In the last class we were discussing about liquid rocket engines and we had seen that what are the different kinds of feed system possible and what is the classification of liquid rocket engines. Now one of the things that I said in the last class about liquid rocket engines is that in this case the thrust chamber is the one where the combustion takes place and the thrust chamber and the propellant storage are differentiated a propellant is stored elsewhere and brought into the thrust chamber by a feed system and then in the thrust chamber combustion takes place. Now because of this if you look at the volume of the liquid rocket motor as such it is a very small volume and therefore if you look at the amount of heat released the energy release density per unit volume is very very high in liquid rocket engines. In fact if you were to compare energy density of different systems firstly a steam power plant then jet engine and lastly liquid rocket engine you will find that this is somewhere around 0.3 megawatt per meter cube and just goes to something like 300 megawatt per meter cube and this is something like 30,000 megawatt per meter cube. So it is a very very large heat release per unit volume that is taking place in a liquid rocket motor as a consequence if you do not cool it appropriately it could melt down the entire rocket motor within a few seconds okay. So in a liquid rocket motor cooling is very very essential as opposed to this in a solid rocket motor if you look at it the propellant itself in a sense if it is a port burning configuration the propellant itself protects the walls so there is no need to insulate the thrust rocket motor chamber whereas only the nozzle needs some kind of thermal protection in a solid rocket motor whereas in a liquid rocket motor both the thrust chamber as well as the nozzle both of them need cooling okay. Now before we look at which is the area that has the highest heat transfer all that let us look at the different cooling techniques that are adopted in liquid rocket motors or in general in all rocket motors firstly there is something known as film cooling then there is heat sink and regenerative cooling and lastly ablative cooling okay. These are the four techniques that are used in all kinds of rocket motors in order to cool the system as we discussed the other day regenerative cooling is a very very efficient way of cooling primarily because whatever heat is lost to the walls a significant portion of it is brought back into the system okay. So this has very very little heat loss to the surroundings whereas the others are not so efficient as this okay so there is a very efficient way of cooling in a solid rocket motor only these two are used okay whereas in a liquid rocket motor in a sense you can all use all of these okay primarily because in a solid rocket motor you do not have any other liquid to circulate around and cool the system in one sense the heat transfer in a liquid rocket engine is a very very tough problem to crack because if you look at any other application which requires cooling one of the advantage you have is you can choose the kind of coolant you want okay. So therefore you can do a very good job with it right here you are not given that freedom to choose the coolant you have essentially if it is a mono propellant system only one liquid or if it is a bi propellant system two liquids and you have to choose one of them as a coolant and in addition to that you do not have a control on the flow rate the flow rate is also fixed because that is what it gets fed into the engine so that is also fixed the coolant properties are fixed so and the coolant type is also fixed so it is a very very what should I say a very tough problem for a liquid rocket motor cooling okay as I said we will look at where the heat flux is maximum because that is the region which needs to be cooled much more than the other regions so let us look at where what portion of the rocket motor gets the highest heat flux intuitively where do you think should be the highest heat flux why you are right no if you look at see we are looking at convective heat transfer firstly if you look at this where do you think the mass flux would be highest it is at the throat and that is where you will find that the heating will be or the heat transfer coefficient will be the highest okay so let us try and derive that let us say we have a rocket motor like this then from our heat transfer it seen earlier while dealing with erosive burning that from heat transfer considerations this flow if you take a look at some low thrust liquid rocket motors the flow in the chamber could be laminar in certain regions okay but the flow in the nozzle is always turbulent okay so for a turbulent flow we are going to deal with the nozzle first primarily because this is something that is common to all kinds of rocket motors and then we will see how what we need to do for the entire liquid rocket motor okay so for a turbulent flow we had seen earlier that we can write Nusselt number as and we had said that the Prandtl number for most gases that we deal with is of the order of somewhere around 0.7 to 1 and if this is raised to a fractional power this gets very close to 1 and we could kind of neglect this as this is very close to 1 so if you write the Nusselt number in this fashion then we can further simplify it because we know Nusselt number is nothing but okay and we also know Reynolds number is nothing but Ud by Mu or in terms of mass flow rate it is 4 m. by I d Mu the reason for expressing this in terms of mass flow rate is if you look at the flow through a choke nozzle which is always going to be the case in rocket motors the mass flow rate at any section is the same right it is a constant so it is better to write it in terms of m. the Reynolds number we will see that we can find out certain things better so if you use this then we can write h is equal to 0.023 so from this relationship we see very clearly that it is a very strong function of the diameter okay and it goes as d power 1 bar 1.8 so if the diameter is a small that is where the highest heat transfer coefficient is going to be so the throat is the region where you have maximum heat transfer coefficient okay so we know that the throat is the region of highest heat transfer coefficient and if we were to calculate the heat flux that is coming back to the surface we can do that like this q. double prime that is a heat flux right will be equal to h into TC- T wall where TC is the chamber temperature and T wall is the maximum allowable wall temperature okay so depending on this T wall and TC you will have q. double prime right now if we were to plot what is the heat a convective heat that is transferred to the surface and where you have the highest heat transfer coefficient if we were to plot that we will have a plot like this where in on the x-axis you have a nozzle along the axis and on the y-axis you have h in kilowatt per meter square goes like this so you can see that the throat is the highest and as we go away from the throat it again drops because the flux is reducing now we can also recast this equation in terms of pressure by using the following that we know that for a choke flow the mass flow rate through the nozzle is given by PC 80 by C star so using this we can recast this and write it in terms of pressure equation as which is equal to okay so you see that if you want to operate the rocket motor at a very high pressure then you need to have very good material to withstand the kind of heat flux because this is now a very strong function of chamber pressure okay higher the chamber pressure higher will be the heat flux back to the wall and unless you have a material that can resist very high temperatures the engine will not be able to function okay now this is what we have looked at is only one part of how the heat gets transferred back to the walls that is by convection in addition to this there is radiation if you look at a composite propellants solid rocket motor it will have something like 18% of aluminum right if you remember we said this propellant cannot be used in tactical missiles because of its high heat signature which also means that the radiation heat flux in these motors will be higher if there is a larger fraction of aluminum. So the radiation heat transfer increases with increase in aluminum content and we also know that carbon dioxide and hydro water are called greenhouse gases right the reason is they to absorb radiation right and in a sense they prevent the cooling of the atmosphere right the earth re radiates back heat to the space which gets absorbed by the CO2 and H2 now if you look at what is the gas composition in the exhaust of a rocket motor it is going to be rich in both these compounds are right so you will have both CO2 and H2O in the exhaust and they add to the radiative heat transfer which one sorry this is m dot if you you have replaced yes I agree but if you look at that equation it is m dot to the power of 0.8 and if you look at this equation this is nothing to do with diameter right. So if I take m dot to the power of 0.9 then m dot by pi D2 D2 will become 1.8 and therefore that will get cancelled out so that is why it has no diameter dependence and it was only mass flow rate dependence okay so if you look at this radiation is significant if you have a solid rocket motor because of the aluminum content and also you have CO2 and H2O so typically the radiative heat transfer part is something like 10 to 30% of the convective heat transfer and we can estimate it by the following relationship TC to the power of 4 okay where AW is the absorptivity of the wall and sigma T is Stefan Boltzmann constant this is something like 5.67 x 10 power – 8 watt per meter square okay and then TC is the this is let me make it consistent with the earlier notation this is T wall TC is the chamber temperature and T wall is the wall temperature okay. So you have now realized that this is something like 30% 10 to 30% the higher being when aluminum is present okay now we understood that the throat is the region of maximum heat transfer and this requires cooling so let us look at the various cooling techniques that we discussed earlier and firstly let us consider this film cooling film cooling if you look at it is the most inefficient process okay simply because what is done in film cooling is you inject fuel along the walls of the liquid rocket motor so that as it goes through the motor it gets evaporated and therefore protects the material right. So in a sense this does not strictly take part in the combustion that portion is kind of lost for useful energy release so therefore you will find that if you calculate ISPs it will be less because of this okay and as I said you inject a thin layer along the wall and as this evaporates it absorbs the heat that is being coming in from the gas phase and therefore protects the wall right although this has been known to be very inefficient it is in a sense very widely used simply because even in systems that have regenerative cooling it has been known to be used a good example is the Saturn 4 or F1 engine on Saturn 4 okay it has locks kerosene system and kerosene is used for regenerative cooling also in addition to that they do use film cooling primarily because it gives you that kind of buffer right or it in a sense you have redundancy over other forms of heat being taken away okay and that is why it is very popular although it is not very efficient okay. Now the reason for if you look at it you are injecting a film on the wall right would it get mixed and burn up that is a possibility also right but people have noticed this this does not happen simply because if you take any cross section and draw the temperature profile in a liquid rocket motor you will always find something like this that it will have a profile like this which you can trace it back to the fuel and oxidizer injectors. So the temperature profiles are depending on where the fuel and oxidizer injectors are you will have a higher temperature okay in the other regions it will be lower and if you are aware of something called as pattern factor that is used in aircraft engines aircraft gas turbine combustors okay how good is the temperature distribution if you take any cross section you will you would want it to be very uniform right but in this case it is not uniform and therefore there is a in a sense very little mixing that is taking place and which is good for this kind of film cooling if there was a lot of mixing this film cooling would have been very ineffective okay. So the reason for film cooling being effective is that if you look at the fuel and oxidizer jets let us say this is fuel this is oxidizer because they are injected at sufficiently high velocities the momentum of these carry forward and you will have jets of high temperature and in between you will also have jets of I mean regions of low temperature and therefore this kind of film cooling works and as I said earlier in some low thrust liquid rocket motors you could have a certain region in the combustion chamber which is laminar and other regions could be turbulent we looked at how to take care of things if the flow is turbulent for a laminar case and you is given by 0.15 where RET if you look at the Reynolds number you need some diameter to be given to the Reynolds number or it is based on a certain diameter RET indicates Reynolds number based on throat. So this is about film cooling then let us look at the next cooling technique that we discussed namely the heat sink and radiative cooling now this type of cooling is very popular in satellite applications simply because you do not need to expand anything to do this if you design a motor based on this it takes care of itself this is also used in if you look at film cooling you need to kind of use a particular fluid that is carried on board to achieve the cooling in this case there is no such requirement and therefore it is quite popular in satellite applications and also this is used in the divergent position of the nozzle if you look at what happens in the divergent portion we said that the heat transfer coefficient drops after the throat. So in this region you could actually use radiative cooling in order to ensure that the temperatures do not go beyond a particular limit as a thumb rule typically this is used for motors with less than 100 kN thrust and chamber pressures not exceeding 10 atmospheres if you look at satellite applications I said they are very small thrusters right very small thrusters and they are pulsed so in a sense if you are looking at any of the other cooling techniques right it will be a little difficult because when you are pulsing it if you have regenerative cooling or other things then there could be starting issues okay. So you do not want that and therefore this is quite popular as I said in satellite applications but this is also been known to be used on a certain other engines primarily a significant use is there in the Vikas engine that is there on PSLV okay although the thrust is not below this mark it still uses it in Vikas engine to cool the divergent portion of the nozzle. So as the name itself suggests it is something like a heat sink right so it should be able to absorb this energy and hold it and also the other part is radiative cooling so if you look at how the heat is coming in and how the heat is going out let us say if this were the wall of the motor rocket engine now let us say this is the hot side right then you have TC here here you have convection and in the wall you have conduction and outside is radiation now if you remember the equation that we have written here for radiation it is very clear if you want to have the radiative heat flux higher then the temperatures must be higher right it is a very strong function of temperature. So therefore they should be high so in a sense here you need to have material that have the capability of which standing very high temperatures okay so okay because you want the radiation to be higher what is the other thing that you want to be higher in that equation if you look at this absorptivity in this case it will be the emissivity of the wall okay the emissivity of the wall should be higher and it is typically around 0.8 or varies from 0.7 to 0.85 and in order to achieve this special materials like molybdenum then tungsten alloys are used okay it is also given some kind of coating so as to ensure that the emissivity is higher so it is given aluminide coating plus pyrochrome plating in order to ensure that there is a high emissivity okay now if you look at this figure here we said that there is convection from the hot gas side and in the wall there is conduction and outside there is radiation okay this is like a series connection right this is like a series connection and if we were to write the equations for this so what is there in series connection is the heat flux has to be the same right because this is a series connection in a series connection in electrical circuits current is the same here heat flux is the same you got Hg H tc minus T wall is equal to K wall okay here let me call this temperature as Tg wall and this temperature as T wall and the ambient or the far field temperature as T infinity okay so there is heat transfer by convection that is given by this then in the wall there is conduction heat transfer given by this and outside to the ambient there is radiation given by this now if you look at this equation how many unknowns are there Tc will be known to you depending on what kind of propellants you are using what is the pressure and what is the flow rate right then T infinity is also known so there are two unknowns namely Tg wall and T wall okay and we can solve for this from these equations and we will get Tg wall as Hg Tc H tc plus h tw one minute okay where H wall is nothing but K wall by T wall if you look at the units of convective heat transfer coefficient and thermal conductivity thermal conductivity will have a meter term in the denominator so if you divide it by a length scale then you will get both the units to be the same so you can write in this fashion and so you can get these two temperatures in this way okay so now we know both this and this so therefore we can calculate what is the heat flux that is coming into the material and what is being transferred out now which one TC- sorry one minute TC- Tg wall thank you this is Tg wall this is T wall so if you look at it there is a convection between TC and Tg wall Tg wall is on the gas side and T wall is on the other side so there is conduction between Tg wall and T wall and then there is radiation okay okay then we will stop here and in the next class look at the other modes of heat transfer namely regenerative cooling and ablative cooling okay thank you.


She is going to talk about access to Python education for schoolgirls using avocados, zombies and Korean. That sounds amazing. Okay. Okay, well, good morning, or at least good morning from London. I hope you're having a good year of Python. I'm sorry, we couldn't be doing this in person. I'm sure we're all sorry actually. It's been a pretty stressful customer once I'm sure for everyone, but you know, at least we're at least we're here sharing online and I'm having a one sided conversation with you, which is quite weird but same for everyone. Okay, so I'm just going to start me just adjust that I so I see less people. Okay, so accessible Python educate from schools using avocados, zombies and Korean, which in more general terms. Oops, make sure I can move my slides would be about accessible Python education using scientific computing and data science. So, I would also just want to say like, in normal presentation, I want to ask, you know, I want to understand yourself as an audience I'd like to understand, you know your background and your interests and you know are you educators are you school teachers and so forth but I can't obviously do that. So what I'm going to do. I think the way I'm going to try and use this time. I'm basically just kind of try and highlight the aspects of this story. The slides are actually meant to be. They're actually overly detailed they're supposed to be standalone. So I'm just going to set this expectation up front just so you understand how I'm going to present. The slides are meant to be standalone so if you don't listen to talk, you can understand it fully. It's also supposed to compensate for the fact that obviously we're using English. And that's obviously not the most accessible for everyone. So I've written out a lot of the text so that it's easier to follow. So hopefully that's useful. What I'm going to do is jump around in the slides a little bit and just highlight the main points I want to make. I think that we can have a conversation because I think there's a really big opportunity in this kind of space for school children, you know school girls to access scientific computing. I don't have all the answers, you'll find that out.  So, okay, what I will go into detail is what the point of this talk is. So I'm just going to set the expectation up front. So from my observations, at least in the UK, technical education for teenagers seems to focus on these kinds of things. So, you know, this is, I'm a very visual person, I'm probably going to talk to the visuals more than the text. So if you ask a child who's doing coding, what they're doing, it's going to be very likely one of these kind of options, Raspberry Pi or Arduino, Minecraft, mods, scratch. Really interestingly, I had to make this point. There are actually a lot of competing teachers in UK schools who like VB.net. Yeah, I know it's a blast from the past for a lot of people, but that is the reality. So my point is that when it comes to learning Python, the work that my startup is doing in UK schools is demonstrating that scientific computing and data science education can actually be really effective for some teenage students. So basically this talk is going to present a case study. It's going to be of a scientific data stack education based in a London Girls' School. And I'm going to show you the kind of successful learner outcomes that can be delivered by this kind of stuff. So I hope this is familiar to you. I'm probably not great. So I'm going to have to assume that people sort of understand what Jupiter and these kind of technologies are, but we can obviously talk about the breakout if you want more detail. So basically by the end of this talk, hopefully there is more advocacy for scientific computing and data science as accessible Python education for teenagers.  And it is a lot of fun. I'm not going to lie. I'm biased. So I'm going to show you the data science. But I also want to make a point. Even before the pandemic, I actually found scientific computing. I actually found this science actually really helpful for my mental health. So, you know, if I felt really stressed out or really out of control as someone who is, you know, higher on the autistic spectrum. encoding often helped me, you know, feel more. It gave me a focus. It made me feel more comfortable. And actually, that's been something I've turned to as well in this pandemic. So, you know, in the UK, we've really not handled this COVID very well at all. I'm not going to get political about it. But, you know, I'm still effectively in lockdown. And, you know, although we've been very privileged in the UK in a lot of ways, it has been tough. And, you know, in the same way which Data Science has helped me cope better in this time, you know, I really want to make sure or, you know, really want to give that opportunity to other young people who maybe also might find Data Science and Science of computing, you know, something actually really positive for their well-being and not just from a kind of, you know, job tech future perspective. So, something I have to point out out front. So, obviously, we're talking about children, you know, they're safeguarding. So, the students are not going to be disclosed or identified in any way. So, they're going to be anonymous. I will have you visuals mainly from this is one of the meat communities which I founded, my main one. But if you kind of want to have a sense of the kind of audience I'll be talking about, if you are familiar with Harry Potter, basically Hermione in the first year of Hogwarts is the right kind of age and sort of gender. Sorry, that will give you a bit of a proxy. But, you know, without the magic stuff because that's fun but not real. Okay, so here am I. I am a tech entrepreneur. I've been working for really quite a while now. I think probably the point I want to make is that I don't come from a formal education background. So, I actually I'm a social scientist. Yes, I know it's kind of weird that I've ended up in Python via R. So, this is the first community I founded was called the RLadies Cone Club which turned into RLadies London, which then became a founding member of RLadies Global. But, you know, here we are, here I am at EuroPython for the second time. And so, how did I really get into education? So, over my career, I really found that I had a, I seem to have a sort of particular ability to explain, you know, technical content to non-technical people. And then that was something I turned into community outreach. Obviously, here with R and then with the AI club. And then I managed to turn that passion into a full-time job. So, I founded an edtech startup with a social mission, which is around democratizing opportunities for young people to level up their modern computing literacy. Now, that is not a sales pitch. It actually is generally because I need to set the context for the case study, which is about a project which my startup was commissioned by a girl school. Again, I'm not going to identify the school. It may or may not be represented by this image here. I think that's for you to decide. But the project was around delivering a bootcamp for non-coders to develop Python proficiency. And I just wanted to give a shout out to the project sponsor who I can name. Just giving permission. So, this is Madeleine Copa. She's actually did math at Cambridge. And so, she is the person at the time who initiated this really quite unique pioneering project. And we'll talk about the pioneer aspects actually through this talk. Again, I'm going to go through all the details. The key things I want to pull out here is that it was compulsory. So, this is unlike the kind of meet-ups seen that we probably know and love where people opt in. Here, these girls did not opt in. They were forced to undergo this bootcamp all 120, 11 to 12-year-olds and five of the teachers. So, hopefully that sets some context. Okay, project deliverables. So, what was actually delivered? So, remember it was a bootcamp. I decided, of course, to go with Python for scientific computing as the sort of the computing application. So, I chose this data stack, scientific data stack to introduce the girls to. And, of course, the Jupyter Notebooks as a reference here. And the structure of the bootcamp. So, we said six sessions. So, that was in the last slide. So, I structured it as basically building blocks with, obviously, relevant scaffolding. Because, as I've just said, non-coders, from non-coders to this in six sessions or, frankly, six hours is obviously a stretch. And actually, because it was a stretch, I knew it was going to be challenging. It was designed to be challenging. That's the kind of person I am. I like to stretch myself and stretch other people. So, the project goals in terms of the way it was presented to the girls was basically, I was like, listen, I know, it's like you're 11 years old. It's like, you probably don't code if you do code. I mean, fantastic. But I'm going to assume that you don't have any experience. And that's actually normal. I didn't code when I was 11. I didn't code when I was 20. So, I said, in this bootcamp, anywhere you can get up on this pyramid, I called it, I said is a bonus. So, anything you can develop in terms of your computational thinking, critical thinking, creative thinking, fantastic. I guess one thing to point out here. So, unlike, I guess, other kinds of educational experiences, especially in this kind of school, which is very academic, I said, don't compare yourself. No comparison, no competition.  So, just focus on that. Okay. I'm going to see if by the way you can still hear me because I just feel like I'm just like talking to myself, which I quite frankly could be so sorry. That's why I keep checking on this. It's perfect. It's perfect. Okay, cool. Yeah, just let me know. I don't want to be just babbling. Okay. So, project outcomes. So, there were a small minority of the cohort who had done some coding for some Python, but of course, not scientific computing. So, from a quantification, quantified, from a quantified perspective, we had 100 new teenage pythons, all girls, identified girls, and new coding champion teachers, which was super awesome. But I think I'll let the girls, they're sort of testimony, excuse me, testimonials, do the talking for me, although I guess I'll read out their testimonials, but anyway. So, I guess the things to highlight is that, from a sentiment perspective, I mean, they, on the whole, they really enjoyed it. In fact, so much sorry that one of them said that they love Python, which I'm not going to lie, was really wonderful. And, you know, it's still a really, still a really happy memory for me. But yeah, so, you know, from these kind of responses, you can see, they basically, they just wanted to keep doing it. They wanted to do it at home. They wanted to, in fact, they downloaded Anaconda at home by themselves. They wanted to keep doing it. Again, after the bootcamp was ending, they wanted to do it again next year. They didn't want to go back to normal class. You know, it was just awesome. Okay, this is a point I do want to make. So, obviously, I didn't know the students. I didn't know their backgrounds. But some of the teachers pointed out to me that there were girls who, you know, in science, for example, they were struggling. They weren't historically known for doing, particularly well on that subject. But actually, in the bootcamp, we were basically with Python, they were actually excelling.  And, you know, for me, that was just really powerful. And again, that's just emphasized that, you know, I feel like scientific computing and data science could really give young people the opportunity to discover something that they really enjoy and are good at, you know. And I really want to make sure they have those opportunities to discover that so these awesome outcomes. So why really? Of course, as a data scientist would want to know. So I think basically, this is what I want to stress is that I'm not saying all experiences, especially not a tech education, I'm not saying they're always, you know, negative user experience.  But in this case, you know, for me, my analysis was very much that, yes, there are negatives, you know, there are things we don't enjoy. I mean, I don't know about you, but I don't get a lot of pleasure out of, you know, installation and setup. And that kind of troubleshooting is not my favorite. I also know documentation is really important. I like other people's documentation. I am not something which fills me with joy writing my own documentation. So, you know, these would be the kind of negatives. But, you know, I think in this experience, I guess, I just want to draw out that, you know, I tried really, really hard to sort of decrease the negatives, or, you know, make the things which might be bad, less bad, and the things which were good to really make them as good as possible and better. So I kind of drew out sort of six specific features. So just adjusting myself because I'm sitting on the floor. So six key features that I identified which kind of had the biggest impact on kind of creating that really good user experience. So I'll go through these in turn just to highlight the ones in yellow are the features which made the user experience less bad, the ones you mean, or the features which made the user experience better. So let's talk about that. Okay, so the most important one was really the choice of open source software. Well, the choice to use open source software as opposed to proprietary. So if you work in schools, you have experience with schools, maybe children, I'm sure you'll be aware that the school environment, the IT environment, is dominated by proprietary software. Again, you know, there are reasons, I'm sure. This is just my outsider perspective looking in. But for me, it was really important to introduce for scientific computing, to introduce Jupiter and Anaconda, because of their open source sort of nature. So for me, it really overcame a lot of potential barriers or a lot of barriers, which are often in place with other technical education experiences, such as the some of the ones which I mentioned at the beginning, but I'm not going to cast any shade. So I guess the most important thing is that there's no cost in terms of procurement cost. That's really important. So yes, this was an independent school, a private school. So this is not a state funded school. So they do have more resources than the average UK school. But we can't assume that everyone there, the students especially, so in terms of their ability to use the software outside of school. So that stack, I set up Anaconda and Jupiter or Anaconda, the open source distribution that's now installed in that school, in their labs. So I knew the students could access at school. Of course, I wanted them to also be able to install it at home if they could. And the fact that it was free was obviously a really beneficial aspect. So it was just basically whether they could or whether they had the time. Which also, thanks to the other point I wanted to make is that I really, I mean, I know those reasons why, but for me, for children and for something like computing, which is so such a critical literacy, I don't like that there was a trade off between the quality of software and basically what a child's family or legal guardian on behalf of a child can afford. That is something which I feel is really exclusive. So open source software is really positive for that. There are other things. So Anaconda doesn't need that much connectivity.  And at least for these girls, I can't say for all teenagers, but after I gave them initial explanation and a bit of practice, no problem, they're autonomous. They could do it all on their own, which is, again, why it was so easy for them to set up at home. So really quick tip, the Coronaze app. So a shout out to developer Nicola Holshu, I hope I pronounced your name correctly, who's created this fantastic open source app for iOS. So I do use this for another school where the girls have iPads and it works really, really well. And again, open source. Amazing. Okay, so prototyping focus is a really, for me, was really impactful in terms of creating a better user experience. So again, I just got to focus on the visual really. Basically, I basically got them to do data tricks, or at least at the beginning, because remember, first time coders, there was, you know, for some girls, a bit of trepidation, you know, it was really sort of unfamiliar. I'm sure there's probably some negative stereotypes as well.  So I'm not really surprised that it was a bit intimidating, but data tricks. So especially using Unicode, that really worked really well. So obviously here you can see, you know, this is a good way of so after obviously they've got the code point for avocado, the avocado glyph. This is helpful for them learning how to use the print function, some mathematical operators. So, you know, I was like, okay, how many avocados should we make? Let's try 100. You know, you have a go. How many would you want to make? So it turns out we discovered that on a sort of standard Windows PC, you can make about a thousand, no, about a million avocados before it sort of starts to crash. But obviously no damage, you know, just restart. So from that kind of data trick, then you can start doing some more fun data tricks. So this works really well as well for young children, young or teenagers. A bit of what I'd like to call emoji math. So you can sort of see basically how that kind of prototyping as opposed to, you know, kind of long tedious sort of set exercise, you can see how this, hopefully you'll see this, this is quite fun for children. Scope originality. This is the one I'm just going to also talk about more detailed, oops, this chord, but that's not a message for me. Scope originality. So this is quite related to the last point about prototyping.  So, you know, in terms of these building blocks, that was set. But what I, the way I designed the experience was that, you know, we'd learn a building block, we'd learn some sort of computing information. But then I really encouraged them to think about a kind of a context to link it to. So in the kind of cognitive psychology domain, this is what's called knowledge transfer. So that's obviously a term for some of you, which has got picked up by deep learning. But the idea is that you basically fuse old knowledge with new knowledge. So this is your old knowledge, or your sort of existing memories. And this was the new knowledge to computing. And basically, when you relate the two, it becomes, well, you learn it more effectively, and it also becomes more fun. So let me give you an example. Oh, these are things basically the girls, some of the kind of things that the girls came up with. So, you know, you can see why that was quite fun in a Python class. So these are two examples. Here we go. We talked about avocados here, the zombies and the Korean language. So the building block here is obviously conditional statements. And then the context of the prior knowledge is technical term, was about zombie apocalypse. We did these. These were two things we did together, like as a class.  And then, you know, what kind of actions should we have. So that was really fun for them. And then also another example. So this was obviously around introducing dictionaries or, you know, generates the concept of data structures. And then we used Korean, or I chose Korean as a topic because I assumed correctly that girls that age would at least be familiar with K-pop, if not fans of K-pop. In fact, they were fans of K-pop. So they were really delighted to learn how to say hello in Korean, which is I hope we pronounce that correctly. So I said, in case you ever meet BTS, which is a really famous K-pop band. So they loved that. Okay, I'm just going to whack through these, the last points quite quickly, because I want to kind of finish in the next four minutes so that we can have some sort of questions. So low latency. So the point I want to make here is that there are times in technical education, definitely at these at the adult level, where, you know, you're trying a tutorial, you're trying something out. It's like it's a lot of effort. Okay, well, that's okay, whether regardless of whether it's effort, you know, you do something and you want to find out whether you're right or wrong. Okay, now you don't really mind too much if it's wrong.  Okay, great if you succeed fast, but the worst is basically in terms of speed is if things are slow. So something which I think really helps in this bootcamp was that, so obviously drawing back to this visual, was that you could debug faster or sooner because you could find out your error quicker. So this is related to, so you know, that sequence of avocados and tomatoes, which is supposed to be a sequence. So you can see if they basically, they missed out the nested parentheses, then you get one avocado and a thousand tomatoes, which is not, of course, the intention, but you can find that out really quickly. And actually, it's not that bad, you know, you don't mind getting it wrong because, you know, it's kind of fun to try and solve, at least in this context, you know, they seem to find it, you know, a kind of, you know, just something to try and figure out what was happening and not they didn't feel bad about themselves or frustrated. So hence, less bad user experience. Okay. Okay, really quickly, this slide is about the fact that between myself and then my colleague, so Dario, so dogs remember well. So we were the Python instructors for this course. It, you know, it was noticed by the teachers that the fact that, you know, Dario and I are not, should we say, the sort of stereotypical homogenous tech identities and all background, you know, was noted as relevant by the teachers. So, you know, this is a very academic school, but it's also an ethnically and culturally diverse school. And so, you know, the teachers noticed that this, the fact that these were the people in front of them, you know, doing coding, you know, okay, yes, Dario has a very technical background that, you know, he's won awards from the Royal Society for technical things, computational food dynamics, which I obviously don't understand because I have an economics background. But, you know, again, that sort of challenges the stereotype that, you know, someone who comes from a social science degree, you know, can end up doing, you know, quite, quite cool stuff, which I won't talk about because this is not really the talk for it. But anyway, so that was a positive or less bad user experience that could have been. And then there is the fact that everything was sort of set in as much real world context as possible. So, you know, we talked about the pop culture and the fun sort of aspects and the originality. Because this school is very academic, I also knew that the girls would care about, you know, certain universities, certain kinds of disciplines, you know, certain kinds of organizations. And so I basically made as many links as possible with the Python that they were learning and these kinds of real world things, which definitely helps them or would have made a better user experience. Okay, so to summarize the user experience, those were sort of six key features. Obviously, there are more. But that sort of drove a better user experience, which drove the awesome outcomes that we saw. Of course, that's quite a mouthful really to go through all those different different aspects. I think in the most simple terms, the way I describe it is that the project was successful, because the girls got to discover how to do new relevant things they couldn't do before, and also upgrade things they were currently doing, which I like to call unlock and power up. And not just students, but also the teachers. So this isn't going to make a lot of sense if someone looks at these slides standalone. But this is a, this is a gift, just a little thank you from one of the teachers who had really appreciated the bootcamp experience, for the students, but also for herself. So the other thing I want to mention is that this case study, I've said scientific and computing education is effective. Of course, there are different approaches. I like to divide it into direct and indirect. So this case study would have been direct because it was very Python first. So it's a Python bootcamp, you've got a Python syllabus, yes, then we tie in with your sort of existing, familiar knowledge. But you know, the Python is always the kind of driver. However, there's an indirect approach, which I use with other schools, which can be really effective. So the way that works is that, you know, you've got their interests. You can sort of pick one, which is sort of more common, should we say, or work more students share that. So let's say art and design, ads in Python, computational eyes. And in this instance, for example, you get code art. So like I said, you know, the girls discover or the students would discover how to do new things. So maybe they've never done fractals before, fractal art like this, or maybe they already do fractal art. But actually maybe doing in Python, it gives them, you know, more power, more functionality. And basically, it sort of makes something they're doing already better. So I guess is the point really about meeting kids where they are, not where you are, or not necessarily where you want them to be, but where they are today. So in conclusion, I hope I've convinced you to at least consider that Python for Scientific Computing Day and Science isn't just for grown-ups. You know, it can really spark joy for teenagers and adults. So why not let teenagers have a go. And that was all I had planned. So thank you so much for listening to my talk. And please get in touch or, you know, hopefully we'll have questions. Send you a lot about your message to Cheney in our Discord channels. So I have a few questions for you. Awesome. Hannah is asking, do you have any advice for how to get involved with volunteering to teach coding skills to girls? Well, I mean, of course, you can always, I mean, we would always have volunteers, so my ed tech is, effectively is run as a social enterprise. So, you know, we do charge for projects where sort of possible, but, you know, we do do pro bono work as well. So if you're a volunteer, we would definitely like to find a way of working with you. But in terms of other ways, schoolgirls, I think, you know, there are, there are initiatives to outreach Python, obviously, to, you know, to everyone. I think for me, the scientific computing is really the aspect where, you know, there isn't necessarily that kind of opportunity or access and availability. So I would have to say, I mean, I also, I couldn't say for sure, but I, I fairly certain I haven't seen really anyone else doing what we're doing, or at least not with schools, or kind of on a more successful basis. I know there, there is a, there is a market leader in the UK who, I believe they do do something similar, but they charge a lot. Let's just put that way. And it is outside of school and in certain areas. So I guess, yeah, sorry, the quick answer really is, please go as much, you know, in the breakout room, maybe. Yeah, I think, I think you can. So there is a, you, you can continue this question in the, in the discord channel for this track, but there is also a channel in particular for this talk, the name of the channel is talk school, school gears. Sorry. I think it was okay. I think I saw earlier. I think it's quite into school girls. I have it here is Python for school girls. Yes. Sorry. So it's talk Python for school girls. And then one more question. Lil is saying great talk. How did you find the structure say in terms of technicians supports and you co workers that were involved in the project? What was their, their prayer background? There, sorry, was it? So what was the background of your co workers? Oh, find infrastructure, right? Like, if you have the support technical support, that kind of things.  It is, it was a how do I find my co workers or their background? Well, my background, the micro workers tend to have a kind of more general data science background. And then I kind of tend to use my experience, my experience in industry, basically hacking, you know, it solutions or, you know, just basically making things work. So it tends to be me. So in fact, it is me coordinating with the school ID departments, which is painful. I'm sure people are aware of that. But I hope that answered the question. But yeah, please, we'll talk about the breakout room if that didn't provide the information. Okay, so we have time for one more question. So if anyone wants to ask the question live, you can click the button to raise your hand and I can enable the microphone. So let's go. Okay, so I think we're done. Thank you very much. Cheers.


My name is Sambat Nin and I am the author of Malignant Silk Club, Narcissism Revisited. Is Donald Trump a Narcissist? Is Hillary Clinton a Narcissist? Eight years ago, in July 2008, I published an essay titled, Barack Obama, Narcissist or Merely Narcissistic? It was the first time ever that pathological narcissism has been linked to a prominent politician of national standing. He was not president yet, but he was campaigning to be one. The essay Court Fire was replicated on more than four million websites and trashed and rehashed my conservative talk radio and various print magazines. Since then, it has become standard practice to ask whether a leading politician is a Narcissist or not. Problem is, since 2008, there has been an avalanche of self-styled experts, wannabe gurus, life coaches of one type or another, and all kinds of alleged or ostensible scholars, whose bombast and media-hungry pursuits are dwarfed only by the level of their ignorance. Very, very few of them know what they are talking about. Actually, I've yet to come across one. And yet they make claims and statements nonsensical as they may be, which get replicated throughout the media all over the world. Consider, for example, some of these experts who claim that Hillary Clinton is a covert narcissist. Well, covert narcissists are shy. Actually, in literature, when covert narcissists have been described for the first time in the 80s by the likes of Akhtar and others, they have been labeled shy or fragile narcissists. They shun publicity. They avoid the limelight. They like to be behind the scenes and backstage. They are manipulative. They are sly. They are very envious. But they derive their narcissistic supply by teaming up with overt or classic narcissists or by simply stewing in their own frustration, desperation, envy, and other negative emotions. They are not, repeat, not Hillary Clinton. They do not seek publicity. They avoid it. So there has been a series of debates on several issues. First of all, can we remote diagnose a politician or any other person for that matter? Well, the answer is, of course, no. Proper diagnosis requires a set of tests, structured interviews, and face-to-face meetings where the diagnostician who is a very experienced mental health practitioner is able to observe presenting signs, body language, and other parameters and to administer a series of tests. And so in the absence of this, we cannot diagnose anyone. But there is a big difference between diagnosis and evaluation. We can and do evaluate politicians on a constant basis. The CIA has a department dedicated to remote diagnosing world leaders. The predecessor of the CIA, the OSS, constructed a wonderful psychological profile of Adolf Hitler, which is now available online. Saddam Hussein's psychological profile written by Dr. Post is also available online. And what is psychological profiling of serial killers if not remote evaluation? So we regularly remote evaluate people with public exposure. Actually, there is a thriving scholarly literature which tries to remote diagnose living and dead world leaders. So now the question is an issue of knowing the field, knowing what you're talking about. And as I said, very few scholars, self-styled scholars with self-inputed expertise, know what they're talking about.  Some of these distinctions do not emanate from scholarly literature. They are not grounded in any knowledge, any studies, any research, anything ever seriously written about the disorder. First of all, we must make a distinction between personality, style and personality disorder. Theodore Millen suggested that some people have a narcissistic style. Others may have a narcissistic personality. In other words, they may have narcissistic traits. They may have narcissistic psychological defense mechanisms, defenses. And they may even have or display narcissistic behaviors. All these does not make them narcissists. They merely are have narcissistic personality. To qualify as a narcissist, to earn this badge of honor, one must meet diagnostic criteria which are described in the last two editions of the Diagnostic and Statistical Manual. Edition 4 takes revision in the year 2000 and edition 5 which was published in 2013. These criteria are pretty clear, pretty clear cut. And so if you meet five of these nine criteria according to the Diagnostic and Statistical Manual Edition 4, you are a narcissist. And if you meet several of the dimensional descriptions in the DSM-5, you're also a narcissist. So narcissists, the label of the designation narcissist is a medical diagnosis. It's not a curse word. It's not a pejorative term. It's a medical diagnosis. Someone may be very vain, considered arrogant, delusional, have fantasies of grandeur, be megalomania and still not be a narcissist. We'll come to that later. He may simply have a narcissistic style or a narcissistic personality, but not the disorder. Now people diagnosed with narcissistic personality disorder are the only ones which merit the badge or the label narcissist. And now let's move on to the next question. Narcissists, are they all malignant or are some of them productive and useful? Let's dispense with the nonsense first. There are no productive or useful narcissists, none. All the so-called experts and scholars who claim otherwise are looking for media attention and in all likelihood, they themselves are narcissists. Narcissists are self-destructive and destructive to others, all of them without a single exception. They may construct empires, they may embark on projects, they may build buildings, but at the very end, they implode. And when they implode, they take everything and everyone down with them. They construct and destruct. It's an inevitable cycle and an integral part of narcissism. So no useful narcissists, no productive narcissists. It's utter, unsubstantiated trash. Now let's talk about the issue of malignant versus non-malignant narcissists. It is true that not all narcissists are sadistic. Actually a very small percentage of narcissists are sadistic in the classical sense. Enjoy inflicting pain and humiliation on others. A very small percentage of narcissists are sadistic. A very small percentage of narcissists are, for example, antisocial. A very small percentage end up being criminals.  Something to be attacked, something to be terrorized. Well, terrorists, for example, are usually antisocial narcissists. And these are psychopathic narcissists. And they are a small minority of the entire tribe of narcissists. A bigger portion of narcissists are contumacious. Contumacious means that they defy authority. They don't abide by social rules and conventions. They are a law unto themselves. They hold in contempt anyone who tells them what to do or tries to. They are very bad team players and so on. So they are consummations. Malignant narcissists are sadistic, consummations and also antisocial. Therefore, only a minority of narcissists are also malignant narcissists. What happens to narcissists who are not malignant narcissists? Well, they function somehow in society. They climb the corporate ladder. They have families. They function more or less normally. The only thing is that they are overbearing, overwinning, domineering, grandiose, megalomania, and so on and so forth. But it doesn't slide into antisocial, criminalized, consummations or sadistic behavior. So small percentage are malignant. And now we come to the question of whether there is anything, any series of traits and behaviors that are common to all narcissists. Malignant and non-malignant. The answer is of course yes. All narcissists, malignant and non-malignant lack full-fledged, fully developed empathy. They have something that I call called empathy. It's the ability to read other people, to discern their weaknesses, their failings, their chinks in their armor, and to leverage this information for the benefit of the narcissist and to further his go. So this is called empathy. An X-ray vision which allows the narcissist to realize how he can penetrate and how he can prey upon his victims. But they lack emotional empathy. They lack fully developed full-fledged empathy which allows them to put themselves in other people's shoes to experience however vicariously what other people feel and fear and want and wish and dream. So narcissists, all narcissists lack empathy. Malignant and non-malignant alike. All narcissists are exploitative. They all exploit other people. Exploitation is often abusive. So they all abuse other people. Malignant and non-malignant abuse other people. They are all in some ways self-destructive. Malignant narcissists would be self-destructive in a much bigger way because they usually tend to drag many other people with them. They are also driven much more. They are much more ambitious. So they are alpha males, so to speak. So they construct empires, business empires, political empires, and so on. When they fall down, everything falls with them. Family, community, nation. Non-malignant narcissists also self-destruct, but their self-destruction is more confined, or limited, and usually it is confined and limited to themselves and their immediate circle, nearest, dearest, a few friends, neighborhood, maybe. So it's a matter of scale. But self-destruction is a feature of both malignant and non-malignant narcissists. They are all narcissists malignant and non-malignant. They are grandiose. All of them have grandiose fantasies. All of them have a very poor perception of who they really are. Their strong points, shortcomings, limitations, and abilities. They all have a skewed, prejudiced and biased view of their place in society, in the world, and in interaction with other people. Coupled with the lack of empathy, it makes them cognitively deficient. So all narcissists have cognitive deficiencies, which make it very difficult for them to perceive reality properly. They fail the reality test. So they are, in other words, delusion. They're grandiose fantasies bordered on delusion. So here's another feature, which is common, essentially, to all narcissists. All narcissists are compulsive attention seekers. They need and crave narcissistic supply. Without narcissistic supply, they fall apart. They need other people to support and mattress their delusions. They need other people to tell them that they are brilliant, perfect, omniscient, omnipotent, et cetera, et cetera. When people don't do that, they try to force people to do that. When people disagree with them or criticize them, they become very defensive. They become hyper-vigilant. They scan the field for insults and injuries, real or imaginary.  All narcissists, malignant and non-malignant, are like that. Another feature, which is common to all narcissists, is that they lie. All of them have a false self. A false self is a concoction, a narrative, a piece of fiction, a storyline that the narcissist adopts about himself, and it includes a lot of falsities, non-facts. Simply put, lies. Narcissists are pathological liars. They lie all the time. They don't not only embellish or embroider or confabulate which all of us do from time to time, but they constantly, blatantly, bold, facitely lie. And all of them do it. Malignant and non-malignant. So the question whether Donald Trump is a malignant or non-malignant narcissist, in my view, is absolutely irrelevant. The traits and features and behaviors which are common to all narcissists, malignant or not, are sufficient to disqualify them as president of the United States. And if Hillary Clinton is a narcissist, sufficient to disqualify her as well. But wait a minute, you see. Aren't all politicians narcissists? Aren't narcissists attracted to politics? Don't they gravitate to politics in order to control the faiths and destinies of other people? Doesn't it make them feel good to be in the limelight, to be famous, to be celebrities, to wield power? Aren't all politicians, therefore, to some extent narcissists? Well, yes, they are. But the critical phrase is to some extent. Remember how we started this conversation? Personality style. So many politicians have a narcissistic style. Many of them even have narcissistic personalities, but extremely few have a personality disorder. Donald Trump, in my view, having watched hundreds of hours of video over the last five years, in my view, would satisfy most of the criteria, including the modern dimensional treatment of narcissism, would satisfy most of the criteria for a personality disorder. But that's, of course, just an opinion, a view. I'm not able to diagnose him, and he hasn't been exposed to any proper qualified diagnostician, which I'm not. So we can only evaluate. As we have evaluated Adolf Hitler or Saddam Hussein or others, we can only evaluate Donald Trump. So he seems to have a personality disorder as opposed to a personality style and so on. Hillary Clinton is a more complex case, but it would seem that she also qualified. But that's not the main topic of this discussion. The main topic is how the field of pathological narcissism is replete with hundreds of charlatans, many of them with academic degrees who don't know what the hell they're talking about. And they apply their ignorance with a lot of aplomb and a lot of certitude and implied authority. And they spew nonsense and trash, misleading their readers and listeners and viewers into unnecessary and unimportant debates about distinctions that don't exist at all in the proper scholarly literature, between subtypes of narcissists that are totally invented. I will conclude by giving an example. The Dark Triad. It sounds like the title of a Hong Kong action movie. The Dark Triad is allegedly the confluence of three traits, Machiavellianism, whatever that means, probably means coming. Narcissism and psychopathy. Well, the Dark Triad is a fancy, media-hyped, media-attention-catching name for malignant narcissists. It's exactly the malignant narcissists. Malignant narcissists is skinning, is antisocial, is psychopathic in a way. He is, of course, narcissistic. So why come up with the Dark Triad? Why rename this perfectly excellent label proposed by Otto Kernberg more than 40 years ago? Why do we need that? The Dark Triad was invented to attract the media's attention. The field of psychology and psychiatry and therapy is flooded with narcissists. Believe you me, I've been interacting with them for 20 years. A lot of them, many of them, are outright narcissists, narcissistic style, personality, and many of them suffer from narcissistic personality disorder. They crave attention. They crave celebrity. They crave fame. They need it. They're addicted to it. They are junkies, like all narcissists.  Extreme narcissists, Dark Triads, and I don't know what other types of other unsubstantiated, invalidated, unvalid narcissists. So be vigilant. Be on your guard. Don't swallow everything you have had. Go to multiple sources. Try to limit yourself to reading more scholarly, more substantiated literature, which has reasonable bibliographies and draws on knowledge that has accumulated over decades. Don't listen to instant celebrities who have discovered that there's a lot of money in narcissism and declare themselves a minute later as extras. Vote for the right candidate.