y this is as it is and then this becomes negation so that is the definition of material implication now this is over so now we close this particular kind of thing so now you can open any one of these things it does not matter but sometimes the proof might become simpler if you take into consideration some formulas over the other ones but more or less if you have non branching rule you have to use it first we do not have that thing it does not make big difference so now this is not of not R is R and then negation of disjunction is a conjunction so now this becomes this now all this information you need to provide it in the open branches so each stage you need to see whether a literal end is negation is there in the branch so now this R and not are closes and this branch is still open all these branches are open so now this formula is also over now we are left with two other formulas so now we will open up this one so now this is not S and S and not again the same information you like it here also not S and not R so now again you will see whether there is any conflicting information in the branch are not so here is the branch we have R and not R so that is why it closes so not F and all this remains open and is also open so now this is also over now whatever we have left is this so now this is not of S and not R so sorry so this is simply this one S S and not R or F the same information we need to provide S and not R and F S and not R need to write it properly so that S and not R and F and here is another open branch S and not R one needs to be very clear about these negations suppose if you somehow skip this negation then you will branch will not close or maybe branch closes for a wrong reason so we need to take care of this symbols so again this is you have to be little bit patient in doing while solving the problems it will become simpler for us so now it is S and not R and F now there is a matter this three ends and all so now we need to see whether or not all the branches are closing or not so this is S and not all so now we have S and not S here this branch closes here and you have F here and you have not F here this branch closes and now your S here S here not R and not F not R so this branch is open so now all the other branches are open now you can stop here itself you need not have to worry much about all the other branches and all why because negation of the conclusion leads to some kind of counter example this serves as a counter example one open branch is good enough to show that this argument doesn't follow so even in you not have to inspect all the other open branches just one branch open branch will serve our purpose so what we have achieved here we listed out all the translations of a given English language sentence into the language of prepositional logic we forgot about what you mean by R skews etc. And all then we listed out the conclusion separately and then we negated the conclusion and then we are trying to see whether it leads to the branch closer or not that means all the branches should close in the process we came with at least one branch where it is open that means when you give valuation T S is T R is F and F is formula F is false then obviously it satisfies this particular kind of formula what satisfies this thing it satisfies two premises in a false conclusion that makes its formula this argument invalid that means you have come up with an instance where your your premises are true and the conclusion is false so that will serve our purpose that means this particular kind of argument that is the litmus paper that means therefore it doesn't turn red and the experiment is a failure that is not R and F doesn't follow from these three things the information that we have this is the way in which we can solve this kind of puzzles and we will look into some more problems so let us consider whether or not this particular kind of argument is valid or not if Rogers lives in Bangalore you will be happy Bangalore is a good city it offers many things malls etc and all so probably may be happy in this case there is no question of probability is happy that is the one which we need to take into consideration B ? H is the thing so now the second statement is if he is happy and he likes his work that is H and W implies he will get on well in his job unless he falls in love with someone else so as long as you will not fall in love with someone else you will do well and you will work well fine etc and all so this unless always present some kind of problem and all this unless he falls in love is translated as not L implies J that means L not L is the case then obviously it is J so if then kind of thing sometimes unless is translated in terms of R disjunction etc sometimes it is translated as an implication that is why it presents some kind of problem to us in the process of translation so now this is the second sentence is translated as H and W implies not L implies J now third sentence refers to if he falls in love that is L he likes his work even more it so happens that he falls in love and then obviously might start working in a more effective way L implies W so now this is the conclusion so if he lives in Bangalore he will get on well in his job so now whether or not this particular kind of argument is valid or invalid again we can use either truth table method or semantic tablox method etc and all to show that this particular kind of argument is valid or not now first you list out all these things B implies H that is the first premise that is there written in English language and the second one is H and W H and W if you lose happy and works then understand until he falls in love with someone you will continue to do his job effectively so now third one is this particular kind of thing L implies W and this gets separated by a conclusion the conclusion is if he lives in Bangalore then he will do he will get on well with this job so this is the one which we have once we translated the English language sentence this becomes like this so now again one way of solving this problem is that you list out all the premises and you construct a truth table and your truth table will have for example 1 2 3 4 5 there are 5 propositional variables so that means there will be 2 to the power of 5 entries in your truth table so now you have to inspect all those rows I mean all the 32 rows and you need to see you need to look for a row in which you have whether or not you have true premises in a false conclusion so instead of inspecting all these things so we better solve this problem using the semantic tableau method so now you start with the negation of the conclusion this becomes like this and then you start constructing a tree so as usual we will be using the non-branching rule first that means this is leading to non-branching rules so that is why we apply non-branching rule first for simplification or for you can use all for rule the beta rule so this is not J so now you can open any one of these so since you have checked this formula you put a tick mark to this one and start opening the other formulas so now you will open this one not B and H so if you can write it in this one simplification you will get this one so now this is over you tick mark this one otherwise you will start using it again and again so then we are confusion so now you open up this particular thing now here B and not be this branch closes here each time you apply alpha and beta rule you need to see whether the branch is closing a lot so now this branch is open now you need to expand it with other things which we are unchecked they are all unchecked formulas so now you apply this unchecked formula this one and when you apply this rule alpha rule to this one it becomes this one not L R W so that is the definition this it becomes like this now so this is over now whatever it is unchecked is this one now we need to see whether this branch is closing or not here there is no way in which it is closing so now you expand it with this one this is H and W sorry not of H and W and the same thing not of L implies J the same information you write it here not of H and W and not of L implies J the same information you put it in all the open branches that means this becomes this so now you further simplify this one it becomes not H not H and not W and this becomes L and J and this becomes not H and not W and again this becomes L and J so the board is entered with these things so now we need to there are no further alpha and beta rules can be used because all these things are atomic statements are prepositions so now we need to inspect in each and every branch whether there is any conflicting information or not so now you have not H here and your H here is branch clearly closes here so now you have not W and all the way down so this branch is open so now we do not have to worry again for the validity at least one branch is open you can stop here so that means you need not have to worry much about all the other open branches and all one open branch is clearly establishing us that this is a invalid kind of argument. So what is that we have seen in this lecture is simply this that we began with the semantic tableaux method and we started applying it to solving some of the logical puzzles mainly the Knights and Naves puzzles and then we moved on to some other interesting puzzles interesting problems that occurs in due to the discourse that means given English language passage we translated into the language of appropriate language of prepositional logic and then we have seen whether or not the conclusion follows from the premises are not so this particular kind of semantic tableaux method can be exclusively used for solving the puzzles in particular the Knights and Naves puzzles are one needs one wants to find out a mystery surrounding a robbery or theft etc that is what we have seen in this class or it can even be it will serve as one of the important and effective decision procedure method and with which you can find out whether or not particular person is committed to be guilty or guilty or innocent all these things which will come to know with the help of this particular kind of technique. So far we have covered semantic tableaux method so in the next class we will be seeing another kind of syntactic method so which is called as natural deduction method so we will talk about the natural deduction method in the next class.


of Dr. Kildare, starring Lou Ayres as Dr. Kildare and Lionel Barrymore as Dr. Gillespie. Player General Hospital, one of the great citadels of American medicine. A clump of grey-white buildings planted deep in the heart of New York. Nerve center of medical progress. Great minds and skilled hands wage man's everlasting battle against death and disease. Player General Hospital, where life begins, where life ends, where life goes on. Well, Dr. Kildare, how nice to see you in clothes. I beg your pardon, Mommy. Oh, now you know what I mean. Drs. Tunik's may be all very well and good, but a suit of clothes really does something for a man. I'm glad you approve. What are you doing in Dr. Gillespie's outer office today? His nurse is on relief. You can find more excuses to get at that desk. Well, I started looking after him 20 years ago and I can't seem to break myself of the habit. I see. How aren't you? What are you all dressed up for? Going out. How do I look? I don't like your tie. Oh, what's the matter with it? Not too big. Not his. Not too big. It's just right.  Well, you aren't wearing this. Well, I'm looking at it. You won't be looking at it very long. I'm taking it right out of here. Where are you going? Got a date. With a girl? What else? Well, with you, it's hard to say. You could have a date with a test tube? Somebody sick cat? A monkey in the zoo? All right, all right. You don't have to elaborate any further. I have a date with a girl. Yeah. A very pretty one. So, if you don't mind, I'll be on my way. Who's taking care of things for you? Well, I haven't had any emergency cases. One of the other doctors is standing in for me. Who's the girl? A gal from my hometown. Haven't seen her for several years. Think you'll know her when you do see her? I remember there used to be the prettiest little nurse in Ackensack. One day I went back there and... Yeah? Well, that's another story. Where are you meeting her? At the zoo in Central Park. Why the zoo? Just thought I might get lonely for you. I'll get out of here. Just what I was going to do, Dr. Gillespie. Good night. Oh, you look wonderful. So do you. Were you waiting long? No, I just got here. I've been renewing some old acquaintances. The same lion is here. I know it's the same one. And I'd swear some of the monkeys are the same. How long has it been since... Since we were here? Several years. I thought so many times about how we used to come here to the zoo when I'd get to New York. Now, you were about 20, if I remember correctly. And I was 17. Life was a very serious thing in those days, wasn't it? It certainly was. We spelled it in capital letters. Spent every waking moment worrying about what we were going to do with it. Well, you got what you wanted when you were 20. You're certainly a successful doctor. Did you get what you wanted when you were 17? Hardly. At 17, I wanted to marry you. No. Well, anyway, you're lucky. It isn't much fun being a doctor's wife. I never heard your mother complain. No, she never did, but I know what her life was like. Not just days, but weeks would go by and she'd only see my father as he gulped a cup of coffee on his way out of in a case or on his way to bed at some unholy hour. I thought about you a lot of times, Janet. I meant to write, but somehow there just never was enough time. Jimmy, do you think you'll ever find any time for real living? Don't you think there ought to be some sort of balance to life? Is medicine alone enough for you? It has been for Dr. Gillespie. Do you want to be like him? No. Not really. Not in the sense you mean. I'd like to marry someday and have a home and children. I wonder if you'll ever take the time. Oh, sure I will someday. I've got a lot of time yet. So have you, for the matter. You're so quiet. What are you thinking about? An old Chinese proverb. Oh, what? Enjoy yourself. It is later than you think. It turns cold suddenly, hasn't it?  What was the best dancer I ever knew, Janet? Oh, thank you. We used to dance a lot to this tune. Though there be pain, I'll not complain. The next line. A vertee may come to me. That's true. You never could carry it, too. You could get A for effort, or at least it'd be. Oh, Jimmy, it's so good to see you again. You know how I feel tonight. I feel as though some way we've gone back in your 17 again and 20. Nothing is real except this moment. Oh, Jimmy, I wish nothing was. I wish nothing was. Oh, shall we get back to our table and have a dessert? I'm still hungry. So am I. Well, I'll be darned. Is there someone sitting at our table? It certainly is. Looks like. No. It couldn't be. Hello, Jimmy. Hello, Dr. Kildare. Well, you're certainly the last two people I expected to find here. Do you think you're the only one that can have an evening out? Oh, Janet, I'm sorry. May I present Dr. Gillespie and Ms. Byrd? This is Ms. Norman. How do you do? We do have our own table right over there. We just came over to chat for a moment. Why, Molly, how nice to see you in clothes.  You're from Jimmy's hometown, Ms. Norman. Yes, I am. Then you knew his father. Oh, I should say I did. He could have me a few weeks ago when I had the flu. Hey, look at those kids. I always wished I could dance like that. Who could dance to that music? A weakard. Want to try it, Janet? Really? Of course. Excuse me. You go right ahead. Wheelchair yarn from the sideline. Oh, my. She's a pretty little thing. Yes, she is. There they go. Say, look at them. They really can dance. Leonard, don't you ever dance anymore? Only when they play a tango. You never even danced a tango with me. Oh, yes. You danced a tango when you were taking out that girl from the folly. Molly, there are certain things much better left in the deep dark past. Leonard, why didn't you ever marry? Well, I was meant to. But somehow I was always busy. Boy, you were. I was. Did you say I was? Well, you don't think that if I had married, I'd have married anyone else but you, do you? I wouldn't have dead. I wish I'd known that a long time ago. Oh, here they come. I'll be all right in a minute. I feel so foolish. Something wrong? I'll have to make a few spell on the floor. Here, drink a little water. She's as white as a sheet. Oh, I'm beginning to get my sea legs back now. I had to flew a while back. Oh, I told you that, didn't I? Anyhow, I guess I'm still a little weak from that. It's cold in here. You'd better put your coat around you. Do you want to go? I think perhaps I'd better. I hate to break up the evening though. I've been overdoing it a little. It flew sometimes much harder to get over than you realize. It's been quite some time since I had it though. Of course, I did lose a lot of weight. I suppose that takes time to get over, too. I would like to spend the night in the hospital. I mean, you could have a room there. Oh, my goodness, no, no. There's nothing wrong with me that a good night's rest won't fix. I've, I've felt like this two or three times before when I overdid. I'll be all right in the morning. Oh, nice to have met you, too. Yeah, I'm glad to have met you, too. I hope you feel better tomorrow. Thank you. Sure I will. Good night.  I will. Still wish you'd let me take you over to the hospital for an examination? No, I'll come over in the morning. You'll see I won't even need one. Oh, all right, Miss Stubborn. Good night, Jimmy. Janet. Yes, Jimmy? Tell me, did you ever outgrow that dream you had when you were 17? No, I never did, Jimmy. I don't think I ever will. Well, you know, maybe I've been selfish concentrating on my own dream so exclusively. Maybe we should both concentrate on yours for a while and see if, see if something can't be done about it. Oh, Jimmy. Good morning, Dr. Keldere. Good morning, you beautiful, ravishing creature, you. Yes, sir. Someone should take your temperature. Good morning, Keldere. Good morning, you divine, wonderful being you. Keldere, you're crazy. Oh, sorry, Dr. Glesbie.  Head?  Oh, I am, I'm sorry. Can't stop any longer. She's waiting in my office. You're so right. Hello, Janet. Hello, Jimmy. How do you feel? Oh, better, I think. But just sit down. Now, we'll take your temperature. Oh, I'm sure I don't have. Well, now, there's only one way to find out. Here, under your tongue. That's right.  Now, why kept dreaming of you? Well, what do you think you were saying to me? Why? It's later than you think. Over and over all night, it's later than you think. Funny, isn't it? And then I'd wake up and I'd think of the strangest things. That, uh, that blue formal you had for the senior prom. You remember it? Mm-hmm. And then the day I left for medical school, there was an early snowfall, and you had on a bright red cap. And when I kissed you, goodbye, you were crying. I kept thinking of things like that all night. Things that happened years ago. Oh, Jimmy. Here, let me see the thermometer. Oh, Jimmy. Come in. Good morning, Miss Norman. Hello, Dr. Gladby. Well, how is the patient killed there? Janet. Great, I'm going to have to order you to bed. Why? Well, your temperature's up a little. Oh. Well, there's nothing to worry about. Lots of things can cause the flu to flare up again. That's right. A few days in bed and you'll be as good as new. Oh. I certainly had no idea I was coming here to make a professional call, Jimmy. Janet. You know, you used to say, you thought I'd make a fine doctor. Well, now you'll have a chance to see me in action. You'll have a chance to see if I'm as good as you thought I'd be. Jimmy, I put my life in your hands. Professionally. Or otherwise. Jimmy, it's almost two o'clock in the morning. You've got a hard day tomorrow. I know. I was just standing here by the window thinking, or maybe I was praying, I don't know. These past two days since Janet entered the hospital, I... You won't help her any by losing your sleep. You examined her. Didn't you find anything different? Rapid pulse, heart murmur, temperature 103. Did you see the reports of the blood test? A high leukocytosis, 25,000 in the blood culture. The presence of short gram-negative rods, remnants of flu bacillus that have come detached from the growths on the valves of the heart and are carried by them. The first time in my life I wish a report of yours didn't conform with the report of mine. I wish I were wrong. Jimmy, we've had cases of subacute endocarditis before. It isn't necessarily fatal. We know what to do. Complete rest, penicillin. Medical science has made great progress in this kind of case. How many people realize what dangerous after-effects the flu can have? Well, there are rare exceptions, Jimmy. Now why does she have to be an exception? What is this girl to you, Jimmy? There might be a lot of things, Dr. Gillespie. She might be a lot of things. We're into the story of Dr. Kildare in just a moment. The temperature's down. Well, that's an improvement, isn't it? It certainly is. Now we've got to keep it there. You look tired. Me? Oh, I am a little. A lot of troublesome cases? Yes, a lot of troublesome cases. Janet, Janet, when you get over this, I'd like to have a long talk about everything. Then if you still want to, if you still think you could be happy as a doctor's wife. Jimmy, how do you consider this a proposal? Grade A. Guilt edged with a blue ribbon around it. Oh, Jimmy, if I get well, there's nothing that would make me happy. You know that. I didn't say if, Janet. I said when. I know. I'm the one that said yes. Why? I don't know. Perhaps because of an old Chinese proverb. Dr. Gillespie, I examined it just you asked me to. Yes. The pains in her abdomen are caused by an enlarged spleen. And the. That group of red spots below her collarbone. Badiki eye. You're sure that's what they are? They don't disappear on pressure. They're the right size. I'm sorry, Jimmy. I'm sure they are. I think perhaps you better notify your parents if you haven't already. Parents are dead. She has a young brother. I didn't want to alarm him, like called. He'll be here today. I'm going back to Janet's room. Molly's on duty. She's taking the case over. I think I'll go back with you myself. Temperatures high again. Heartbeat palpitating. Jimmy. Yes, darling. It was like. Don't say that. Don't even think it. I know, Jimmy. I know. But it's late. It's very. I'm going to get the digitalist, Jimmy. Yes. Yes, I don't want to leave her. You stay right here. I'll get it. How is she? She's failing. Developed into a pancarditis. I want the digitalist. I have it right here. Will it help? Well, I hope so. The muscle wall of the heart and the endocrarium of both disease and the heart valves and muscles have become infected. If the digitalist doesn't work, she only's got a short time. There's one more thing we can do. Inject adrenaline directly into the heart to stimulate it. I have the injection ready, doctor. Good. Dr. Gildale. No, will you, doctor? Yes, of course. Now we tried everything we knew. There was nothing that medical science could do to save your sister's life. She was all right when she came to New York. She didn't have any sign of heart trouble. How could it happen so fast? It was the results of the influenza. Then why wasn't that known before? Well, sometimes it takes quite a while for such symptoms to manifest themselves. By the time she collapsed, it was already too late. She was... Well, she was all I had. Yeah, I know, son. Do you know what I'm going to do? No. I'm going to study medicine. I'm going to specialize in heart disease and maybe someday I can find a way to help someone with the same trouble. Son, I think that's a fine idea. And I'd like to do everything I can to help you. How about having dinner with me tonight and we'll talk it over? Thanks, Dr. Gillespie. I'd like to. It's dark already. I didn't realize it was so late. Ah, this has been a very sad day for all of us. You wait here for me. Someone I got to talk to. And if I turn the light on, it's pitch black. How about some dinner? Janet's brother's it in here. No, I couldn't eat. Oh, now look, you're too good a doctor to take an attitude like that. Am I? I wasn't so good a doctor today, was I? Ah, no, Jimmy. Neither were you. In fact, the entire field of medicine didn't make such a good showing today, did it? We can't win every battle, Jimmy. We can try, but we can't always win. Dr. Gillespie, don't think I want to be a doctor anymore. What? Well, what would you be? I don't know. Carpenter, laborer maybe. I don't know what good is it anyway. All the years of study, the work, the devotion that's demanded of you, and if you can't save a life that really matters when the cards are down. You mean? It isn't one life that matters to a doctor. It's all lives. You've lost a case and you'll lose others, but when the results are added up, you'll save a good many more than you'll lose. Do you think you're the first man that ever had to withstand loss and grief?  And the world died with it. But you're still living.  And so are the people you swore to help in that old... Janet's brother is waiting in my office. He wants to take up medicine. Do you think of that now? He wants to study heart disease and maybe someday help someone who has the same illness his sister had. I'm gonna take him to supper. Good night. Talk to Gillespie. May I join you? Ah, I don't know. Jimmy, what happened yesterday's already in the past. And from the pain and grief of yesterday comes the hope of tomorrow. Because the field of medicine's growing and expanding. Nothing can change what was written yesterday, Jimmy. But with study and work and faith, there's still hope of changing what might be written tomorrow. Shall we be on our way, Dr. Kilday? Yes, Dr. Gillespie. Let's be on our way. In just a moment, we will return to the story of Dr. Kilday. Good luck. Thanks, I will. Good night. Is the hospital... Looks like a castle shining in the mist, doesn't it? Yeah, it does. A castle illuminated by hope, rising out of the darkness. Sorry I blew up tonight. Everything got too much of me for a few minutes.  I wouldn't give it up for anything. I know that. Dr. Kilday. We have Dr. Kilday, starring Lou Ayers and Lionel Barrymore. This program was written by Gene Holloway and directed by William P. Russo. Original music was composed and conducted by Walter Schumann. Supporting cast included Lorraine Tuttle, Eleanor Audley and Skip Holmeyer. Dick Joy speaking.


The long awaited Samsung Galaxy S8 has arrived at Appalachian Wireless. Get yours for the introductory price of just $149.99 with a two-year service agreement, better service, bigger savings. That's today's Appalachian Wireless, an East Kentucky network company. Last month, the mudslide on Kentucky 979 in Floyd County caused brief closures and delays, while Kentucky Transportation Cabinet crews removed the mud and debris. But on Wednesday, exactly one month later, the road was covered once again when more of that hillside gave way. Highway District 12 officials say that particular slide is proving more difficult than most to stabilize. We've had the people from abandoned mine lands look at it and they say it is not from a mining operation. It's a spring underground and apparently when it fills up and overflows, it takes part of the hillside down with it onto the roadway. So crews are now having to look at other ways to stabilize the hillside. Most slides are caused from water originating from the surface, but this one is different. We now have a constant source of water feeding this problem. When the slide first occurred in April, crews created a ditch line they hoped would force the water away from the site. But this time, they are planning to go one step further. We're now thinking about putting a pipe in that ditch line so that the water has to go where we want it to instead of where it decides to go. Work should begin soon to install the new drains which will route the spring-fed water away from the slide. Until then, Route 979 at Gretel will be reduced to one lane around the mudslide and drivers are urged to be extra careful. Reporting from Gretel in Floyd County, I'm Shannon Deskins for EKB News.


The Housing and Community Development Division manages two HUD grants, the Community Development Block Grant and the Home Program Grant. The Community Development Block Grant or CDBG Grant is a community-based funding program and it can do a wide variety of things from funding social service organizations and programs that they offer to doing public infrastructure work like street and sidewalk improvements. Their beneficiaries have to be Portland residents. That's where we, that's what our grant is here to serve, so the residents and the occupants of the city of Portland. Last year we funded a micro-enterprise program with CEI. We fund a business assistance program with the City's Economic Development Office. We are doing some work with public works for infrastructure in the Bayside area. And we do ADA curb ramp work through public works. The Milestone Home Team, we did funding for the Amasad Peer Coaching Program. Those are all social service activities. We also provided funding to the Wayside Food Programs, Preble Street Resource Center. The City's Community Policing Office also receives funding from us. Again, all social service activities. Those are type of typical applications that we receive. One thing I really like about the CDBG program is we get different types of applications to help different types of people. Between Preble Street and Milestone and Amasad, for example, and we have plenty others, they are able to help different types of people. So whether it's somebody that is not wanting to seek resources, they're able to go out onto the streets and find those people. If it's people that need more of a peer support system to help them stay sober or to help them stay on medications, we have that available. If it's simply just getting a food and meal and that's all that that person is able to do at this time, that's available to them. And I almost see it as a step-by-step process. It's not one organization doing everything, but there's resources available to help them find housing, to help them with any type of mental health issues that they're having, to help them find a job through our development programs. So it really kind of follows them along the way so that there aren't any gaps in the services that are being provided. The CDBG program nationwide is designed to improve the well-being of the community. Today, for instance, the hot topic issues, the urgent needs in our community, homelessness, substance abuse, housing, those are the kinds of things that CDBG does and that's where you see the impact to the community. Several programs I could mention, the milestone home team program, for instance, if you talk with the police department or the health and human service department, they would tell you what an important program that is to the city of Portland. Helping those people who are out on the street maybe have mental health issues, just providing the service to them and helping them get the things that they need. So that's what CDBG does. In our application, we want to know what impact funding the activity is going to have on the community and what impact not funding the activity is going to have on the community. So for example, if it's an organization that's been funded in the past, they may need that extra bit of funding they're asking for or same level funding that they're asking for knowing that if we don't give them that funding, the chance of that service being available in Portland is slim to none. They report to us on an outcome-based process.  How many people do you think that you'll be able to impact? And then we review them on a quarterly basis to see how they're meeting those goals. Because the amount of CDBG funding seems to be level or cut every year, I believe we were getting more funding in the 1990s than we are now. So when you don't have that much funding available, you have to really pay attention to how this service is going to affect the people in Portland. In some cases, you can see where that program or activity has caused a decrease in the number of people who need that service. In other cases, for instance, with homelessness or food programs, depending on the year, the time, the need for those increase, and there's just not enough resources that we can put towards them so that we would see the numbers decrease. Part of ways into the Allocation Committee's decision, but more the city manager's decision, is how this is impacting the city as a whole and the entire city budget. So we want to make sure that the funds that we're giving out are helping Portland as a whole. There's more and more people who need food assistance or emergency shelter. So those numbers keep going up. But without funding like this, it would be even worse. So that's what CDBG is designed to do.