Thank you very much David. Appreciate it and good afternoon everyone. So when I was asked to come and talk at the present at the FIBO conference, I had to make sure that I was going to be doing the right thing. So did I need to turn up and show my rippling muscles off at the world's premier fitness and bodybuilding conference in Germany? Or did I need to teach our kids to find their hidden artistic creativity at the FIBO Kids Art Academy? Or maybe I needed to earn my fortune by applying Fibonacci mathematics to the financial markets? Or maybe I needed to come along to talk at this conference about the financial industry business ontology. So my point is that really understanding the information, understanding its meaning is essential to ensure that you don't turn up to a business conference wearing your speedos. So within the enterprise we have this huge amount of diverse information and what we're helping our customers to do is to really unify all of that information that exists in different systems in order to get an understanding of the risk at an enterprise level, such that they can control and manage that risk. But also to be able to gain a real 360-degree view of the customer and to be able to gain insights into the financial markets. So we see FIBO and FIBO V as a real powerful enabler into addressing these key business drivers for the banks. And you might think that semantic technologies and ontologies are really bleeding age and certainly they are new, but actually we have hundreds of customers within the Fortune Thousand that are now using semantics today. So this has moved away from bleeding age into real technology that's been applied at enterprise scale to solve real business problems. And in banking we see the ontologies being used to support the massive burden of regulatory compliance that the banks are mandated to be able to automate business processes that are very rich with content and to be able to gain new insights within their business analytics layer because they're able to unify information and deal with new information or different or wider range of information types. So the problem really, particularly for those organizations that have consolidated and grown for acquisition, they have all of these different systems in different divisions of the bank. All of those systems use different schemers and they all use different vocabaries. And so everything describes the same thing in a different way. And for the end users, this means that they struggle to really understand the data, to find the data that's meaningful and important to them and to know its real heritage and trustworthiness. And also it's very difficult to be able to work with all the unstructured content such as agreements and contracts that exist within the organization. So sometimes banks will try and address this through traditional ETL processes. The problem with those is that they're very time consuming to build, but more so they're very brittle as the data itself changes or the types of questions people are trying to answer change, then these ETL processes can break down. So Fiber provides a real solution to a lot of this problem because when combined with other taxonomies and vocabaries covering issuers and counterparties and securities and instrument types and all those other things, if you can combine those things together, link them in a way that makes sense for the bank and be able to enrich them for the purposes of the bank, then you've got a real powerful source of truth that can be used across the enterprise. So that can be integrated into different line of business applications and data sources, but also it can be used to enrich the transformation of data as it comes into data warehouses, data hubs to make that information well described, consistent in its vocabulary and really meaningful to end users. So data columns that are similar can be identified and combined together across multiple systems. Data filled with different vocabulary can be mapped to a consistent set of vocabulary, so a single meaning for a single thing. The data becomes much more traversable and understandable by end users because it's well described and the facts and information that are contained in unstructured documents such as contracts and agreements can be brought into the mix as well and combined with the structured data to answer important questions for the business. So as you'll see in the live demonstration, assuming everything goes well, there are three parts that make up SEMA4. First is a platform for ingesting, customizing, sharing and managing taxonomies and ontologies and we use the SCOS Excel format and we've focused very much on making it really easy for business users, subject matter experts and analysts to be based the vocabulary and structured data, but also to be able to extract facts and relationships as RDF triples from unstructured data which can be stored in the triple store of your choice. And then we also provide a whole set of interfaces and components for knowledge discovery and surfacing of all of this information for end users. That SEMA4 can run on-premise or in the cloud. Just a couple of examples before we go into demonstration. So first of these is Thomson Reuters and I use this case not only because they have a lot of financial markets information, but because they've grown through a lot of acquisitions and actually the data that's behind all of those TR applications exists in many many different systems which have been acquired over time. And the problem that they face is that it's very hard to understand what data is in there and what the data really means and how to use that even for developers it's very difficult for them to build new applications or to enhance existing products for their customers because the data is so opaque. So what they did is to build an information layer which allows them to describe all of that underlying data to organize the data into hierarchies so it's easy for people to reverse and access and to create rich metadata that really helps people to correctly understand that data. And so on top of that semantic layer they're now able to build new products and enhance existing products much much more quickly but also be able to for their end users to give them much better access to be able to report and query and analyze that information. So rather than ripping and replacing a whole set of systems which were simply deemed too expensive and risky they've been able to abstract the problem away. The second example is with KPMG who are providing a service by which tier one and tier two investment banks can onboard customers. The process of onboarding a customer involves hundreds of different document types with thousands of different information data points required to actually onboard that customer correctly. And so what they've done is to use semantics and ontologies to be able to automate the processing of all of these different documents as part of the onboarding workflows to cross-reference all the data from these different documents to make sure that everything lines up and there's no suspicious behavior and then as a result onboard the customer in a fraction of the time and create all of the reference data that then feeds the other banking systems involved in those counterparty interactions. So it ensures compliance, it cuts time and cost but it also creates all of the reference data required. So just to summarize, we provide a platform by which you can ingest FIBOV very easily, share that around the organization to get feedback and collaboration with different parts of the bank to be able to apply that to all of the downstream systems to provide a single source of truth based on FIBOV and to be able to automate the process of getting that data into data lakes in a consistent and harmonized fashion. So I'm going to hand over to my colleague from the live demo. We're making the URL for this instance of semaphore in the cloud available. So if anybody would like to actually access FIBOV through the software they can do so just based on this URL which we'll provide at the end. We can see okay. So yeah so what we want to do now in this section is just give a live demo of actually a few different things. So first the FIBOV itself, I should be very specific here and then secondly some of the other things that you'll want to model as you go through expanding FIBOV into specific use cases across the organization. So some of the things I'll show are some of the things that we did on projects like the Thomson Reuters one like the KPMG project. But we're going to start with FIBOV. So as you come into the tool of course you can have a look at all of the information that FIBOV has. And I think a lot of people have already said this that there's kind of a challenge at the moment with adoption. So you know how do we get everybody to adopt FIBOV and you know by exposing it to as many people as possible in the most usable way possible hopefully that's going to aid in that adoption. So as we come into the ontology we can of course see you know all of the things of want or the concepts that have been converted through those spin processes from the owl into skulls exhale. And as we look at any of these we can then start to see all of the definitions that form the model itself. What we can also do in semaphore is then additionally visualize that. So we can walk through that more as a graph more of a chart view. So we can drive into you know lots of the different areas see that. And then we can see all of the additional metadata again. So proof that it is going to go wrong. Let's try that. There we go. It's just a bit slow. So what we've got there is now you know a nice way that people don't have to understand you know all of the technical details of of the semantic technologies so of skulls of RDIF of our constructs. But now it can come in a very easily navigate around the ontology find out what things are, find out what things mean. And so you can see here the definition of a contract all the different concepts that it's related to and how it's specifically related to them. So that's the first point in adoption. So let's get people to see it. Let's get people to start to understand it. Start to see if it's going to be useful in their environment. The next piece and I think it's alluded to on a couple of other talks is then how do we get comments back. So as you spread it across the enterprise then there's features in the tool for example to leave comments so you can get all the people in different departments collaborating together on the ontology and potentially these comments could also then and suggestions be fed back directly to the EDM council. So you've got mechanisms in the tool automatically potentially to feed that back. But then the next stage is always going to be extension. So there's always going to be a few things that are different in my environment or new that we need to create and control. So what we can do in the next step is actually start to customize the FIBO V vocabulary. And we don't want to really alter the main vocabulary. What we want to do is link to it so we can reuse as much information as possible. So what we're going to do here is actually instead of creating anything from scratch bring in my FIBO V model and then have an instance where I can just extend it to my own use cases. So if I come in here and have a look at the model now we have the well hopefully it's thinking about it. Here we go. So we now have the model linked in. So what we can see there is in front of every concept or we will and again in a second because I clicked it too fast. We'll see a link in front of each concept. So that means it's just linked in. It's a reference to the original FIBO V vocabulary. We're not duplicating anything here. Anything we do here is going to be directly linked back. And then we might want to extend it. So there's certain things that our kind of clients and prospects have talked about. And if we want to we can go into things like dates, specified dates maybe. We might want to specifically add in a piece of information. It might be called a settlement date. Let's do that again. Here we go. So what we can do here is then add in things like the settlement date. That might be a new thing that we want to monitor or talk about in the organization. And we can add that. And then we can also add additional definitions to it. So all of the information inside the ontology is completely customizable. You can put whatever relationships and information here. And what I'm going to do with that in a definition and actually a definition of origin. And it happens to be provided to me before. So I've got this page or specific section of page from the MSRB. And I want to come in here and add that as our definition origin. So very easy to come in and extend it, to define it in ways that are more suitable for the applications that you're using. Once we've done that link, one of the interesting capabilities we've got here is actually to bring in that information directly that page that we saw just a second ago. So if I actually review this in the side panel, again we'll see if my internet connection is going to allow me to do this. But what it's going to do is automatically look up that URL and bring back the page and the specific definition for it. So again, we're trying to be as interoperable as possible. We don't want to be copying lots of data from here, there and everywhere. We wanted to link to either directly to the FIBO V vocabulary, or to the external references as well. So you can see the page being displayed there specifically to say this is the definition for that concept. So that's our starting point. We can start to adopt the specified vocabulary, but then again we may want to extend them. So one of the big challenges for Thomson Reuters, for example, is actually then detailing and knowing what information lived in which sections of which system. So again, they added that to the model. So for settlement date, for example, what we could do is say in a specific system, it might be referred to just by settlement. That might be its title. So what we could do there is specify a specific alternate label to say in our reference sources, this is how we might identify a column or field. And of course, you'd have many, many different ones of those for all the different systems you have, all the different data types that you have. And again, it might not be done manually, you might have profiling tools that actually build this information into the ontology. But the idea is there, it's customizing, you can put this information in, and then as you go to query the ontology, you get all of this information back so you can easily connect back to all of those different sources that you're describing. So as we then look to extend it even further, and as I think as the previous conversations mentioned, what you really want to do then is extend it with vocabulary. So the terminology that backs the fields that we've got. So once we know where everything lives, we now need to know how to standardize it individually. So in one system, you might have an issuer name, a counterparty name. In another system, you might have a Dunham-Brown Street number. You might have a different way of referring to exactly the same thing. So once we've normalized the where things are, we now need to normalize what is the information inside those systems. And again, we can do that. In this case, I've got a different ontology and many different sources for these, counterparty ontology. And again, as we go in here, we'll see all of the information. In this case, just been imported again. So we can come in here. We can see the additional information. And as we come in, we'll see all of the counterparties. And we'll see again, a lot of additional information that's relevant to any of those counterparties. So if we click on one of the companies, we can see that we have, excuse me, a number of related concepts. So the industry that the organizations are operating in, locations that they're operating in, that of course links off to then currency exposure, many different ways of kind of modeling this information. But then you've also got all of the alternate labels. Again, the terminology, the tickers, the other ways of identifying these organizations. As we look down the list, we've got things like the Dunn's numbers, you know, other information that again might be relevant when we start to query. So with 7.4, you've got a pretty easy tool to, you know, build out, to adopt FIBOV, to build it out, to comment back to the standards council and internally so you can build out the right structures, to then build out the terminologies that you're also going to use when you standardize the information. So again, you know, as Toby mentioned, the goal of the design here is to make it as easy as possible to make it accessible to the business. And so that's why we've gone for a lot of the design choices that we have. But then we've kind of covered two scenarios so far. So we've discovered or covered the ability to adopt the standard, maybe customize it a little bit to a specific organization, and maybe then to extend it to understand what fields are using which data and what data is being used in each field. So we've modeled that out. So now what's the next step is all of that and structured content. So now you've got all of the structured content dealt with, you need to get in there and analyze all of the other bits. So all of the contracts, anything else that comes in that's not already structured. So again, what we've got in there or in here is a different model for dealing with that kind of capability. So what we're doing in Semaphore now is defining a way of extracting information from each of those contract types. So as Toby mentioned, there's hundreds of different documents that come in. There's potentially hundreds of different fields in each of those documents. And we want to be able to take them out of that unstructured text, make them structured so we can now again incorporate them in our analytics and our queries. So this model is all about the document structure and not really about terminology anymore. But as we look through some of these, what we'll find is that they actually link very nicely back into the definitions in Fiber. So a lot of the elements that we might want to extract from each of these documents actually tie nicely back into the contract elements that are defined in Fiber. So what we can see here is all of the different document types we can work with. Obviously, there's many pages here. And you can see all of the things that we might want to extract. So as we go through an article of incorporation, we obviously want to know the company that that's incorporating. We want to know who the directors are, what the addresses are, maybe what the purpose of the company is or any clauses if we're going through contract. So we can use the ontology editor again to maintain all of this information to make it very easy for business to use. But then as we look at the results, we actually look at content coming in. What we might have is very different documents. So as we come in, there's a couple of examples of articles in corporation. So one, very kind of textual, very kind of decently formatted. It's come in obviously in electronic form already. So that makes it slightly easier for the extraction. When we look at the other example, of course, that's very, very different. That's come in as a text document. It's been scanned in OCR. And then we're going to try the same extraction form that document as well. So as we do that, we can come into the classification engine. We can literally, obviously you wouldn't do this one by one in real life, but we do this just for a demonstration. You can come in here, put those documents in and then see the kind of extractions that are coming back out. So as we see on the right hand side, we've got the representation of the document. On the left hand side, we've got all of the things we tried to extract and all of the things that actually were successfully extracted. And so the key behind this extraction is not that we're just looking for entities and things in a document. We're looking for entities in a specific way, in specific sections, so it means exactly what we want it to mean. And so as we look through this example, we can see that immediately that we've actually identified the correct document type. It's an article of incorporation. That's the first step, the document fingerprint. Then once we know that, we know the fields that we want to extract from this document. So from the article of incorporation, we definitely want to get an entity name. And again, we've got that entity name very easily extracted. So when we do these extractions, then we've got a couple of different options, we can actually then manage that and put that back into the context of the ontology. So where we had that counterparty ontology a second ago, that Florida Greenways and Trails Foundation might have already been a known instance. So instead of just building a piece of text here to say this is what the document's about, we can give it a URI, we can say this is your reference in the ontology to your counterparty. So again, making it very connected. We also then do extract just pure entities, things like dates, things like people's names that we might not be controlling yet. So dates we probably never want to control, but people name we might want to monitor over time. So again, that could be a source of information of feedback into the ontology itself. And then there's also information that might be purely textual. So the purpose of the organization, for example, might not just be a simple thing, it might be actually a complex piece of text that does need further processing, further review. So what you've also got then is around the core semaphore tools, you're going to want to set up the workflow that actually helps you validate all of that information that's being extracted. So it's definitely not a 100% tool, it's a way of reducing the effort of manually processing content on contracts and then building ontologies, building semantic data warehouses with that information. So hopefully, mostly those demos actually worked a little bit slow, but I think that's a success in its own right. So really in summary, I mean, the semaphore tools can help with a lot of things. What we really want to do is help people adopt FI, though, so trying to make it easy for them to see it, to view it, to understand it, then to use the ontology editor to expand on that, to make it relevant to themselves, to expand it with the reference vocabulary that they need to, and then to be able to process the unstructured content to bring out of all of those facts and information so that all of the data is described in exactly the way you want it to. And that, do you want to talk about the trial? Yeah, the URL is available here. We've also got some fact sheets, so the URL is on there. If you want to take a look at FIBOV loaded up in semaphore on the cloud, all you need is that URL, so feel free to grab a copy of that. When you've decided that you can't live without it and you want to buy it, then there's my email address and happy to take any questions. Dean? So Dean, perhaps I'll jump in and actually answer the question because I think that's really on us, in a sense. And what we've already positioned ourselves to do is that, so the question is, is how do you really transition from FIBO vocabulary? And this was a great demonstration of the operational use of the vocabulary itself without going to the RDF OWL implementation. However, if you did want to transition to the RDF OWL implementation, how would you go about doing that? And what would be that migration path? And we're actually providing that link because what we're publishing in the FIBO vocabulary, which we didn't see here, but it's rolling into our basic release of FIBO vocabulary, is the link to the actual element in the RDF OWL ontology, so that we'll be able to show the linkage and interoperability. So just by having that already, we're well positioned to align with the RDF OWL. But Toby Stewart, did you have any other comments to extend beyond that? Okay. And there's a one back there has a question. So I think it's an evolutionary process and many organizations, as Dean had alluded to earlier, are really not ready to get their arms around the much more expressive but at the same time complex RDF OWL representation of the same concept in FIBO. So the SCOS representation is much closer to a vocabulary that organizations can more easily assimilate because the model is much more coarse grained if you will in many ways and aligns much more easily with the notion of a vocabulary of a glossary. It also drops very easily into vendor products that have positioned themselves to support SCOS vocabularies and it provides the visualization. And this was a very nice demonstration of showing the multi-dimensional visualization of concepts with their superclasses and subclasses in a broader narrow within relation as well as the related properties and attributes and the metadata. So I think as far as a evolutionary process, this provides a very good initial ability to be immediately valuable for a BCBS 239 type of business need that will allow companies to begin to start assimilating the value of ontology and then using this as a stepping stone to migrate to the RDF OWL and it's not an either or it's based on use case we will support both. Both our vocabulary and RDF OWL have operational benefits for organizations. So with that we are out of time. I want to very much thank Toby and Stuart from Smart Logic for succeeding with a live demo which was was really awesome and thanks everyone. So what we're going to do is resume at one o'clock after lunch. Now for those of you who have been speakers this morning, Dennis wants to get a picture.


It is a remarkable dichotomy in many ways. Clark is the most human of us all. Then he shoots fire from the skies. And it is difficult not to think of him as a god. And how fortunate we all are that it does not occur to him. That quote is a quote from Batman. And I've always wondered, what is it like being Superman? The man who has everything. The most invulnerable being on the planet. Faster than a speeding bullet can lead buildings in a single bound.  Even though he himself is just a man. I wonder what it's like to be able to hear every single sound. Every single human on earth. Even sorting out the different voices he hears. Bruce Wayne, Jimmy Olson, Diana Prince, Lex Luthor, and of course, Lois Lane. His history is mostly known. Born on the planet Krypton, brought to earth as a baby, and was raised by two loving individuals, Jonathan and Martha Kent. And due to yellow sun exposure, people of his kind, Kryptonians, gain superhuman abilities. But how do you humanize Cal-El? The character that can be seen as a god amongst men. The many depictions of Superman fascinate me. Cartoon Network's Justice League and Justice League Unlimited, as well as Superman vs. The Elite, are all proper depictions of Superman's restraint. And is restrained from killing. The extended universe Superman understands sacrifice, but he does not capture the same restraint. And with this outcome, people believe that he believes he is the judge, jury, and executioner. When he himself does not believe that. And with that, I believe he is the most brooding of all Superman depictions. And then following that, there are hundreds of reiterations of comic book Superman. I think All-Star Superman is one of the best re-imaginings of the Man of Steel. I'm going to show what is probably the most iconic scene of the All-Star Superman comic. The scene of him talking a girl, Regan, out of taking her own life. I found this scene very interesting, because at that moment, Superman was dying, and he was in his final day. He was in the middle of completing his 12 labors, the modern version of Hercules. Superman was in the middle of conquering death, creating an artificial heart for the sun, and leaving the formula for a second Superman behind. To talk a lone individual out of taking their own life. Because Superman believed that this was the right thing to do at that moment. And that this girl, Regan, whose therapist couldn't make it on time, needed someone. And Superman was there for her. That is what Superman represents. He is the pinnacle of humanity. And it is also what makes Lex Luthor his perfect adversary. For the simple fact that Lex represents everything that Superman is not. He represents humanity's ugliest side. The one that is rooted in arrogance and pride. Luthor has the intellect to cure cancer, to help people. And as Superman states, he could have saved the world years ago, but instead, wastes his time on trying to defeat Superman and prove to Metropolis that he is better, and that he will be the savior of Metropolis. Before reading about Superman, I didn't like him very much. Over the fact that I thought he simply represented power. I thought the alien of steel solved his problems with his fists. Superman is a Kryptonian, with power levels that are unrecorded, speed that is unrivaled, and a genius level intellect. I thought Superman didn't feel pain. I thought he couldn't. But what I would soon learn is that Superman's struggle and pain was rooted inside of his humanity. Superman's identity as a hero is what pains him. It is the fact that he cannot save everyone, which grounds him. Through experience, Superman learns that even saving one person, if they need you, is more than enough. Superman is not meant to be a god. He does not have obligations to humankind, and it's his dilemma and that burden that he holds every single day is that he wants to save everyone. But he can't. So he leans on choosing the right thing, always. Superman is a product of his environment. He isn't a good person because of Krypton, or because he has these incredible abilities. If we strip Clark Kent down to his core and remove him of all the powers that he has, all of his decisions would be the same. Clark Kent would have the same compassion, the same love, and he would inspire hope to mankind in the very same way, because he was raised by two good people, and because his moral compass is so rich and so good. Superman, the alien with a human heart, a heart that has compassion, and an ideal that we should aspire to. Superman, the most human of us all.


Connective tissues are an incredibly diverse set of tissues. So let's look at the functions or some characteristics, some significant characteristics of connective tissues. First of all, holy diverse. And when we get down to classifying connective tissue, we'll see the mad number of tissues that are included in connective tissue land. That's why there are 10 and a half of all of our tissues that we're going to learn today are connective tissues. Most connective tissues are vascular. Now think about that for a second. So what? Well, why is this relevant? Connective tissues are vascular. Epithelial tissues are vascular. All connective tissues, except for cartilage. Bone and cartilage are both connective tissues. Cartilage is an avascular connective tissue. And we'll talk about the significance of that when we talk about bones and joints. Otherwise, connective tissue really is how epithelial tissue gets taken care of. So yes, please be vascular. Connective tissues are where the cells and epithelial tissues were closely packed together. In connective tissues, the cells are usually far apart. And there's lots of stuff in between the different cells. In a connective tissue, there are no spaces. Now, I say that, and I guarantee in lab today you will look into your microscope and you'll be like, dude, this is an example of dense irregular connective tissue. And look, there's a space and there's a space. There's definitely things that look like spaces. And often in histology, the slides have what we call artifacts, which means there are spaces in places where that's not actually where a space is in life. It's a space because the tissue dried up and shrunk or the process of slicing it made a hole. And so sometimes you'll see spaces. So histology is kind of magic sometimes when you get to know like, is that a real space or is that not a space? And you will get a sense of it as we work through the course. In general, you can make the assumption that if you are in a connective tissue, you're not going to be seeing a defined space. What are connective tissues? Well, funny that you should ask such a thing. They do have a definition. Connective tissues are cells embedded in a matrix. Okay, look at how I'm going to do this. Cells in a matrix of ground substance and fibers. But of course, that is what a connective tissue is. You've learned that cartilage is a connective tissue.  These are examples of connective tissues that are like weird, like, oh man, that's a really diverse group of things. Plus you have like normal, normal connective tissues like dense regular or dense irregular connective tissue. Sometimes identifying the matrix of ground substance and fibers is easy and you can see the cells like embedded in there, other times not so much. The ground substance is like the, I don't know, I don't know. The ground substance is like the soup. It's like the, really, I'm going to throw this out there for you. It's like the extracellular fluid of the tissue. So really, this ground substance is whatever the fluid is that the fibers are sitting in. Ground substance includes the fluid plus any solutes in the fluid. Some solutes that are found. Peptidoglycans, have you ever heard of, so glucosamine? It's a supplement that you can take for joint pain. It's actually a superhydrophilic solute found in the ground substance of connective tissues like cartilage. So the more of these hydrophilic ground substance things like glycosim, whatever I just said, the more fluid that can be moved in and out of the cartilage. Moist cartilage is healthy cartilage because you remember it doesn't have any blood supply. So if you have a lot of water in the cartilage, you actually are going to diffuse your nutrients and garbage faster and more efficiently. So the solutes can play a really important role in sort of maintaining the characteristics of that extracellular fluid. In that fluid, now different connective tissues are going to have different things in their extracellular fluid. Think about blood. The blood plasma is the ground substance.  There's proteins in there and there's salts and all sorts of good stuff. But it's a very fluid ground substance. Fibers are found running through that ground substance. And we actually have three different flavors of fibers that we're looking at. The biggest, actually truly the biggest fiber that you're going to look at is collagen. They're kind of thick. They're strong. The nature of the fibers is going to tell you the characteristics of the tissue. The nature of the matrix is going to tell you the characteristics of the tissue. So think about that for a second. Think about bone versus blood. Both of them are connective tissues. Both of them have a matrix of ground substance and fibers. Bone matrix is solid. The solutes in the ground substance are calcified and the fibers are strong collagen fibers. Blood fibers are rare. There's not very many fibers. And the ground substance is lots. So the characteristics of our matrix will determine what we're going to see for our connective tissues. Collagen is one fiber type. We also have elastic fibers. There's elastic cartilage that is found like in your ear and the tip of your nose. The cartilage found in those places is elastic. That just means that there are these elastic fibers running through the extracellular matrix. And then there's also these fibers called reticular fibers. Reticular fibers, again, are just another kind of fiber. The fibers that we're going to see today in our studies, we're going to see collagen fibers and elastic fibers. And being able to identify the fibers will help you distinguish between different kinds of connective tissues and other things that might look like connective tissues, but actually aren't. So that's what a connective tissue is. Yaw. Excellent. Blood cells, I didn't tell you anything about the cells. Hmm, this will shock you. The kinds of cells that are found in connective tissue vary depending on the connective tissue that you have. Blood cells are found in blood. Adipose tissue, connective tissue, is composed of adipocytes or adipose cells. Bone has osteocytes. Most of the tissues have cells called fibroblasts. Fibroblasts. Blast, I don't know, we should look up what it actually means. But in my brain, blast means building. And so fibroblasts are blasting out fibers. It's like they're pooping out massive amounts of fibers. They're actually the fiber builders in connective tissues. They're building collagen elastic and reticular fibers and barfing them into the matrix, which is how you end up with them. In addition to fibroblasts, you have a doodoo load of immune cells in connective tissues. And they're doing their job of actually going around and patrolling the area. White blood cells are immune cells, and they actually can travel from the bloodstream and into the connective tissues.  Let's look at how we classify connective tissue, which is not a simple process considering how complicated the tissue or how diverse the tissues actually are.


In fact no let's start this video very differently. Let's start with you telling me what is your go-to club in the bag. Comments down below. So for me the most difficult part of the bag to fill is that long end of the bag and very much the difference between where your sort of final iron in the bag is up to your driver. How do you fill that gap and often if you can find the right club to fill it it will be what is your go-to club off the tee off the fairway. The most difficult shot in the bag which is very much those long iron replacements and the options are simple. You've either got hybrid, you've got fairway woods or you've got driving irons and they all perform very very differently. Some of them might be suited to your game some of them might not and the idea of today's video originally started with a review of the Mizuno Fly High driving iron and we will do that but we're also going to throw in a few added options into that mix and that's where it gets really interesting and through in a real dilemma for me on a personal level which will reveal as the video pans out. So in today's video what I want to explore is the differences between these three clubs because when we make some adjustments to the five wood and the two hybrid all the loss will be equal and that's at 16 and a half degrees which is where the unadjustable fly high sits but what are we expecting to see now the five wood is the longest shaft the two hybrid is then the sort of the second longest shaft and the short out the three will be the hybrid so from a distance perspective I'm fully expecting the five hybrid to be the longest of them and that will fall down to the two iron to be the shortest I'm also expecting to see a significant difference in ball flight and launch angle and again for me logically in the brain I'm thinking with the bulk and mass and the cg way back in the five wood that'll be the highest launch it will have the tallest peak height and again much flatter ball flight down into this two fly high so there the difference is the question is what happens when we start to record some dry ball data and does that ring true so in other words is what you think in your mentality and what the obvious things that you would suggest might happen do they ring true when I start it in some golf balls it's time to find out I think I am very much a strong advocate of getting as much loft as you can on kind of hybrids fairway woods I like the idea of kind of like five six hybrids and again five and seven woods as well I think they're a great help to majority of average golfers but we do need to look at the long end of the long end of the bag and even so much as options off the tee instead of driver which is something I favored in the past so for me the idea of playing a shorter length driving iron is really appealing I'm going to hit a couple of balls just with this fly high to start with now give you my sort of opinion and feedback on this club because ultimately that's where this video started that was where the planning was and that's what we intend to do it sits so nice at address I love they did what they did with the ES 21 wedges and then it's two colors it's this dark sort of gray color and then a silver top line silver face and I think what that does really well is it frames the ball and acts superb alignment aid the other thing to notice at address it's not overly bulky there's a but you do see a little bit at that back end and it's interesting where you go from when it's a game improvement iron you don't want to see any bulk and mass you want to see everything stripped down you want to be looking like a classic blade but when you've got a club like this you're under two iron with only 16 and a half degrees of loft you actually want to see a little bit of bulk because it's mentally telling you there might be a bit of help there so again just the odd mentality the golfer shines through there where it's okay for one club but not for another I'll hit like I said a couple of balls but I've got to say from a looks perspective and the black shaft as well it's absolutely stunning I would have no problems having this on the bag in terms of from a looks perspective the next thing you'll you'll hear hopefully is the sound and feel don't forget hollow bodied again very much in the vein of the hmb's which was a huge fan of in recent weeks in the 225 range this again is that from that mazuno pro the sound is very much similar to that hmb um yes it's hollow bodied no it's not forged they've put the face in this is similar to what they've had or not similar it's the same as what they've got in some of their fairway woods at the moment and again so a very sort of powerful ball strike um ball speed rather out of the face and it's sort of recognizable a really decent ball there to start with what surprised me about the fly high is the kind of things that I said just two minutes ago was you're expecting a sort of very low pace in ball fighting yes it does that but probably launch is just a little bit higher than I would have expected it to and also does it a little bit easier I've got this teed up on sort of a very low tee but something that I'd be comfortable with playing off the tee well it one more with this before we move on and then explain why there's a massive dilemma in this testing that we've did with this club and there's something I wasn't expecting at all that's a super shot that is I mean I'm amazed I tried the p790 drive an iron udi just a few weeks back and again I reported with that was just how easy these clubs are now to play I mean it's a two iron with 16 and a half degrees a loft it would have generally frightened me to death but it is very very playable and I'm more than happy with what we did there but I said like earlier in the video this is about a long game replacement somewhere you go to next we've got this lost it down a little bit for the purpose of the video and that's all this isn't a comparison this is a ping g425 two hybrid 16 and a half degrees totally different because all of a sudden now you are seeing a lot of bulk and mass and I think it's again it's that confidence factor isn't it two iron frightened you to death hybrid much more familiar with it even though we've not got a great deal of lost on it we can certainly see something on the face there with the way ping have got this designed and again what's really interesting is how good the hybrid sounds in compared to the rest of the g425 range because it's been a criticism that I've got with the driver and with the fairy woods and sort of how loud they are and those seem to do quite the same with the hybrid but again really easy to play great launch on the ball I can't believe how far this thing is going again we're in the ball pretty decent here this morning I kind of almost like to see these reviews when you're not hitting the ball that well and it throws that question again back to the two fly high if you're not hitting the ball that well what happens then but again real good option as that long game replacement and certainly I would suggest we've seen there that it goes further than that of the two iron gets there in a different way then you move on to the five wood and we know what to expect we're now standing a little bit further away from the ball don't forget that long a shaft is going to make a difference in terms of clubhead speed and in theory should produce a longer carry but let's see if that's the case I don't know whether you heard the noise there can you hear the noise on that it's just so different out of the five wood compared to the hybrid this is much more in line with the driver it's almost like a gunshot going off the hybrid for some reason and as far as a no faith in everything it's the same in that g425 range the sound is so much softer in the hybrid right one more shot with this and I'll tell you why this has become such a massive dilemma on a personal level and why an intended video of a review of a Mizuno pro fly high turned into something very different for me personally there's that gunshot my god can you hear it but what you can't argue with is the ball has gone and it's probably done with what we'd have expected you've just seen on screen there hopefully um ball has flown extremely high fairly long to say the least quite surprisingly long as with the other two and that leads me on to why I'm so confused personally and the big shock I had with all the numbers that I've just collected on these three very different clubs now another interesting fact for me is the these are all lofted exactly the same but perform very very differently and I think for me I've very much been someone who's driven home this idea that for particularly the people who are not comfortable with strong losted irons they're always against the sort of strength of loft but I think what you'll see in today's video is that although these three clubs that we're going to be testing have identical lofts they all perform very very differently so loft is only a small part of the equation when it comes to a golf club's performance or how it gets from me to be the point to mention for me is the kind of positives and negatives of each of these clubs as an option if you start with the five would maybe the more difficult to use because of length of shaft so that could be a control issue but it's certainly versatile in terms of you'd be happy to play it off the tee and off of the fairway I think it's the hybrid which I think naturally would be probably the most versatile option out of these three again very comfortable off the tee and off the fairway and also that shorter length shaft or sitting in the middle of these three at least bit more control so most people be confident over that kind of shaft length add address the one negative with the any hybrid is a lot of people have that fear of the sort of that shot to the left often a hook can be quite an easy one to produce with a hybrid and then maybe the least versatile would be the two fly high for me 16 and a half degree two iron would only be an option off the tee really unlikely to feel confident playing off the fairway but going back to this idea about the reviewing of the fly high mizuno pro iron it is available in a three and a four iron option as well and for me that's probably where you'd feel a little bit more comfortable where you could perhaps bag a four or three and it would give you the versatile versatility that the five would and the hybrid offer as well although I will say I am at this point incredibly surprised at just how playable this two iron option has been so the question you must all be asking yourself is what was the dilemma it threw up for me and I'll get there very very soon we'll start off with the numbers of the five word that I collected and what I can't believe and I think that I've not watched it back yet but I've got a feeling I hit a ball 240 yards with the five where we were doing that test in there but I don't know I haven't seen that footage back yet I hit the ball really well to date and if I have it a five would 242 yards which I think it said then that's incredible but the data I recorded prior to that I didn't quite get one there but what I did do is perform really well clubbed speed 91 mile an hour ball speeds 142 which is phenomenal off that clubbed speed 225 an average carry the longest ball it was 232 launching at 13.1 peak height of 89 and a spin rate of three two so it probably did everything that I would expect it to do probably perform a little bit better in terms of yards if you'd have asked me what do I hit a five would it have been sort of around that sort of 220 mark and like I said we got that one weird knuckle ball out there which was probably a bit of an outlier on it all but on average 225 carry it in the ball the way I did today really really pleased with that and that's where it would have been now into that fly high which was the original review and again 89 clubbed speed which again don't forget short of shaft so that's where that couple of mile clubbed speed will be different but 138 ball speeds are really consistent across all those numbers 216 carry longest ball being 222 but again 222 221 219 218 that's the bit that surprised me about the fly high in that yeah we had a couple drop out at what was it lower one ball really 208 when I recorded days and one at 211 one at 213 so clearly suggest a little bit more difficult to play in you've got to get that middle but overall really surprised 11.7 again a couple of degrees lower than the five would so that peak height was only 62 and the spin was a lot lower so again a totally different club and how you'd look to use that particular to fly high so at this stage the numbers I've seen were probably what I was expecting although the fly high probably performed better than I would have expected it to in my hands so where does the dilemma come in and what happened well I've had the sort of g4 25 to hybrid as a sample from ping for well best part of a year I suppose and not really took much notice of it because too hybrid not much loft I'm an advocate of playing hybrids with loft so I haven't bothered with it maybe I shouldn't have ignored it for quite so long because we had a clubbed speed of 89.6 again length of shaft ball speed at 140.5 an average of 228 carry launching at 13.6 peak height of 83 2 and a half thousand revs but look at the consistency on the carry distances the lowest ball was 220 the other five other four are literally separated by a couple of yards either side of 230 yards I cannot stress the fact that yes I have it the ball probably as good as I have done on a camera today so we've got to bear that in mind having said that 230 yards carry with a two hybrid was a phenomenal number I'm one that I really have to now think about putting in the bag as a go-to club it performed as you've seen out there on the fairways again I like the idea of having that shorter shaft and if I've got an option of it the two hybrid or a five wood I'd rather play the two hybrid and have that shorter shaft in hand than the greater control so that's it video ended I think that maybe the club's out for everybody maybe the loft isn't for everybody but for me again I do launch the ball quite high as well then it seemed to really play into my hands it was a video that was never intended to be about my own personal dilemmas about the long end in the bag but trying to see whether a fly high was an option for an average golfer at 16.5 degrees or loft I think on that base I would say yes it's well worth a try certainly the three and four long irons in that fly eye range is certainly worth giving a go but the biggest surprise out of all of this was give yourself a go of a two hybrid and it might end up being your new go-to club in the bag right as ever thank you for watching thank you for card and part for letting us use this fantastic facility which has been brilliant we've had the heat from throughout it's been what a glory of stay out on the fairways as well so yeah we're grateful for that thank you for watching don't forget that comment early on I asked for what is your go-to club hit that like button and I will see you all very soon


So those of you who have read the program carefully might be surprised that there's only one person on the stage and not two My colleague Odin who was supposed to present with me has been prevented from attending today Which is unfortunate because he is actually the Programmer who made the tool that I'm presenting So yeah, I'm to the huggles, which is rather an awkward name to have when you work and live abroad as I've done extensively Actually the first time I used moodle was I believe in 2007 We had a private English school in Seoul South Korea teaching English to Korean middle schoolers any Koreans in the house No But now then I'm working for the Norwegian directorate of for education and training so essentially the Norwegian national government now we don't Do education directly that's a municipal Responsibility in our way, but we have a moodle site where we do some what you call Supplementary training in those rare instances where the municipal response of the Municipalities are not be able to sort of fulfill the responsibilities because Norway as Those who saw the presentation from Chef Fredx yesterday's heard is a very like Why long country few people sparsely populated? and the different municipalities Ability to fulfill the responsibilities in in education varies a lot from from Municipality to municipality So that's why we have this service another Quirk of Norway is we're we don't have many people, you know five and a half million. That's About the same as greater Barcelona But we have actually many languages we have to deal with There are two official languages in Norway Norwegian and Sami Of which there are several writings written standards. So Norwegian has two written standards Book mall and Nino's Sami comes in three variants South Sami Lule Sami and North Sami. So just in the official languages we have to deal with five different Languages so for us it's a bit weird that moodle like groups all of this into one Main language Norwegian and then the other language packs are sub packs to that main language And then we have three recognized minority languages Qvian, Romani and Romanez So the service that we run they call digila.no because of the Training we provide there we also have to support some more languages. So we support arabic Tigrinja and Somali and because of Ukrainian refugees from the war we also have a service so we support Ukrainian So our site our moodle sites has to support 12 different languages. So obviously for us translations and the quality of translations is very important Right, so the quality the challenge for us then is that The moodle language packs are crowdsourced in the AMOS. So anyone who wants to can just go in online and start translating Or suggest an improved translation or at least a translation Whether it's improved an improvement or not this might be up for debate And then there are these language pack maintainers that approve contributions Any who has contributed translations to moodle There are quite a few yes any language pack maintainers in the room Same right how about we give you guys This When we say that there is a challenge here that's in no way a disparagement on your work, which is very important But more our recognition that this is a huge task with thousands and thousands of language strings And that keep changing when functionality changes keeps you keep adding new strings with new plugins You know every time some new plugin comes out. It has to be translated into 55 or how many languages, right? So what we've seen is that the quality varies a lot with translations just looking at Our site we see things like typos. I've seen typos that actually break Placeholders in language strings. There are sometimes placeholders and other code So if you have a typo in there, it can actually break functionality in moodle We see lack of context sensitivity and now I'm in the sort of Norwegian context we see words that are actually valid Norwegian by like Dictionary definition, but they're not really used in that way in that context Incorrect Norwegian syntax, so we have a translation that where each individual word is valid Norwegian But the syntax is like in the original English syntax so There are some we have some issues with some of the translations and we actually also I should say I'm talking about Norwegian now, but we have funded Translations of the Sami languages because they are very small. They're actually in danger of being extinct So we've funded some translation of moodle into the Sami the three Sami languages say I mentioned earlier All right, so with this challenge You know what could be a solution So again leaving behind those 11 other languages we have to deal with for now and just focusing on on Norwegian We thought what about if we build some kind of Tool where we reduce the need for manual review all these like language string for some strings like 47,000 strings And we can pinpoint where which strings Need to be manually reviewed And also help translators and maintainers doing this manual review and using AI So that was the the idea so we decided to build proof of concept or pock of such a tool And this is an external tool as of now. It's not a moodle plugin or anything like that We're one of those many apps that was mentioned in the keynote on in the beginning of the conference where we are basically just One of many apps piggybacking on chat GPT So we did a test first using the chat GPT model text Da Vinci 003 be a command-lined interface And we only asked chat GPT to give a thumbs up thumbs down, you know are these is this string of other translation or not? true false So a very simple test really Ran all the language strings Through that So we got a Result of 10% being considered invalid by chat GPT so 10 thumbs down But that still leaves, you know for report maintainers for about 4200 strings to review and that's a lot of work So that's not very good Another problem was false positives so things that strings that were actually correct, but were flagged as incorrect or invalid so Da Vinci was not a good fit for us. So we went on to The next model the turbo 0301 model is still sort of these are all like submodels of the chat GPT 3.5 model Which has an API connection. So we hooked on to that And we made a chat where there would be three roles You have a system role that initiates the chat and defines its context sort of that the whole prompt escaping that you need to Give it get good answers as you know The quality of the answers you get from chat GPT is dependent on the quality of the questions you ask so we had the the system role set the The context, you know the user is working on a Norwegian Translation of an application used by middle school students in Norway i.e. our middle-sites And you are a helpful assistant who will for each other users messages respond with in this case then an integer between zero and a hundred Basically a quality rating of this translation. I won't read the whole prompt, but basically the idea is to Create a prompt for for chat GPT to give good answers And then the user asking the questions or in the in the process here like feeding chat GPT the language strings and Then the assistant i.e. chat GPT answering the questions In the way that it has been told to answer it by the prompt All right. So actually we did this in three separate processes So for each language each string and language pack we would then get three outputs Okay, so when we had the User ask or you know send in The current Norwegian translation in the Norwegian language pack We would ask okay question one is this a valid translation or not true false So basically the same as we did with Da Vinci In a separate process we would send the same thing Current Norwegian translation, but this time as you saw in the previous slide We would ask it ask a chat GPT to rate this translation How good is it on a scale from zero to a hundred or one to a hundred and Again in a third process We would send in the original English language string and ask chat GPT to come up with a Translation you know you suggest a translation of this into Norwegian. So what we'll get back would be true false rating from one to a hundred and Suggested Norwegian translation for each of the 40 some thousand strings in the middle database All right, so results of of this test done something weird is happening where The animation is showing on that screen but not on that screen That's very interesting, so I guess you just get all at once So as you see now, then you had about 25% were chat GPT Rated 100% and Suggested the same thing as is in the original translation. So then it's good to go About 50% was rated 100% but a different suggested translation still probably fine and Then you can go down to you know a rating of 80 to 100 that's 12% rating 30 to 80 that's 7% Rating less than 30. That's 4% and Rating less than 30 and Thumbs down this this is not considered a valid translation by chat GPT. That's only 1% So if you're gonna do manual review Start here Right, then you have it if you remember back to Da Vinci We got a 10% considered invalid So you would have to sift through about 42,000 sorry 4200 Strings now we're down to about 400 strings. So that's much more manageable And of course as you have researches you can go resources you can Start there go up to the less than 30% 30 points the 4% or and not going up the scale as needed So if you refer back to our goals with this proof of concept Can we reduce the need for manual review of strings check? You know you only have to review 1% of the strings Can we pinpoint where manual review is most needed? Yes, we get a list of this 1% so you can just use that list and go through it and we've looked at this list and It's a lot of strange text there and That brings us to the thing that the third one help translators and maintainers with manual review check because chat GPT has provided us with an Alternative translation which again we've reviewed some of these and we just copy and paste them right in this perfect translation So this is a very promising tool For and of course this is just for for Norwegian, which is kind of like in a in a sweet spot Where it's a small language. So you don't have that many translators But it's not so small that it's big enough that you have data online. You have a lot of Norwegian text online Right so going forward then This was just like a proof of concept a test will this work and how will the results be and in all honesty We haven't gotten to do as much with this as we had intended again. My colleague who couldn't be a today has For health reasons not been working for us for a while But some of the things we thought about when it comes to improving that tool, you know not product in it You know, it says product improvement, but it's not this is not something we're gonna sell or anything. You know, this is open source We could work on getting like automatic checks on new strings. So when there are new strings new plugins We can have the tool automatically check this We could define parameters where the The AI would automatically just fix it for us So we could have have sort of limits that okay these In these areas, we trust you and you know, you just make the changes But others will have set aside for manual reviews. So the maintainers still have control We also thought it could be a good idea to have the AI output its reasons for Rating, you know, it kind of like explainable AI. Why did you give this string an 80 or why did you give this string a 30? Which could help also improve the the tool going forward So those are some of the ideas you have and again, these are Ideas that anyone can just sort of grab and go with we can share. I don't know if our code is Open it's on github. I'm not sure if it's an open repository, but we will share it And we can use new AI models, you know, we did chat GPT 3.5 but four is already out. There are other models out there you can try And then ideas for how to sort of disseminate this tool The lowest sort of level in a way would be to create a moodle plug-in so that everyone just like installs the plug-in connects to their their AI of choice and Chucks their local install that would be kind of a very low-level use case of course the high-level use case would be to integrate with Amos so that Package maintainers or even translators could actually use this when they are working on Amos That way everyone Can benefit from their their work For someone has to foot the bill to connect to to the AI because that that costs money right to subscribe to chat GPT or what have you and Hopefully the result will be better translations easier and faster for all languages That's Thank you, that's really interesting. Do we have any questions we have some time we've just under 10 minutes So if we have any questions, please put your hand up and we can go around with the mic Okay I've got lots, but I'll let her let other people ask some questions first Thank you for presentation if I'm right this algorithm can be adjusted to other languages as well Yeah, we just connected it with the moodle language packs for English the original language packs and the Norwegian Translations in model so if you do the same and connected just to the original language packs and Slovenian or Mexican or what have you or sorry Spanish what have you then you do the same thing Great. Thank you. Oh This is one over there Yeah, I have no question But I have the idea for Dissemination that we should as a moodle open source community not rely on chat GPT but on That we should look at hugging face and find large language models that are free and open source and use them and Support this community as well. So we have we have to struggle with Salesforce in the in the Moodle partner community and I don't want to struggle with chat GPT in the whole moodle community Right, that's that's actually a very good idea. I hadn't thought of that but That seems to be the thing going forward that a lot of people are making their own language models Of course big companies are doing that corporations are doing that We are looking at Some other some are very interesting Establishing our own AI systems, but if you had like a sort of moodle AI they could do this for us. That would be great Thanks for presentation Tori. Is there a kind of consistency? Does it remember that it take one term to Translate a certain thing for example in Germany if you go to Simon to do a submission That can be an eichrein Upgabe it's it's and the thing with Human translated thing is I out there depending on what year the string was translated. It's sometimes not consistent Have you done any observation this is it consistent? Is it? We key Yeah, no, we've we've simply seen places where for example that the word sites In Norwegian at some point when it when someone started translating moodle into Norwegian They just made a choice of using the word portal the portal in Norwegian instead of sites and so Chat GPT keeps suggesting you know use the Norwegian word for site instead of put all which is But we could just sort of make a kind of like whitelist thing like you know Remember in this in this application when they use Put all as the translation. That's okay. You know don't don't fix that or but yeah, obviously you would have to work on the prompts to create that kind of sensitivity to the moodle specific terminology in a way I'm I'm curious about how you will continue forward with much smaller languages that perhaps chat GPT or some other large language model doesn't have much training data on And I have you any ideas on how Well, actually, I was I said before that that Norwegian is kind of like in the sweet spot where where it's big enough that there is Some or quite a lot of text online Whereas this three semi languages for example that we have in Norway are too small That's sort of the problem But the idea that our our colleague over there had about our own AI Maybe we could like train the AI on smaller languages to ourselves to address that in advocacy my tour my colleague One suggestion just for for this problem with the portal stuff is this solution is actually not marking any Translation as yes, that's what we want. So we just have we're just guessing on on the complete result list Seeing chat GPT is taking 50 percent or 75 percent. Yeah, that's a good translation But we're not training it So that would be the next step if we take our moodle translation And we every translation we take and then just saying okay This one is 100% cool and then we feed that stuff into chat GPT and then we would have We wouldn't have that issue with sites and portals because we define that's a good result So that would be we should train our language model to keep up with good translations Yeah, I know that the maintainer is mad at us. I was thinking about Consistency and we have a model.org in our Basque community at Glossary of those terms That we use translating moodle so you can train this AI with that kind of glossaries of good terms to translate To your language so you can have best translations in that way. Yeah, excellent Yeah, I didn't it was in the in the prompt on the screen, but I didn't read out loud But we told in our prompt we told them to use the Norwegian Dictionary, but we could also say use it in the Norwegian dictionary but also refer to the Glossary and moodle.org and you know, yeah Well, okay, we've just got a couple of minutes so if you could you go back one slide I think you were talking about the way forward. It doesn't matter Okay, and you talked of possibly having a moodle plug-in, but you thought that will be quite low-level Potentially having it in core. So are you in contact? Do you have accounts on langa.moodle.org? Which is the translation site for translators? Have you talked about this there? Have you are you in contact with you know? David Mudrach, who's sadly not here, but he he made Amos basically and Kun Rohamans who looks after all of the translators They're both teaching in high schools at the moment actually as we speak They'd be really interested in knowing more about this No, we haven't Yes, I said before we We had expected to come further in this both in terms of developing the tool itself and the dissemination part And actually we we thought that maybe someone else I thought of this too Well, I shall be speaking to them in our moodle chat very shortly. Okay


Hello and welcome to the session, the given question says prove that 1 divided by cosec theta minus cot theta minus 1 divided by sin theta is equal to 1 divided by sin theta minus 1 divided by cosec theta plus cot theta. So, let us start with the solution and we shall be solving both the left hand side and right hand side and show that after solving we get the same terms. So, let us start the left hand side we have 1 divided by cosec theta minus cot theta minus 1 divided by sin theta this is equal to 1 divided by sin theta minus 1 divided by cosec theta plus cot theta or it can further be written as 1 divided by cosec theta minus cot theta minus 1 divided by sin theta is cosec theta this is equal to again 1 divided by sin theta is cosec theta minus 1 divided by cosec theta plus cot theta. Now, we know that cosec square theta is equal to 1 plus cot square theta therefore, cosec square theta minus cot square theta is equal to 1 and this can further be written as cosec theta minus cot theta into cosec theta plus cot theta is equal to 1 right. So, here in case of 1 let us substitute cosec theta minus cot theta into cosec theta plus cot theta. So, we have cosec theta minus cot theta into cosec theta plus cot theta whole divided by cosec theta minus cot theta minus cosec theta this is equal to cosec theta minus cosec theta minus cot theta into cosec theta plus cot theta divided by cosec theta plus cot theta and now canceling cosec theta minus cot theta by cosec theta minus cot theta and here also cosec theta plus cot theta by cosec theta plus cot theta. We have on the left hand side cosik theta plus cot theta minus cosik theta is equal to cosik theta minus cosik theta minus cot theta. Now canceling cosik theta with minus cosik theta and here also canceling cosik theta with minus cosik theta. On the left hand side we have cot theta and on the right hand side also we have cot theta. So this shows that left hand side is equal to the right hand side. Hence we have 1 divided by cosik theta minus cot theta minus 1 divided by sin theta is equal to 1 divided by sin theta minus 1 divided by cosik theta plus cot theta. So this completes the solution. Hope you have understood it. Bye and take care.


convention Melbourne Australia 2012 what number convention is this is this the tenth one it's freaking crazy that means that I've spoken at eight the first convention that I spoke of was 2008 but the first convention was ever held was actually in Orlando Florida and this kid put it together and it's totally fucking crazy he got some of the best speakers in the world on in terms of personal development and stuff that he was interested in that matched his ideals personal development better skills with women and trying to be a better man and through the template and through the vision of a 17 year old kid that's pretty crazy and the form the formation of that renting the rooms orchestrating the the speakers and the production of it later in 2008 when I came on board it was already a professional act you know it had amazing technical crew the the caliber of speakers was was even better than it was the year before and ever since then I've seen it grow but what makes that grow and what I was saying is all the speakers up here we have our own individual message we have our own things that we want to say and share what we think and value is important to us however that is all through the filter of one guy you know who started this off when he was a kid and still to this day you might even say he's kind of a kid but he's done so much with his life he's a role model for what you guys can all do with what your idea is right now what you guys think is important and want to manifest into a dream that guy is Anthony Johnson he's doing his first speech of this convention which is really cool and opening up the day I hope you guys have already realized this convention can change your life because this guy has proven to me that anything is possible Anthony come on let's do it thanks sir thank you Steve morning guys I got a good morning or morning thank you thanks for showing up nice and early I know Sunday morning is the toughest that's why it starts the latest because it's just you guys go out at night you're tired you'd a lot of food a lot of curry last night God the title of my speech today is an introduction to the psychology of romantic love it's a topic I have never covered before at this convention or anywhere else as far speaking I've done a little bit of my blog and writing but nothing as far as speaking and this topic is somewhat unusual for me to cover because usually this convention I cover the convention itself the direction I want to take it the ideal man health fitness nutrition exercise topics that are not psychology romantic love conceptual deeply conceptual things like that so this is new but I'm excited to present it to you because it is based on a book as you can see the bottom here that is one of my top three favorite books of all time my favorite books of all time that have impacted me the deepest the most the most profoundly are the psychology romantic love as you guys will see here the fountain head and body by science so this book as we'll get to in a second year is just huge and completely underrated to a degree that I can't put into words so this is the book actually Steve can you go to the top there I have the book with me this year is a copy of the book a picture it was originally published in 1980 it was updated and expand in 2007 and as of this presentation the author Nathaniel Brendan is still alive although if one understands held isn't that great so unfortunately I don't know how much longer that'll be the case which is very sad sweet this is also the physical book is my first copy I read through it in day and a half pretty quick it's not super big but it's big enough the introduction will be through exploration so we're gonna as one of the speakers at the convention once put it about exercise we're gonna explore these ideas I say explore because these ideas are gonna be well in general this convention there's nothing that's not controversial everything at this convention every speaker every idea is entirely against conventional wisdom against the grain and it's not heard almost anywhere else this is no exception except I would say that in particular it's it will even be controversial in this room so kind of in and of the 21 convention even more so than usual anyway exploration through introduction or introduction through exploration excuse me we're gonna explore what romantic love is not first followed by what romantic love is and then we're gonna cover to my top 10 myths of romantic love that are in a way inferred from the book from the author from his ideas and yet it's important to note that the majority of this presentation consists of ideas that I haven't heard so I don't represent the author I'm not I am not the author obviously and I don't represent him officially in any capacity just a huge fan and I think I have a pretty good understanding of the book and the ideas within and if there is a direct quote from the book I'll put that in quotes and you'll see his name next to it that's how you can know that it's officially from him what romantic love is not romantic love is not a literary invention an adolescent fantasy an unattainable dream an irrational pursuit temporary neurosis false hope a fleeting emotion or an immature ideal one of my favorite quotes from the author Nathaniel Brandon is the opening passage of the book before you even get into a chapter and it's that above all romantic love is not for children not in the physical sense and not in the psychological sense what he means and what I mean when I when I put that up there that's a paraphrase is that much like Steve mentioned at the introduction of the speech a person can have they implied a person can have a physical age it's very obvious or not so obvious in some cases I look much older than I am I guess because a group of Florida I have like a crow's feet so you have a physical age but you also have a psychological age and as Steve implied or hinted at I'm young I'm 24 but most of you would say that I look and then I talk I come across as much older than that and that's because for the past six years of this convention I've traveled all the world and I have packed like decades of experience in a few years so for those of you that might have met me and thought I was older that I was close to 30 or something or who knows that's not the case and that's because at least I feel within myself as I experienced my life I feel much older than I physically am which is just 24 still young but this is important for romantic love because


What's up guys and welcome to one take I'm gil and today we're talking about the expanse season 5 episode 6 titled tribes This will be a full recap and review So it'll be full of spoilers through episode 6, but no book spoilers So nothing from any future episodes. I thought this was a solid episode and a step up from last week's We saw some very powerful character moments We see Avasarala more rattled than I think we've ever seen her before We see Amos and Clarissa both really having to struggle and confront who they are as people We also see Marco challenged by drummer and sin, which I really enjoyed similar to last week's episode There are a few things I'm still not loving about the Amos and Clarissa storyline Which I'll get into but as I mentioned with the increased focus on character development for both of them this episode I still thought it was an improvement with that Let's get into the recap first quick reminder if you're enjoying these videos Please go ahead and hit the like button hit the subscribe button and hit the bell icon So you get notified the next time we do a video We start with Avasarala in her office this whole scene was pretty heartbreaking since as I mentioned I don't think we've ever seen her in this state before She has tears in her eyes and sounds broken when she calls Arjun again and just barely starts her message She's interrupted by David pastor the minister of transportation who reveals he is the new acting secretary general He talks about the destruction he witnessed and promises to pull every string He can to try and locate Avasarala's husband They do a great job here of showing how in over his head David is he shares his credentials And we know his expertise is in transportation He's not exactly the man for the job on top of that He's not used to off-planet gravity So he stumbles as he reaches her desk which creates a great visual of his inexperience So within seconds at putting the dialogue aside we already have an impression of this person David asks if she'll join his provisional cabinet and she of course accepts After he leaves the room the camera lingers on Avasarala for about a minute as her hands shake She puts her jewelry back on and she attempts to pull herself together Again, I love this scene and my only complaint which is really a compliment is that I want to see more I'm very ready to watch Avasarala get back into the fold see how she responds to Marco and Deals with the massive tragedy on earth I think this will be her biggest professional and personal challenge yet And I'm psyched to see it play out next we'll quickly check in with Holden on the Rossi They've checked the reactor and hopefully have everything back in working order after Sakai's tampering Then Monica shows up and insists on coming along for the ride Bull is against it, but she insists it's thanks to her. They even know where the Zamiya is going Plus some of Marco's goons are probably still after her so she's safer on this ship Bull relents and they let her stay then Holden tells the computer to grant Monica guest privileges only And I love the detail here where in the background on the computer You see a big list of privileges and when he says guest only you see a bunch of them get grayed out Finally Holden notices an unread message from Naomi with the subject if something goes wrong My impression is that Naomi left this message before finding Philip and getting mixed up with Marco Meaning she knew there was some risk going into this and wanted to leave something behind for Holden in case things went south So I'm very curious to see what is in that message next. Let's talk about Alex and Bobby Last episode they dumped their core meaning they ejected the fusion reactor the plasma out of their ship And until that reaction starts back up they're relying on thrusters Which would get you a fraction of the speed you get with fusion power Now that is the least of their problems as they're currently being boarded by a belter ship as the Belters Cross the bridge and begin to open the door of the razorback Bobby comes out guns blazing Shooting one of the men in the face in her Martian power armor Bobby easily dispatches the men on the bridge and Drives any survivors back onto their ship the Belters begin to disconnect from the razorback in retreat Which is a problem for Alex who is holding on to the side of their ship Bobby tries holding the ships together and by Alex some time There's a great shot here of her suit being stretched to his limit reminiscent of spider-man 2 at the last second Alex Plays a bomb in the belter ships thruster and leaps back toward the razorback Another great moment here as Alex makes his way back to the ship the razorback is spinning So for a second Alex sees nothing but the void of space I felt real tension here as getting spaced Floating through the empty abyss is something that never gets less scary on this show But Alex reaches the razorback they get inside and leave victorious I thought this was a solid moment But emphasis on the word moment with so many different POVs in each episode It is starting to be a bit of a bummer when we get so little screen time for some of the storylines But again, that's sort of a complaint. That's really a compliment because I'm just saying I want to see more I also just want to add I kind of love the way this scene started out Where we have very little context and then all of a sudden Bobby comes out blasting away and we get this moment of extreme violence It was a pretty visceral and surprising way to start out the scene next. Let's go to Marco Naomi and drummer Marco is very frustrated with Philip. Thanks to Philip bringing Naomi on their ship She was able to warn Holden about the Gamara code saving the Ross and Ante when Philip apologizes Marco demands he space Naomi sin butts in and tells him to do it himself afterward Marco gives the lame excuse that he has better things to do first I loved sin shouting at Marco that was a great emotional release after watching Marco berate his son the last few episodes I also read a lot into this scene last episode I talked about how a lot of people involved in Marco's plot really don't have an appreciation for the horror of what they've done They can hear the sentence you killed millions, but they don't see the children or families they executed They just hear the statistic to me. This scene tells us that Marco is the same He talks about sacrifice, but he won't go kill Naomi right now And it's hard to imagine a mass murderer hesitating to kill someone even if he has an emotional attachment to them But Marco doesn't think of himself as a mass murderer He doesn't see the full scope of what he's done to him Those asteroids were a calculated act of war and nothing more than that And I don't know if he'll ever have his eyes opened it to the real tragedy of what he's done But I think Philip might afterward Philip goes to see Naomi She learns her crew survived and again tells Philip that Marco made him a murderer The highlight though is when Naomi tells Philip that Marco only loves himself and he wouldn't die for you But he would let you die for him That is a brilliant line because it rang so true and it is exactly the sort of thought which could fester in Philip's brain Until he turns against his father It's also very likely that more and more people will die for Marco's cause Which will just further reinforce that thought for Philip Eventually we get to the moment I've been waiting for this episode drummers meeting with Marco First off I laughed at Marco's intro drummer and associates The conversation starts to go south quickly with drummer bringing up Marco's murder of Ashford and Fred But Oksana brings up the future tries to get them refocused and asks about food Currently they're dependent on earth But Marco assures them that agricultural domes will eventually outproduce earth Finally he invites them to join the free navy The biggest highlight for me in this conversation is that Marco believes he already won the war And I knew he was cocky but this sort of crossed the line for me into delusional and naive territory And I think Val will have to be his downfall He'll trust the wrong person maybe Philip or underestimate his enemies and it'll get the best of him back on their ship Drummer and her crew debate their next move They realize that turning down Marco is a death sentence and they join him before drummer leaves Marco introduces her to Philip In their conversation drummers time with Naomi on the behemoth comes up And when drummer mentions that Naomi saved every soul in the solar system Philip says he wants to hear that story So we start to see that he's warming up to his mother He also makes it pretty obvious that they have Naomi aboard And I love the look Marco gives him at that point So I think drummer will suspect that Naomi is being held captive Which of course makes this even more personal for her Right now she needs to be level headed going up against Marco since he is currently in such a position of power And it'll be interesting to watch her struggle to hold back and not charge in to save her friend After already losing two of them to Marco Philip heads back to Naomi though this time he joins her in the cell He asks her about her time on the behemoth and she begins telling the story I loved seeing this. It was sort of the first moment of joy We have for Naomi this season as she finally gets to connect with her son Sadly, I can't see a happy ending for them Again, Philip is complicit in one of the most heinous acts in history So I think these few moments of joy are kind of tinged in tragedy Destined to be short-lived. Also, we see Marco watching them on a security camera So he knows they're bonding and I think he'll take that out on Philip He also pulls up an image of Naomi's ship. So it seems he's plotting something to strike back against the two of them I'm excited to see what it is and also kind of dreading it as I said I don't think this ends well for Naomi and Philip. Finally, let's check in on amos and peaches We see them by an aid station But they can't go in it because there are cops and Clarissa is an escaped convict Amos suggests they take the long hike to baltimore where he knows the right people to be around in these situations So I think we'll eventually see a reluctant reunion between Eric and amos They begin their hike through the chesapeake conservancy zone And this is a pretty dialogue heavy episode for the two of them, which I was very happy with I mentioned a couple of weeks back that Clarissa is a character I never really connected or sympathized with something about killing innocent people or letting them die Just sort of rubbed me the wrong way But this episode started to humanize her for me And we do see that she is really struggling to live with the things she's done As they make their way through the woods Clarissa surprised to learn that amos never went to this reforestation area on a school field trip Which made her seem very naive and out of touch just sort of unaware of the privileges She grew up with that not everybody had Which helped me understand how she could be swayed into her misguided revenge mission They also discussed their parents and we get amos giving Clarissa a small version of the conversation he had with Lydia years ago There are ways that you can live a good life Without being a good person I think this is an important moment for Clarissa from the poem we hear from her later We know she doesn't want to be a bad person. She doesn't want to believe that she is a monster But that's not enough. She's clearly tortured and doesn't know how to function or live with herself Versus amos who is clearly introspecting and thinking things over but he gets by just fine Here he's trying to tell her how he does that. He tells her essentially Don't worry about am I a good person or not? You know what a good person would do So just do that they bump into a guy by a campfire who warns them about a survivalist nearby Who is shooting potential trespassers? They leave him and when amos checks if he's following them afterward Clarissa says the guy is harmless and also notes that amos seems like he's done this before he explains I grew up like this Everyone else is playing catch up People are tribal The more subtle things are the bigger the tribes can be The churn comes and the tribes get small again Right now you and I are a tribe of two I thought this episode was filled with some great pieces of dialogue and that was one of them It takes an idea which we all intuitively understand in times of crisis your circle of trust shrinks But it puts it in a way you haven't heard before That feels very true and so succinctly describes amos's mindset amos takes them to survivalist guy And he walks right up to the front door. He pretends they want to trade But the man goes to kill him anyway before he can pull the trigger Clarissa activates her mods And moves at superhuman speed to kill him then she passes out and amos brings her inside I thought her attack looked pretty cheesy, but I figured that's partially a budget thing So I won't hold it against the show. I will say though I mentioned up front that there were some things I didn't love about this storyline And this survivalist guy is mainly what I was referring to One of my issues with the prison escape was the convenience built into it And I think we saw more of that here what I mean by that is something happens Which stretches credulity in a way that seems convenient for the storyline Because I don't mind if something unrealistic happens, especially in a sci-fi show Accept when it benefits our characters in a way that makes things seem too easy Here amos and Clarissa need shelter supplies and transportation So they walk into the woods and boom some guy tells them. Hey, there's somebody nearby with everything you need And bonus he's a scumbag so you can kill him take all his stuff and not feel too bad about it It felt a little like trying to have your cake and eat it too Amos and Clarissa wonder if it's wrong to kill someone purely for your own benefit But there's the escape hatch if he was going to kill us first So we look at this moral gray area without having to really dive into it to be fair She does point out that they sort of provoked him So that saves it a little for me and I like where it ultimately leads from a character standpoint And that's my feeling on this storyline overall this episode from a plot standpoint I didn't love where it went but on an emotional and character level which to me is more important It did work at the end of the episode Clarissa points out that going out of your way to murder someone and take their stuff It's not the kind of thing good people do It's not even the kind of thing bad people trying to live like good people do and I loved amos's response to that Yeah All the never would have proven to move like that I need to get back to my crew I think he realizes that as far as he's come his journey is far from over He still doesn't quite know how to be an entirely good person But it's very self aware of him to note that he needs to be around others He needs to get back to his crew Who have a little bit of a better idea how to be good? And it made me really excited to see the eventual reunion with amos and his crew Because i'm so curious what their relationship will look like now He's clearly changed and I think holden and Naomi will recognize that I also think they'll be able to help him along on his journey to be good Though I imagine it won't be an easy one I also think there will be some mixed feelings if he tries to bring Clarissa along Anyway, I think we can wrap it up there. Like I said, I thought this was a solid episode And I'm excited to see how things progress in the next four Let me know what you thought of the episode in the comments Let me know if you agreed with my take where you disagreed and we'll keep the conversation going And if you enjoyed this video, please go ahead and hit the like button Hit the subscribe button and hit the bell icon so you get notified when our next video drops We'll continue to review the show every week and have some other expanse related videos on the way Including one deep diving into fred johnson's character So stay tuned for that with that. Thanks for watching and see you on the next one take


Hey, what's going on everybody? My name is John Hammond. Coming back at you with a new challenge prompt. This one is spelling states and it says all but three of the 50 United States contain at least one of two particular letters.  Some states may use both. So what are these letters and what states don't use them? So this one takes a little bit more thought. We can still whip it out in Python or I'm sure you can whip it out in any other code or program language of your choice. So if you're if you want to try your hand at it, please do so. Please share some code or whatever you can with me. But regardless, I'll crank out a solution and I'll have that uploaded and showing you guys tomorrow. So thanks and I'll see you then.