I was inspired by Stephanie Welsh's little blitz this morning. I'm giving my talk barefoot right now. It feels different. I also want to thank Stefan Guinefer's awesome talk this morning. I was very inspired by that. And also because it helped set up some of the concepts I'm going to be jumping off into my talk today. That line of my talk, how does eating refined foods cause cognitive impairments and mood disorders? Why do we eat refined foods? And finally, I'm going to finish with, how can we banish refined foods from our diet? Very important. I'm going to jump off with work from my own lab I've been doing over the past few years in rats. And rats are actually a pretty good animal model to use to study the relationship between diet and cognition and other health aspects because their neurophysiology and digestive physiology is quite similar to that of humans and many other mammals, especially generalist omnivores, like humans. And so what we can learn about rats often translates very nicely to what we understand about humans and can corroborate with human research. So I'm going to begin by talking about the rat studies that involve looking at the effects of giving rats either a standard control diet that's derived mostly from whole food type ingredients sources to create these little rat pellets and compare rats that consume that to rats that are going to consume a refined diet that is made of highly purified and refined ingredients. I list some of the major components of each of the two diets here. If you wanted to get more information on these two diets, just send me an email. I could always send you the PDFs that have all the details from the manufacturers. And both of these diets are generally low in carbs, low in fat, I should say, I'm sorry, and high in carbs. They differ a little bit on protein, but they were selected to be roughly comparable on macronutrient ratios. They're not exactly comparable, but they're roughly comparable. Know what happens first when these rats, two groups of rats are placed on these diets. Within two months of being placed on the diets, we see there's a major difference in the fat mass that develops with the refined diet rats being significantly more fat tissue than the control diet rats. But there's no difference in lean mass tissue. I'm not showing here, but there's only a difference in fat mass, so we know it causes adiposity. But also, I've learned that it has significant effects on some cognitive markers of health or healthy cognition.  It's a standard skinner box. It has a lever, it has a light, it has a food receptacle. But we're not using the light in this study. All the rat has to do in this study is press the lever to get food, little food reinforcers. And what we use is a schedule of reinforcement where they have to make more and more lever presses for each next reinforcer.  Then they have to press 10 times to get the next one. And then they have to press an additional 15 times for the next and so on, so it progressively increases more and more effort for each subsequent reward. And what you see is this is a very sensitive assay for measuring motivation. It's used a lot in rat research and in pharmacology work to measure a pharmacological effects on motivation. Well, here we're looking at dietary effects on motivation. And what we see, we measure by the end of the session how many rewards have they received, and that reflects how much work they put into getting those rewards. And the refined rats that have become obese on this diet have earned far fewer, significantly fewer reinforcers. So they have an impaired motivation compared to rats that are eating a normal control, healthy control diet. And those data, by the way, I've already published a couple of years ago in the Journal of Physiology and Behavior, a newer study that I've done since then is now looking at other aspects of cognition, specifically attention and behavioral control. And so we developed in our lab a two choice vigilance task. Basically it's a task where the rat sits in a chamber and now there are two levers, one on either side of the food cup, and there are two lights, one above each lever, and the food cup's in the center. And what we do is the levers are not normally in the box, they're normally retracted.  That causes the levers to enter the cage so they're both available. And then either immediately when the two levers enter the cage or after some delaying after the two levers enter the cage, one of the two lights turns on for one second. So it's a brief presentation of a visual cue. The rat, so that's kind of shown in this diagram here, the levers come in and then either the light immediately comes on, zero delay, or after a three, six, or 12 second delay. So it's a variable delay for when this brief presentation of a light. And they have a limited amount of time from the onset of the light to get their food. They have to press the lever to get the food. They have to press the lever under where the light is or was. They have a six second period. So they basically have to kind of be vigilant and monitoring, okay, where is the light gonna be? And then the light comes on and they have a limited amount of time to go and press that lever. And what I'm gonna ask is, how do rats on these two diets, how do they perform in terms of the delay? How does delay affect performance? And the two major findings I've found from this is that the refined diet rats are more impulsive. And that's shown over here with premature responses where the levers have come in but the light hasn't been presented yet but the rat makes a lever press. All right, so that's a premature response. We see that in both groups, the controlled diet and the refined diet rats, there's an increase in the likelihood of making a premature response with an increased delay of the light. But there's a major significant effect, especially at the long delay, where the refined diet rats are much more impulsive. They're more likely to make a premature response. So there's a disruption of behavioral regulation in that respect. And also we see there's a main effect of omissions and this is the refined diet rats are less vigilant. So they're missing opportunities for the light to come on as if they're not able to pay as much attention and maintain that sustained attention to wait for the light and then make the response. You see there's a much larger number of omissions emitted by the refined rat diet rats than by the controlled diet rats. So we see now that behavioral control is dysregulated, attentional processing is dysregulated. I'm gonna turn to some other research with rats, not from my lab but from colleagues labs that also characterize some of the other kinds of cognitive deficits that accrue with refined diets. And here I'm gonna turn to work that generally uses Western diets which are higher in fat than the diets I was using but they're also pretty high in sugar. And these have been known to cause obesity and impaired behavioral control of different cognitive markers in rats. So here's a study looking at the Western diet and the effects of Western diet on working memory. So I'll just talk, describe the task briefly. This is what's called a radial arm maze and it's called that because there's a central platform where the rat is first placed and then there's a series of eight arms that radiate out from the center. Each one is baited with a single food pellet. So the rat then starts each trial by going and collecting all the foods by entering each arm, getting the food coming out, going to the next arm, going to another arm. The most efficient way is to avoid arms that you've already been to and only go to the arms you haven't been to yet and that requires working memory, keeping track of the places you've been. And so if we count memory errors that is revisits to arms they've already been before they've depleted the maze, and this is work by Greenwood and Winnaker, we see that rats that are on a standard chow diet make fewer errors, memory errors on this than rats that are on a Western diet when they're in their home cages. So some impairment in working memory. Another aspect of memory that's impaired to other people, Kenoski and his group have shown, involves a more like a reference type memory. And specifically there's a kind of memory that a lot of our memories require the hippocampus, abbreviated HP here, but require this memory structure in our brains called the hippocampus, and that's one of the structures that can decline with age and is related to with Alzheimer's and dementia. And so we see that rats on a Western diet versus on a chow diet, if they're given a learning task where they're learning something that we know doesn't require the hippocampus, they learn at an equal rate, the Western diet rats, learn at an equal rate as rats on a chow diet. But when you look at a hippocampal dependent type task, I won't go into the details here, we know that it's a type of task that requires an intact hippocampus to perform well. We see that rats on a Western diet perform much more poorly than rats on the controlled diet, even though there's a main effect that it's a more difficult task than the non-hippocampal task. Another thing that these researchers did was look at a marker of blood brain barrier integrity. And those are the data reported over here. And what they saw is that if you look at the hippocampus and the blood vessels that kind of are close to the blood brain barrier where the hippocampus is located, compared to other cortical structures like the prefrontal cortex in the frontal part of the brain and striatum, which is a little bit lower down in humans, that the hippocampus in particular shows a much greater increase in this marker of blood brain barrier permeability. So it looks like the blood brain barrier is being compromised by this Western diet near the hippocampus. And that might be one of the important things about the link between diet-induced cognitive impairments and specifically the effects on learning and memory. One more rodent study. And this one is looking at spatial learning, which is another type of learning that requires the hippocampus to navigate space and keep track of places in space. So what this task involves is comparing, again, healthy control rats to rats on a Western diet. And what they have is this kind of task that's called an object-place-recognition task. And it's very simple. This is a top-down view of schematic. The rat is placed into kind of a box about this big, so they're just placed on the platform, so about that big, and they can walk around on the platform. And there are two objects on the initial five-minute period that they're in the platform. And rats are curious little creatures. They'll go and they'll sniff them, investigate them, and presumably encoding something about the details of these two objects. Then you take them out for five minutes, and what you do in the meantime is you either move one of those objects to a new location, so this object here has now been moved to this location, or what you can do as the experimenter is you can replace one of the objects with a new object type as different features, but it's in the same place where one of the original objects was. And the question is, with the place task, do they recognize and go and spend more time investigating the familiar object but at a new location, which requires remembering where in space the object was originally? Or, and or can they spend more time investigating the new object as new features, even though it hasn't changed its place? And that's recognizing that the object has changed. Well, we see here that the Western diet rats are just as good at recognizing the change in object, but what they show is a deficit in recognizing the change in the location of a familiar object, so specifically spatial cognition as being affected by the Western diet as shown in this study. Okay, a couple more things about the way that diet affects mental health. It's not just about cognition, but we know it can affect mood as well. So refined ingredients such as sugar and seed oils increase systemic inflammation by stimulating cytokine production. Chronically elevated inflammatory signaling can dysregulate neurotransmitter and neuromodulator metabolism, such as the dopamine, glutamate, and serotonin are three well-known neurotransmitters and neuromodulators that are affected by diet and play a role in inflammatory processes. Inflammation mediated depression. Okay, so inflammation in the nervous system that causes a depression resembles sickness behavior. So when you get a cold, when you especially when you get something like a flu, you just wanna hide under your covers and not talk to people and kind of, it's a conservation withdrawal kind of state. That's a typical sickness behavior. Diet-induced obesity or inflammatory process mediated depression is really resembles sickness behavior and doesn't resemble the kind of depression that's clinically diagnosed based on like anhedonia. Okay, so they're actually clinically very different types of presentations. Also, refined foods are related to anxiety. There are several micronutrient deficiencies that are associated with anxiety and depression, including minerals like zinc, magnesium, lithium, and chromium. Refined foods are often deficient in such micronutrients and also it's been shown, a study by these people here, that consuming nutrient dense foods is associated with positive affect. That is positive mood, happiness, things like that. So given that we see these strong links in some of them causal between diet and cognition and mood, then why do we continue as a population? Why do we continue to consume refined foods as such a major part of our diet? And here's where I think a lot of understanding of psychology and psychological processes, how they're affected by diet are responsible for this. I'm gonna go through these eight in successive slides. So one I wanna start with is the concept of supernormal stimuli. This is starting to gain attention in the research community. And it's been known for a long time since Nico Tinbergen and other seminal ethologists that when you study animals in the natural environment, you see lots of interesting things when you start looking at what are the cues that they respond to to try and regulate their natural behavior like parental care. And so here's, according to ethologists, an artificial stimulus, someone that the experimenter can create and then give to the subject out in the wild, an artificial stimulus that elicits a greater response than a normal stimulus, they called that a supernormal stimulus. So here's an example, an oyster catcher mother. Here's her regular egg sitting over here. Here's an artificially largeened egg that's larger, maybe more speckled than her own egg. And she'll prefer to go and tend this artificial stimulus. It's supernormal, it drives, it attracts her more than the natural egg. Here's another famous one that Tinbergen had experimented on in the wild with the herringgull. Herringgull chicks peck at the beak on the mother. There's a little red spot at the tip and that causes the mother to regurgitate the fish that she recently caught and then the chick feeds by eating that. I know, we've all been there, right? All of us, the mommy's in the crowd, raise your hand if you've kind of pre-masticated some of your food for your infant. Yeah, yeah, yeah. All humans do this in other cultures too, actually. So just don't think about your own experiences as a baby. So what Tinbergen did was created these artificial stimuli, then especially this one here, this long red rod with this high contrast white bands, and noted that the chick would prefer to peck at that rather than at a natural, more naturalistic stimulus. So these idea of a supernormal stimulus has been around in ethology since the 1930s or 40s at least. But I think it really explains something about the kinds of hyperpalatable foods that have been created by the industrial food industry to elicit a greater amount of consumption, so overconsumption, compared to a regular whole foods. And so I think that these kinds of foods here are supernormal and that one of the reasons that leads to overconsumption. Here's another one, this one involves learning. So payovlovian flavor calorie associations have been studied quite a bit in rats and in humans. And we know now that a lot of our preferences, food preferences, develop by learning, especially with omnivores. We eat different things, little amounts, and rats do this too. And things that don't make you sick and things that are followed by a reduction in hunger because they have calories entering the system are things that we associate now, those flavors with something good. So we're learning to associate those flavors with calories. And so this is the normal kinds of foods, whole foods of different types that we would learn flavor calorie associations with. But when you have refined foods, they're calorically dense. And you think of the calories, that's the unconditioned stimulus in like a Pavlovian sense. That's what's driving the learning process. The bigger and more stronger the unconditioned stimulus, the stronger will be the associate of learning process. And so these calorie dense foods is basically like a much bigger US. So it's causing much more rapid and stronger learning of flavor calorie associations. And as a result, we enjoy those flavors and develop cravings for them much more than we would in a normal range of whole foods. Habit learning, here's another thing that's affected by diet. As we learn a skill or a procedure, we tend, we turn that behavior into a habit. Habit learning is great, it's very useful because it allows us to offload and automate daily tasks that we don't wanna have to use our limited attentional resources to always be monitoring. So we wanna do a lot of things on autopilot while we focus on the things that we're goal directed about. And there's a number of studies that have shown that refined foods accelerate and strengthen habit learning. Rats that consume hyper palatable food in binges in particular show faster habit learning than rats eating a control diet. There are more neurons in the brain regions, and this is a human study, there are more neurons in the brain regions that code for value and saliency of food. And this is in an area called the basal ganglia that's involved in habit learning and control of action. And so there are more neurons in that region for in obese than in lean people. So obese people haven't had a shift in the amount of brain tissue and neural processing dedicated to the value, coding for value and saliency of food cues. Another study, obese women acquire habits more quickly than lean women in a laboratory task setting. Another study yet, men with high BMI are associated with stronger habit learning with respect to motivational value of food. So I'm just finding some things in literature and there's more in the literature just like these studies. So the idea from these studies and others is that acceleration in habit learning can interfere with breaking bad habits. You can be stuck in a rut maybe because your habit system is overloaded, is hard to disengage. And then things like mindless eating and susceptibility to food cues can result. Here's another one that's from psychology, delayed discounting. The idea here is that we are able to forego immediate rewards if we value a future outcome even more. So we might avoid the piece of cake now that's presented to us and no, because I'm trying to maintain lean figure or I don't wanna have to run to the toilet or get gut dysbiosis, which I know I'll get if I eat this now. So you're putting off some, you're valuing something in the future more than the immediate reward. But we do discount rewards that are too far in the future or when the immediate reward is too enticing. And so here's an actual study that came out a few years ago looking at delayed discounting functions for both monetary rewards and food rewards in normal weight individuals and obese individuals. And what this is showing is a subjective value of a particular reward, like a monetary item or food item as a function of the number of months in the future that they're expected to get it. So how much would you value $10 right now? How much does it mean to you a month from now or that's the kind of nature of the questions that are asked. And you see, of course, for both kinds of subjects, for everybody, the further in the future some item of reward is, the more you discount its value, its subjective value decreases. But that discounting function is much steeper for obese people than for lean people. So we know that whatever is contributing to obesity is also affecting their ability to apply a subjective value to something in the future, a goal in the future. So this can further dysregulate behavioral control and planning, long-term planning. Another one, learned helplessness. And this is from the work of Martin Seligman and his colleagues. And what this is is a task where an animal, such early work was with dogs, they're placed in what's called a shuttle box. They can jump back and forth over this partition to be in one side or the other.  So if they learn that, they can jump over to the other side and avoid getting the shock. Then they have a few minutes of safety and then the auditory cue comes on again. They have maybe 10 seconds to jump back to avoid the shock. If they don't jump back in time, they get the mild electric shock. No dogs were harmed, they're just annoyed in this study. They use low levels of shock, but enough that it makes them want to jump. But if you previously prevent the dog from jumping, so you put them in one side of the box and you have a barrier so it's completely closed and they can't escape the shock and you expose them to a number of shocks without being able to escape, then you open the barrier, so now they can make an escape or an avoidance response. You see that they're very impaired in learning to make that escape response. And this was a model for studying a phenomenon of learned helplessness that has been discovered clinically in humans where you feel helpless about your situation in life and so you feel like, well, I can't do anything about it anyway, I can't get out of this bad situation, so I'm just gonna give up, not do anything. And that was the reason they developed an animal model to study that process in humans. But really, when you think about the role of yo-yo dieting, then what you see is that when you start a diet, you can stick to it by sheer force of will of calorie restriction, but if you're eating the kinds of foods that are driving you to crave them, usually you end up going off the diet and you gain back that weight and some and then you try a diet again and you see this is that pattern of yo-yo dieting and eventually what I think is people learn that they're helpless to control their own weight with the standard conventional calorie restriction methods and so I think learned helplessness is really one of the factors that's affecting the phenomenon of people giving up. Overshadowing, I'm gonna try and speed up a little, make sure I have time for Q and A at the end. Overshadowing is a phenomenon discovered by Pavlov, he's studied how dogs associate a cue such as a bell with a reward like food. When multiple cues are present, however, then the dogs will tend to learn only an association between the most salient or the loudest or brightest cue with the food and that learning, so really loud sound will be associated with the food and it'll overshadow a quieter sound so they won't learn about the other one. Well, I think that when we're eating a diet of healthy flavors and refined foods, refined foods are so potent in their saliency of their flavors, I think the flavor calorie associations I was talking about, you can get overshadowing possibly, these are, some of these are hypothetical, overshadowing of learning associations between normal, healthy foods and their calories, so that flavor calorie learning, if you're also at the same time consuming hyperpalatable food, so maybe overshadowing is possibly playing a role in this phenomenon and I think this is very important to understand for children, not exposing them to these hyperpalatable foods too early because that might prevent them from ever learning that the more whole foods are nutritious or tasty, really. Counter conditioning, who enjoys the flavors of these monstrosities? Yes, I've been there, in a way I could still imagine I would like to put this in my mouth and think that that tastes good. Now, the very first time somebody encounters one of these foods, it probably doesn't taste that great, it's overly sweet, but also there's these, a lot of the additives and stuff don't actually naturally taste good, in fact, Starburst, I've never liked Starburst, I'm more of an M&M's guy. And they say so, it's plasticky tasting and I think that a lot of people might, when they're young kids and first exposed to these things, I think the very first exposure maybe, you wouldn't like that taste normally, but because there's so much sugar along there that it's causing some kind of counter conditioning, you're associating these bad tastes with the sugar, which provides a caloric increase and a very quick one, a rush of dopamine and so, which is involved in reward processing, I think that you associate these bad flavors with the good outcome and you then counter condition them. So now you start to like those flavors. Finally, sensory adaptation and habituation, you've all experienced jumping into a cold lake, the first moment is bracing and it's cold, but very quickly your skin cells adapt as a sensory organ, so you feel less cold. And also, if you hear a ticking of a clock, you get a new clock and it's really loud, but over time you kind of filter it out, that's kind of, you habituated, you learn to tune that out. Those are two related types of learning processes or learning and behavioral control processes. Well, sensory adaptation is to sweetness in our diet. If you're eating a high-sweet diet, you might actually be down-regulating the taste receptors that are able to taste sweetness and here's a study that showed this back in the late 70s. Subjects, human subjects were exposed to sodas with either high or low sweetness or a mixture of both. Then after they had some exposure with the high or lower mixed sweetness sodas, they were given a range of sodas that they ranged in sweetness from low sweetness to high sweetness concentration and they were asked then to rate how sweet is it and you see the people that had been pre-exposed to high sweetness, they're less able to judge how sweet, or they judge those high-sweet sodas as being less sweet.  That's kind of the point here. Also habituation, we all get used to the, oh that lower back pain I have or every time I take the steps I get a creak in my left knee, true, it started happening a year ago for me. You know, we habituate to these things and we kind of have to tune them out in order to kind of get by in life. I think we forget sometimes because we're habituating to the feelings of unwellness to what it felt like to thrive. Okay, I know I'm kind of getting close to my Q&A time, but I wanna quickly go over the message of hope. Despite these problems, there's a lot of hope that we have. So now I'm just starting the Q&A period. I'm gonna try and stick to five minutes. Pavlov showed that dogs that salivate when the bell predicts food, but he also showed that if you then present the bell by itself a number of times, they stop salivating. That is, you can extinguish the salivation response. So I know I've extinguished quite a bit of the sounds of a rustling sound of the opening a bag of chips or the seeing these cues or smelling cues that had previously I had associated with good things because I've abstained from them for a long time and seeing the cues without actually imbibing. I've extinguished some of those associations. So that's one of the hopes that you can actually take back into your hands. My late friend and collaborator Seth Roberts had done some really groundbreaking work applying Pavlovian conditioning principles. I won't go into the details of the theory. It's based on Pavlovian conditioning principles and to be able to break your body fat set point. So if you think of body fat as or adiposity as something that your body is regulating as a homeostatic system, then if you wanna lower your body fat set point, then that will reduce hunger and you will then lose weight naturally from that. And he's got lots of data from subjects that have participated online with doing this. For example, consuming some extra light olive oil or I've tried it with refined coconut oil which is very low in flavor is like giving yourself an unconditioned stimulus without a CS. And what that does is that also like extinction I could break the CS, US association, these kind of Pavlovian associations and it seems to be a very effective method of reducing hunger. Reward devaluation. This is what I've put in practice myself and it really works. A rat learns to press lever for a sugar pellet. If the sugar pellet is then, if they then eat the sugar pellet and get an upset stomach, they will no longer want to eat the sugar pellet. This is called a conditioned taste aversion. This is one way of devaluing the original value of a food. And I've done it not through inducing stomach upset but mentally thinking, oh, this is not good. This is really bad for me and I'm gonna make myself sick. And I've kind of be able to mentally create my own devaluation of hyperpalatable foods, refined foods. And related to that, very closely related to that, is this idea of equivalence class formation. When we look at the world, we don't just see a bunch of random objects. We kind of classify things as chairs. There are people, there are lights and we kind of group things in the categories for classes of objects. Well, we're typically, the typical person will think of these kind of refined foods as in the class of maybe not necessarily healthy but definitely edible things. Well, I switched and I said, nope, that's the wrong class. That's the class that this belongs to, inedible and toxic ingredients. So now, when I go to a coffee shop, I realize I'm just there for coffee.   Remember that, coffee shops sell coffee. That's all you should be getting there. You can also cultivate no eating habits by consistently training yourself to avoid, when you see something, you say, I'm just not gonna do it today. And then the next day you say, oh, all right, I'm just gonna avoid taking it for another day. And it's kind of the way it works with alcoholics too. You just day by day, you train in a habit of saying no to something that you previously really wanted and choose something else instead. You can eventually establish a habit that will replace your old ones. So this does take more work but it has a long-term payoff of being sustainable.  These will be online anyway. But I wanna point you to the work that Brian Wansink at Cornell University and other people have been doing showing that how we can take control over our eating, mindful eating practices.  Social support is very important. You're not alone. Surround yourself with people that support the kind of choices you're making. Seek out a community. I know one in particular that's really good. And that help support your goals. And the final thing, wait one more slide after this, the final thing is to redefine yourself. And this is what I've done.   I won't go beyond that because I don't want TMI. Transform yourself. I'm not that person anymore. I am now this other person. Don't be a slave to the old you but be a vibrant, healthy person not controlled by the food. So become the one at the party that never touches the cookies or never drinks the soda and define yourself in that and fall in love with that. Just to bring all the way back to the rat research I've done, even in my rat research I found that if we get the rats, well we force them, they don't choose this, to after they've been on a refined diet for like nine months, we now put them only on the control diet for five weeks. Okay, so that's all they have access to now is now they were obese on the refined food, now they're eating the control diet. Then we test them on that motivation task, right? Progressively increasing the amount of work to get each reinforcer here and we see that they recover their motivation. So you can change yourself and if a rat can do it, so can you. Thanks. That was the best take home ever. So again, we have maybe time for two questions. I'm going to exert my chair's privilege again. So one of the things that you know, bloggers, right? Our job here is to help motivate people to actually dedicate an amount of time to Rob's whole thing of try it for 30 days, right? See how you look, feel and perform. How does this research inform a challenge, right? So you're challenging somebody to ditch all of these foods that are really messing with their ability to have a healthy relationship with food. So you're gonna say, I want you to go without these foods for X period of time. How can we refine those challenges to increase success? So you don't have the people who are jumping on a 30 day challenge and then falling back face first into a gallon of ice cream, not talking from personal experience at all there. But how can you use this research to improve the success rate of people who are starting on that pathway and not falling back into those yo-yo patterns? Yeah, it's a good question. And I think that my answer would be to actually explicitly teach them about these, the last eight, what can you do to take hold and control of your diet? To start actually explicitly making bullet points of those and that people can read and understand and start to work on. Those are actionable steps, I think. Thank you for an excellent presentation. Could we go backwards a few slides to the depression section? Because I wanted to ask for some clarifications. You mentioned magnesium. Oh yeah, this was just from that one paper I have linked here. I don't know how to pronounce it. Zinc, magnesium. Oh, it's not up there. How do you? Okay, in that study they talked about how zinc, magnesium, lithium and chromium are trace minerals that are deficient in people who have anxiety, diagnosed with anxiety and depression disorders. And are they suggesting supplementing lithium? Because I'm not really at all familiar with that. I don't remember the exact details. I think they were just saying that there's a relationship there. I don't remember if they were then advocating supplementation of those in particular. Or do they mention that? I don't know what they, I don't remember what they mentioned. If you want to email me later, and my email should be available, I'll send you the actual PDF of that paper. Okay, and then maybe another quick clarification on the habit formation, or how the habits are, yeah. You're talking about the disruption of habits? Right. So are you primarily talking about negative habits? So for example, Just habits in general. So maybe somebody who's obese if they have sped up habit learning, maybe they'll actually acquire the good habits more quickly. Possibly. By eating refined foods. What I did was I pulled out, well no, I mean the refined foods led them to a state. They're now in a phenotypic state where they more rapidly, at least according to research, can more rapidly acquire habits. They shift from doing something by knowing about the goal to doing it kind of on autopilot. That shift happens more quickly. So there's two different parts of the basal ganglia system I won't go into, but they that are involved with this transition. And they're shifting from one to the other more quickly is the idea. That's what I'm saying. Okay, so as far as acquiring new healthy habits, what does that suggest in terms of diet? Good, well there's hypotheses, one could test that could they then, if they then gave up those foods, that was the habit they were trying to train in. Would they be at an advantage compared to somebody who eats junk food but wasn't obese and didn't show an impaired habit learning? Would they have an advantage in actually acquiring a quicker habit to reject junk foods? Okay, thank you. Good question.


So hi everyone, I'm Henrik, and with me on stage today is Christian, and as I already said we're going to talk about how we integrated a lot of Kubeflow components in an end-to-end workflow, and we brought a nice example which is a anomaly detection model training pipeline where we use data from the International Space Station, so deep learning and rocket science and buzzwords is top. Right, but before we dive in, let me say two words for myself, so I'm Henrik, I call myself a data scientist, and I'm doing, actually I'm trying to finish my PhD on machine learning for cyber-physical systems, so that's where the ISS also comes in. And I used to be a data science consultant with a background in engineering, and now I turned into a Kubeflow enthusiast I would say, and with this I hand over to Christian. Thank you. So I consider myself nowadays like a data engineer or data jack of all trades and master of none used to be a physicist, and nowadays I'm mostly involved in building platforms based on Kubernetes, but also in this use case we're going to talk about a bit. Actually we're here only as representatives of a bit larger group, we actually also wrote a paper about what we're presenting today, which actually got published this morning I think, and those people all were involved in that, but also those are only like representatives of a bit larger project, which is called the KISS project. We also talked last year at KubeCon about that a bit, about the platform that we built for that, but today is going to be especially about that anomaly detection. And so just to give you a very first quick overview, this project, as mentioned already several times, uses data from the ISS, and on that we do anomaly detection, so detecting if something's wrong up there, and then do diagnostics and even reconfiguration to bring it back into a safe state. And that project is funded by the German state and also the European Union, and you see that also two universities and Airbus and just at AI and ProCube are involved in that. So what will we be talking about today? First, I'm going to give you a bit higher level overview of our use case, and then we're going to talk about what parts of Kubeflow and also wider ecosystems, so not only Kubeflow, but some other tools we are using and for what purpose, and especially how they all fit together. And with that, share some challenges, solutions we found, tips and tricks. But also, there's some things we won't be talking about, so if you're here because you're really interested in the ISS, I'm sorry, we won't really be talking about that at all. Also, not scientific methods, results, anomaly detection or anything like that. But the good news for that part is if you're interested, check the references in the end of our talk. So now on to the high level overview of that use case. So we have time series data coming in from the ISS and then do anomaly detection on that. If we found some anomalies, we're doing a root cause analysis for that, then a reconfiguration and finally like a supervision, which just makes sure that any reconfigurations we calculate aren't doing anything dangerous. And the setup in general is that we have like dashboards built into that, which load the data from there, and then spacecraft engineers can look at that and decide if that's like a good thing to do or not. We're using Kafka to tie all of that together, have some Postgres databases and so on, but also we're not talking about that today, but instead mostly we're going to talk about this neural network machine learning model, which is only used for the anomaly detection and especially how we end up there. All the other parts use symbolic AI. We also use case of with custom transformers and predictors for that. But as said, we're talking now about how do we get to that part. And we face some pretty standard challenges for that actually, I would say, like we want to do distributed pre-processing because we have quite a lot of data. We want to train a model, do hyperparameter search, want to deploy our model. We have multi GPU model training that we want to do. We want to do inference on streaming data. And finally we want some pipelines to tie all of that together. And luckily, Kubeflow has us covered here. So we have Kubeflow pipelines on the far right for, well, tying it all together. We use case of the training operator, Catab, and then also not really part of Kubeflow, but we still like it, dusk for the distributed pre-processing. And so how does KFP allow doing all of this end-to-end? So what we want to do here is distributed pre-processing, then hyperparameter tuning with multi GPU model training, and finally deploy all of that. And well, if we stand here, you also already know what the answer is. Yes, that's totally possible with Kubeflow pipelines. And now we're going to dive into a bit more detail, how this looks for what we're doing here. So here on the left part, you see that duck we are using here. Actually, all of that code you can have a look at under that GitHub address on the web. But a quick note, this is not really like our production code. We clean this up quite a bit to make it easier, digestible, and understandable to make it easier for reuse and use as a template for similar setups. And as a first note, we use KFP version two only, which we think is a lot nicer than KFP one, but has some issues. And especially because we're using that with the open source back end only and things like parallelization, for example, don't work as nicely there. But some general notes, so we use a mix of lightweight components and container components. And for, well, at the top here, so perhaps a quick note for that duck. I quickly want to get that laser pointer working. So pretty standard, really, mostly what you expect. At the top, we have data pre-processing. In the middle, we have like model training. And at the bottom, we have evaluations somewhere here and like serving at the bottom left. So at the top, we use parallelization also for some pre-processing steps. And at the bottom, then, we automatically deploy if some metrics are better than a given threshold and so on. For those container components, we use one single image, which has multiple entry points. So you can see they're used like more or less all over. But we're going to see that in more details in a minute. And then finally, Dask already mentioned that. We're using the Dask operator and also a cube cluster to make the best use of Dask. But also, Henrik is going to show you some more of that in a minute. And then finally, we use the Python Kubernetes API and Minio to tie Catep PyTorch operator in case you serve into all of that. And we're going to have a look at that in details now as well. Thank you very much, Christian. Now that we know how our pipeline looks like on a high level and we know what our core feature implementation features are, I'd like to use the rest of our talk, which is 10 minutes or so, to highlight a few of those details. And the first one is that we actually use, as Christian said, only one image with multiple entry points. For example, in all our container components for KFP. But we actually not only use them for the container components, but everywhere where we need custom images, which is Catep training trials, those Dask workers, but also PyTorch trainings, distributed ones, and even for a case of for the custom predictors and transformers. So that means if you have a look at our repository, you will only find one single Docker file. And it looks like this. It's not very exciting. We start off from a rather large base image, which holds Python and PyTorch, but also those CUDA drivers to do deep learning. And since we only need one image, we can also treat all the functionality that we implemented in Python as one large Python project, where we manage our dependencies using poetry. Now the rest is pretty default, but then the question is now, how do we make multiple entry points of this? And somewhere in the image, we have this main.py file, which is the main entry point. And we have a lot of functions there that we use to create the KFP components. And this is one of the examples of the functions, which is called Dask run preprocessing, sorry, run Dask preprocessing. And the function actually does exactly what it's promising. In order to create a CLI, we use click. And this is where the different entry points come in. We can use different arguments to this click.command method, such that when we run Python and then main.py and say run Dask preprocessing, then we actually enter this function. Now, if we want to create a component out of this, as you might already know, we just, in a different file, in this case, we call it components.py, we define all our components. And if we use this decorator, we actually just need to specify three things, the image, the command and the arguments. As I said, the image is always the same and we start somewhere in our configuration. The command is Python and then the path to the main.py file and the first argument specified which function within this main.py file to run. So this is pretty handy, but it also allows us, just like any other container components, to run the code locally. So if I pull the repository and then run poetry install, I can actually, on my local machine, run something like poetry run Python and then the main.py file again with the corresponding arguments. I just need to download the corresponding files of the previous tasks in the pipeline such that I can locally debug. And it turns out this really speeds up our development process compared to, like this, as a data scientist, I can debug like any other Python project compared to building a new image, pushing it to the registry and then running the pipeline again. So this is great and the second thing I'd like to highlight is that we, from within Qflow pipeline lightweight components, we make use of the Python Kubernetes API to actually talk to the external services such as kserve or cut-tip. Now how does this work? Let's have a look at the cut-tip example. So this is our code. Again, we are looking at the components.py file where we define a different component. In this case, the run cut-tip experiment component, which as you see from the decorator is a lightweight component, which means we can install packages using these packages to install argument. And you see we install Kubernetes, which is the key point here. Log guru is just for logging. And if you've seen a cut-tip experiment manifest, you know there's a lot to specify. For example, what code to run in each cut-tip trial. This is what we specify here. So, and this should look familiar to you already. We again run Python and then the main.py file. But in this case, not run does preprocessing, but run training. But we use the same image again. There are a lot of other options we need to specify to get a comprehensive cut-tip experiment. And instead of creating a YAML manifest, we use this Python dictionary. At the end of the day, we store every of those components, of those configurations in this dictionary. Then we create a Kubernetes client using the in cluster configuration. And we eventually actually start the experiment. This create namespace object such that we have a cut-tip experiment running. We then check like in a while loop every minute how the response looks like. And eventually it hopefully changes its status from running to succeed it. And in that case, we can get the ideal hyper parameters from the response of the Kubernetes client. And in that case, this is then the output of the lightweight component and it returns a dictionary that holds the optimal hyper parameters of our experiment. So far so good that didn't look too difficult. So what's the big deal? Well, it turns out it's more challenging than we initially thought because we are leaving the comfort of Kubeflow Pipelines IO features. So let's have a look at that. Usually in a pipeline like visualized here on the left-hand side, we have different tasks in a deck. Each task, as you probably know, is executed as a pot. And Kubeflow is great because it stores the outputs of the first task and MinIO and takes care of copying it to the second task. So we don't have to take care of that as a data scientist. However, if we do something fancy like integrating a desk operator that spins up a whole bunch of pots, worker pots, and a scheduler pot, all of those workers won't have access to the data that Kubeflow usually copies inside the pots. So that's bad news. Same holds for the cut-up tray. The KFP component used earlier, the lightweight components uses this experiment controller and the trial controller. And each trial actually then uses a Kubernetes drop, in our case, or even a PyTorch drop or a Argo workflow. Eventually, in any case, you end up with a pot that is supposed to run your training code. But also here, Kubeflow doesn't take care of copying data in there. Lastly, for the PyTorch cluster, that's also the case. It spins up a whole lot of workers. And in our case, we use four GPUs for our model training with PyTorch distributed parallel here, DDP, which then internally use ring all reduce in order to average the weights in an efficient way. But also those worker pots, they obviously need access to the training data and the validation data, and they wouldn't if we didn't take care of it. So that's the workaround. We need a workaround. And our workaround basically holds three steps. And let's have a look at the cut-up experiment again. So the first thing we do is basically get the Minio path or the artifacts to the data in Minio. It's a bit hacky, but what we do is we look inside the component and we have this data frame for training and validation data. And those Python objects, they are of type input and data set, and they have this dot path attribute, which holds the path to the data inside of the keep float pipeline task, which happens to also hold the information to the artifact in Minio. So we know where the data lives in Minio. Second thing we do is we inject the Minio credentials from the corresponding secret into the environment of the running pot, whether it is a PyTorch training worker or a desk worker or whatever it is. And lastly, we implement a custom function which lives inside our image that is actually capable of reading from and writing to Minio. And if you wonder why it looks so messy here, it's the case because the path from Minio actually looks different depending on whether you copy it from Minio directly or from the pipeline UI or in the setup that we just shown. Right, so problem solved. And doing this, we were actually able to integrate all of the tools we mentioned into one single keep float pipeline's workflow. And thus, this leads me to our last slide. So if you would like to remember anything from today, from what we told you, we would like you to remember two things. First, yes, it is actually possible to integrate all the tools mentioned, which is desk, cut-up and PyTorch jobs into one single keep float pipeline. However, it does still require some hacks. And second, it really shortens the debug loop if you are able to run your component code locally. We would highly recommend that. We'd be really glad if you rated our talk. QR code is listed here. And in case you are interested in more details of the implementation, check out our GitHub repository for this project. And maybe also the papers we wrote about related stuff. So there you will also find information about the ISS and more on the machine learning side of things. So, questions? Thank you for the great talk, very exciting. So I'm just wondering, you've been using the pure Kubernetes Python client to for your keep float pipeline's components for KT or for desk. So did you try to look for our upstream SDK, Python SDK to simplify your components and not maintaining this part by itself? So we did a few little commits and pull request. Actually, is it more than one? I'm not sure. But we did actually write issues. And for whatever we found, so we try to come contribute as good as we can. And we will continue doing that. That's great to hear. Because I think we should work with you together to understand the downside of using this as part of keep float pipelines because they're a huge task to use this SDK inside as exactly what you show on the flow, right? And so maybe we can collaborate with you to improve upstream SDK better. We'd love to do that. Thank you. Yeah, I do have one question myself, which is for integration with Dask. Because we have in the hiring physics community, Dask is quite popular. The integration has been done in different levels from Jupyter Lab directly with the extensions and everything. What's your experience of the integration of Dask with the flow as well? You mentioned a few things, but yeah. So that was pretty seamlessly, I have to say. So once I found this, we found this keep flow. I think it's cube cluster object and the operator. It was pretty easy aid to use Dask from within notebooks for exploration stuff. And also reading and writing from and to Minio work rate. With this integration into pipeline, it was a bit more tricky because of the issue I talked about. Other than that is what was great. One issue I just, it just pops up. I think in the default keep flow version, it wasn't easy for us to get this. I think it's also a Dask component that allows you to run the Dask dashboard inside keep flow notebooks. We didn't spend a lot of time, but we didn't get that running. So we always use Power Forwarding to see what's going on in Dask. Okay, thank you. Yeah, sorry about the Dask. I'm just wondering, so how do you exchange data between your Dask workloads and the other part of pipeline today? I didn't get the first bit. How did you exchange your data basically? Are you using S3 or any like an envelope storage to exchange your data between workloads? Yeah, so we have Minio running. And we actually, in the pipeline, we do a lot of pre-processing to split up large parquet files such that we have nice chunks that we can work on with Dask. And then Dask reads those partitions directly. Does that answer the question? Yeah, and then how do you use this part of data in your training workloads? Just fetching them from some blob storage, right? So, yeah, well, we use Dask and it is really the way to come up with a smaller aggregated dataset that we use for training. And that we can handle using pandas. I see, so that's a lot of features, right? I see, yeah, thank you. Yeah, regarding the Dask dashboard, you can clearly integrate that into the pipeline. You can also do it with TensorBoards and any other kind of web application. You can have a pipeline step and you click start and you get that easily redirected within the Kubeflow UI to the Dask dashboard. So if you want, please reach out. Yeah, I will definitely do. That sounds exciting. I'll do as well. All right, any other question? Still have a bit of time? If not, let's thank again. This was a really nice talk. Thank you very much.


This is ESL 137-001, a part of the Norma Galaxy cluster. The image not only captures the galaxy and its backdrop in stunning detail, but also includes intense blue streaks streaming outwards from the galaxy, seen shining brightly in ultraviolet light. These streaks are actually hot young stars encased in wispy streams of gas that are being torn away from the galaxy by its surroundings as it moves through the Norma cluster. This violent galactic star extraction is due to a process known as ram pressure stripping, a drag force felt by an object moving through a fluid. The fluid in question here is superheated gas that exists at the center of galaxy clusters.


Interpol is a truly global organization working to turn back crime. The journey began 100 years ago. In 1914 at the first International Criminal Police Congress in Monaco, an idea was born. If police could cooperate internationally, the world would be safer. Plans were interrupted by the First World War, but in 1923, Interpol was officially created in Vienna by 20 countries. Special units were set up to handle fingerprints, drugs, fugitives, fake money and forged passports. These remain core activities today. To facilitate cooperation, each member country agreed to establish an Interpol office known today as a National Central Bureau. In 1935, an independent radio network gave police a private communications channel. But with the advent of the Second World War, the organization ceased to function. After the war, Interpol started rebuilding with a new headquarters in Paris and created its emblematic tool, the red notice. To alert member countries to wanted persons, red notices are vital for tracking down international fugitives and were the first in a color-coded series of alerts. Interpol's membership grew steadily as more countries saw the need for police cooperation. Cooperation with the United Nations goes from strength to strength. UN recognition in 1971 reinforced Interpol status, while the organization's role in combating terrorism is highlighted through a joint Interpol UN special notice created in 2005 and a UN Security Council resolution from 2014. In 1982, a special commission was set up to ensure the organization's processing of data respected the rights of individuals. In 1989, Interpol relocated its General Secretariat headquarters from Paris to Lyon and went on to open seven regional bureaus as well as representative offices at the United Nations and the European Union. The terrorist attacks of 9-11 marked a new era of terrorism and a turning point for Interpol. In response, a command and coordination center was open to provide round-the-clock support to member countries, while a global communication system called I-247 allowed police to exchange messages securely and to access Interpol's databases in real time. A database of stolen and lost travel documents was also created, helping to detect criminals trying to cross borders. Databases are at the heart of Interpol's work, holding records on stolen items from vehicles to works of art and crime data such as fingerprints and DNA profiles. From this time, Interpol became more operational, deploying response teams to assist national police forces in the field. Law enforcement operations target the wide range of crimes the organization is actively fighting today. Crimes against children, trafficking in human beings, counterfeit goods, illicit medicines, drugs, environmental crime, tracking down fugitives and more. Interpol now has 190 member countries, all committed to making the world a safer place. But crimes keep evolving and today's new threat is cyber crime. The Interpol Global Complex for Innovation in Singapore will better support the world's police in tackling the challenges that lie ahead. Fighting crime could be much more effective if the world's citizens could play a part. The Turnback Crime Campaign aims to make this a reality as Interpol looks to the future.


Australasian Fresh began in 1993 with a vision to transform pasta manufacturing. The expansion of the company has seen significant investment in workforce development, the incorporation of Toyota lean production processes and improved waste management systems. Australasian Fresh has collaborated with Victoria University's Advanced Food Systems Institute to further enhance the safety and quality standards of their products. From their site in Tottenham, the company exports to international markets, including Korea, Malaysia, Singapore and Hong Kong.


The DuPont Company of Wilmington, Delaware, makers of better things for better living through chemistry, presents the Cavalcade of America. Tonight's star, Charles Boyer. Tonight's DuPont Cavalcade is called The Grand Design and begins in the year 1791. Charles Boyer stars in the role of Major Pierre-Charles L'Enfant, a Parisian by birth, an artist by inheritance and training, a soldier by force of circumstance. This is his story. I remember the day it began. I had received a summons from the man I respected above all of the man living, a soldier in whose service I had fought through the war of revolution, President George Washington. At Philadelphia I was ushered into the President's study. Well, Major L'Enfant, this is indeed a pleasure and an honor, sir, for me. It's rather a coincidence, too, you're arriving at just this moment. I'd been going through some old papers this morning and not five minutes past I found this. Your pencil portrait of me, Major, made in winter quarters, twelve years ago. A dreadful winter. Dreadful indeed. Well, as I recall, General, well, I prolonged the sittings beyond all necessity.  So I drew and drew and baked my chili bones. Yes, yes. Perhaps that accounts for the felicity of your drawing. Major. Yes, General? You've heard about the dispute concerning the location of our national capital. Oh, of course. But when I left New York, sir, a settlement was rumored, no? A compromise has been accomplished, yes. We shall start afresh and build a new city. People rise not fifteen miles from my own home on the banks of the Potomac. Major, you begin to suspect why I've required you to come to Philadelphia? You... General Washington, I would give my right arm, my life itself, if I could be chosen to draw the plans for that new city. No such sacrifice will be required, Major. The commission is yours. Well, Major. Well, sir, I'm overwhelmed, but it's so hard to believe that I, a Frenchman with few friends with no influence, that I should be chosen. You have been chosen because I believe you are best fitted for the task. And because I remember a long ago winter, you have been one of us since Valley Forge. The President warned me. I cannot say I had no hint at all of what was to come. There would be difficulties of a practical nature. Well, the practical difficulties began with purchase of the land. At a meeting house in Georgetown, President Washington addressed the owners of the ten-mile-square block of brushwood wilderness chosen for the new capital. And so, gentlemen, if I may recapitulate, the Congress will pay each owner 25 pounds per acre for his land. Surveyors under Major Lanfond and Captain Robert Dau are now engaged in dividing the tract into city lots. Half of these lots will be sold at public auction. The proceeds going into the national treasury. But you landholders will retain ownership in every other lot in the new city. But lots will remain your own property. In return for this generous offer, the Congress and the commissioners advance but one stipulation. No payment will be made to you for the relatively small amount of land needed for roads or for avenues and streets. Well, I trust I have made myself clear. Mr. Shortliff, will we put the matter to a vote? And the vote was carried. But after the meeting, a small group of landowners led by one Mr. Burnham met in a nearby tavern by chance my assistant, Isaac Roberto, occupied a nearby table. Mr. Burnham was more talkative than he had appeared earlier in the evening in the public meeting. Ah, if only they hadn't popped the thing upon us so sudden like why we could have made our eternal fortunes. By holding them up? You may call it that, I say, by getting our just desserts and it can still be done. Oh, what do you mean? Ah, you're interested, eh? Well, it's as plain as the nose on your face. Now, listen, it'll be years and years before all of the capital district lots will be worth real money. But some of them, some of them, some of those lots they're going to auction off, eh, the man who knew which lots to buy in. Oh, yes, he could sell them again for, for thousands. But that's only for the right lots, the ones right spang next to the big public buildings, the capital, the president's palace, the treasury, so on. Now, who knows where those buildings are going to go up? Who knows, eh? The Frenchman, what's his name? Longfong. He's our man. If he'd show us his plan, why we could afford to let him in on the venture. What venture? Burnham, you can count me out of this. I'm satisfied with the payment as it is, so are most of us. Good night to you, Burnham. Ah, good old Billings always want to have his joke. A bit of a stuck up Nambi-Pambi, too, I'd say. Don't care, Burnham.  But it would take money, a lot of money to swing this sort of thing. I haven't got it. You haven't got it. So... Wait a minute. Wait a minute. Ever hear of Daniel Carrill of Duttington? Of course. The richest man in the district. Ah, but not rich enough, not as Daniel sees it. And Daniel's uncle is on the Congressional Commission. Now, Daniel, he's a friend of mine, and I think, I just think mine, you're... I think he'd be interested. Oh, yes. I think he'd be interested, indeed. By day I work with the surveyors, and by night, often all through the night, I sleep at my drafting board. No eyes save mine beheld the master plan. No mine but my own as yet knew the grandeur of my conception. At last, when the design was completed, I placed it before my friend, Roberto. Major, it is magnificent, magnificent. Now, now, wait. Look, you understand the principal design, the capital building here on what they call Jenkins Hill, then this great avenue leading to the Palace of the President. Yes. Fountains here, and here, with a great cascade between. Beautiful. What's all about these great circles, monumented with avenues connecting them, like the spokes of a wheel. A city of vistas. More beautiful than the earthen of Pericles, more stately than Augustan Rome. Huh? You do not think so? Oh, yes, yes. No city so fine has ever been built upon this earth. But Pierre. What, my friend? Will these people understand it? It is people who make a city not artists. Oh, my dear Roberto, these people, these Americans, they are chosen for a destiny of incomparable majesty and power. My city is the city of the future, freedom's home, the home of liberty under order. Perhaps, but here and now, look again at the plant here. This grand avenue, 400 feet wide, 400 feet, Pierre, and these radiating thoroughfares with their great circles. Each square inch of that land comes out of the pockets of the original owners. What will the owners say to that? I am confident that General Washington will persuade them to act with generosity and simple patriotism. Well, it is possible. For your sake, Major, I hope it is possible. Who is that? Come in. Good afternoon, gentlemen. Major, it's Burnham. Who the man I told you about? Major Laffar, I believe. Yes. My name is Laffon. And mine is Burnham. Gentlemen, I represent a group of patriotic citizens interested in investing funds in the new city lots to be sold at auction. Well... Yes, Mr. Burnham, continue. Well, naturally, we wish to see the plan of the city. And I have been deputized. The plan is not available to you, Mr. Burnham, nor to any other avaricious speculator. Avery? Now, see here, Major Laffar, the people I represent are great admirers of yours. Purely as a gesture of friendship and admiration, sir, purely as a gesture, we are prepared to tend to you a tenth share in our capital venture. Now, of course, as your associate, we, well, naturally as your friends, we would be entitled to see the plan. Get out, Mr. Burnham. What?  Now, you lucky here, Frenchie. Nobody's going to buy that public land without they see the plan first.  And what's more, we don't like interfering foreigners. And let me tell you this, my friends are powerful, powerful in the right places, and we... Captain Roberto. Yes, sir? Kindly sees this... What? This carry-on crow by the seat of his britches and throw him out of my office. Well, you're nearly... You can't do this. I know. Whether or not, Daniel Carroll of Duttington was one of the powerful friends of Mr. Burnham, and he found out for his certainty. But a week after Burnham's visit, Mr. Carroll began to build a house. And Mr. Carroll built this house directly across the land I had intended as one of my main avenues, blocking a majestic vista. I acted at once. Well, here, here. What is the meaning of this? Major L'Enfant, what are these men doing on my property? What are these, these, these strange engines? Spattering rams, Mr. Carroll. What? You're not going to.  I'm going to level it to the ground. Yeah, what right have you to take such action on what authority? On the authority of President Washington and the Congress of the United States. I happen to know you have had no such instructions from your superiors. Now, if you would let me see your plans... No one sees my plans. But until the lots are sold. You must be mad. L'Enfant, my uncle is a member of the Congressional Commission. If you commit this outrage, I'll see to it that you were dismissed and disgraced. You may try if you wish, Mr. Carroll, but the house comes down. Captain Roberto. Yes, Major. You will instruct the workman to begin demolition. Yeah, my friend. Are you sure you wish to take this step? There'll be no turning back. I'm not accustomed to turn back. Give the orders, Captain. Daniel Carroll and Mr. Burnham had plenty of company. Soon the Congressional Commission for the new federal district was under siege by hundreds of aspiring land speculators. Pressure to release my plan before the sale of lots reached a crescendo. And then I received a letter from President Washington. He wrote in part, your actions have come to my attention. In future, I must strictly enjoy you to touch no man's property without his consent or the previous order of the commissioners. Having only the beauty and regularity of your plan in view, you pursue it as if every person or thing were obliged to yield to it. At your earliest convenience, my dear L'Enfant, will you please call upon me at Philadelphia? You are listening to the Cavalcade of America starring Charles Boyer in the Grand Design sponsored by the DuPont Company, makers of better things for better living through chemistry. Among DuPont's better things for better living is DuPont neoprene rubber used for many products and in a wide variety of ways. Recently, we heard of another interesting use of neoprene. A California couple developed a new household tool for polishing silverware. They used a block of DuPont neoprene because it is resistant to the oils and chemicals in silver polish and because it contains no sulfur which discolors silverware. In the block of DuPont neoprene, there are places for knives, forks and spoons in which the silver polish is put and the utensils rubbed back and forth. This unique use of DuPont neoprene is another example of how many new businesses have started with the help of the DuPont Company's better things for better living through chemistry. The Cavalcade continues starring Charles Boyer as Major Pierre Charles L'Enfant, soldier, artist, builder, telling the story of the great work of his life, the plan for the capital city of Washington, D.C. In answer to General Washington's letter requesting me to call upon him, I set forth for Philadelphia and met with the president in his study. Major, may I congratulate you upon your design. You've fully justified my choice. In fact, you've exceeded my fondest hopes. Thank you, Mr. President. But in other ways, Major, you have, I'm very much afraid, acted in, well, in a rash manner. I should like to hear the reasons for your action, sir. Why, sir, they are most simple. If this horde of speculators is permitted to see the plan of my city, there will be no city worthy of the name. Loss would be sold and houses would be built only upon land adjacent to the public buildings. A cluster of taverns and boarding houses will spring up about a varied temples of government. In between wilderness, my plan will be utterly defeated. My friend, unless your plan is displayed, there will be no city at all. Better no city at all than the hideous shambles of the city. I cannot agree with you, Major. Nor do I foresee consequences quite so horrible as you imagine. I fear we must compromise in this instance. As a klutzman, sir, I never compromise. As an administrator, Major, I often must, though I understand. I understand and I sympathize. But I too have cherished grand designs, Major, and I've seen men tear them down. I've tried to create a beautiful city. I cannot see it destroyed. Let me tell you this. The victory of our arms, Major, the very victory at Yorktown came as a result of compromise. Perhaps you did not know that. No, I did not, sir. Your general Roshambo had arrived with a French army at Newport in Rhode Island. It was my plan, my cherished plan, to join our forces with his at the Hudson River and descend upon the British in New York. But Roshambo urged instead a march far into the south against Cornwallis. He was supported by the French ambassador and the admiral of the French fleet. I yielded, Major. I gave up my precious design. Victory was the result. Will you not yield? I'm sorry, General, but with the best will in the world, I cannot agree that the situations are a lie. Not exactly, Major. Not exactly. Surely you've learned that life is not a matter of exactitudes. In life there are no straight lines, my friend. Yield but a little, lest you yourself be destroyed. When my city, Mr. President, the lines are straight and clean and pure. Major L'Enfant, it is not your city. It is the people's city, and the people are... are, well, what they are. They are human, fallible, seeing only the present moment. Yet they're worth cherishing above all plans. Major, it is not my custom to plead for obedience. With some men, I should have acted otherwise. But there is genius in your design. I can recognize... Oh, please, please, Mr. President, I'm not a genius, and I claim no privilege of genius. I'm a craftsman, and these greedy, thoughtless people would destroy the work of my hands. Oh, believe me, sir, with all my heart, I wish I could yield. I've prayed for the strength to let my city be destroyed. I cannot do it. Please, believe me, I am most sorry. I must ask that you resign your commission. Sir, you will have my resignation within the hour. You may use my plans, Mr. President, or not. In either event, I shall accept no payment from the Congress. Major, yes, Mr. President? I say, sir, that I envy you. In all my life, I have never been able to afford the luxury of such an action as yours. Had I been honest or merely proud, had I acted with integrity or with a great selfishness, I never then could be quite sure. And it was that uncertainty that made my heartbreak doubly hard to bear. As the years went by, my fortunes ebbed, and the tide ran almost out. In my poor lodgings at Philadelphia... Major, I cannot see you. On the table. Be candle-lighted, Captain Roberto. There. That's better. Major L'Enfant. Yes, sir. I'm a poor spectator, I know. My poor friend. Major, I bring you wonderful news. The Congress has voted you 500 guineas, $2,500 on this new currency, for your services at Washington. I shall not accept it. Not as soon. But, Pierre, they are following your great plan. Major, the outline is there. The spirit is not. All is mad, squalor, and littleness. Major, you need help. Why, you need clothing and food and a decent place to live. Please, please, you must take the money. What is so, Captain? What is so? Can one live with honor of her bread? No, but one can quid the scene with honor. This man is dying, Mr. Dave's. I can do nothing more. Do you know him well? No, I don't think that anyone has ever known him well, Doctor. He wandered to my door a year ago. I've given him shelter, bed, and food here in Maryland for the past year. He asked for you just now. I'll go to him. Somewhere, some time, this poor shell of a man has known greatness. Mr. Diggs. Mr. Diggs. I'm here, sir. I'm here. Listen, listen to me. I made a city once. A great city. A home of freedom. A city of grandeur and light. A city of liberty and order. Mr. Diggs. Mr. Diggs. Yes, I am listening. Never let anyone tell you. Never let anyone tell you dreams. I can hear you. Never let anyone tell you. And freedom cannot exist together. One day, in my city, it will be shown forth how free men can rule themselves with courage and wisdom and gentleness. Mr. Diggs. In the year 1825, Pierre-Charles Lafont died at the home of William Diggs. He was buried there at the foot of a great tree. An inventory of his personal goods and chattels showed that they consisted in three watches, three compasses, some books, a map and a few surveying instruments, the whole being valued at $46. With the help of other architects, the city of Washington grew into the grand design of our national capital. And it came to pass that in 1909, the mortal remains of Pierre-Charles Lafont were removed to Arlington Cemetery. And his monument, a draftsman's table engraved with his city plan was dedicated in 1911 by Elie Huart, Secretary of State. So on this occasion, let us remember one thing. Few men can afford to wait a hundred years to be remembered. It is not a change in Pierre-Charles Lafont that brings us here. It is we who have changed who have just become able to appreciate his work. And our tribute to him should be this. To continue his work. To continue his work until we have truly at last made a city, a nation, a world in which freedom and order may live together in reason, in fortitude, in love. Cablecade players for tonight's story, The Grand Design. And now, Bill Hamilton speaking for the DuPont Company. Once every two years, automotive jobbers from all parts of the country get together at their Automotive Service Industry show. The 1950 meeting is being held this week in Chicago. Just what is an automotive jobber? Well, you might call him a wholesaler of parts and accessories. A supply house between the manufacturer and your local dealer. The jobber stocks thousands of items so that your dealer can supply you at any time. If it were not for these automotive jobbers, you might have to wait weeks for your service man to get a needed part from the manufacturer. We at the DuPont Company have good reason to recognize the valuable services the automotive jobber performs. He is the man who gets our DuPont products into your hands. Products such as Xerone and Xerex antifreeze, Duco and Dulux automobile finishes, and the DuPont number seven line of polishes, radiator cleaners and other automotive chemicals. Alert for every improvement, the jobber delivers these DuPont developments along with those of other manufacturers to your local dealer so that he can serve you better. Chemical science and the DuPont Company contribute much more to the modern automobile than many people realize. In addition to the products the jobber brings you, there are a number that come to you by way of the manufacturer of your car. Cordura viscose rayon tire yarn for long lasting safer tires. Neoprene rubber for ignition wire and radiator and heater hose. Plastic interlayers for safety glass. Nylon for upholstery and seat covers to mention just a few. The automotive service industry show this week in Chicago is another illustration of the way other industries make use of the products of chemistry. It illustrates also how business firms of all kinds and sizes join hands to serve you. How the automotive jobbers help to bring you some of DuPont's better things for better living through chemistry. Next week the DuPont Cavalcade star will be Ronald Reagan. Our play Ulysses in Love tells a heartwarming story of the youthful Ulysses S. Grant and the girl he loved Julia Dent. Be sure to listen. Tonight's DuPont Cavalcade was written by George H. Faulkner. Charles Boyer may soon be seen in the 20th century Fox production, the 13th letter. In support of Mr. Boyer was Stott's Cotsworth in the role of George Washington. Music for the DuPont Cavalcade is composed by Arden Cornwell and conducted by Donald Torres. The program is directed by John Zoller, Mrs. Sy Harris speaking, and reminding you as we approach the holiday season not to forget the Salvation Army Christmas Fund. Your contributions dropped in its kettles. You'll make it possible for the Salvation Army to help others at Christmas time. Give as much as you can. Don't forget, next week, Ronald Reagan. The DuPont Cavalcade of America comes to you from the Velasco Theater in New York and is sponsored by the DuPont Company of Wilmington, Delaware. Makers of better things for better living through chemistry. Have fun with baby snooks. Three times mean good times on NBC.


Hi, so I thought today I would talk about decapsulating a chip, specifically this is a ceramic package chip, and you can tell that it's ceramic because you can click your finger on it and it sounds ceramic as opposed to plastic. It's not as black as the plastic package. It also has this sort of separation in here, and this separation is the adhesive, which is called glass frit. It's some sort of a paste with little glass particles in it that gets melted together when the package gets put together. Also, this is a 5400 series logic chip. This is a TTL chip as opposed to the 7400 series, which is also a TTL chip. However, the 5400 series has a higher temperature range, so it's called automotive grade, or sometimes even mill spec, and they typically come in ceramic packages because ceramic can take more heat, which is going to be an issue for us because we want to use a lot of heat to melt the glass frit and take off the top to get to the dye. I have a bernzomatic torch. This takes map gas. Map is methyl acetylene probodyne. It's a gas that reaches about 2000 centigrade in air. You can just buy this at any Home Depot or Lowe's or whatever. I also have a toolmaker's vise, which is a small, nice little vise, which is completely metal. It's not painted. It's not covered in rubber or plastic that will burn, so that's why I like this little compact vise. I also have this piece of aluminum. It's about 0.3 by 0.6 inches, which is nice because the legs on a small dip package like this are 0.3 inches apart, so you can just fit it under there to provide a base for heating. The larger chips will go on the 0.6 side.  I'm going to try to press it down so that it's nice and pressed up against the aluminum. I guess that's good, so not too tight. I also have a set of pliers that I'm going to use to every so often check the top to see if I can just flip it off. If I can flip it off, that means that the paste is all melted, which means the package has been decapsulated. Here we go. It will probably take about 20 seconds of heat. There is going to be the tip of the flame is going to be about here, and then there's going to be a large flame over here. We're not going to use the tip of the flame, which is the hottest part. We're going to use that sort of outer edge. About 20 seconds of heat should do it maybe, so let's see. There you go. There you have it. That's the die, which you can look at under a microscope, but basically that is how you decapsulate a ceramic chip very quickly and very easily. What happened was when I was taking the chip off with my pliers, because of course it's quite hot now, I dropped it on the concrete floor and it just cracked open. You do have to be pretty careful. You can see that, and there I go, dropping it again. So here, I'll just risk the burns. You can see that on this side, there are actually bond wires coming off of the leads, and those connect up to the die. Those got broken off, which is okay, I don't really care because I don't really care about the functionality of the chip. I just want to get to the die. Luckily the package did not fracture along with the die, so this is still usable, which is nice.