Hey it's Kristen from Six Sister Stuff. Today I'm sharing with you six recipes everyone should be making with their air fryer. So we all know that summer is hot and no one likes to turn on their oven. That is where the air fryer comes in very handy. So I'm showing you six easy things to make that you might not have known you could make in your air fryer and the best part is they're super simple and you don't have to turn on the oven. Now if you want more recipes such as air fryer or instant pot or just any simple recipe make sure you subscribe and push that bell so you don't miss any of my uploads. All right guys let's just jump right in. The first thing I'm making is bacon. Now I love making in the air fryer because you don't get the stinky greasy bacon smell that stays in your house forever and cleanup is a breeze. Go ahead and preheat the oven to 400 degrees. Okay once it's all preheated go ahead and open it up and you can put in your bacon. So we're just going to spread them out. I did cut these in half they used to be a lot bigger just to make my life a little bit easier so we can put in as many as we can. Then we're just going to close it up and cook it. Okay so we're going to push the bacon button. It's going to go for eight minutes go ahead and push start. Okay it's about halfway through. Oh it's looking good. I personally don't think we need to flip it. We're going to let it finish cooking because I like it crispy. Okay our eight minutes is up. Let's see how it looks. Oh it looks great. All right bacon taste test. I love bacon. It is good and the cleanup was so easy. I'm a fan. Huge fan of this. The next recipe is grilled cheese.  This one you can just pop it in. You don't have to worry and it cooks perfectly. So for this recipe I'm using sourdough bread, a little bit of butter that I've melted and some American cheese. All right the first thing I'm going to do is butter one side of my bread. Then I like to add a few pieces of cheese because we like our grilled cheese nice and cheesy. Okay then we're just going to flip on the tops and butter the tops. Then I'm going to use the air fryer lid today for this one. You can use your normal air fryer too and we're just going to put the sandwiches right in.  Okay so we're going to air fry at 360 degrees for just three minutes. All right this is all done. Let's take a look at it. Okay so one side is cooked so we're just going to pull this out real quick so we can flip them. I'm just going to use some tongs. Get in there. Oh nice. Oh it's starting to get nice and cheesy. So we're just going to cook these a little bit longer like three to five minutes. We'll check it in three. All right this should be done. Let's pull it and look at it. Oh yeah it is it is looking good. All right let's just pull these out. That is a good grilled cheese. All right time for the grilled cheese you guys. I'm excited. Here we go. The sourdough. Highly recommend it. The next recipe I'm making is air fryer hot dogs. Now one of you suggested this so I thought I'd give it a try and I like it more than over the fire. It's delicious. So all you need for this one is hot dogs, hot dog buns and I'm adding some cheese to mine.  Okay so you're just going to open up your buns and put them just right in the base of your air fryer and this is where I like to add the cheese. Then you're just going to place this in. Okay so we're going to cook it at 390 for only two minutes because we just want them a little crusty. Okay buns are done. Those are looking so good. Okay we're just going to set these out so we can cook our hot dogs. Okay now it's the hot dog time. I'm just going to stick these all in because my kids will eat them all and my husband and okay me too. All right then we're going to stick these in. Cook them for 390 and then we are going down to just three minutes. Let's check out these hot dogs. Oh those look much better. Then you just add all your favorite toppings. We're just going basic today with some ketchup and mustard. Hey guys, hot dog time. The next recipe I'm making is roasted broccoli. Now this is just not your ordinary broccoli. This is bacon cheesy broccoli which is one of my favorites. So for this recipe you need a pre-cooked bacon. We already cooked it so we're going to use it in this recipe. A little bit of cheese, some broccoli. I like to use garlic salt and a little bit of olive oil. Okay so we're just going to put the broccoli in a bowl right now and add our olive oil. You just want to get the olive oil all around the broccoli because we don't want it to burn. This will help it burn so bad. Then I'm just going to add some garlic salt because it's my favorite with roasted broccoli. Go ahead and mix that all together. Now I'm just going to add my cheese so I have about a half cup of cheese here and then about three pieces of bacon and we're almost ready to cook it. All right let's put it in. Okay so whether you have an air fryer lid or a normal air fryer it's the same time and temperature so we're going to use the air fryer lid right now. So I'm going to put in the little basket that comes with the air fryer lid and then I'm going to just dump in my broccoli mixture. Make sure you want my cheese on the top and you're just going to spread it around a little bit. Okay go ahead and put on your lid. We're going to air fry. We're going to go to 400 degrees and then we want to cook it for about five minutes. Okay let's check on this broccoli. All right let's pull this out. Oh it's looking and smelling so good. Okay time for the taste test. That's good broccoli. All right so for the steak bits we're going to be steak cut up into bite sized pieces then we have minced garlic, salt and pepper, Italian seasoning and some olive oil. Okay so I threw the meat in there just to make life easier then we're going to add two tablespoons of olive oil, about a half teaspoon of salt, about a fourth teaspoon of pepper and then one teaspoon of Italian seasoning. Then we have about three or so cloves of minced garlic. Then we're just going to mix that all together. Okay and we're just going to pour this right into the bottom of the air fryer. Spread it out so it's it's a single layer. Then we're just going to put this in. We're going to push the steak button so that makes it 400 degrees for six minutes. Let's try it out. Okay so we're going to check the inside here. I'm guessing we still have a little ways to go. We want it to be about 145 so we're going to just do these for a little bit longer. Mix them around a little bit. Let's cook these for another three minutes or so and we'll go from there. Okay while that's finishing up we're going to make some yummy butter. I have a fourth cup, a fourth of a cup of melted butter ready to go here. Then we have a half teaspoon of thyme, half teaspoon of rosemary and then a whole teaspoon of parsley and we're just going to mix that up. All right set this aside and we'll check on the steak. Okay this is all done. Let's give this a check. We'll do this dude. Perfect that's looking great. Okay let's dump these out and add the butter. All right and I'm just going to dump. I'm going to mix this all up. Well obviously my dog wants them too but time for sample. There we go. Much better. Much better steak. The last recipe I'm making is homemade air fryer s'mores. Now if you don't have a campfire, you don't want to turn on the hot stove, this is the perfect way to cook a s'more. So all you need for this is some little Hershey's chocolates, marshmallows and graham crackers. So first you just want to take your marshmallows and put them right on top of the graham crackers then these are going to go in the air fryer. All right just placing them very carefully. You don't want the marshmallows to fall. Okay we're ready let's stick this in. Okay so our temperature we're going to go to 390 and then our time we're going to go to five minutes. I like them a little golden brown so that's why we're doing five. Okay let's check these. Oh my word. Okay well that didn't work out as well as I'd planned. Change of plans. We're trying it for two minutes. I couldn't remember how long I had done it before so two minutes is time. All right let's see how it goes. Oh it's hilarious they like wiggle but those look so much better. It's funny I made them in my air fryer lid they didn't move like this so we're just going to gently roll them back on. There we go. Okay we're still counting it as a win. So now I'm just going to put the chocolate right on the marshmallow. I'm just going to let it sit there a little bit and it will melt. That is gooey. Then you just have to put the tops on that's the most important part. It's a good looking s'more. Hey guys taste test we already know this is going to be good but this tastes good. Yep it's good. Now if you want more air fryer recipes I have some amazing ones right up there just for you. All right guys see you later.


Hi everyone. Missed you.  And it's been weird for everybody. I know you guys know.  And I understand. So not going to talk about that today. And usually when I do talks and get to see all of you, it's a real celebratory thing. And I get to talk about all the great things and all the amazing people that I'm lucky enough to work with have managed to do. And they have managed to do a lot of really amazing things in the interim. But I'm not going to talk about those today either. We have a lot of announcements and those will come soon. But just didn't seem like the right thing to talk about this time. So often, the things that we work on and the things that we talk about are very grand in scale. We're always trying to work on things that have very high impact, very politically controversial, very broadly applicable, very macro ethical. But I thought I'd shift gears a little bit and talk about some of the micro ethical things. Some of the things that don't save lives, but get you through the day, maybe a little more. Some of them may be safe lives, but smaller things, everyday things, survival things. Because we're all kind of wired into a bit of a survival trip right now. And there's this danger that we're all in of being in a mode of survival that we never come out of. If you want to look at some of that, I recommend the neurobiology of it and the human behavioral biology of it. We studied very well by a guy named Robert Sapolsky. I'm a huge fan of his and he has been generous enough to put all of his lectures on YouTube and a playlist. I'll try and put those here so that you can watch them if you want. Additionally, I am so much a fan of that I managed to put together an entire bundle of all of the books and all of the articles that he referenced so that if you work through his course, you can read through them. I'll try and put that here. We'll see if that actually works in the other thing. We've all felt the impact. Things have shifted despite whether you've actually been touched by the virus in question. We've all felt health impacts, slowing metabolisms, increasing myopia, depression, fitness degradation. All of these things happen and one of the things that's really disappointing about thinking about all the ancillary health effects that have been coming along, including all the secondary outbreaks of other things that are also quite scary is that they seem to get left by the wayside. There's this rather disappointingly callous approach that so many people seem to bring of the, oh, but did you die? Sort of question. And if the answer is no, you're not going to get a lot of attention or care or help or solutions or people working towards those sorts of things, which is sad and needless and disappointing. So I'm going to try and talk a little bit about some of those things. And it's one of those things that's very individual and it's very personal. It's personal to all of us. And I know that I have lost a lot of people to depression in general, and especially during this era. And that the typical advice that is given in the cases of looking at things like self-care is of a very childish and kind of condescending nature, where rather obvious or entirely impossible or fairly useless things are talked about. The sort of, you know, have you looked behind the sofa? No, no, my goldfish are dead. Sort of problem that is all too common. And it's really sad. It's really sad and it's really enough to make you kind of angry when the same things get repeated over and over again.  There's not a single person that doesn't think that those things would be good to do. The very fact that those coping mechanisms are necessary is indicative of the fact that things are in a much more dire state. And there are other people who will sort of throw out these panaceas of saying that if you take enough ketamine or mushrooms that, you know, everything will come up roses. And of course, everything is much more complicated than that. The human psyche is much more complicated than that. Your life is much more complicated than that. Everyone's life is more complicated than that. And that's one of the things that there needs to be a little more recognition of for all the great things that science and Western medicine have managed to unpack about human biology and neuropsychology. We don't have good fixes for most things. So I think this is going to be kind of short, but I just wanted to throw out a couple of little fixes for mostly little things that don't solve things per se, but make them a little bit better. And I've found aren't terribly well known. You might know some or all of these already, but I haven't found a lot or at least enough being discussed about most of these things. And so maybe this handful of tricks will make things a little easier for you or somebody you know or somebody you care about. So the first one is that I imagine most people are probably drinking a little more than they used to or maybe a little more than they should a little more often. And yeah, of course, that's another one of these stopgap coping mechanisms that we all use. It's very simple. It's ubiquitous. It's legal almost everywhere. And there are repercussions to that, of course, but most of them are pretty long term. And so they're reversible if you're careful. But in a more immediate sense, sometimes when you've had a few too many and you wake up in the next morning, don't feel very good. And nobody likes to hangover, of course, it's not pleasant. And at the same time, also, it can keep you from being very productive the next day. So there are a couple of little things that you can do to make that just a little bit easier. The first one is an acetylcystine, often abbreviated as NAC. It's a simple dietary supplement that's sold in most health food stores. And it's a free radical scavenger. And oftentimes, if you take some of that in the morning, when you're not feeling so great, it can help after a little while. And of course, if it's a really severe hangover, it probably won't do a whole lot. And you might not even be able to keep it down. But in the case that you're just feeling a little bit rough, and you had maybe one or two more than you should have, it can take the edge off. Another thing that's maybe a little more serious, it's actually a lot more serious, is when you take a painkiller, you should be careful about which one you take. Now, oftentimes, when we think of painkillers, they're just kind of different brands, but they have different active ingredients. And there are basically, in this particular case, kind of two categories. There are the ones that have acetaminophen in them, and the ones that don't. And these include brand names like Tylenol or Panadol. And acetaminophen also goes by a few other names. I'll try to list them here. And the brands that have them, maybe I'll try and put over here. These are things you shouldn't take if you have a hangover. And the reason for that is because they're very hard on your liver. Now, normally, that's not a big deal. If you have some pain, you can take something that's going to be effective, and your liver can do a little bit of extra work. And that's fine. But one of the things about alcohol is that it keeps your liver very, very busy.  And this is not something that's even terribly uncommon. This happens a whole lot more often than usual. In fact, one of the biggest dangers of people using Vicodin is not the Vicodin, it's not the opiate inside there that I believe is hydrocodone. But it's the fact that there is Tylenol mixed in there. And I personally know people who have died who were self medicating with Vicodin. Not in huge amounts, but over a long period of time. And eventually, their liver gave out, and their kidneys gave out, and they died. And by the time they found out, it was too late, and they were told they had three days to live, and that was the end of it. And it was really sad. And I've seen that happen, in fact, more than once in different cases. So be wary of that. And if you are the sort of person who is using Vicodin, for one reason or another, keep in mind that you can do a fairly simple what's called a cold water extraction to remove the opiate and use it exclusively while leaving Tylenol behind. You can look that up. Our friends over at Arrowhead have some instructions. I'll try and put those here as well. So, just be careful. Of course, there are a few other things that you can do for hangover. One of the things is that you sap your body of B12 pretty strongly. So you can get high dose versions of that. The methylated versions of B12 are probably a little bit better, and you can get a sublingual form. The high dose tends to be 5000 micrograms, and maybe take two in the morning. It'll flush out of your system pretty fast. One of the magic things that you can do for hangovers, of course, give yourself a saline IV, which is very hard to get access to, depending on where you are. United States centauriously blocks citizens from having access to saline, which is about the safest thing in the world. But there are ways of getting around that, of course. So, keep yourselves healthy. Keep yourself safe. Try and be conscious if you have a hangover of not damage yourself any further. Another big one is sleep. Oftentimes, people are having a hard time. Sleep goes, but it's, of course, hard to sleep well if you're not sleeping well. If there are the sorts of things that are affecting you that you're suffering from bad sleep, then the sorts of things that are going to be recommended again in this sort of paternalistic condescending way are not going to be terribly effective. There are a couple of stop-gap treatments. I know most people have heard of melatonin. I tend to recommend to my friends who are having trouble sleeping that they do a dose of three milligrams of instantaneous release and three milligrams of extended release melatonin. And that can be sort of a combination, one that helps you fall asleep and one that helps you stay asleep. On top of that, oftentimes, one of the things that will make sleep difficult is anxiety. And 5-HTP, which is a, again, another supplement available in health food stores, is a serotonin precursor. And it can sometimes take the edge off a little bit. 200 milligrams or something can help. Some people even go so far as to take Benadryl. And of course, it's one of those things where, yes, Benadryl is not the sort of thing that is going to be very friendly to your system if you're taking it chronically, repeatedly over and over. But again, when you're in a desperate situation where you can't sleep and nothing else is possible, and that's something worth considering when you're trying to reduce histamine levels in the brain, and that helps you fall into an unconscious state. So maybe try that. And one of the other things that a lot of people in very difficult and stressful times seem to suffer from is the sort of brain fog, the seeming degradation of memory, cognition not as sharp as it used to be, focus lessened. This is one of the things that seems to be a major issue in the long haulers. And it seems to be endemic anyway. Now there's a whole host of new tropics out there that people are expert in and you can get good advice about. Some of those are hard to come by though. The common things that again are more available, easy to find, include choline enhancers. And two key choline enhancers include alpha GPC and DMAE, both generally recognized as safe and easily available. Alpha GPC is something that can help tremendously with memory. It's important to take it with food in order for it to be effective, but it's something you can take after breakfast. And you'll know if it's effective for you after about a week. Worth trying. It's not expensive as well. DMAE is another choline enhancer that works by a slightly different mechanism that a lot of people indicate helps them focus better.  So just be cautious and try to be friendly and nice to the people around you if you're trying to do that. So the last thing I'll mention just a little bit about again is this question of depression. Now, the 5-HTP I mentioned before of course is a good tool because serotonin precursors and the adjustment of serotonin in the body can be helpful. It can sometimes take the edge off. And of course there are degrees of depression as to how severe it is and how it's affecting a person and how much those different techniques can help varies. If somebody is in the major depression where they can't even get out of bed then it's very hard to sort of break out of that cycle to make things better. But here are some tools that will work sometimes for some people in some brackets of the depression spectrum. And again Sapolsky the guy I mentioned in that lecture series, the depression lecture is notably missing often. I'll try and mark that especially here. There's a place where he gave the lecture that was outside of Stanford and you can hopefully watch that separately. Again I mentioned that often there's a lot of really useless advice out there where people say things like hey have you tried not being depressed or hey why don't you exercise or change your diet or and of course those things aren't wrong but they're often inapplicable for the people who are really suffering. But there is one thing that I have come across that's not very well known but it is fairly well documented and it seems like a lot of action in the neurobiology of depression happens in the hippocampus. It's very well documented that people who are chronically depressed, their hippocampus will actually atrophy. It will actually shrink and the action of it will lessen and the hippocampus is a really fascinating thing. It covers all sorts of interesting forms of cognition. It's very complicated and connects a lot of dots and to have it shrink is a really interesting thing to witness. The other time the hippocampus atrophies is when people utilize turn-by-turn directions when they are navigating or in other cases when they are not in control of some sort of navigation in this sort of way that the human brain orients itself is really critical and when you're no longer in charge of doing that when you're no longer when it is no longer incumbent upon you to orient yourself for whatever reason if you've offloaded it to a machine or another person or you're just not going anywhere then again the hippocampus will atrophy. Now interestingly in a somewhat predictable form of symmetry in people who spend a lot of time navigating very carefully using only their brain and not a machine you will see people with a hippocampi that are larger and more active but very classic cases that of old London cab drivers who were required by law to memorize the structure of London streets and be able to from memory give the most efficient route from point A to point B utilizing the really bizarre one-way system that exists in London and and they have huge growth in the hippocampus. So one of the things that is suggested by the research is that if you go out and do some navigation without the help of a machine telling you where to go that it can start to grow the hippocampus and that if you do grow the hippocampus it can be a tool in combating depression. So if you know somebody who's depressed and they're in a state where trying to go outside isn't an inaccessible thing try offering that to them sit down with a map or print out a map and say let's pick a place that's close by that you've not gone before and we're going to pick out a route in advance and we'll go there and then you go with them and they leave their phone at home or they leave their phone in their pocket and you stay with them and you let them lead the way you tell them that you're there that they're safe you're not going to get lost but you're just going to navigate to this point and then turn around and head home and if that's too much even just the thought exercise of course can help this just I'm helping them imagine going to that place and coming back and what those landmarks look like and orienteering that have even been suggestions of playing video games that require you to explore uncharted territory in a virtual space being helpful that might even be worth trying but working with map and compass or working with just a map even if somebody is really really uh emotionally attached to their phone have them just turn off gps and they can still use the map but they'll have to figure out where they are from looking around and they'll have to figure out where to go from consulting the map and that will activate that system in the hippocampus and can maybe make a little thing a little bit better especially if it's done repeatedly so hopefully that can help somebody a little bit and we can continue to try and get things together so again I will be back online soon with a lot of really exciting things to announce about four thieves and what we've done in the past year and I look forward to the possibility of seeing you all in person again before too long and I I hope that that all works out if you like four thieves and what we do in general and you want to support the cause find somebody who needs your help and help them and do it whether you think they deserve your help or not keep each other healthy keep each other safe thanks so much here's the toast to the dead for children with cancer and age to cure existing you probably could have been saved sad to see medicine divorce morality corporate home records giving up a salary


Ja jos se on hyvää rikkoa, olen pystynyt tämän YouTube-yhtiön kanavalle. Sitä voidaan tehdä jotain, jotain, jotain, jotain? Joo, joo, joo, joo, joo. Tämä on tärkeintä, miten se vaikuttaa. Jos haluan muistaa paljon, niin haluan vain... Haluan vain puhua online ja... ...unlistaa videon vain, johon olen pystynyt. Noin, nyt on aikaa. Ja... Olen huomattu, että olen tullut 7 vuotta, mutta olen tullut niin, että katsotaan. Ja sitten olen tullut katsomaan Reza ja Reza, josta olen tullut ensimmäinen kautta, mutta hän oli visa-asio, joten hän ei tullut tullut tullut tullut. Tällä kertaa, että katsotaan, että katsotaan, että katsotaan, että katsotaan, että katsotaan. Ja hän katsotaan, että hän tullut tullut katsotaan, että katsotaan, että katsotaan, että katsotaan, että katsotaan. Ja sitten hän tullut se, että katsotaan Reza ja hän tullut ensimmäinen kautta katsotaan Reza-asioon, joka on vain ei ole helppoa. Täällä olemme, mutta olen tullut se. Ja tämän kertaa on entisempilä-aurintaa, ja olemme taloutuneet seuraavalla ja measurements-asioon. Parti on aina, mitä Reza on ja täysin mennä. Mietin se, että tämän lopullekijöiden hänä on tosiaan residence-asioon ja hän paitaa Reza-asioon. Kyllä me olemme taloutuneet seuraavalla ja measurements-asioon, koska hän ei tullut paremmin tiedä asioon laittamista, vuonna olet tapauksessa, että hän hän hänesää. Tämä on vähän problemaattista, koska olemme nähneet, että on missä matkaisuja, mitä on EO-konsektua ja miten se on oikeastaan ympäristö. Ja sitten on vähän asioita, että ympäristö, prosessuus ja modelen prosessuus on se, että se on tärkeintä asioita. Joten, mitä on EO? EO on tietysti ympäristö, johon se on tärkeintä asioita, johon se on tärkeintä asioita, johon se on tärkeintä prosessuus, innovatioita ja riske-takka, tai se on ollut ympäristö, johon se on tärkeintä asioita, mutta on missä tärkeintä asioita, prosessuus, innovatioita ja riske-takka. On myös 5-tärkeintä asioita, mutta me olemme vain nämä 3-tärkeintä asioita, kaikki, että sanoin, on myös ympäristö, mutta, tietysti näin, johon se on tärkeintä asioita, johon se on tärkeintä asioita, esim. Koska jät kardeşim viimeista seikkailua, jaнаam Victorian ryhmistä, formarilya tai mon drovech wordt eluvelliselt. weeks, but we have had independent effects on outcomes, so innovative effect of performance, independently of the evolution. And we measure the model, and as a component of the EEO, we are confounding the EEO concept with the independent effects of the models. Let's take a look at the background of the paper. I'm just going to skim through the background. The idea of EEO was originally that it was kind of like a label for a collection of attributes. So it started from Miller's 1984 paper where he was just looking for indicators or correlates of entrepreneurship. So he was not thinking about a concept that exists on its own, but simply a collection of trades. Like you might think about a talented person who would have certain trades and talent itself might not be something that you are interested in, but you're just referring to this collection. And then after, you know, in somewhere late 80s, early 90s EEO started to have kind of like theoretical existence of its own independently of these dimensions. So that's the background, and there are three conceptual issues about how we define EEO that we talk about in the paper. The first problem is that how we understand entrepreneurship has evolved over time, but EEO has not kept up. So if we call something entrepreneur orientation, then it must be related to entrepreneurship, otherwise we are just confusing everybody. But entrepreneurship, what it refers to, has been shifting. So we resurrected these various things that entrepreneurship has been identified with. And when Miller did his work, entrepreneurship was about creating new organizations, entering new markets. It was more about these actions and maybe some kind of processes. But nowadays we look at it instead of a process or a trade, we look at entrepreneurship more as a practice. So the conceptualization of EEO of entrepreneurship has shifted. We look more at opportunities instead of new organizations or new entries to new markets. And EEO has been basically the same three dimensions since Miller's work and his does not kept up. So entrepreneurship has been going there and EEO is going there. So we have an increasing disconnection between these two concepts. Then we talk about our dispositional versus behavioral aspect of EEO. And this was highlighted in Anderson's 2015 paper where he talks about EEO as containing two dimensions of behaviors and dispositions which contain attitude towards risk and behaviors contained proactiveness in the way it is. The problem with this dispositional versus behavioral is that dispositions and behaviors are not the same. So they are causally related. So we have dispositional EEO and behavioral EEO that are both referred to as EEO. And this causes confusion because then a reader of a paper about EEO would not know whether that paper is about behaviors or whether it's about dispositions. So there is referring to both cause and effect using the same term is potentially confusing. Then there is the third question which is perhaps the most important conceptual question in our paper. And it is the link between EEO and innovativeness. And this relates to the area of philosophical meteorology which relates to part-hole relationships. And there are two extremes that we can think of. One is that the EEO is simply a convenient label for innovativeness, risk taking and proactiveness and nothing more. EEO is simply a sum of these parts and then the other extreme is EEO exists independently of these dimensions and these dimensions only exist as measures. EEO started basically from here and it has been shifting more to the right but still the measures we apply for EEO are the same. If we apply innovativeness, risk taking and proactiveness as measures of EEO, this causes a problem because not all innovativeness is entrepreneurial, not all entrepreneurship is innovative. So innovativeness has effects that are unique, not depending on entrepreneurship. Entrepreneurial orientation has effects that are not depending on innovativeness. So if we have innovativeness as measure of entrepreneurial orientation, we are confounding two different things. The same argument applies to risk taking and proactiveness. So there are three conceptual issues. One defining EEO through these traits has not kept up with how evolving conceptualization of what entrepreneurship is. So we think about entrepreneurship differently now but our thinking about EEO has not kept pace. Defining EEO as this positional concept we have here concept is confusing and it's not according to good scientific practice where one label should refer to one concept. It is confusing to refer use the same label or same concept for two different meanings depending on the context. Innovativeness, proactiveness, risk taking are problematic as measures because they have independent existence of EEO. Of course not all researchers define EEO in terms of these dimensions but they are still used as measures. Now we go to the main part of the paper which is empirical issues in EEO measurement slash modeling. There is currently a debate and has been a debate for some years about whether EEO should be modeled as reflectively or formatively. The idea of this reflective model is that a firm is innovative, proactive and risk taking because it is entrepreneurial. Being entrepreneurial courses are your company to be high on innovative and proactive risk taking and then in the formative or conceptualization or formative modeling the idea is the firm is entrepreneurial because it's innovative, proactive and takes risks so the direction of model causality goes in the different ways. The reflective model has received lots of criticism lately so this is not realistic because it assumes that the dimensions are highly correlated. They are not empirical correlated. They are expected to share the same causes. That's not very realistic. Innovativeness has different causes than risk taking for example. They are not uniformly caused by the same things. The formative model is gaining popularity but there are issues that we talk about in this paper that have gone unnoticed in the formative modeling of EEO. We need to understand why this became popular. The popularity of formative approach can be attributed to two main papers. There is George 2011 in a Journal of Management if I remember correctly. He did a simulation study where he showed that if you mis-specify a reflective model where a formative model is correct your estimates are biased by two and a half fold which is pretty big bias. Then Anderson continued on that and refers to these as nomological errors. They do an intricate study where they show that the data do not support the use of reflective model and they strongly recommend the formative model. But there is a bit of a but to George's argument. It was shown by Agura Uretan Maracas in 2012 using a different context that this bias is actually just a methodological problem related to how latent variables are scaling. I will not walk you through the argument. We present it in the paper and we replicate George's paper and we show that this bias dimension just goes away basically when you consider standardised estimates which have the same scale between two samples. So this is something one problem we talk about in the paper. Then there is another problem called interpretation confounding. This is discussed in the methodological literature but it's not discussed in the EOL literature. The problem is that when this kind of formative model we estimate these weights so innovator is productive and risk taking we estimate them for each sample for each study separately. So we would think that our original EOL was a sum of these items but nowadays we actually use a weighted sum. So one study might have innovator's productive risk taking all weighted equally. Another study might have risk taking weighted 10 times more than innovator's proactiveness. Another study might have innovation weighted 10 times more than proactiveness and risk taking. So are these studies really focusing or talking about the same thing. In one study EOL is innovativeness 90 percent and other study EOL is 80 percent risk taking. Do these talk about the same things empirically. Then of course we might have scenarios and we do have scenarios where risk taking particularly has a negative effect. So one study says that EOL is positively related to risk. They define EOL as positive correlate of risk. Another study defines EOL as a negative correlate of risk. So what do we expect when we have this kind of models. Another thing that has been not addressed in the EOL literature that is discussed in the methodological literature comes from Rigdon's research. That's not cited on the slides but he explains this really well. The paper is that if we have the formative conceptualization innovativeness proactiveness risk taking. They cause EOL which then causes different outcomes. This model assumes that the effects of innovativeness proactiveness risk taking are always at the same proportions. So if risk taking is twice as important determinant of some outcome compared to innovativeness. Then it must be twice as important determinant of any other outcome. That does not sound very realistic. And this is something that means also that the dimensions are interchangeable this model. So it means that if you lack innovativeness you can compensate for by increasing your risk taking. And that's because EOL is measured model as weighted sum. You know from high school from elementary school math that if you take a sum of two things. If you lack one thing you can increase the other thing and that increases that makes it some of the same. So we build on Anderson's argument who says that EOL dimensions don't co-vary in a way that would support the reflective model. We argue that they don't co-vary with the outcomes in a way that would support the use of the formative model. And we test this with meta-analysis. So what we do in the paper is that we collect various studies and we collect the effect sizes of these three different dimensions. Of those studies that study the effects of innovativeness risk taking and proactiveness separately. We run a model, we test the hypothesis that the proportions are constant across studies. This hypothesis is strongly rejected. So the effects are not the same for every possible outcome which is pretty obvious. But we need to support it with data. Then there is a third problem. So we had a problem of interpretation of confounding. We had a problem of full media so it's not supported. And we have this interesting problem still called identification problem. I will not talk about the technical issue here. But this model requires that you have two reflective indicators for the formatively measured latent variable. The problem is, and this comes from Aguira Oretas and my research published in measurement. The problem is that in this case the empirical meaning of entrepreneurial orientation does not come from these dimensions at all. It comes from these two indicators. We show this by replicating Andersson's paper. So we generate data set that has the same covariance that they have. So it produces the same results. So we reproduce the results using synthetic data. And then we test what happens if we have two reflective indicators and two these formative dimensions that are not related. So does the result of EO on performance, does that effect depend on how the EO dimension is related performance? Or does it depend on how these identification indicators determine performance? We show that if these two indicators that we just add for identification purposes, if they are not related to performance at all, all performance effects disappear. So it means that these behaviors or these effects of the dimensions and EO on performance, they disappear because EO is not in this model defined as some of these dimensions. Rather it's a latent variable with two reflective measures. We also show by replicating another scenario where EO dimensions are unrelated to performance. And we show that when performance is considered, if the indicators that are used for identification on related performance, there is no effect. If EO dimensions are not related performance, there is no difference. We can also freely leave out all the EO dimensions. And the result will not change. So we leave out no EO dimensions. We leave under bear behaviors away. We leave attitude away from the model. The result does not change. It shows that these kind of models don't measure the latent variable through the dimensions. Okay, so we showed a couple of problems in the current practice in modeling EO in the paper. So what do we do with under preorientation? We have a couple of key arguments. And this is something that we are still working on before we submit this to the journal. Our key claim, our key recommendation is that we should stop forcing these dimensions into a single latent variable because they don't have the same causes and the same consequences. Innovative product is a risk taking, our separate variables and they should be modeled separately. The next thing that we think about is maybe we should retire the concept to EO. So if we have EO and if we use EO to refer to organizational level entrepreneurial behaviors, why don't just call them organizational entrepreneurial behaviors, our organizational intelligence systems instead of EO, which is pretty vague as a term. And then we think also that maybe we should go back to the rules to Miller's work and use EO simply as a convenient index. So sometimes you have so many variables and maybe entrepreneurship is a minor thing in your paper that an index of these dimensions might be a crude measure like Miller did. But calling this as EO would be a bit problematic because the term has some theoretical meaning. So maybe we should just then call it as entrepreneurship index instead of EO. Thank you. Any thoughts or questions? Do you have a hunch how this could be? Well, you talked about now a mixture of empirical and conceptual things. When we now take a look on what has been done so far, so is there anything that we could do better? For instance, when we now, when we replicate the study that has been done already, or only empirically speaking, so would it be helpful to model a second latent factor, an unmeasured latent factor, something like that? This would it be helpful to, I don't know, to loosen some covariance between the indicators of EO? Would it be, do you have any ideas in this regard or is that simply meaningless? I'm not saying that EO's meaning, as EO clearly has meaning as a theoretical concept, but the measurement approach is problematic. And if you have the three measures, innovativeness, productivity, and risk taking, I would think that it's very important to understand under which conditions each of those has the positive or negative effects instead of lumping them together as one thing. This builds on Edward's argument in 2001 in the organization research methods, where he points out that typically when field matures, we start with these very abstract concepts and then we start modeling dimensions. And EO is pretty mature already, so maybe we should start moving forward, looking at individual dimensions instead of lumping them together. So that's, as replications go, I think that's what we should do. And then entrepreneurial orientation clearly needs a bit more of a conceptual refinement, like unification. There are so many different ways of defining EO and maybe we should also start talking about, like not having this dispositional EO attitude, behavioral EO, individual level EO, what not EO and just use different terms to avoid confusing. Yeah. Have you seen any papers that do this, that move away already or? Minority of papers do model in the measures separately, and that allowed us to do the meta analysis to check how much the effects vary between studies. But most studies lump them together and don't necessarily report the formative weights. So there might be a structural equation model where risk taking has a negative effect on EO, and it's called an EO that is defined through risk taking, and yet the effect is negative, which is inconsistent with the theory. We have developed the paper quite a lot since the R&M submission. If someone wants to read the most recent version, I can send it by mail. Okay. All right, yeah. Time is also up. Thank you so much. Yeah, you're welcome.


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Good afternoon. There are a lot of chairs up here. Well, welcome to the final day of Cloud Foundry Summit Silicon Valley edition. Thank you all for staying and hanging out with us. We have the distinct honor of having John Rose join us. He was the chairman of the Cloud Foundry Foundation board to do a little closing fireside chat minus the fire. But we thought we could go through a couple of, get your opinions and your thoughts on some things to have your finger on the pulse of what's going on right now. Can you tell us a little bit about your new role since the acquisition? Yeah, we had a small combination of two companies. We're now about eight, nine months into this creation of something called Dell Technologies, which is the combination of the Dell ecosystem and the EMC ecosystem, which includes VMware, Pivotal, RSA, SecureWorks, Virtustream, Dell, Dell EMC. I think we're running $75 billion a year now, pretty much all aspects of infrastructure, keeping us very busy. I mean, I spent the first year prior to the acquisition figuring out the strategy to put the two companies together. Thank God that's done. That was a lot of work. It seemed to work reasonably well. Now my responsibilities are the overall CTO for Dell EMC, and I run a kind of virtual CTO structure for the Dell Technologies side. And then that would be enough. But unfortunately, I also am responsible for what's called cross-profit operations. So many of you who probably are in large companies know that the challenge isn't innovation in a silo. It's trying to make everything work together. And so CTOs tend to be responsible for setting a strategy. I got the pleasure of also being asked to make sure that we put the underpinnings underneath it. So I run cross-product operations, which is all of the things that the engineering organizations use and share, and the things that we want to do in common across all of our portfolio need to be done in a more centralized way. And so I describe us as bookends. And then given that I had, you know, co-ed this amount of free time after that, a couple of years ago when we formed the foundation, I took the board seat and got elected chair. It's been a lot of fun. We had a little transition last year, putting Abby in place and Sam moving over to Google. I realized that when you're the chairman of a nonprofit and you have a leadership change, your job gets quite busy because certain things like signing legal documents suddenly become your responsibility. So anyway, super excited, you know, love what's going on in the foundation right now and in this ecosystem. You know, who would have thought a couple of years ago that, you know, we would have this level of population of end users and people putting this technology into practice. In fact, I think that Cloud Foundry by and large is probably the most adopted and used in real-world scenarios, cloud-native architecture in the world. And, you know, that's pretty humbling, given that every technology has an opportunity to be successful. But the measure of that is whether or not it actually gets used by real people doing real things that have real meaning. We're absolutely at that stage now, so super excited. Well, we are pleased to have you here and still continuing to be the chairman of our board. You know, since you've been here since the foundation was created, how do you feel about the progress that's happened so far and even like at this event from last year, how do you feel about the momentum we have? Yeah, yeah, I think, you know, like everything we went through in evolution, the first was, you know, launching Cloud Foundry. How do you make this a large open source initiative? And if you think about it, you know, we actually started later than most other kind of current open source projects that are out there. You know, Cloud Foundry came into existence after a number of cloud-native stacks had already been out there and definitely things like OpenStack. But the progress that we made in the last couple of years is just staggering. I mean, we went from, okay, let's build and deliver something that people can use. By the way, that's where most open source projects actually fail. Open source communities and foundations think that they're there for the purpose of just encouraging people to figure it out and hoping that the ecosystem actually delivers something usable, I think, with the certification programs and the kind of discipline that we have around this ecosystem. The fact that pretty much every Cloud Foundry distribution out there works can be consumed and is utilized by real customers is a huge testimony. So that's item number one. Number two is if all you have is a collection of people building the technology and you don't have an ecosystem of people using it, then you probably will fail also because, again, great technology nobody uses isn't really all that interesting. In the last year, we've begun to see that pivot. And I think this year the summit is a great indication, just a number of end users that are here, the number of people putting it into practice. The last panel is a great example of that. That is exciting. This is not theoretical work. This is now real. I put a challenge out in the Cloud Foundry Summit in Europe at the end of last year that I still think we have more work to do on and that is that it's great to have the technology and it's great to have the customers that are going to use it and are putting it into practice. There's another dimension of ecosystem around that that has to form. And I think we're making huge progress on the developer ecosystem. I still think we need to do more and spend more time as an overall ecosystem encouraging services companies and professional services companies and even infrastructure companies to step up and make it easier for the customer to consume the technology. Because the technology exists well. The demand is there. The customers want to use it. It's a question of how do you fill in all those gaps. Simple things like training. We have a nice program now that has got plenty of content. Now we need companies to embrace it and to leverage it. Professional services companies need to pivot from being kind of dark ages, legacy development methodologies to building practices around cloud-native development practices so that we can scale that. But overall, I'm incredibly happy with the progress given that this is literally a two-and-a-half-year journey and we've gone from beginning to really a very significant presence in the overall industry and real-world environments without anything miraculously happening. Just a lot of good effort and great technology that people can actually use. Turns out hard work can make you an overnight success. Yes, exactly. We've talked a lot this week about digital transformation. I opened talking about the role developers play in that. But I do think that's something that's been top of mind this week and most of your day-to-day. As you think about when we talk about digital transformation and cloud-native practices and cloud-native application architectures, do you think there's an opportunity thinking beyond cloud foundry to start applying some of those methodologies to edge devices and development happening on the edge? Oh, yeah, absolutely. I think we're already seeing it, actually. I think, you know, at the risk of using buzzwords, I'm not a big buzzword fan. I'll digress for a second. I'm a networking guy from a long time ago. I used to be the CTO of a company called CableTron Systems in the 1990s. For any of you who are networking people, today we call networking devices switches. We used to call them bridges.  And then somebody decided to create a buzzword called switch. And most of us in the standards body kind of looked and said, this is nuts. Why are we renaming something? So we have a lot of buzzwords out there. I'll try to be accurate and not marketing. But there's this buzzword called IOT, the Internet of Things. It is, you know, conservatively described as a multi-trillion-dollar market. Now, it's really not a multi-trillion-dollar market all by itself as a new market. It represents a fundamental shift that people are realizing that you used to build IT systems to scale to the number of users in your business, internal users. When we became digital in the first wave, we started to think about building our systems to be able to scale to the number of consumers of our service. But the definition of consumer was a human being.  You built a system that allowed your customers to do electronic banking. It was a great shift, and we went from building IT systems that scaled to tens of thousands of users to maybe millions of users in some cases. IOT is different because it basically says we're redefining what a user is. A user is now any intelligent device, even if it's marginally intelligent, that benefits from being connected to this broader ecosystem of services that represent the IT infrastructure. Like a fridge. Like a fridge, exactly. I still don't quite get that one, but I think that's something useful. But fridges are good. I'm not sure there's a great business model there yet. Anyway, punchline though is when we move into the IOT world, one of the things that we've realized is I like to describe it as there's a conservation of IT, the law of conservation of IT. For those of you who are scientists, there's law of conservation of energy, things of that nature. What it means is all the things that are necessary to make IT happen have to happen somewhere, regardless of what's involved in it. You have to be able to access data. You have to be able to process data. You have to be able to get results. You have to be able to have management. You have to be able to understand how to survive. When you move to IOT, what happens is we shift the intelligence of the thing, the client, down to a very minimal level. In fact, we have to. We have to make it incredibly dumb. You don't want to put a lot of data out there necessarily and store it there forever. You don't want infinite amounts of compute. People are saying, hey, Tesla's building a data center in a car. That's not really the goal, because if you put a data center in a car, you couldn't put enough batteries in there to actually make it run very long. You actually want the minimal amount of compute capacity in that car, but you want it to appear as if it has a data center in the car by being able to connect to the rest of the IT infrastructure. And so I think, in order to make that work, this interrelationship between what's happening at the edge, which is this pervasive connectedness of new things and their need to interact with the other things requires us to think in a cloud native model. Because if we don't, if we think in a legacy model, we'll try to build a data center in a fridge or build a data center in a car. Instead, in a cloud native world, we can simply build microservices in containers and we can connect them to an agile framework and that, whether it be smart or dumb, application close to that car that has certain access to certain data can seamlessly interact with the other microservices and containers and other services that exist within the overall cloud. It can form dynamic relationships and ultimately you can create this seamlessness in which the overall end-to-end experience is under one framework, something like Cloud Foundry, but the instantiation of the containerized, microservice, API-driven applications can be distributed appropriately into very lightweight edge devices or very high-capacity data centers or whatever else and it can work as a coherent system. I don't think you can solve IoT without a cloud native paradigm. I don't think you can solve IoT cost-effectively without rethinking how you design applications across this and I don't think you can solve the edge without the core and if you solve them independently, you'll solve nothing. So you have to have these frameworks to tie them together. Yeah, absolutely. And so as we're continuing on that and we're seeing a broader proliferation of IoT and use cases around the edge, where do you see this going and the momentum that we've talked about this week even with cloud native and cloud native applications and looking at just the number of users that are attending this event and the interesting things they're already doing with this technology, where do you think this can go? Where do you see things going over the next couple of years? Well, first of all, I think we're just at the beginning. I mean, you know, we're applauding ourselves righteously for having lots of users now of Cloud Foundry, but if you look, there are entire industries that really haven't pivoted yet. The funny thing is the industries that have pivoted are not the ones I would have expected five years ago. The fact that the industrial industries have pivoted and our cloud native early is stunning to me. I've dealt with that industry for 25 years and never seen anything like this where early and fast adoption of a new technology is happening out of the industrial side. Normally, they take a lot longer, which is great. At the same time, you know, we look in the banking sector and we've seen certain, you know, disruptive areas adopt it, but the core systems haven't pivoted yet entirely. When we look into areas like healthcare, which are very obvious ones that we think we ought to be doing a lot of new application development and new ways to deliver IT systems, we've actually seen very little yet relative to the size of the industry. And so I think we're kind of at the beginning of that journey. So the first principle of what I expect to happen over the next couple of years is some of these industries that are still figuring out how to make that jump, how to move into this paradigm will figure it out because there'll be enough examples from other industries and enough maturation of the technology and hopefully enough maturation of the ecosystem to help them make that jump. And so we should see a lot more diversity and balance that won't be overly concentrated on a specific set of early industries and what we'll see is a representative sample of all industries sitting in this audience over the next couple of years. So that's number one. Number two is we're going to discover all kinds of horrible unintended consequences of moving to the cloud native world that have nothing to do with technology. You know, Abby and I were talking about it. One of the ones that we're seeing already, which is a victim of our success, is when you apply a cloud native continuous integration, continuous delivery technology, it doesn't have to be cloud foundry, to a regulated environment. You start to run into weird human problems. For instance, if I'm continuously streaming new componentry into an active environment, which is kind of the principle of how you do this stuff, yet that active environment is regulated and somebody has to sign off on the risk profile of it and guarantee that it is safe and that it's predictable. That human intervention, that it's historically been a gate between testing and productization, starts to become a problem. And now we've worked through that by a lot of manual intervention and trying to constrain the use cases, but we're gonna have to solve that problem more systemically. We're going to have to develop architectures, not just in cloud foundry, but across the board, that allow you to accommodate for risk models that are different than a web scale company or are different than a consumer company. And I think that's a huge area of innovation that I'd be very disappointed if we haven't solved those not by just throwing bodies at it, but by actually thinking about better ways to sign code and to profile code and to be able to do kind of intelligent, maybe AI-driven certification and testing so that the person responsible for the risk profile feels comfortable that they can absorb code very quickly into a production environment even in a regulated environment. So there's a bunch of these new technical problems that emerged because we've actually had use of the technology that we're gonna have to solve. And so I think it's gonna be both a breath of adoption transformation over the next several years and a bunch of these kind of unintended technical obstacles that we're gonna work through that will ultimately harden and evolve the technology to make sure that that breath of customers can actually adopt cloud-native architectures without compromising on their business success or their business profile or their industry dynamics like regulation. Which will probably also drive the technology in new ways. Absolutely. And the trick is, you know, just to be careful, let's not drive it off a cliff by chasing something that only two customers need. So we have to have this balance of let's keep the core pure but recognize where these incremental problems can be solved and in the spirit of building something cloud-native, build it modular, build it with APIs, build it so that somebody who doesn't need that value-added service is not encumbered by it. And if we do it the right way, we'll actually have probably for the first time in history a nice modular consistent architecture that can address the needs of a consumer company equally well to a regulated bank. That would be a nice aspirational goal. Well, that's one we hope we can get on stage and talk about in a year or two. With one final note, we have an amazing group of contributors, committers, users, developers that are here and in the audience and watching on the live stream. If you had one ask, one call to action for them, what would it be? Well, the simple call is stay engaged. This can't be done without you. I am consistently amazed as to, let's call it the size of the teams accomplishing the things that are done within the various sub-projects of Cloud Foundry. Now, that doesn't mean we don't want more people engaged, but what it tells me is that when people engage, if you are an active committer, if you are involved in those projects, the proof that developing in this way and really embracing modern architectures and modern development methodologies can actually deliver things that historically would require thousands of people and take years and years to bureaucratically get to an end state. The first message is, first thanks, it's incredibly important that you're contributing. The second is, stay in the front end of the curve in terms of development methodologies because the amount of productivity that these relatively small cross-company development teams are able to actually achieve in this architecture is just staggering, and so stay the course. The second piece, though, is recognize that, you know, this project, just like any other, is going to continue to expand and there will be continuously new demands. There will be new architectures, and so along with staying consistent with Cloud Native Development principles, have an open mind about the fact that when a new user environment materializes from a new industry that you know nothing about, educate yourself about it. So now with those customers, try to figure out why they want some crazy regulatory framework to be put in place or why they need this particular way of interacting with some small form factor compute device stuck in a windmill. These things will help you think creatively about how we actually make sure the project is flexible enough to address a larger set of use cases. And, you know, the good news is, we now have this wonderful cross-pollination between end users and the core developers across the ecosystem, and I think we need to make sure that we continue to do that because it's that insight from the end user that allows the creativeness inside of the development games to actually result in the kind of things that we've been able to achieve. 100%. Well, John, thank you for coming on stage and sharing your time with us, and I'm going to wrap up real quick, but thank you so much for coming and hanging out. Right, thank you, Abby.


FNN. The Tiger. Financial News Network. News update. Hi everyone, Basel Chapman. Here this is the Tiger Financial News Network 10 a.m. market update here on Friday the 18th of February. Don't forget we've got a holiday on Monday so we'll be back here on Tuesday. 34,362 up 50 points. It sounds great. Look at this pattern. The lowercase H pattern is still in place. We could not get more than just a little mini arch. Really important that sometime next week we start to trade in the now 34,800, 900 area rather than break 34,000. It's important of course we've got a weekend coming up here. So even though there could be that Friday squeeze with options monthly options expiration today it might be ameliorated by the fact that there's a lot of pressure on the market right now. Both political, bonds, everything. So here we go. S&P. S&P is up 9 at 43,889. Now it has not yet taken out the left side low of just a few days ago. So far this is good action but when you're looking at this arch pattern which also failed to make a decent M formation it's really important by the end of the day or at least intraday we need to see a good 18 points to 22 points up in the S&P. The doubt needs to make a 250 point rally and then maybe by the end of the day everyone gets a little nervous but you need to have that. We've had no signs of strength at all. QQQ and DX100 had a sign of strength earlier in the futures. Now it's down 20 cents at 345.22. Also not very good pattern here. IWM the Russell 2000. It's up 90 cents at 202.09. It's a much better chart pattern on the day that looking the weekly chart is terrible and the monthly is terrible. Gold. Gold's been the star all week. Pulling back just a little bit down five at 1897. I've got in the legs see the GDX which is the gold mine as I'll talk about this when I get back is in a leg D made I have 35.11 trading now down nine cents. There's a lot to talk about in this whole area. Let's go to the TLT which I think is absolutely imperative to talk about up a little bit today at 58 cents. Are we going to see yields pull back here the financial stocks maybe take a bit of a breather. There's a lot to talk about from my Tiger technicians hour. I'll be back in a moment and just wanted to mention the crude off is as we said pulling back from the high that was made five days ago. Not much but it's tough. I'll be back. Check out my opening call my dating you


No problem. And if this got a 99% uprate, I love it. Okay, so let's just do that 14 pages again right quick here. Don't think so. Look at that. There were you asking where the table was. It's right there. There's the table. There's where you get the 68 for a excluded 8 tenths of that must be 54 for included. That's where you take care of the fact that they are cutting the threads, cutting the shank. Same way on this one and that one for a higher strength bolt and then just plain old threaded parts that you don't know what they are, but you know they're F sub use. And then I'm not going to go through all this, but I would suggest you go through it. It'd be a good idea tension on the gross area, old stuff, tension on the net area, gross section yield, net section fracture, block shear strength, all of the things that go on here, UCBS, you remember what UCBS was? Anybody? It was for block shear. Tell me again. Welded? No. Where are the back of the plate? Well, here you go. Here was one of them right here where you have coped the top and you have more than one column of bolts. And so when you have something on here tending to pull this little piece out, the stresses are distributed not linearly and cause higher stresses on some of the part of the steel than other and they made you use UCBS, I forget. You only got half or something instead of 100 percent was the stress distribution down on the bottom. Then they had 15 things they showed you, UCBS, UCBS is equal to one, is equal to one. The only one I think they showed you was this one. More than one column, it was a 0.5. So design strength for bolt and shear, they added all the numbers up, they got 71, a slip critical. This is a mistake in my book. I'm not sure if it's still in years or not. The numbers, actually the numbers from last year when there was a different, some of the numbers changed as they do. He's got the right number on page 398. He just forgot to make the change here. So it's 38 kips, tension on the gross area, tension on the net area, block shear strength, loss of everything was the slip critical, and it usually is. So good enough. It'll take the 38 kips we need, and it will back up with bearing strengths if it comes to that. We hope it doesn't. It usually works out that way, yes. Usually when that's fine, then we won't design it as a slip critical. And if you don't design it as a slip critical, then it'll slip. And in most buildings when it slips, it only does it once because they only get these horrible wind loads once in the life of the building and we don't care. But in a bridge when the truck goes in this span and the bolts go, and then he goes to the other side of the span and the bolts go, and then the bolts go, did you see that? A little bolt fell out. Well, the little bolt fatigued and it broke. And you know, that's not that bad. There's one less bolt out of 40 in there. Probably live with that. By the time we inspect it, we notice three bolts are missing. And so we got to have a real slip critical connection and put no more load on it than that for some cases. All right, now we can get all of these numbers, most of them, tables for bolt strengths. There are bolts that are there are tables that will give you these strengths for shear. There are tables for end pullout distance between the bolts, pulling the little plug out. There they have some assumptions in them that you pretty much have to go by, but they're not severe and they're commonly what you use anyway. If you get outside of that range, then you just have to know how to where they got the numbers from and do your own numbers. So he wants to determine the strength of the connection we just did based on shear, slip critical and bearing strength. So we already know the numbers. In summary, it was a set of four, three-quarter inch group A shear threads included single shear spacing of the bolts was three inches and the and the end dimension was one and a half inches. L-clare was this number minus a half of a drill size that was bolt size plus only one-sixteenth and this L-clare was the distance between the center of the holes minus a complete hole size as opposed to a half of a hole size. Things of the plate was three inch and they were standard holes. So it says from manual page seven dash one. All right, I got a table seven dash one for three-quarter group A for three-quarter inch. There's three-quarter inch group A. Here's group A, group B, crummy A307s. So I have shear planes through the threads and shear planes where the threads are excluded. Ours were included and the connection itself was either in single or double shear. 17.9 kips per bolt is the strength of the bolts. That's not that hard to work the number out. It's just always easier to just go pick it out of a table someplace. Notice the tables go up to about an inch and a inch and a half diameter bolts. That doesn't mean to say that that much load in the bolt won't just crush the plate into jelly. So that still has to be checked, too. The 17.9 is what we've got. 17.9. I don't know where it is to tell you the truth. It's too far back now. 17.9 kips per bolt. There's sample seven-four. So what he says, sample seven-four, shear strength of one bolt. Something's fishy here. Strength of one bolt, 23.86. Very good. All right. That's nice. Look at that, man. Wow. Goosebumps. Yeah. Fee. We didn't bother putting any fees on this thing yet, because we weren't there yet. We were getting all the way to the end, and we put all the fees on it one time. Fee is .75. Well, the fire number times .75, you get the number in the table. I say, why didn't you leave that off? He says, well, look, we've got people who really do this for a living, not like you. They just wouldn't know the number with everything included, including the fee. So that can get confusing. Be careful. Next, he would like to know the slip critical strength from table seven-three for group A bolt for the coefficient of extra .3. You use the standard old single shear. 9.49. These are group A bolts. That's the right table. Group A bolts. We've got another page probably with group B somewhere. This just takes up the whole page. They were three-quarter inch diameter. They were STD standard holes. They were loaded in single loading. We are not doing the allowed stress. We're doing the LRFD 9.49 kips per bolt. When I got something else, but, well, no, we should have got 9.49, shouldn't we? Why? Because I feel he was one. So let's just see right quick for slip critical. 9.49. He tells us down at the bottom. There we go. We're going to say, surely he tells us for the standard holes one, we take care of the non-standard holes slotted in one direction or another, and it's a little harder to get, you know, to have the bolt bear up against something to .85 and then this kind .7. Time to find out. Lots of slip, Lollie. Don't know. Key's right above it. Smart Lollie. Long slotted holes, transverse or parallel to the line of the force. And what is OBS? OBS. And what is STD? Standard hole. All right. So there's two things we could have pulled right out of the table. And I would have a lot rather he did. This is number one. And then he went in and did that as number two. And then he did this as we did, you know, because this is just a different thing than the other things.  Bearing strength. There's two tables. Well, that makes sense because we have end holes and we have interior holes. So he says for the inner bolts from table 7-4, there's table 7-4, these are three-quarter inch diameter bolts. Here's three-quarter inch diameter bolts. We have a loud stress. We have the good stuff, LRFD. The fee is already attached. He uses a small case R, lower case R to indicate just one bolt. Like he uses a big R for the whole connection or something. Then he goes down to, he says, are your spaces, this is the strength based on bolt spacing between the bolts of interior bolts. That's like this. Our bolts, they're either three inches is pretty common and recommended, permitted two and two thirds times diameter of the bolt. But, you know, you may have to have a discussion with the guy with the wrench or the lady with the wrench because that's, that's getting it pretty close. Ours were three inches. They were 58 KSI or 65 KSI ultimate on the steel. That was 58 and 78.3. You will also notice that for a standard, well actually for any of these things, you see the 78.3 coming in a bunch of times and down here. That is limited by what they call the full bearing strength. That's the crushing number. In other words, the tearing of a plug on this size bolt was smaller than the crushing number. And so you can tell that crushing number because there's no reason for them to be the same like this in so many places. So that one was limited by crushing. So you actually have the numbers in this table for both tearing the plug out and the crushing strength of the plate. Now you say, well I don't care, they're good, right? Well yeah, they're good. If on the other hand I gave you a three inch spacing, seven-eighths inch bolt and ask you for a three inch spacing or for a two and two-thirds inch spacing, does the crushing strength control or does the tearing between the bolt holes control? Which controls? Tearing between these two holes are crushing of the plate for a seven-eighths inch bolt spaced at two and two-thirds of times seven-eighths on a 58 KSI plate. Well, you see the 72.9? I don't see it anywhere else. Look at this 91.4, 91.4, 91.4. Guess what that 91.4 is? That's the crushing of the plate and that means that because this isn't this number you see repeated a whole bunch of times, that was controlled by pulling the little plug out. They say, how the devil would I ever figure out that? You don't have to. You just, if I ask you that, then you're going to have to work them both out and see what controlled when the 72.9 came out of your calculations. That is correct. Plate crushing is where the little L clear was so long that it just wasn't possible to pull out the plug and the plate crushed. And do you remember how much it crushed when everybody said, no, no, no, no, no, no, that's no, no more please. Quarter inch. That's exactly right. And he tells you that down here incidentally. He says spacing to get the full bearing strength possible under any conditions including pulling the little plug out or crushing the plate. See that there? That's called s full a says decimal value has been rounded in there. 16th of an inch for these holes right here. These are how long the spacing would have to be. And I don't really see where he says that that's what these numbers are. But that's what they are. In other words, if you're bolt spacing between the two holes is this much or more, you'll crush the plate. And you can forget about calculating the L clear shear the plug out numbers. It's what he calls spacing required to get the full possible bearing strength. Okay. Now you just have to tell me to go up or down or left or right there and down a little left or right over to the right or left. Okay. This one all the way to the end. Okay. I'm sorry that that is correct. That's what he's telling you here. If you have your spacing, this is Oh, I see what you're saying. That's where the 63 5.3 is coming from. I thank you. I forgot about that. You're right. This is where the 63 is coming from. It's coming from this number right here. Because up to that number, it's a tie between crushing the plate and pulling out the plug. And he's saying that if you have the spacing bigger than s full, you will get 65 3. So that's how I was easily able to find out the duplicates, you know, you'll find nothing any, nothing matching itself like 65 3, 65 3, 65 3, that's crushing the plates or 58 Casas deal for this one is 73 1. There you see the 73 1, 73 1, 73 1, 73 1. And also you'll notice on the second layer of all this, there isn't anything bigger than 73 1 because it can't be because you've crushed the plate. No star when plate crushing starts to control this happens. This is a table for a one inch thick plate that we don't know what the thickness of the plate is. He says, look, I'm going to just give you the numbers for a one inch plate. And if yours is only half a inch thick, guess what you should do? I said, I don't know. He says, well, then I don't think you ever ought to do this for a living. And next, well, okay, I got it. You multiply times a half because you only get half of these numbers. So that's what we're going for now. We're going for bearing strength, inner bolts, edge bolts, edge end bolts, inner bolts. It is a three quarter inch group a three inch spacing, three quarter inch. A group A has got nothing to do with it. Because the bolts aren't ever going to fail in bearing. S is equal to three. Here's our S is equal to three. Here's the type of hole that we have. This is what we're talking about right here. We have one of these kind of S abuse in there. 58 was our A36 steel. We go to the three quarter inch bolts, 78.3 kips per inch. 78.3 kips per inch, 78.3 kips per inch. Since our plate was only three eighths of an inch thick, for the thinner of the two plates, we get 29.4. And of course, it's already got the fee on it. For the edge bolts, it only gives you two edge distance, one and a quarter and two. If you don't have that, you can either interpolate or you can do it yourself. Hours on the end was, go back and take a look at it now. Hours on the end was an inch and a half. And so this is the strength between those two bolts. And here it is for the end. We don't have an inch and a half. So I'll tell you what, what we'll just take, what I was trying to find out a minute ago, let's just take an inch and a quarter. If it's still okay, then we know ours is at an inch and a half is perfect. It's okay. Have a standard hole. Here are only two choices. 58 ksi steel, three-quarter inch diameter bolts have a strength of 44 kips per inch thick plates per bolt. 44 kips, our plate was three eighths of an inch thick, 16.5 kips per bolt. And I forget what we got, but that was more than we needed, whether we had his end distance and ours gave more. So that's a quick way to pull all the numbers out of the tables and you're welcome to use them. The table itself, what page? It's on page seven dash 28. All the others are very close by. Design examples, nothing more than an analysis example. All you got to do first is pick something and try it out. You can kind of go backwards because you can use the tables. And you want you to use a certain size of bolts, once a five eighths inch diameter bolt, so you can go in the tables and pick out how strong the bolts are so you figure out how many you need. So he puts the numbers in. You could put eight in a row and eight in a row and make the plate a little longer and destroy a little less of its net section fracture or you can do it like this. Somebody's got to decide that's part of the part of the game. And from then on, that's all you're going to do. Same thing we did before, found out how much load, one for two dead, one for six live, calculate how many bolts total load necessary divided by how strong the bolts are in shear. You say, well, wait, what about bearing? I'm going to assume shear controls and bearing going of work. Why do I know it's going to work? I'm going to make it work. I'm going to make the little slot links longer. You say, well, the little slot links may get so long that they won't control crushing will control. We'll find a way. You can almost always find a way. And if you can't find a way within what you're probably going to do is you're going to have to add some more bolts to get the bearing strength down where it's acceptable. For instance, if you have a plate and you decide to use one bolt, you may have a problem. That bolt may be so strong it doesn't work in growth section yield, it doesn't work in bearing, it doesn't work in crushing, it doesn't work in anything. You say, well, okay, I'll move it back same plate, I'll move it back to here. Oh, that may not be good enough. You need more bolts. So you can check the numbers here. Got several more examples. And they're all the same. Of course, that's why this is such a nice book. Got tons of examples so that you can go see different numbers. Check them out. A lot of repetition, tension area, obviously block shear. You see anything I got scratched out? Oh, that's a loud stress is why. But I'll leave it for you to check out these examples. See you next time. Thank you. Yes, sir. I was doing the homework for on Wednesday. I was able to do the first two problems. Okay. The last problem is 7.8. Yeah. And I thought you would cover it in class today, but you didn't. Well, I sure been trying to keep up. But in other words, you need today's lecture to work seven, eight. Well, yeah, I mean, I mean, I looked at it, but I was like, no, I mean, I could teach myself from the book, but I just thought maybe he's going to teach it today. So I waited. What, what on it was different from what we've done so far? No prying. No, I don't want you to work any of those problems. Okay. Then it was intention. We haven't done the tension on the bolts yet. Yeah. All right. I understand. Oh, minute for now. And I'll email everybody you're going to email me first because my mind is you're going to say problem 7.8 not do till you cover it in class assigned them. Okay. And I'll forward that to everybody. Don't know who is next. Yes, sir. Um, last after the test, when I went in there and sat down on the computer, the only one that was a gentleman in a cross, I guess he was working on the test. No, I don't think anything. I just, just don't know. No, not a problem. No, but you wouldn't know. You wouldn't even know who he is necessarily. You know, you would just go ahead and talk about the quiz. So I need him someplace else next time. Yes, sir. No idea. Before the Q drive. I'm hoping, you know, at the very least, since you've had it, you know, that may help you decide, but I'm really hoping to have them by then. Okay. And so you don't want me to pick on you when you come in late? I mean, what's it? What fun am I going to have? If you come in late and I start on you, we'll just go like this. You know, and I say, okay, okay. All right. Thank you. Sure.


A double header set on a day that can be branded do or die for two teams in Jamaica All Schools and Ingenious Elite but before that clash Lorde Hill Lions and Rush Select Academy locked horns. Coach Tom Durkin made 10 changes from the team that defeated the Jamaicans and it showed in the first half as a second team were unable to show the same quality from a day earlier. At the half, 10 changes were made with only the goalkeeper remaining on the field. Even though Lorde Hill Lions took the lead within two minutes of the restart, the difference in class was obvious. Rush Select replied with five unanswered goals. They topped off the win with the beautiful free kick. Lorde Hill Lions 2, Rush Select Academy 6. We decided we would rotate the team to give those guys a little extra rest and we told the first group, hey, if you do well, you stay on. So we'll probably use the same strategy Saturday and hope for the best that we can not make it through till Sunday. Next up were the Jamaicans in a must-win game and they were indeed fully focused in the locker room. The Jamaicans made four changes from the team that lost to Rush the night before and from the start they looked like a team on a mission. They took the lead through guess who, Taheem Dixon of course and his manager from Clarendon College made the trick to see it first hand. The Jamaican All-Schools team looked much more settled against a very Jamaican ingenious elite team as Omario Henry of Heidel made it 2-0 in the 23rd minute. The Jamaicans now coasting but no more goals before the break. In the second half it was much more of the same and after 16 minutes Dixon showed why he's one of the best players in the tournament with the second goal of the match it's fourth in two games. Both teams rung in the changes and the Jamaicans continued to press for more goals with Dixon seeking his hat trick but it was not to be. Final score, Jamaica All-Schools 3, ingenious elite, nil.  I mean kudos to the boys, they dug deep you know after a rough game last night come back to the tonight win tree love you know, credit again. All we need to do is take care of business Saturday you know and leave it up in the hands of you know the father.


Okay, welcome to Python for Java coders. This is lesson nine. I've been at it for two hours now and this is the last one I'm gonna do today for sure. So in this lesson, we're gonna take a look at how functions or methods, whatever you wanna call them, work in Java versus in Python. Okay, so let's get started. Again, Java, you need class structure, Python, you do not. So we're going to make a method called printpy. So in this case, I am calling the method. Again, notice, camel casing versus snake casing. So then if I scroll down here, you'll see I've got this method, public static void printpy, system out printlin 3.14159. So in Python, the equivalent code would be the following. Def means define printpy, parentheses, colon, because we always use colons. And after colon, you're always gonna see an indent. So you can see which is part of the function, which is part is not. And print 3.14159. And it's a number, so I don't need to put it in quotation marks, although I could. So let's go ahead and run this and let's see if it works. Okay, very interesting. Okay, at this point, you think, wow, that's kinda weird. The printpy method's been defined. I've called it, but it says that it's not defined. So here's a little bit of a difference. In Python, you've got to define your functions first before you can call them. Now in Java, I guess because it's pre-compiled into bytecode, it reads the whole thing and it knows that you're going to have this method eventually.  So let's go ahead and run that, make sure it's working. Okay, very good. Now notice in Java, I had to declare this as a static method because it's not attached to an object. Python, I didn't have to do that. I had to declare the return type, avoid in this case because there's no return, didn't have to do that. And here's the same thing, there's nothing in the parentheses, so I didn't have to put anything there. Let's move on. Next function is print. Let's see, I'll put this, oops, old habits. Call functions and up here I'll call this define functions and functions are methods that you can use interchangeably. So the next one is print double two. So let's go find print double. Okay, so here's our definition of our method. So again, don't worry about public, don't worry about static, don't worry about void, don't worry about anything like that. Just go ahead and print double. And now in this case, it's using X because we are sending a value. Of course, here we had to declare it as an int, here we don't. And then I can go print X times two. Okay, so I'm gonna go ahead and run that. And what did I do wrong? Print double, ah, forgot the def. And go ahead and run that. And there is the answer, which matches up with what we have here. Now here's something interesting, two interesting things about Python. I can send anything to that because there is no strict typing. If I wanna send, you know, my name, my nickname will say Tokyo EdTech, I can send that. Let's go ahead and run that. And this is another interesting Python thing I didn't talk about in the string video, but if you multiply a string, it just prints it out twice. Now how cool is that? That comes in handy in a lot of situations. Okay, so if I'm gonna put that back to a, now if I, again, if I put that as a string, I wanna see two, two. But the, what I wanna see is two, times two is four. Interesting. Next one, okay, is getpy. Alrighty, this is an interesting one. So, let's say def getpy, again look at the snake casing. And this is just going to return 3.14159. Again, I don't have to, where's that print getpy? I don't have to declare it static, don't have to say I'm returning a double. I just do it. Okay, so here I'm gonna go ahead and to match this, I'm gonna say py equals getpy and print. So I did not need to declare that at all. Cause it knows that I'm returning a double. Okay, this is gonna be a double now. If I had to return a string, it would be a string. Next up, greatest equals getgreatest. Okay, so this is where it's getting a little more interesting. Getgreatest, and let's go find the definition down here. Oh, I should have done get.one, missed that one. Let's, yeah, get.one, let's go ahead and do that one. Get double. So in these functions, in these methods, here I was not sending a value and not returning a value. Here I was sending a value and not returning a value. Here I was not sending a value but returning a value. And in this last example, I'm gonna be sending a value and returning a value. So get double. So I think I used x, get double, yeah, x. Again, I don't have to declare it as an int. And I'm just gonna return x times two. Then when I call it down here, I'll say y equals get double, four. And then we'll go ahead and print y. That should give us eight. Okay, so far so good. And our next one is getgreatest. Okay, so I'm gonna go ahead and define that. Define getgreatest. And this is just an example to show you that we can send more than one value. Again, in Java, you need to declare it, and by that I need you not, colon. And then if, again, the parentheses are optional. You can have them, you do not have them. Say return x, else return y. Again, parallel structure, but you don't need the braces or the semi-valence. I'm gonna go down to here and actually try and call this method a little bit. So I'm gonna say greatest equals getgreatest. We've got 42 and 16. And then go ahead and print greatest. And of course it should print 42. The answer to life, the universe, and everything. And the last one. Okay, so in this case, we're actually gonna be returning a Boolean instead. And again, the function definition goes before the function call. So I'm gonna say define is even using my snake casing, x. And if percent, oops, x percent two equals zero. Again, two equal signs. Return true, true is capitalized. Else, oops, forgot the colon. Return false capital letters. And in my calling part here, I'm going to go ahead and make a little if statement. So if is even, 42 colon. And again, I didn't need these extra parentheses. I could have just done this. Whatever you think makes it look nicer. Print even. And otherwise, of course, we've got two options. Print, oops, odd's not odd. Let's go ahead and run that. And we should see even at the bottom. It takes a little bit of time sometimes. So we're dealing with a remote server. So maybe they get busy. And it is even. Let's go ahead and just try a different number. Let's try 43 just to test it and make sure our code's working correctly. And odd, there we go. Okay, I'm gonna put that back to 42 though, because that's a better number. So you can see here with the difference between a couple of differences between Java and Python. Python, you need to declare the function ahead of time before you call it. We don't need to declare whether it's static or non-static. It's done a different way in Python. We don't need to declare whether the return type is void or double or int or boolean. It's just automatic. We don't have to declare the values that we send the type as integers or whatever. We just send them and hope that we send the right thing. Now the advantage of the Java way of doing it is that when you compile it, it catches a lot of errors. Okay, so for example, if I had done this, it would catch that error. It would say, oh, you're trying to send a string even though it's looking for an integer and it won't let you run that program. It won't let you run it until you correct that issue. That's the advantage of doing it the Java way. It's also much, much faster. The Java code is faster than Python code, generally speaking. So it's an advantage, but as a programmer, you have to take care of a few more details. So you have to think about what's the trade-off for you as a coder or for you as trying to solve a particular problem. And yeah, so when you're declaring a function or a method here, you say public. You have to declare if it's public or private. Python, it's actually very, very different. Java's really strict with that. I'll just show you a quick example to give you an idea. If I do private here, the equivalent in Python I think is you do one underscore before and after. I can't remember if it's private or if it's two underscores, one's protected. I forget the actual rule on that. I should have looked it up before I did the video. I'm sorry, but anyway, you don't actually use public and private. You use underscores to indicate whether it's public, private, or protected. And even if it is private, you can just ignore it, which is kind of cool. Which is I think kind of cool, but it's probably bad programming practice for large programs, especially. So there you have it. That is lesson nine. I have done this in about two hours, this entire series. And I'm gonna stop there. And because that's all I have for you for this particular thing, hopefully that will give you a pretty good idea how to at least get you started on your Python journey if you have already gone through at least part of your Java journey, which has nicer alliteration. So yeah, thanks for watching. Subscribe if you like what you see and keep on coding. Take care.